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Zheutlin AR, Sharareh N, Guadamuz JS, Berchie RO, Derington CG, Jacobs JA, Mondesir FL, Alexander GC, Levitan EB, Safford M, Vos RO, Qato DM, Bress AP. Association Between Pharmacy Proximity With Cardiovascular Medication Use and Risk Factor Control in the United States. J Am Heart Assoc 2024; 13:e031717. [PMID: 38390820 PMCID: PMC10944071 DOI: 10.1161/jaha.123.031717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 01/16/2024] [Indexed: 02/24/2024]
Abstract
BACKGROUND Poor neighborhood-level access to health care, including community pharmacies, contributes to cardiovascular disparities in the United States. The authors quantified the association between pharmacy proximity, antihypertensive and statin use, and blood pressure (BP) and low-density lipoprotein cholesterol (LDL-C) among a large, diverse US cohort. METHODS AND RESULTS A cross-sectional analysis of Black and White participants in the REGARDS (Reasons for Geographic and Racial Differences in Stroke) study during 2013 to 2016 was conducted. The authors designated pharmacy proximity by census tract using road network analysis with population-weighted centroids within a 10-minute drive time, with 5- and 20-minute sensitivity analyses. Pill bottle review measured medication use, and BP and LDL-C were assessed using standard methods. Poisson regression was used to quantify the association between pharmacy proximity with medication use and BP control, and linear regression for LDL-C. Among 16 150 REGARDS participants between 2013 and 2016, 8319 (51.5%) and 8569 (53.1%) had an indication for antihypertensive and statin medication, respectively, and pharmacy proximity data. The authors did not find a consistent association between living in a census tract with higher pharmacy proximity and antihypertensive medication use, BP control, or statin medication use and LDL-C levels, regardless of whether the area was rural, suburban, or urban. Results were similar among the 5- and 20-minute drive-time analyses. CONCLUSIONS Living in a low pharmacy proximity census tract may be associated with antihypertensive and statin medication use, or with BP control and LDL-C levels. Although, in this US cohort, outcomes were similar for adults living in high or low pharmacy proximity census tracts.
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Affiliation(s)
- Alexander R. Zheutlin
- Division of Cardiology, Feinberg School of MedicineNorthwestern UniversityChicagoILUSA
| | - Nasser Sharareh
- Department of Population Health Sciences, Spencer Fox Eccles School of MedicineUniversity of UtahSalt Lake CityUTUSA
| | - Jenny S. Guadamuz
- Division of Health Policy and ManagementUniversity of California, Berkeley, School of Public HealthBerkeleyCAUSA
| | - Ransmond O. Berchie
- Department of Population Health Sciences, Spencer Fox Eccles School of MedicineUniversity of UtahSalt Lake CityUTUSA
| | - Catherine G. Derington
- Department of Population Health Sciences, Spencer Fox Eccles School of MedicineUniversity of UtahSalt Lake CityUTUSA
| | - Joshua A. Jacobs
- Department of Population Health Sciences, Spencer Fox Eccles School of MedicineUniversity of UtahSalt Lake CityUTUSA
| | - Favel L. Mondesir
- Department of EpidemiologyUniversity of Alabama at Birmingham School of Public HealthBirminghamALUSA
| | - G. Caleb Alexander
- Department of EpidemiologyCenter for Drug Safety and Effectiveness, Johns Hopkins Bloomberg School of Public HealthBaltimoreMDUSA
- Department of MedicineJohns Hopkins MedicineBaltimoreMDUSA
| | - Emily B. Levitan
- Department of EpidemiologyUniversity of Alabama at Birmingham School of Public HealthBirminghamALUSA
| | - Monika Safford
- Division of General Internal Medicine, Department of Medicine, Weill Cornell Medical CollegeCornell UniversityNew YorkNYUSA
| | - Robert O. Vos
- Spatial Sciences Institute, Dornsife College of Letters, Arts, and SciencesUniversity of Southern CaliforniaLos AngelesCAUSA
| | - Dima M. Qato
- Spatial Sciences Institute, Dornsife College of Letters, Arts, and SciencesUniversity of Southern CaliforniaLos AngelesCAUSA
- Program on Medicines and Public Health, Titus Family Department of Clinical Pharmacy, School of Pharmacy, University of Southern CaliforniaLos AngelesCAUSA
- Leonard D. Schaeffer Center for Health Policy and Economics, University of Southern CaliforniaLos AngelesCAUSA
- Program on Medicines and Public Health, Alfred Mann School of Pharmacy and Pharmaceutical SciencesUniversity of Southern CaliforniaLos AngelesCAUSA
| | - Adam P. Bress
- Department of Population Health Sciences, Spencer Fox Eccles School of MedicineUniversity of UtahSalt Lake CityUTUSA
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Tajeu GS, Ruiz-Negrón N, Moran AE, Zhang Z, Kolm P, Weintraub WS, Bress AP, Bellows BK. Cost of Cardiovascular Disease Event and Cardiovascular Disease Treatment-Related Complication Hospitalizations in the United States. Circ Cardiovasc Qual Outcomes 2024; 17:e009999. [PMID: 38328916 PMCID: PMC11099996 DOI: 10.1161/circoutcomes.123.009999] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 11/17/2023] [Indexed: 02/09/2024]
Abstract
BACKGROUND Cardiovascular disease (CVD) is among the costliest conditions in the United States, and cost-effectiveness analyses can be used to assess economic impact and prioritize CVD treatments. We aimed to develop standardized, nationally representative CVD events and selected possible CVD treatment-related complication hospitalization costs for use in cost-effectiveness analyses. METHODS Nationally representative costs were derived using publicly available inpatient hospital discharge data from the 2012-2018 National Inpatient Sample. Events were identified using the principal International Classification of Diseases, Ninth Revision and International Classification of Diseases, Tenth Revision codes. Facility charges were converted to costs using charge-to-cost ratios, and total costs were estimated by applying a published professional fee ratio. All costs are reported in 2021 US dollars. Mean costs were estimated for events overall and stratified by age, sex, and survival status at discharge. Annual costs to the US health care system were estimated by multiplying the mean annual number of events by the mean total cost per discharge. RESULTS The annual mean number of hospital discharges among CVD events was the highest for heart failure (1 087 000 per year) and cerebrovascular disease (800 600 per year). The mean cost per hospital discharge was the highest for peripheral vascular disease ($33 700 [95% CI, $33 300-$34 000]) and ventricular tachycardia/ventricular fibrillation ($32 500 [95% CI, $32 100-$32 900]). Hospitalizations contributing the most to annual US health care costs were heart failure ($19 500 [95% CI, $19 300-$19 800] million) and acute myocardial infarction ($18 300, [95% CI, $18 200-$18 500] million). Acute kidney injury was the most frequent possible treatment complication (515 000 per year), and bradycardia had the highest mean hospitalization costs ($17 400 [95% CI, $17 200-$17 500]). CONCLUSIONS The hospitalization cost estimates and statistical code reported in the current study have the potential to increase transparency and comparability of cost-effectiveness analyses for CVD in the United States.
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Affiliation(s)
- Gabriel S. Tajeu
- Department of Health Services Administration and Policy, Temple University, Philadelphia, PA
| | | | - Andrew E. Moran
- Division of General Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | | | - Paul Kolm
- MedStar Health Research Institute and Department of Medicine, Georgetown University, Washington, DC
| | - William S. Weintraub
- MedStar Health Research Institute and Department of Medicine, Georgetown University, Washington, DC
| | - Adam P. Bress
- Department of Population Health Sciences, University of Utah, Salt Lake City, UT
| | - Brandon K. Bellows
- Division of General Medicine, Columbia University Irving Medical Center, New York, NY, USA
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Cohen JB, Bress AP. Entering a New Era of Antihypertensive Therapy. Am J Kidney Dis 2024; 83:411-414. [PMID: 37939995 DOI: 10.1053/j.ajkd.2023.09.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 09/20/2023] [Accepted: 09/24/2023] [Indexed: 11/10/2023]
Affiliation(s)
- Jordana B Cohen
- Renal-Electrolyte and Hypertension Division, Philadelphia, Pennsylvania; Department of Biostatistics, Epidemiology, and Informatics, Philadelphia, Pennsylvania; Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
| | - Adam P Bress
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, Utah
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Jacobs JA, Zheutlin AR, Derington CG, King JB, Pandey A, Bress AP. Glucagon-like peptide-1 receptor agonist and sodium-glucose cotransporter 2 inhibitor use among adults with diabetes mellitus by cardiovascular-kidney disease risk: National Health and Nutrition Examination Surveys, 2015-2020. Am J Prev Cardiol 2024; 17:100624. [PMID: 38125205 PMCID: PMC10730337 DOI: 10.1016/j.ajpc.2023.100624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 11/19/2023] [Accepted: 11/25/2023] [Indexed: 12/23/2023] Open
Abstract
Objective Glucagon-like peptide-1 receptor agonists (GLP1-RAs) and sodium-glucose cotransporter 2 inhibitors (SGLT2Is) lower adverse cardiac and kidney events among high-risk patients with diabetes mellitus (DM) and are now guideline-recommended as first-line therapy alongside metformin. However, the adoption of these new treatments from 2015 to 2020 among the highest-risk adults with DM remains unclear. Methods We performed a cross-sectional analysis of the National Health and Nutrition Examination Surveys (NHANES) 2015-2020 to estimate the use of GLP1-RAs and SGLT2Is among adults with DM overall and by level of cardiovascular and kidney risk (CKR). We defined high CKR by history of atherosclerotic cardiovascular disease (ASCVD), chronic kidney disease (CKD), heart failure, or age ≥55 years with at least 2 ASCVD risk factors (i.e., obesity, hypertension, hyperlipidemia, or current smoker). Results Overall, 2,432 participants with DM (mean age 60.6 years, 46.8 % female, 58.8 % Non-Hispanic White) were included, of which 1,869 and 563 were with and without high CKR, respectively. Participants with vs. without high CKR were more likely to be older, have higher systolic blood pressure, lower estimated glomerular filtration rate, use oral antidiabetic agents, and have health insurance. Overall, the weighted prevalence of GLP1-RA or SGLT2I was 9.0 % (95 % confidence interval [CI] 6.9-11.0): 4.8 % (95 % CI 3.6-6.1) took GLP1-RAs, and 5.1 % (95 % CI 3.3-7.0) took SGLT2Is. Use of GLP1-RAs or SGLT2Is did not differ between participants with vs. without high CKR (adjusted prevalence ratio [aPR] 1.00; 95 % CI 0.98-1.02). Participants with ASCVD were more likely to be on a GLP1-RA or SGLT2I (aPR 1.28; 95 % CI 1.25-1.31), while adults with CKD were less likely (aPR 0.84; 95 % CI 0.82-0.86). Conclusion Among US adults with DM, GLP1-RA and SGLT2I use was low regardless of CKR. Data since 2020 analyzing the utilization of GLP1-RAs and SGLT2Is among high-CKR patients with DM is needed to identify implementation strategies for increased utilization.
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Affiliation(s)
- Joshua A. Jacobs
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, UT, United States
| | - Alexander R. Zheutlin
- Division of Cardiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Catherine G. Derington
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, UT, United States
| | - Jordan B. King
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, UT, United States
- Institute for Health Research, Kaiser Permanente Colorado, Aurora, CO, United States
| | - Ambarish Pandey
- Division of Cardiology, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Adam P. Bress
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, UT, United States
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Jacobs JA, Derington CG, Zheutlin AR, King JB, Cohen JB, Bucheit J, Kronish IM, Addo DK, Morisky DE, Greene TH, Bress AP. Association Between Self-Reported Medication Adherence and Therapeutic Inertia in Hypertension: A Secondary Analysis of SPRINT (Systolic Blood Pressure Intervention Trial). J Am Heart Assoc 2024; 13:e031574. [PMID: 38240275 PMCID: PMC11056166 DOI: 10.1161/jaha.123.031574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 12/06/2023] [Indexed: 02/07/2024]
Abstract
BACKGROUND Therapeutic inertia (TI), failure to intensify antihypertensive medication when blood pressure (BP) is above goal, remains prevalent in hypertension management. The degree to which self-reported antihypertensive adherence is associated with TI with intensive BP goals remains unclear. METHODS AND RESULTS Cross-sectional analysis was performed of the 12-month visit of participants in the intensive arm of SPRINT (Systolic Blood Pressure Intervention Trial), which randomized adults to intensive (<120 mm Hg) versus standard (<140 mm Hg) systolic BP goals. TI was defined as no increase in antihypertensive regimen intensity score, which incorporates medication number and dose, when systolic BP is ≥120 mm Hg. Self-reported adherence was assessed using the 8-Item Morisky Medication Adherence Scale (MMAS-8) and categorized as low (MMAS-8 score <6), medium (MMAS-8 score 6 to <8), and high (MMAS-8 score 8). Poisson regressions estimated prevalence ratios (PRs) and 95% CIs for TI associated with MMAS-8. Among 1009 intensive arm participants with systolic BP >120 mm Hg at the 12-month visit (mean age, 69.6 years; 35.2% female, 28.8% non-Hispanic Black), TI occurred in 50.8% of participants. Participants with low adherence (versus high) were younger and more likely to be non-Hispanic Black or smokers. The prevalence of TI among patients with low, medium, and high adherence was 45.0%, 53.5%, and 50.4%, respectively. After adjustment, neither low nor medium adherence (versus high) were associated with TI (PR, 1.11 [95% CI, 0.87-1.42]; PR, 1.08 [95% CI, 0.84-1.38], respectively). CONCLUSIONS Although clinician uncertainty about adherence is often cited as a reason for why antihypertensive intensification is withheld when above BP goals, we observed no evidence of an association between self-reported adherence and TI.
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Affiliation(s)
- Joshua A. Jacobs
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of MedicineUniversity of UtahSalt Lake CityUTUSA
| | - Catherine G. Derington
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of MedicineUniversity of UtahSalt Lake CityUTUSA
| | - Alexander R. Zheutlin
- Division of Cardiology, Feinberg School of Medicine,Northwestern UniversityChicagoILUSA
| | - Jordan B. King
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of MedicineUniversity of UtahSalt Lake CityUTUSA
- Institute for Health ResearchKaiser Permanente ColoradoAuroraCOUSA
| | - Jordana B. Cohen
- Renal‐Electrolyte and Hypertension Division, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPAUSA
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPAUSA
| | - John Bucheit
- Department of Pharmacotherapy and Outcomes ScienceVirginia Commonwealth University School of PharmacyRichmondVAUSA
| | - Ian M. Kronish
- Center for Behavioral Cardiovascular HealthColumbia University Irving Medical CenterNew YorkNYUSA
| | - Daniel K. Addo
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of MedicineUniversity of UtahSalt Lake CityUTUSA
| | - Donald E. Morisky
- Department of Community Health Sciences UCLA Fielding School of Public HealthLos AngelesCAUSA
| | - Tom H. Greene
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of MedicineUniversity of UtahSalt Lake CityUTUSA
| | - Adam P. Bress
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of MedicineUniversity of UtahSalt Lake CityUTUSA
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Zhang F, Bryant KB, Moran AE, Zhang Y, Cohen JB, Bress AP, Sheppard JP, King JB, Derington CG, Weintraub WS, Kronish IM, Shea S, Bellows BK. Effectiveness of Hypertension Management Strategies in SPRINT-Eligible US Adults: A Simulation Study. J Am Heart Assoc 2024; 13:e032370. [PMID: 38214272 PMCID: PMC10926802 DOI: 10.1161/jaha.123.032370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 12/01/2023] [Indexed: 01/13/2024]
Abstract
BACKGROUND Despite reducing cardiovascular disease (CVD) events and death in SPRINT (Systolic Blood Pressure Intervention Trial), intensive systolic blood pressure goals have not been adopted in the United States. This study aimed to simulate the potential long-term impact of 4 hypertension management strategies in SPRINT-eligible US adults. METHODS AND RESULTS The validated Blood Pressure Control-Cardiovascular Disease Policy Model, a discrete event simulation of hypertension care processes (ie, visit frequency, blood pressure [BP] measurement accuracy, medication intensification, and medication adherence) and CVD outcomes, was populated with 25 000 SPRINT-eligible US adults. Four hypertension management strategies were simulated: (1) usual care targeting BP <140/90 mm Hg (Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure usual care), (2) intensive care per the SPRINT protocol targeting BP <120/90 mm Hg (SPRINT intensive), (3) usual care targeting guideline-recommended BP <130/80 mm Hg (American College of Cardiology/American Heart Association usual care), and (4) team-based care added to usual care and targeting BP <130/80 mm Hg. Relative to the Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure usual care, among the 18.1 million SPRINT-eligible US adults, an estimated 138 100 total CVD events could be prevented per year with SPRINT intensive, 33 900 with American College of Cardiology/American Heart Association usual care, and 89 100 with team-based care. Compared with the Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure usual care, SPRINT intensive care was projected to increase treatment-related serious adverse events by 77 600 per year, American College of Cardiology/American Heart Association usual care by 33 300, and team-based care by 27 200. CONCLUSIONS As BP control has declined in recent years, health systems must prioritize hypertension management and invest in effective strategies. Adding team-based care to usual care may be a pragmatic way to manage risk in this high-CVD-risk population.
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Affiliation(s)
- Fengdi Zhang
- Department of MedicineColumbia UniversityNew YorkNYUSA
| | | | | | - Yiyi Zhang
- Department of MedicineColumbia UniversityNew YorkNYUSA
| | - Jordana B. Cohen
- Department of Medicine and Department of Biostatistics, Epidemiology, and InformaticsUniversity of PennsylvaniaPhiladelphiaPAUSA
| | - Adam P. Bress
- Intermountain Healthcare Department of Population Health SciencesUniversity of UtahSalt Lake CityUTUSA
| | - James P. Sheppard
- Nuffield Department of Primary Care Health SciencesUniversity of OxfordUK
| | - Jordan B. King
- Intermountain Healthcare Department of Population Health SciencesUniversity of UtahSalt Lake CityUTUSA
- Institute for Health ResearchKaiser Permanente ColoradoAuroraCOUSA
| | - Catherine G. Derington
- Intermountain Healthcare Department of Population Health SciencesUniversity of UtahSalt Lake CityUTUSA
| | - William S. Weintraub
- Department of MedicineGeorgetown UniversityWashingtonDCUSA
- MedStar Health Research InstituteWashingtonDCUSA
| | | | - Steven Shea
- Department of MedicineColumbia UniversityNew YorkNYUSA
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Weintraub WS, Bhatt DL, Zhang Z, Dolman S, Boden WE, Bress AP, Bellows BK, Derington CG, Philip S, Steg G, Miller M, Brinton EA, Jacobson TA, Tardif J, Ballantyne CM, Kolm P. Cost-Effectiveness of Icosapent Ethyl in REDUCE-IT USA: Results From Patients Randomized in the United States. J Am Heart Assoc 2024; 13:e032413. [PMID: 38156550 PMCID: PMC10863822 DOI: 10.1161/jaha.123.032413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Accepted: 11/28/2023] [Indexed: 12/30/2023]
Abstract
BACKGROUND In 3146 REDUCE-IT USA (Reduction of Cardiovascular Events With Icosapent Ethyl Intervention Trial USA) participants, icosapent ethyl (IPE) reduced first and total cardiovascular events by 31% and 36%, respectively, over 4.9 years of follow-up. METHODS AND RESULTS We used participant-level data from REDUCE-IT USA, 2021 US costs, and IPE costs ranging from $4.59 to $11.48 per day, allowing us to examine a range of possible medication costs. The in-trial analysis was participant-level, whereas the lifetime analysis used a Markov model. Both analyses considered value from a US health sector perspective. The incremental cost-effectiveness ratio (incremental costs divided by incremental quality-adjusted life-years) of IPE compared with standard care (SC) was the primary outcome measure. There was incremental gain in quality-adjusted life-years with IPE compared with SC using in-trial (3.28 versus 3.13) and lifetime (10.36 versus 9.83) horizons. Using an IPE cost of $4.59 per day, health care costs were lower with IPE compared with SC for both in-trial ($29 420 versus $30 947) and lifetime ($216 243 versus $219 212) analyses. IPE versus SC was a dominant strategy in trial and over the lifetime, with 99.7% lifetime probability of an incremental cost-effectiveness ratio <$50 000 per quality-adjusted life-year gained. At a medication cost of $11.48 per day, the cost per quality-adjusted life-year gained was $36 208 in trial and $9582 over the lifetime. CONCLUSIONS In this analysis, at $4.59 per day, IPE offers better outcomes than SC at lower costs in trial and over a lifetime and is cost-effective at $11.48 per day for conventional willingness-to-pay thresholds. Treatment with IPE should be strongly considered in US patients like those enrolled in REDUCE-IT USA. REGISTRATION URL: https://www.clinicaltrials.gov; Unique identifier: NCT01492361.
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Affiliation(s)
- William S. Weintraub
- MedStar Healthcare Delivery Research NetworkMedStar Health Research InstituteWashingtonDCUSA
- Department of MedicineGeorgetown UniversityWashingtonDCUSA
| | - Deepak L. Bhatt
- Mount Sinai HeartIcahn School of Medicine at Mount Sinai Health SystemNew YorkNYUSA
| | - Zugui Zhang
- Institute for Research on Equity and Community HealthChristiana Care Health SystemNewarkDEUSA
| | - Sarahfaye Dolman
- MedStar Healthcare Delivery Research NetworkMedStar Health Research InstituteWashingtonDCUSA
| | - William E. Boden
- Cardiology Section, Department of MedicineVeterans Affairs Boston Healthcare SystemBostonMAUSA
- Department of MedicineBoston University School of MedicineBostonMAUSA
| | - Adam P. Bress
- Division of Health System Innovation and Research, Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of MedicineUniversity of UtahSalt Lake CityUTUSA
| | | | - Catherine G. Derington
- Division of Health System Innovation and Research, Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of MedicineUniversity of UtahSalt Lake CityUTUSA
| | | | - Gabriel Steg
- Medical School of Université de Paris‐CitéParisFrance
- Cardiology Department, Assistance Publique–Hôpitaux de ParisHôpital BichatParisFrance
- French Alliance for Cardiovascular Trials, INSERM U‐1148ParisFrance
| | - Michael Miller
- Department of MedicineCorporal Michael J Crescenz Veterans Affairs Medical Center and Hospital of the University of PennsylvaniaPhiladelphiaPAUSA
| | | | - Terry A. Jacobson
- Lipid Clinic and Cardiovascular Risk Reduction Program, Department of MedicineEmory UniversityAtlantaGAUSA
| | | | | | - Paul Kolm
- Center of Biostatistics, Informatics and Data ScienceMedStar Health Research InstituteWashingtonDCUSA
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Mentias A, Keshvani N, Sumarsono A, Desai R, Khan MS, Menon V, Hsich E, Bress AP, Jacobs J, Vasan RS, Fonarow GC, Pandey A. Patterns, Prognostic Implications, and Rural-Urban Disparities in Optimal GDMT Following HFrEF Diagnosis Among Medicare Beneficiaries. JACC Heart Fail 2023:S2213-1779(23)00597-8. [PMID: 37943222 DOI: 10.1016/j.jchf.2023.08.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 08/28/2023] [Accepted: 08/30/2023] [Indexed: 11/10/2023]
Abstract
BACKGROUND Patterns and disparities in guideline-directed medical therapy (GDMT) uptake for heart failure with reduced ejection fraction (HFrEF) across rural vs urban regions are not well described. OBJECTIVES This study aims to evaluate patterns, prognostic implications, and rural-urban differences in GDMT use among Medicare beneficiaries following new-onset HFrEF. METHODS Patients with a diagnosis of new-onset HFrEF in a 5% Medicare sample with available data for Part D medication use were identified from January 2015 through December 2020. The primary exposure was residence in rural vs urban zip codes. Optimal triple GDMT was defined as ≥50% of the target daily dose of beta-blockers, ≥50% of the target daily dose of angiotensin-converting enzyme inhibitors/angiotensin receptor blocker or any dose of sacubitril/valsartan, and any dose of mineralocorticoid receptor antagonist. The association between the achievement of optimal GDMT over time following new-onset HFrEF diagnosis and risk of all-cause mortality and subsequent HF hospitalization was also evaluated using adjusted Cox models. The association between living in rural vs urban location and time to optimal GDMT achievement over a 12-month follow-up was assessed using cumulative incidence curves and adjusted Fine-Gray subdistribution hazard models. RESULTS A total of 41,296 patients (age: 76.7 years; 15.0% Black; 27.6% rural) were included. Optimal GDMT use over the 12-month follow-up was low, with 22.5% initiated on any dose of triple GDMT and 9.1% on optimal GDMT doses. Optimal GDMT on follow-up was significantly associated with a lower risk of death (HR: 0.89 [95% CI: 0.85-0.94]; P < 0.001) and subsequent HF hospitalization (HR: 0.93 [95% CI: 0.87-0.98]; P = 0.02). Optimal GDMT use at 12 months was significantly lower among patients living in rural (vs urban) areas (8.4% vs 9.3%; P = 0.02). In adjusted analysis, living in rural (vs urban) locations was associated with a significantly lower probability of achieving optimal GDMT (HR: 0.92 [95% CI: 0.86-0.98]; P = 0.01 Differences in optimal GDMT use following HFrEF diagnosis accounted for 16% of excess mortality risk among patients living in rural (vs urban) areas. CONCLUSIONS Use of optimal GDMT following new-onset HFrEF diagnosis is low, with substantially lower use noted among patients living in rural vs urban locations. Suboptimal GDMT use following new-onset HFrEF was associated with an increased risk of mortality and subsequent HF hospitalization.
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Affiliation(s)
- Amgad Mentias
- Department of Cardiology, Cleveland Clinic, Cleveland, Ohio, USA
| | - Neil Keshvani
- Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Andrew Sumarsono
- Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | | | | | - Venu Menon
- Department of Cardiology, Cleveland Clinic, Cleveland, Ohio, USA
| | - Eileen Hsich
- Department of Cardiology, Cleveland Clinic, Cleveland, Ohio, USA
| | - Adam P Bress
- Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Joshua Jacobs
- Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Ramachandran S Vasan
- School of Public Health, Department of Population Health, and Division of Cardiology, Long School of Medicine, University of Texas San Antonio, San Antonio, Texas, USA
| | - Gregg C Fonarow
- Division of Cardiology, David Geffen School of Medicine, University of California, Los Angeles Medical Center, Los Angeles, California, USA
| | - Ambarish Pandey
- Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
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King JB, Berchie RO, Derington CG, Marcum ZA, Scharfstein DO, Greene TH, Herrick JS, Jacobs JA, Zheutlin AR, Bress AP, Cohen JB. New Users of Angiotensin II Receptor Blocker-Versus Angiotensin-Converting Enzyme Inhibitor-Based Antihypertensive Medication Regimens and Cardiovascular Disease Events: A Secondary Analysis of ACCORD-BP and SPRINT. J Am Heart Assoc 2023; 12:e030311. [PMID: 37646208 PMCID: PMC10547357 DOI: 10.1161/jaha.123.030311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 08/01/2023] [Indexed: 09/01/2023]
Abstract
BACKGROUND Angiotensin II receptor blockers (ARBs) and angiotensin-converting enzyme inhibitors (ACEIs) block distinct components of the renin-angiotensin system. Whether this translates into differential effects on cardiovascular disease events remains unclear. METHODS AND RESULTS We used the ACCORD-BP (Action to Control Cardiovascular Risk in Diabetes-Blood Pressure) trial and the SPRINT (Systolic Blood Pressure Intervention Trial) to emulate target trials of new users of ARBs versus ACEIs on cardiovascular disease events (primary outcome) and death (secondary outcome). We estimated marginal cause-specific hazard ratios (HRs) and treatment-specific cumulative incidence functions with inverse probability of treatment weights. We identified 3298 new users of ARBs or ACEIs (ACCORD-BP: 374 ARB versus 884 ACEI; SPRINT: 727 ARB versus 1313 ACEI). For participants initiating ARBs versus ACEIs, the inverse probability of treatment weight rate of the primary outcome was 3.2 versus 3.5 per 100 person-years in ACCORD-BP (HR, 0.91 [95% CI, 0.63-1.31]) and 1.8 versus 2.2 per 100 person-years in SPRINT (HR, 0.81 [95% CI, 0.56-1.18]). There were no appreciable differences in pooled analyses, except that ARBs versus ACEIs were associated with a lower death rate (HR, 0.56 [95% CI, 0.37-0.85]). ARBs were associated with a lower rate of the primary outcome among subgroups of male versus female participants, non-Hispanic Black versus non-Hispanic White participants, and those randomly assigned to standard versus intensive blood pressure (Pinteraction: <0.01, 0.05, and <0.01, respectively). CONCLUSIONS In this secondary analysis of ACCORD-BP and SPRINT, new users of ARB- versus ACEI-based antihypertensive medication regimens experienced similar cardiovascular disease events rates, with important subgroup differences and lower rates of death overall. REGISTRATION URL: https://www.clinicaltrials.gov; Unique identifiers: NCT01206062, NCT00000620.
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Affiliation(s)
- Jordan B. King
- Intermountain Healthcare Department of Population Health SciencesUniversity of Utah Spencer Fox Eccles School of MedicineUTSalt Lake CityUSA
- Institute for Health ResearchKaiser Permanente ColoradoCOAuroraUSA
| | - Ransmond O. Berchie
- Intermountain Healthcare Department of Population Health SciencesUniversity of Utah Spencer Fox Eccles School of MedicineUTSalt Lake CityUSA
| | - Catherine G. Derington
- Intermountain Healthcare Department of Population Health SciencesUniversity of Utah Spencer Fox Eccles School of MedicineUTSalt Lake CityUSA
| | - Zachary A. Marcum
- Department of Pharmacy, School of PharmacyUniversity of WashingtonWASeattleUSA
| | - Daniel O. Scharfstein
- Intermountain Healthcare Department of Population Health SciencesUniversity of Utah Spencer Fox Eccles School of MedicineUTSalt Lake CityUSA
| | - Tom H. Greene
- Intermountain Healthcare Department of Population Health SciencesUniversity of Utah Spencer Fox Eccles School of MedicineUTSalt Lake CityUSA
- Department of Internal MedicineUniversity of Utah Spencer Fox Eccles School of MedicineUTSalt Lake CityUSA
| | - Jennifer S. Herrick
- Department of Internal MedicineUniversity of Utah Spencer Fox Eccles School of MedicineUTSalt Lake CityUSA
| | - Joshua A. Jacobs
- Intermountain Healthcare Department of Population Health SciencesUniversity of Utah Spencer Fox Eccles School of MedicineUTSalt Lake CityUSA
| | - Alexander R. Zheutlin
- Division of CardiologyFeinberg School of Medicine, Northwestern UniversityChicagoILUSA
| | - Adam P. Bress
- Intermountain Healthcare Department of Population Health SciencesUniversity of Utah Spencer Fox Eccles School of MedicineUTSalt Lake CityUSA
| | - Jordana B. Cohen
- Department of Medicine, Renal‐Electrolyte and Hypertension DivisionPerelman School of Medicine at the University of PennsylvaniaPAPhiladelphiaUSA
- Department of Biostatistics, Epidemiology, and InformaticsPerelman School of Medicine, University of PennsylvaniaPAPhiladelphiaUSA
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Zheutlin AR, Jacobs JA, Derington CG, Chaitoff A, Navar AM, Bress AP. Age-based disparities in statin use for primary prevention in US adults: National Health and Nutrition Examination Surveys 2013-2020. J Clin Lipidol 2023; 17:688-693. [PMID: 37599197 DOI: 10.1016/j.jacl.2023.08.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 07/31/2023] [Accepted: 08/07/2023] [Indexed: 08/22/2023]
Abstract
Statin use among younger adults at high atherosclerotic cardiovascular disease (ASCVD) risk compared with older adults at the same risk is unclear. We determined prevalent statin use by 10-year ASCVD risk and age among US participants aged 40-75 eligible for risk-indicated primary prevention statins from the 2013-2020 National Health and Nutrition Examination Survey cycles. Among 3,503 participants, statin use by ASCVD risk (5-<7.5%, 7.5-<20%, and ≥20%) was 9.4%, 9.0%, and 12.2% among those age 40-54 compared to 22.0%, 23.9%, and 14.3% among adults 55-64 years and 39.3%, 33.6%, and 38.1% age 65-75 years. After adjusting for sociodemographic and healthcare access, the prevalence ratio (vs. 65-75 years) for statin use among adults with an ASCVD risk of 7.5-<20% age 40-54 years was 0.40 (95% confidence interval [CI] 0.39,0.41) and 0.87 (95% CI 0.87,0.88) for adults 55-64 years. Among high ASCVD-risk adults aged 40-75 years, primary prevention statin use was lower among adults <65 years despite similar ASCVD risk as older adults.
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Affiliation(s)
- Alexander R Zheutlin
- Division of Cardiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
| | - Joshua A Jacobs
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, UT, USA
| | - Catherine G Derington
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, UT, USA
| | - Alexander Chaitoff
- Center for Healthcare Delivery Science, Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital/Harvard Medical School, Boston, MA, USA
| | - Ann Marie Navar
- Division of Cardiology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Adam P Bress
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, UT, USA
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Derington CG, Bress AP, Berchie RO, Herrick JS, Shen J, Ying J, Greene T, Tajeu GS, Sakhuja S, Ruiz-Negrón N, Zhang Y, Howard G, Levitan EB, Muntner P, Safford MM, Whelton PK, Weintraub WS, Moran AE, Bellows BK. Estimated Population Health Benefits of Intensive Systolic Blood Pressure Treatment Among SPRINT-Eligible US Adults. Am J Hypertens 2023; 36:498-508. [PMID: 37378472 PMCID: PMC10403972 DOI: 10.1093/ajh/hpad047] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 04/06/2023] [Accepted: 05/11/2023] [Indexed: 06/29/2023] Open
Abstract
BACKGROUND The Systolic Blood Pressure Intervention Trial (SPRINT) demonstrated an intensive (<120 mm Hg) vs. standard (<140 mm Hg) systolic blood pressure (SBP) goal lowered cardiovascular disease (CVD) risk. Estimating the effect of intensive SBP lowering among SPRINT-eligible adults most likely to benefit can guide implementation efforts. METHODS We studied SPRINT participants and SPRINT-eligible participants in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) Study and National Health and Nutrition Examination Surveys (NHANES). A published algorithm of predicted CVD benefit with intensive SBP treatment was used to categorize participants into low, medium, or high predicted benefit. CVD event rates were estimated with intensive and standard treatment. RESULTS Median age was 67.0, 72.0, and 64.0 years in SPRINT, SPRINT-eligible REGARDS, and SPRINT-eligible NHANES participants, respectively. The proportion with high predicted benefit was 33.0% in SPRINT, 39.0% in SPRINT-eligible REGARDS, and 23.5% in SPRINT-eligible NHANES. The estimated difference in CVD event rate (standard minus intensive) was 7.0 (95% confidence interval [CI] 3.4-10.7), 8.4 (95% CI 8.2-8.5), and 6.1 (95% CI 5.9-6.3) per 1,000 person-years in SPRINT, SPRINT-eligible REGARDS participants, and SPRINT-eligible NHANES participants, respectively (median 3.2-year follow-up). Intensive SBP treatment could prevent 84,300 (95% CI 80,800-87,920) CVD events per year in 14.1 million SPRINT-eligible US adults; 29,400 and 28,600 would be in 7.0 million individuals with medium or high predicted benefit, respectively. CONCLUSIONS Most of the population health benefit from intensive SBP goals could be achieved by treating those characterized by a previously published algorithm as having medium or high predicted benefit.
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Affiliation(s)
- Catherine G Derington
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Adam P Bress
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Ransmond O Berchie
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Jennifer S Herrick
- Department of Internal Medicine, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Jincheng Shen
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Jian Ying
- Department of Internal Medicine, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Tom Greene
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Gabriel S Tajeu
- Department of Health Services Administration and Policy, Temple University, Philadelphia, Pennsylvania, USA
| | - Swati Sakhuja
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Natalia Ruiz-Negrón
- Department of Pharmacotherapy, University of Utah College of Pharmacy, Salt Lake City, Utah, USA
| | - Yiyi Zhang
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - George Howard
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Emily B Levitan
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Paul Muntner
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Monika M Safford
- Department of Medicine, Weill Cornell Medical College, New York, New York, USA
| | - Paul K Whelton
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, USA
| | - William S Weintraub
- Department of Medicine, Georgetown University, Washington, District of Columbia, USA
- MedStar Health Research Institute, Washington, District of Columbia, USA
| | - Andrew E Moran
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Brandon K Bellows
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
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12
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King JB, Derington CG, Herrick JS, Jacobs JA, Zheutlin AR, Conroy MB, Cushman WC, Bress AP. Single-Pill Combination Product Availability of the Antihypertensive Regimens Used for Intensive Systolic Blood Pressure Treatment in the Systolic Blood Pressure Intervention Trial. Hypertension 2023; 80:1749-1758. [PMID: 37288570 PMCID: PMC10483993 DOI: 10.1161/hypertensionaha.123.21132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 05/19/2023] [Indexed: 06/09/2023]
Abstract
BACKGROUND Single-pill combination (SPC) antihypertensive products improve blood pressure control and medication adherence among patients with hypertension. It is unknown to what degree commercially available SPC products could be used to target an intensive systolic blood pressure goal of <120 mm Hg. METHODS This cross-sectional analysis included participants randomized to the intensive treatment arm (goal systolic blood pressure <120 mm Hg) of the Systolic Blood Pressure Intervention Trial (SPRINT) using ≥2 antihypertensive medication classes at the 12-month postrandomization visit. Antihypertensive medication data were collected using pill bottle review by research coordinators, and regimens were categorized by the unique combinations of antihypertensive classes. We calculated the proportion of regimens used, which are commercially available as one of the 7 SPC class combinations in the United States as of January 2023. RESULTS Among the 3833 SPRINT intensive arm participants included (median age, 67.0 years; 35.5% female), participants were using 219 unique antihypertensive regimens. The 7 regimens for which there are class-equivalent SPC products were used by 40.3% of participants. Only 3.2% of all medication class regimens used are available as a class-equivalent SPC product (7/219). There are no SPC products available with 4 or more medication classes, which were used by 1060 participants (27.7%). CONCLUSIONS Most SPRINT participants in the intensive arm used an antihypertensive medication regimen, which is not commercially available as a class equivalent SPC product. To achieve the SPRINT results in real-world settings, maximize the potential benefit of SPCs, and reduce pill burden, improvements in the product landscape are needed. REGISTRATION URL: https://www. CLINICALTRIALS gov/ct2/show/NCT01206062; Unique identifier: NCT01206062.
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Affiliation(s)
- Jordan B King
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City (J.B.K., C.G.D., J.A.J., M.B.C., A.P.B.)
- Institute for Health Research, Kaiser Permanente Colorado, Aurora (J.B.K.)
| | - Catherine G Derington
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City (J.B.K., C.G.D., J.A.J., M.B.C., A.P.B.)
| | - Jennifer S Herrick
- Department of Internal Medicine, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City (J.S.H., A.R.Z., M.B.C.)
| | - Joshua A Jacobs
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City (J.B.K., C.G.D., J.A.J., M.B.C., A.P.B.)
| | - Alexander R Zheutlin
- Department of Internal Medicine, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City (J.S.H., A.R.Z., M.B.C.)
| | - Molly B Conroy
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City (J.B.K., C.G.D., J.A.J., M.B.C., A.P.B.)
- Department of Internal Medicine, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City (J.S.H., A.R.Z., M.B.C.)
| | - William C Cushman
- Department of Preventative Medicine, University of Tennessee Health Science Center, Memphis, TN (W.C.C.)
| | - Adam P Bress
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City (J.B.K., C.G.D., J.A.J., M.B.C., A.P.B.)
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13
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Zheutlin AR, Addo DK, Jacobs JA, Derington CG, Herrick JS, Greene T, Stulberg EL, Berlowitz DR, Williamson JD, Pajewski NM, Supiano MA, Bress AP. Evidence for Age Bias Contributing to Therapeutic Inertia in Blood Pressure Management: A Secondary Analysis of SPRINT. Hypertension 2023; 80:1484-1493. [PMID: 37165900 PMCID: PMC10438422 DOI: 10.1161/hypertensionaha.123.21323] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 04/25/2023] [Indexed: 05/12/2023]
Abstract
BACKGROUND Despite evidence supporting the cardiovascular and cognitive benefits of intensive blood pressure management, older adults have the lowest rates of blood pressure control. We determined the association between age and therapeutic inertia (TI) in SPRINT (Systolic Blood Pressure Intervention Trial), and whether frailty, cognitive function, or gait speed moderate or mediate these associations. METHODS We performed a secondary analysis of SPRINT of participant visits with blood pressure above randomized treatment goal. We categorized baseline age as <60, 60 to <70, 70 to <80, and ≥80 years and TI as no antihypertensive medication intensification per participant visit. Generalized estimating equations generated odds ratios for TI associated with age, stratified by treatment group based on nested models adjusted for baseline frailty index score (fit [frailty index, ≤0.10], less fit [0.10 RESULTS Participants 60 to <70, 70 to <80, and ≥80 years of age had a higher prevalence of TI in both treatment groups versus participants <60 years of age (standard: 59.7%, 60.5%, and 60.1% versus 56.0%; 29 527 participant visits; intensive: 55.1%, 57.2%, and 57.8% versus 53.8%; 47 129 participant visits). The adjusted odds ratios for TI comparing participants ≥80 versus <60 years of age were 1.32 (95% CI, 1.14-1.53) and 1.25 (95% CI, 1.11-1.41) in the standard and intensive treatment groups, respectively. Adjustment for frailty, cognitive function, or gait speed did not attenuate the association or demonstrate effect modification (all Pinteraction, >0.10). CONCLUSIONS Older age is associated with greater TI independent of physical or cognitive function, implying age bias in hypertension management.
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Affiliation(s)
- Alexander R Zheutlin
- Department of Internal Medicine (A.R.Z.), Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Daniel K Addo
- Intermountain Healthcare Department of Population Health Sciences (D.K.A., J.A.J., C.G.D., J.S.H., T.G., A.P.B.), Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Joshua A Jacobs
- Intermountain Healthcare Department of Population Health Sciences (D.K.A., J.A.J., C.G.D., J.S.H., T.G., A.P.B.), Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Catherine G Derington
- Intermountain Healthcare Department of Population Health Sciences (D.K.A., J.A.J., C.G.D., J.S.H., T.G., A.P.B.), Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Jennifer S Herrick
- Intermountain Healthcare Department of Population Health Sciences (D.K.A., J.A.J., C.G.D., J.S.H., T.G., A.P.B.), Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
- Informatics, Decision-Enhancement, and Analytic Sciences Center, Veterans Affairs, Salt Lake City Health Care System, Utah (J.S.H., A.P.B.)
| | - Tom Greene
- Intermountain Healthcare Department of Population Health Sciences (D.K.A., J.A.J., C.G.D., J.S.H., T.G., A.P.B.), Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Eric L Stulberg
- Department of Neurology (E.L.S.), Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Dan R Berlowitz
- Department of Public Health, University of Massachusetts-Lowell (D.R.B.)
| | - Jeff D Williamson
- Section on Gerontology and Geriatric Medicine, Department of Internal Medicine (J.D.W.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Nicholas M Pajewski
- Department of Biostatistics and Data Science, Division of Public Health Sciences (N.M.P.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Mark A Supiano
- Geriatrics Division, Spencer Fox Eccles School of Medicine, University of Utah Center on Aging, Salt Lake City (M.A.S.)
| | - Adam P Bress
- Intermountain Healthcare Department of Population Health Sciences (D.K.A., J.A.J., C.G.D., J.S.H., T.G., A.P.B.), Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
- Informatics, Decision-Enhancement, and Analytic Sciences Center, Veterans Affairs, Salt Lake City Health Care System, Utah (J.S.H., A.P.B.)
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Muntner P, Foti K, Wang Z, Alanaeme CJ, Choi E, Bress AP, Shimbo D, Kronish I. Discontinuation of Renin-Angiotensin System Inhibitors During the Early Stage of the COVID-19 Pandemic. Am J Hypertens 2023; 36:404-410. [PMID: 36960855 PMCID: PMC10267613 DOI: 10.1093/ajh/hpad027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 03/01/2023] [Accepted: 03/20/2023] [Indexed: 03/25/2023] Open
Abstract
BACKGROUND In March and April 2020, medical societies published statements recommending continued use of renin-angiotensin system (RAS) inhibitors despite theoretical concerns that these medications could increase COVID-19 severity. Determining if patients discontinued RAS inhibitors during the COVID-19 pandemic could inform responses to future public health emergencies. METHODS We analyzed claims data from US adults with health insurance in the Marketscan database. We identified patients who filled a RAS inhibitor and were persistent, defined by not having a ≥30-day gap without medication available, and high adherence, defined by having medication available on ≥80% of days, from March 2019 to February 2020. Among these patients, we estimated the proportion who discontinued their RAS inhibitor (i.e., had ≥30 consecutive days without a RAS inhibitor available to take) between March and August 2020. For comparison, we estimated the proportion of patients that discontinued a RAS inhibitor between March and August 2019 after being persistent with high adherence from March 2018 to February 2019. RESULTS Among 816,380 adults who were persistent and adherent to a RAS inhibitor from March 2019 to February 2020, 10.8% discontinued this medication between March and August 2020. Among 822,873 adults who were persistent and adherent to a RAS inhibitor from March 2018 to February 2019, 11.7% discontinued this medication between March and August 2019. The multivariable-adjusted relative risk for RAS inhibitor discontinuation in 2020 vs. 2019 was 0.94 (95% CI 0.93-0.95). CONCLUSIONS There was no evidence of an increase in RAS inhibitor discontinuation during the early stage of the COVID-19 pandemic.
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Affiliation(s)
- Paul Muntner
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Kathryn Foti
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Zhixin Wang
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Chibuike J Alanaeme
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Eunhee Choi
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Adam P Bress
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Daichi Shimbo
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Ian Kronish
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
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15
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Derington CG, Bress AP, Herrick JS, Jacobs JA, Zheutlin AR, Berchie RO, Conroy MB, Cushman WC, King JB. Antihypertensive Medication Regimens Used by US Adults With Hypertension and the Potential for Fixed-Dose Combination Products: The National Health and Nutrition Examination Surveys 2015 to 2020. J Am Heart Assoc 2023; 12:e028573. [PMID: 37158068 PMCID: PMC10381985 DOI: 10.1161/jaha.122.028573] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 03/20/2023] [Indexed: 05/10/2023]
Abstract
Background Fixed-dose combination (FDC) antihypertensive products improve blood pressure control and adherence among patients with hypertension. It is unknown to what degree commercially available FDC products meet the current hypertension management prescription patterns in the United States. Methods and Results This cross-sectional analysis of the National Health and Nutrition Examination Surveys 2015 to March 2020 included participants with hypertension taking ≥2 antihypertensive medications (N=2451). After constructing each participant's regimen according to antihypertensive classes used, we estimated the extent to which the 7 class-level FDC regimens available in the United States as of January 2023 would match the regimens used. Among a weighted population of 34.1 million US adults (mean age, 66.0 years; 52.8% women; 69.1% non-Hispanic White race and ethnicity), the proportions using 2, 3, 4, and ≥5 antihypertensive classes were 60.6%, 28.2%, 9.1%, and 1.6%, respectively. The 7 FDC regimens were among 189 total regimens used (3.7%), and 39.2% of the population used one of the FDC regimens (95% CI, 35.5%-43.0%; 13.4 million US adults); 60.8% of the population (95% CI, 57.0%-64.5%; 20.7 million US adults) were using a regimen not available as a class-equivalent FDC product. Conclusions Three in 5 US adults with hypertension taking ≥2 antihypertensive classes are using a regimen that is not commercially available as a class-equivalent FDC product as of January 2023. To maximize the potential benefit of FDCs to improve medication adherence (and thus blood pressure control) among patients taking multiple antihypertensive medications, use of FDC-compatible regimens and improvements in the product landscape are needed.
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Affiliation(s)
- Catherine G. Derington
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of MedicineUniversity of UtahSalt Lake CityUTUSA
| | - Adam P. Bress
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of MedicineUniversity of UtahSalt Lake CityUTUSA
| | - Jennifer S. Herrick
- Department of Internal Medicine, Spencer Fox Eccles School of MedicineUniversity of UtahSalt Lake CityUTUSA
| | - Joshua A. Jacobs
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of MedicineUniversity of UtahSalt Lake CityUTUSA
| | - Alexander R. Zheutlin
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of MedicineUniversity of UtahSalt Lake CityUTUSA
- Department of Internal Medicine, Spencer Fox Eccles School of MedicineUniversity of UtahSalt Lake CityUTUSA
| | - Ransmond O. Berchie
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of MedicineUniversity of UtahSalt Lake CityUTUSA
- Department of Internal Medicine, Spencer Fox Eccles School of MedicineUniversity of UtahSalt Lake CityUTUSA
| | - Molly B. Conroy
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of MedicineUniversity of UtahSalt Lake CityUTUSA
- Department of Internal Medicine, Spencer Fox Eccles School of MedicineUniversity of UtahSalt Lake CityUTUSA
| | - William C. Cushman
- Department of Preventive MedicineUniversity of Tennessee Health Science CenterTNMemphisUSA
| | - Jordan B. King
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of MedicineUniversity of UtahSalt Lake CityUTUSA
- Institute for Health Research, Kaiser Permanente ColoradoAuroraCOUSA
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16
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Jaeger BC, Chen L, Foti K, Hardy ST, Bress AP, Kane SP, Huang L, Herrick JS, Derington CG, Poudel B, Christenson A, Colantonio LD, Muntner P. Hypertension Statistics for US Adults: An Open-Source Web Application for Analysis and Visualization of National Health and Nutrition Examination Survey Data. Hypertension 2023; 80:1311-1320. [PMID: 37082970 PMCID: PMC10424908 DOI: 10.1161/hypertensionaha.123.20900] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 03/27/2023] [Indexed: 04/22/2023]
Abstract
BACKGROUND Data from the US National Health and Nutrition Examination Survey are freely available and can be analyzed to produce hypertension statistics for the noninstitutionalized US population. The analysis of these data requires statistical programming expertise and knowledge of National Health and Nutrition Examination Survey methodology. METHODS We developed a web-based application that provides hypertension statistics for US adults using 10 cycles of National Health and Nutrition Examination Survey data, 1999 to 2000 through 2017 to 2020. We validated the application by reproducing results from prior publications. The application's interface allows users to estimate crude and age-adjusted means, quantiles, and proportions. Population counts can also be estimated. To demonstrate the application's capabilities, we estimated hypertension statistics for noninstitutionalized US adults. RESULTS The estimated mean systolic blood pressure (BP) declined from 123 mm Hg in 1999 to 2000 to 120 mm Hg in 2009 to 2010 and increased to 123 mm Hg in 2017 to 2020. The age-adjusted prevalence of hypertension (ie, systolic BP≥130 mm Hg, diastolic BP≥80 mm Hg or self-reported antihypertensive medication use) was 47.9% in 1999 to 2000, 43.0% in 2009 to 2010, and 44.7% in 2017 to 2020. In 2017 to 2020, an estimated 115.3 million US adults had hypertension. The age-adjusted prevalence of controlled BP, defined by the 2017 American College of Cardiology/American Heart Association BP guideline, among nonpregnant US adults with hypertension was 9.7% in 1999 to 2000, 25.0% in 2013 to 2014, and 21.9% in 2017 to 2020. After age adjustment and among nonpregnant US adults who self-reported taking antihypertensive medication, 27.5%, 48.5%, and 43.0% had controlled BP in 1999 to 2000, 2013 to 2014, and 2017 to 2020, respectively. CONCLUSIONS The application developed in the current study is publicly available at https://bcjaeger.shinyapps.io/nhanesShinyBP/ and produced valid, transparent and reproducible results.
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Affiliation(s)
- Byron C Jaeger
- Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, NC (B.C.J.)
| | - Ligong Chen
- Department of Epidemiology, University of Alabama at Birmingham (L.C., K.F., S.T.H., L.H., B.P., A.C., L.D.C., P.M.)
| | - Kathryn Foti
- Department of Epidemiology, University of Alabama at Birmingham (L.C., K.F., S.T.H., L.H., B.P., A.C., L.D.C., P.M.)
| | - Shakia T Hardy
- Department of Epidemiology, University of Alabama at Birmingham (L.C., K.F., S.T.H., L.H., B.P., A.C., L.D.C., P.M.)
| | - Adam P Bress
- Informatics, Decision-Enhancement, and Analytic Sciences (IDEAS) Center, Veterans Affairs, Salt Lake City Health Care System, UT (A.P.B., J.S.H.)
- Intermountain Healthcare Department of Population Health Sciences (A.P.B., C.G.D.), Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Sean P Kane
- Department of Pharmacy Practice, Rosalind Franklin University of Medicine and Science, North Chicago, IL (S.P.K.)
| | - Lei Huang
- Department of Epidemiology, University of Alabama at Birmingham (L.C., K.F., S.T.H., L.H., B.P., A.C., L.D.C., P.M.)
| | - Jennifer S Herrick
- Informatics, Decision-Enhancement, and Analytic Sciences (IDEAS) Center, Veterans Affairs, Salt Lake City Health Care System, UT (A.P.B., J.S.H.)
- Department of Internal Medicine (J.S.H.), Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Catherine G Derington
- Intermountain Healthcare Department of Population Health Sciences (A.P.B., C.G.D.), Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Bharat Poudel
- Department of Epidemiology, University of Alabama at Birmingham (L.C., K.F., S.T.H., L.H., B.P., A.C., L.D.C., P.M.)
| | - Ashley Christenson
- Department of Epidemiology, University of Alabama at Birmingham (L.C., K.F., S.T.H., L.H., B.P., A.C., L.D.C., P.M.)
| | - Lisandro D Colantonio
- Department of Epidemiology, University of Alabama at Birmingham (L.C., K.F., S.T.H., L.H., B.P., A.C., L.D.C., P.M.)
| | - Paul Muntner
- Department of Epidemiology, University of Alabama at Birmingham (L.C., K.F., S.T.H., L.H., B.P., A.C., L.D.C., P.M.)
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Ghazi L, Shen J, Ying J, Derington CG, Cohen JB, Marcum ZA, Herrick JS, King JB, Cheung AK, Williamson JD, Pajewski NM, Bryan N, Supiano M, Sonnen J, Weintraub WS, Greene TH, Bress AP. Identifying Patients for Intensive Blood Pressure Treatment Based on Cognitive Benefit: A Secondary Analysis of the SPRINT Randomized Clinical Trial. JAMA Netw Open 2023; 6:e2314443. [PMID: 37204788 PMCID: PMC10199351 DOI: 10.1001/jamanetworkopen.2023.14443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 03/25/2023] [Indexed: 05/20/2023] Open
Abstract
Importance Intensive vs standard treatment to lower systolic blood pressure (SBP) reduces risk of mild cognitive impairment (MCI) or dementia; however, the magnitude of cognitive benefit likely varies among patients. Objective To estimate the magnitude of cognitive benefit of intensive vs standard systolic BP (SBP) treatment. Design, Setting, and Participants In this ad hoc secondary analysis of the Systolic Blood Pressure Intervention Trial (SPRINT), 9361 randomized clinical trial participants 50 years or older with high cardiovascular risk but without a history of diabetes, stroke, or dementia were followed up. The SPRINT trial was conducted between November 1, 2010, and August 31, 2016, and the present analysis was completed on October 31, 2022. Intervention Systolic blood pressure treatment to an intensive (<120 mm Hg) vs standard (<140 mm Hg) target. Main Outcomes and Measures The primary outcome was a composite of adjudicated probable dementia or amnestic MCI. Results A total of 7918 SPRINT participants were included in the analysis; 3989 were in the intensive treatment group (mean [SD] age, 67.9 [9.2] years; 2570 [64.4%] men; 1212 [30.4%] non-Hispanic Black) and 3929 were in the standard treatment group (mean [SD] age, 67.9 [9.4] years; 2570 [65.4%] men; 1249 [31.8%] non-Hispanic Black). Over a median follow-up of 4.13 (IQR, 3.50-5.88) years, there were 765 and 828 primary outcome events in the intensive treatment group and standard treatment group, respectively. Older age (hazard ratio [HR] per 1 SD, 1.87 [95% CI, 1.78-1.96]), Medicare enrollment (HR per 1 SD, 1.42 [95% CI, 1.35-1.49]), and higher baseline serum creatinine level (HR per 1 SD, 1.24 [95% CI, 1.19-1.29]) were associated with higher risk of the primary outcome, while better baseline cognitive functioning (HR per 1 SD, 0.43 [95% CI, 0.41-0.44]) and active employment status (HR per 1 SD, 0.44 [95% CI, 0.42-0.46]) were associated with lower risk of the primary outcome. Risk of the primary outcome by treatment goal was estimated accurately based on similar projected and observed absolute risk differences (C statistic = 0.79). Higher baseline risk for the primary outcome was associated with greater benefit (ie, larger absolute reduction of probable dementia or amnestic MCI) of intensive vs standard treatment across the full range of estimated baseline risk. Conclusions and Relevance In this secondary analysis of the SPRINT trial, participants with higher baseline projected risk of probable dementia or amnestic MCI gained greater absolute cognitive benefit from intensive vs standard SBP treatment in a monotonic fashion. Trial Registration ClinicalTrials.gov Identifier: NCT01206062.
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Affiliation(s)
- Lama Ghazi
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham
| | - Jincheng Shen
- Department of Family and Preventive Medicine, University of Utah, Salt Lake City
| | - Jian Ying
- Department of Internal Medicine, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Catherine G. Derington
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Jordana B. Cohen
- Department of Medicine, Renal-Electrolyte and Hypertension Division, Perelman School of Medicine at the University of Pennsylvania, Philadelphia
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Zachary A. Marcum
- Department of Pharmacy, University of Washington School of Pharmacy, Seattle
| | - Jennifer S. Herrick
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, Utah
| | - Jordan B. King
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
- Institute for Health Research, Kaiser Permanente Colorado, Aurora
| | - Alfred K. Cheung
- Department of Internal Medicine, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, Utah
| | - Jeff D. Williamson
- The Sticht Center for Healthy Aging and Alzheimer’s Prevention, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Nicholas M. Pajewski
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Nick Bryan
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Mark Supiano
- Division of Geriatrics, University of Utah School of Medicine, and The Center on Aging, University of Utah, Salt Lake City
| | - Josh Sonnen
- Department of Pathology and Neurology and Neurosurgery, McGill University School of Medicine, Montreal, Quebec, Canada
| | | | - Tom H. Greene
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Adam P. Bress
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, Utah
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18
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Jacobs JA, Addo DK, Zheutlin AR, Derington CG, Essien UR, Navar AM, Hernandez I, Lloyd-Jones DM, King JB, Rao S, Herrick JS, Bress AP, Pandey A. Prevalence of Statin Use for Primary Prevention of Atherosclerotic Cardiovascular Disease by Race, Ethnicity, and 10-Year Disease Risk in the US: National Health and Nutrition Examination Surveys, 2013 to March 2020. JAMA Cardiol 2023; 8:443-452. [PMID: 36947031 PMCID: PMC10034667 DOI: 10.1001/jamacardio.2023.0228] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 01/25/2023] [Indexed: 03/23/2023]
Abstract
Importance The burden of atherosclerotic cardiovascular disease (ASCVD) in the US is higher among Black and Hispanic vs White adults. Inclusion of race in guidance for statin indication may lead to decreased disparities in statin use. Objective To evaluate prevalence of primary prevention statin use by race and ethnicity according to 10-year ASCVD risk. Design, Setting, and Participants This serial, cross-sectional analysis performed in May 2022 used data from the National Health and Nutrition Examination Survey, a nationally representative sample of health status in the US, from 2013 to March 2020 (limited cycle due to the COVID-19 pandemic), to evaluate statin use for primary prevention of ASCVD and to estimate 10-year ASCVD risk. Participants aged 40 to 75 years without ASCVD, diabetes, low-density lipoprotein cholesterol levels 190 mg/dL or greater, and with data on medication use were included. Exposures Self-identified race and ethnicity (Asian, Black, Hispanic, and White) and 10-year ASCVD risk category (5%-<7.5%, 7.5%-<20%, ≥20%). Main Outcomes and Measures Prevalence of statin use, defined as identification of statin use on pill bottle review. Results A total of 3417 participants representing 39.4 million US adults after applying sampling weights (mean [SD] age, 61.8 [8.0] years; 1289 women [weighted percentage, 37.8%] and 2128 men [weighted percentage, 62.2%]; 329 Asian [weighted percentage, 4.2%], 1032 Black [weighted percentage, 12.7%], 786 Hispanic [weighted percentage, 10.1%], and 1270 White [weighted percentage, 73.0%]) were included. Compared with White participants, statin use was lower in Black and Hispanic participants and comparable among Asian participants in the overall cohort (Asian, 25.5%; Black, 20.0%; Hispanic, 15.4%; White, 27.9%) and within ASCVD risk strata. Within each race and ethnicity group, a graded increase in statin use was observed across increasing ASCVD risk strata. Statin use was low in the highest risk stratum overall with significantly lower rates of use among Black (23.8%; prevalence ratio [PR], 0.90; 95% CI, 0.82-0.98 vs White) and Hispanic participants (23.9%; PR, 0.90; 95% CI, 0.81-0.99 vs White). Among other factors, routine health care access and health insurance were significantly associated with higher statin use in Black, Hispanic, and White adults. Prevalence of statin use did not meaningfully change over time by race and ethnicity or by ASCVD risk stratum. Conclusions and Relevance In this study, statin use for primary prevention of ASCVD was low among all race and ethnicity groups regardless of ASCVD risk, with the lowest use occurring among Black and Hispanic adults. Improvements in access to care may promote equitable use of primary prevention statins in Black and Hispanic adults.
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Affiliation(s)
- Joshua A. Jacobs
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Daniel K. Addo
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Alexander R. Zheutlin
- Department of Internal Medicine, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Catherine G. Derington
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Utibe R. Essien
- Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine at the University of California, Los Angeles
- Center for the Study of Healthcare Innovation, Implementation & Policy, Greater Los Angeles VA Healthcare System, Los Angeles, California
| | - Ann Marie Navar
- Division of Cardiology, University of Texas Southwestern Medical Center, Dallas
- Deputy Editor, Diversity, Equity, and Inclusion, JAMA Cardiology
| | | | - Donald M. Lloyd-Jones
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Jordan B. King
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
- Institute for Health Research, Kaiser Permanente Colorado, Aurora
| | - Shreya Rao
- Division of Cardiology, University of Texas Southwestern Medical Center, Dallas
| | - Jennifer S. Herrick
- Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City
| | - Adam P. Bress
- Intermountain Healthcare Department of Population Health Sciences, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Ambarish Pandey
- Division of Cardiology, University of Texas Southwestern Medical Center, Dallas
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19
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Derington CG, Bress AP, Moran AE, Weintraub WS, Herrick JS, Cushman WC, Kronish IM, Stults B, Shimbo D, Muntner P, Greene T, Bates JT, Chang TI, Katz LA, Rehman SU, Roumie CL, Tamariz L, King JB. Antihypertensive Medication Regimens Used in the Systolic Blood Pressure Intervention Trial. Hypertension 2023; 80:590-597. [PMID: 36519451 PMCID: PMC9931643 DOI: 10.1161/hypertensionaha.122.20373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 11/25/2022] [Indexed: 12/23/2022]
Abstract
BACKGROUND Describing the antihypertensive medication regimens used in the SPRINT (Systolic Blood Pressure Intervention Trial) would contextualize the standard and intensive systolic blood pressure (SBP) interventions and may inform future implementation efforts to achieve population-wide intensive SBP goals. METHODS We included SPRINT participants with complete medication data at the prerandomization and 12-month visits. Regimens were categorized by antihypertensive medication class. Analyses were stratified by treatment group (standard goal SBP <140 mm Hg versus intensive goal SBP <120 mm Hg). RESULTS Among 7860 participants (83.7% of 9361 randomized), the median number of classes used at the prerandomization visit was 2.0 and 2.0 in the standard and intensive groups (P=0.559). At 12-months, the median number of classes used was 3.0 and 2.0 in the intensive and standard groups (P<0.001). Prerandomization, angiotensin-converting enzyme inhibitor (ACE), or angiotensin-II receptor blocker (ARB) monotherapy was the most common regimen in the intensive and standard groups (12.6% versus 12.2%). At 12-months, ACE/ARB monotherapy was still the most common regimen among standard group participants (14.7%) and was used by 5.3% of intensive group participants. Multidrug regimens used by the intensive and standard participants at 12 months were as follows: an ACE/ARB with thiazide (12.2% and 7.9%); an ACE/ARB with calcium channel blocker (6.2% and 6.8%); an ACE/ARB, thiazide, and calcium channel blocker (11.4% and 4.3%); and an ACE/ARB, thiazide, calcium channel blocker, and beta-blocker (6.5% and 1.2%). CONCLUSIONS SPRINT investigators favored combining ACEs or ARBs, thiazide diuretics, and calcium channel blockers to target SBP <120 mm Hg, compared to ACE/ARB monotherapy to target SBP <140 mm Hg. REGISTRATION URL: https://clinicaltrials.gov; Unique identifier: NCT01206062.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Daichi Shimbo
- Columbia University Irving Medical Center, New York, NY
| | - Paul Muntner
- University of Alabama at Birmingham, Birmingham, AL
| | | | - Jeffrey T. Bates
- Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX
- Baylor College of Medicine, Houston, TX
| | - Tara I. Chang
- Stanford University School of Medicine, Stanford, CA
| | - Lois Anne Katz
- New York University Grossman School of Medicine, New York, NY
- VA New York Harbor Healthcare System, New York, NY
| | - Shakaib U. Rehman
- Phoenix Veterans Affairs Health Care Systems, Phoenix, AZ
- University of Arizona College of Medicine-Phoenix, Phoenix, AZ
| | - Christianne L. Roumie
- Vanderbilt University Medical Center, Nashville, TN
- VA Tennessee Valley Healthcare System Geriatric Research Education and Clinical Center, Nashville, TN
| | | | - Jordan B. King
- University of Utah, Salt Lake City, UT
- Institute for Health Research, Kaiser Permanente Colorado, Aurora, CO
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20
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Buckley LF, Baker WL, Van Tassell BW, Cohen JB, Alkhezi O, Bress AP, Dixon DL. Systolic Blood Pressure Time in Target Range and Major Adverse Kidney and Cardiovascular Events. Hypertension 2023; 80:305-313. [PMID: 36254738 PMCID: PMC9851984 DOI: 10.1161/hypertensionaha.122.20141] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 09/23/2022] [Indexed: 01/22/2023]
Abstract
BACKGROUND Whether time-in-target range (TTR) for systolic blood pressure (SBP) associates with adverse kidney and cardiovascular events remains incompletely understood. METHODS This study included participants in 2 clinical trials that compared intensive (<120 mm Hg) and standard (<140 mm Hg) SBP lowering. SBP-TTR for months 0 to 3 was calculated using therapeutic ranges of 110 to 130 mm Hg and 120 to 140 mm Hg for the intensive and standard arms, respectively. Adverse kidney events included the composite of dialysis, kidney transplant, serum creatinine >3.3 mg/dL, sustained eGFR <15 mL/(min·1.73 m2), or sustained eGFR decline >40%. Adverse cardiovascular events included myocardial infarction, stroke, heart failure, and cardiovascular death. Adjusted Cox proportional hazards regression models were used to estimate the association between SBP-TTR and kidney and cardiovascular events. RESULTS Participants with higher TTR were younger and less likely to have preexisting cardiovascular disease. Compared with participants with TTR of 0%, the risk of adverse kidney events was lower for participants with TTR of >0% to 43% (hazard ratio [95% CI], 0.57 [0.42-0.76]; P<0.001), 43% to <70% (0.57 [0.42-0.78]; P=0.001), 70% to <100% (0.53 [0.38-0.74]; P<0.001), and 100% (0.33 [0.20-0.57]; P<0.001) in fully adjusted models. The risk of major adverse cardiovascular events was lower for participants with TTR of >0% to 43% (0.66 [0.52-0.83]; P=0.001), 43% to <70% (0.70 [0.55-0.90]; P=0.005), 70% to <100% (0.65 [0.50-0.84]; P=0.001), or 100% (0.56 [0.39-0.80]; P=0.001) compared with those with TTR of 0%. CONCLUSIONS Higher SBP-TTR associates with lower risks of adverse kidney and cardiovascular events in adults with hypertension. SBP-TTR may be a potential therapeutic target and quality metric.
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Affiliation(s)
- Leo F. Buckley
- Department of Pharmacy Services, Brigham and Women’s Hospital, MA
| | | | | | | | - Omar Alkhezi
- Department of Pharmacy Services, Brigham and Women’s Hospital, MA
- Pharmacy Practice Department, Unaizah College of Pharmacy, Qassim University, Qassim, Saudi Arabia
| | | | - Dave L. Dixon
- Department of Pharmacotherapy and Outcomes Science, Virginia Commonwealth University, VA
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21
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Marcum ZA, Gabriel N, Bress AP, Hernandez I. Association of New Use of Antihypertensives That Stimulate vs Inhibit Type 2 and 4 Angiotensin II Receptors With Dementia Among Medicare Beneficiaries. JAMA Netw Open 2023; 6:e2249370. [PMID: 36598787 PMCID: PMC9856661 DOI: 10.1001/jamanetworkopen.2022.49370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 11/11/2022] [Indexed: 01/05/2023] Open
Abstract
Importance Prevalent use of antihypertensive medications that stimulate type 2 and 4 angiotensin II receptors, compared with those that do not stimulate these receptors, has been associated with a lower risk of dementia. However, previous studies were limited by inclusion of individuals with prevalent hypertension and a history of antihypertensive use prior to the start of the study, which can introduce bias. Objective To examine the association of new use of antihypertensive medication regimens that stimulate vs inhibit type 2 and 4 angiotensin II receptors with Alzheimer disease and related dementias (ADRD) among Medicare beneficiaries. Design, Setting, and Participants This cohort study was conducted among 57 773 Medicare fee-for-service beneficiaries (January 1, 2006, through December 31, 2018) aged 65 years or older with incident hypertension. Data analysis was conducted from January 1 through June 30, 2022. Exposures Initiation of antihypertensive medication regimens that stimulate or inhibit type 2 and 4 angiotensin II receptors, or mixed regimens (both stimulating and inhibiting), with the time-dependent measure being each 30-day interval. Main Outcomes and Measures The primary outcome was time to first occurrence of ADRD (Centers for Medicare & Medicaid Services Chronic Conditions Data Warehouse definition). Cox proportional hazards regression modeling with time-dependent variables was performed to estimate the association between time-dependent treatment groups and time to ADRD, after adjusting for sociodemographic and clinical characteristics. Results The sample included 57 773 Medicare beneficiaries (36 348 women [62.9%]; mean [SD] age, 73.8 [6.3] years; 2954 [5.1%] Black, 1545 [2.7%] Hispanic; 50 184 [86.9%] White, and 3090 [5.4%] Other individuals [the Other category included individuals of American Indian, Asian, other, or unknown race and ethnicity]). During a median of 6.9 years (IQR, 4.7-9.3 years) of follow-up, the unadjusted incidence density rate of ADRD was 2.2 cases per 100 person-years (95% CI, 2.1-2.4 cases per 100 person-years) for the group receiving regimens that stimulate type 2 and 4 angiotensin II receptors compared with 3.1 cases per 100 person-years (95% CI, 3.0-3.2 cases per 100 person-years) for the group receiving regimens that inhibit type 2 and 4 angiotensin II receptors and 2.7 cases per 100 person-years (95% CI, 2.6-2.9 cases per 100 person-years) for the group receiving mixed treatment regimens. In adjusted Cox proportional hazards regression modeling, stimulating treatment was associated with a statistically significant 16% reduction in the hazard of ADRD compared with inhibiting treatment (hazard ratio, 0.84; 95% CI, 0.79-0.90). Mixed regimen use was also associated with reduced hazards of ADRD compared with the inhibiting group (hazard ratio, 0.90; 95% CI, 0.84-0.96). Conclusions and Relevance This cohort study of Medicare beneficiaries suggests that use of antihypertensive medications that stimulate type 2 and 4 angiotensin II receptors was associated with lower risk of ADRD compared with antihypertensive medications that inhibit these receptors. Confirmation is needed in a randomized trial.
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Affiliation(s)
- Zachary A. Marcum
- Department of Pharmacy, University of Washington School of Pharmacy, Seattle
| | - Nico Gabriel
- Division of Clinical Pharmacy, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla
| | - Adam P. Bress
- Division of Health System Innovation and Research, Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, Utah
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City
| | - Inmaculada Hernandez
- Division of Clinical Pharmacy, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla
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22
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Zheutlin AR, Derington CG, Herrick JS, Rosenson RS, Poudel B, Safford MM, Brown TM, Jackson EA, Woodward M, Reading S, Orroth K, Exter J, Virani SS, Muntner P, Bress AP. Lipid-Lowering Therapy Use and Intensification Among United States Veterans Following Myocardial Infarction or Coronary Revascularization Between 2015 and 2019. Circ Cardiovasc Qual Outcomes 2022; 15:e008861. [PMID: 36252093 PMCID: PMC10680021 DOI: 10.1161/circoutcomes.121.008861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 06/14/2022] [Indexed: 01/13/2023]
Abstract
BACKGROUND Understanding how statins, ezetimibe, and PCSK9i (proprotein convertase subtilisin/kexin type 9 serine protease inhibitors) are prescribed after a myocardial infarction (MI) or elective coronary revascularization may improve lipid-lowering therapy (LLT) intensification and reduce recurrent atherosclerotic cardiovascular disease events. We described the use and intensification of LLT among US veterans who had a MI or elective coronary revascularization between July 24, 2015, and December 9, 2019, within 12 months of hospital discharge. METHODS LLT intensification was defined as increasing statin dose, or initiating a statin, ezetimibe, or a PCSK9i, overall and among those with an LDL-C (low-density lipoprotein cholesterol) ≥70 or 100 mg/dL. Poisson regression was used to determine patient characteristics associated with a greater likelihood of LLT intensification following hospitalization for MI or elective coronary revascularization. RESULTS Among 81 372 index events (mean age, 69.0 years, 2.3% female, mean LDL-C 89.6 mg/dL, 33.8% with LDL-C <70 mg/dL), 39.7% were not taking any LLT, and 22.0%, 37.2%, and 0.6% were taking a low-moderate intensity statin, a high-intensity statin, and ezetimibe, respectively, before MI/coronary revascularization during the study period. Within 14 days, 3 months, and 12 months posthospitalization, 33.3%, 41.9%, and 47.3%, respectively, of veterans received LLT intensification. LLT intensification was most common among veterans taking no LLT (82.5%, n=26 637) before MI/coronary revascularization. Higher baseline LDL-C, having a lipid test, and attending a cardiology visit were each associated with a greater likelihood of LLT intensification, while age ≥75 versus <65 years was associated with a lower likelihood of LLT intensification within 12 months posthospitalization. CONCLUSIONS Less than half of veterans received LLT intensification in the year after MI or coronary revascularization suggesting a missed opportunity to reduce atherosclerotic cardiovascular disease risk.
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Affiliation(s)
| | - Catherine G Derington
- Department of Population Health Sciences, Division of Health System Innovation and Research, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Jennifer S Herrick
- Department of Internal Medicine, Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, UT, USA
- Informatics, Decision Enhancement and Analytic Sciences (IDEAS) Center of Innovation, Veterans Affairs Salt Lake City Health Care System, Salt Lake City, UT, USA
| | - Robert S Rosenson
- Mount Sinai Heart, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bharat Poudel
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Monika M Safford
- Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Todd M Brown
- Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Elizabeth A Jackson
- Department of Medicine, Division of Cardiovascular Disease, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Mark Woodward
- The George Institute for Global Health, School of Public Health, Imperial College London, UK
- The George Institute for Global Health, University of New South Wales, Sydney, Australia
| | - Stephanie Reading
- Center for Observational Research, Amgen Inc., Amgen Inc., Thousand Oaks, CA, USA
| | - Kate Orroth
- Center for Observational Research, Amgen Inc., Amgen Inc., Thousand Oaks, CA, USA
| | - Jason Exter
- Center for Observational Research, Amgen Inc., Amgen Inc., Thousand Oaks, CA, USA
| | - Salim S Virani
- Section of Cardiovascular Research, Department of Medicine, Baylor College of Medicine, Houston, TX, USA
- Health Policy and Quality Program, Michael E. DeBakey Veterans Affairs Medical Center Health Services Research and Development Center of Excellence, Houston, TX, USA
| | - Paul Muntner
- Department of Epidemiology, University of Alabama at Birmingham School of Public Health, Birmingham, AL, USA
| | - Adam P Bress
- Department of Population Health Sciences, Division of Health System Innovation and Research, University of Utah School of Medicine, Salt Lake City, UT, USA
- Informatics, Decision Enhancement and Analytic Sciences (IDEAS) Center of Innovation, Veterans Affairs Salt Lake City Health Care System, Salt Lake City, UT, USA
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23
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Hsiao CJ, Dumeny L, Bress AP, Johnson DA, Shimbo D, Cavallari LH, Mulligan CJ. Identification of a SGCD × Discrimination Interaction Effect on Systolic Blood Pressure in African American Adults in the Jackson Heart Study. Am J Hypertens 2022; 35:938-947. [PMID: 35999027 PMCID: PMC9629434 DOI: 10.1093/ajh/hpac098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 04/12/2022] [Accepted: 08/18/2022] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND In the United States, hypertension disproportionately afflicts over half of African American adults, many of whom also experience racial discrimination. Understanding gene × discrimination effects may help explain racial disparities in hypertension. METHODS We tested for the main effects and interactive effects of 5 candidate single nucleotide polymorphisms (SNPs: rs2116737, rs11190458, rs2445762, rs2597955, and rs2416545) and experiences of discrimination on blood pressure (BP) in African Americans not taking antihypertensive medications in the Jackson Heart Study from Mississippi (n = 2,933). Multiple linear regression models assumed an additive genetic model and adjusted for ancestry, age, sex, body mass index, education, and relatedness. We additionally tested recessive and dominant genetic models. RESULTS Discrimination was significantly associated with higher diastolic BP (P = 0.003). In contrast, there were no main effects of any SNP on BP. When analyzing SNPs and discrimination together, SGCD (Sarcoglycan Delta; rs2116737) demonstrated a gene × environment interaction. Specifically, an SGCD × Discrimination interaction was associated with systolic BP (β =1.95, P = 0.00028) in a recessive model. Participants carrying a T allele, regardless of discrimination experiences, and participants with a GG genotype and high experiences of discrimination had higher systolic BP than participants with a GG genotype and low experiences of discrimination. This finding suggests the SGCD GG genotype may have a protective effect on systolic BP, but only in a setting of low discrimination. CONCLUSIONS The inclusion of culturally relevant stressors, like discrimination, may be important to understand the gene-environment interplay likely underlying complex diseases with racial health inequities.
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Affiliation(s)
- Chu J Hsiao
- Department of Anthropology, University of Florida, Gainesville, Florida, USA
- Genetics Institute, University of Florida, Gainesville, Florida, USA
| | - Leanne Dumeny
- Genetics Institute, University of Florida, Gainesville, Florida, USA
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | - Adam P Bress
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Dayna A Johnson
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Daichi Shimbo
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Larisa H Cavallari
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | - Connie J Mulligan
- Department of Anthropology, University of Florida, Gainesville, Florida, USA
- Genetics Institute, University of Florida, Gainesville, Florida, USA
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24
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Xu Y, Greene TH, Bress AP, Bellows BK, Zhang Y, Zhang Z, Kolm P, Weintraub WS, Moran AS, Shen J. An efficient approach for optimizing the cost-effective individualized treatment rule using conditional random forest. Stat Methods Med Res 2022; 31:2122-2136. [PMID: 35912490 DOI: 10.1177/09622802221115876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Evidence from observational studies has become increasingly important for supporting healthcare policy making via cost-effectiveness analyses. Similar as in comparative effectiveness studies, health economic evaluations that consider subject-level heterogeneity produce individualized treatment rules that are often more cost-effective than one-size-fits-all treatment. Thus, it is of great interest to develop statistical tools for learning such a cost-effective individualized treatment rule under the causal inference framework that allows proper handling of potential confounding and can be applied to both trials and observational studies. In this paper, we use the concept of net-monetary-benefit to assess the trade-off between health benefits and related costs. We estimate cost-effective individualized treatment rule as a function of patients' characteristics that, when implemented, optimizes the allocation of limited healthcare resources by maximizing health gains while minimizing treatment-related costs. We employ the conditional random forest approach and identify the optimal cost-effective individualized treatment rule using net-monetary-benefit-based classification algorithms, where two partitioned estimators are proposed for the subject-specific weights to effectively incorporate information from censored individuals. We conduct simulation studies to evaluate the performance of our proposals. We apply our top-performing algorithm to the NIH-funded Systolic Blood Pressure Intervention Trial to illustrate the cost-effectiveness gains of assigning customized intensive blood pressure therapy.
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Affiliation(s)
- Yizhe Xu
- Department of Population Health Sciences, 7060University of Utah, SLC, UT, USA
| | - Tom H Greene
- Department of Population Health Sciences, 7060University of Utah, SLC, UT, USA
| | - Adam P Bress
- Department of Population Health Sciences, 7060University of Utah, SLC, UT, USA
| | | | - Yue Zhang
- Department of Population Health Sciences, 7060University of Utah, SLC, UT, USA
| | - Zugui Zhang
- 5973Christiana Care Health System, Newark, DE, USA
| | - Paul Kolm
- Department of Medicine, 121577MedStar Health Research Institute, Washington, DC, USA
| | - William S Weintraub
- Department of Medicine, 121577MedStar Health Research Institute, Washington, DC, USA
| | - Andrew S Moran
- 21611Columbia University Medical Center, New York, NY, USA
| | - Jincheng Shen
- Department of Population Health Sciences, 7060University of Utah, SLC, UT, USA
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25
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Jaeger BC, Bress AP, Bundy JD, Cheung AK, Cushman WC, Drawz PE, Johnson KC, Lewis CE, Oparil S, Rocco MV, Rapp SR, Supiano MA, Whelton PK, Williamson JD, Wright JT, Reboussin DM, Pajewski NM. Longer-Term All-Cause and Cardiovascular Mortality With Intensive Blood Pressure Control: A Secondary Analysis of a Randomized Clinical Trial. JAMA Cardiol 2022; 7:1138-1146. [PMID: 36223105 PMCID: PMC9558058 DOI: 10.1001/jamacardio.2022.3345] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 07/15/2022] [Indexed: 12/15/2022]
Abstract
Importance The Systolic Blood Pressure Intervention Trial (SPRINT) showed that intensive blood pressure control reduced cardiovascular morbidity and mortality. However, the legacy effect of intensive treatment is unknown. Objective To evaluate the long-term effects of randomization to intensive treatment with the incidence of cardiovascular and all-cause mortality approximately 4.5 years after the trial ended. Design, Setting, and Participants In this secondary analysis of a multicenter randomized clinical trial, randomization began on November 8, 2010, the trial intervention ended on August 20, 2015, and trial close-out visits occurred through July 2016. Patients 50 years and older with hypertension and increased cardiovascular risk but without diabetes or history of stroke were included from 102 clinic sites in the US and Puerto Rico. Analyses were conducted between October 2021 and February 2022. Interventions Randomization to systolic blood pressure (SBP) goal of less than 120 mm Hg (intensive treatment group; n = 4678) vs less than 140 mm Hg (standard treatment group; n = 4683). Main Outcomes and Measures Extended observational follow-up for mortality via the US National Death Index from 2016 through 2020. In a subset of 2944 trial participants, outpatient SBP from electronic health records during and after the trial were examined. Results Among 9361 randomized participants, the mean (SD) age was 67.9 (9.4) years, and 3332 (35.6%) were women. Over a median (IQR) intervention period of 3.3 (2.9-3.9) years, intensive treatment was beneficial for both cardiovascular mortality (hazard ratio [HR], 0.66; 95% CI, 0.49-0.89) and all-cause mortality (HR, 0.83; 95% CI, 0.68-1.01). However, at the median (IQR) total follow-up of 8.8 (8.3-9.3) years, there was no longer evidence of benefit for cardiovascular mortality (HR, 1.02; 95% CI, 0.84-1.24) or all-cause mortality (HR, 1.08; 95% CI, 0.94-1.23). In a subgroup of participants, the estimated mean outpatient SBP among participants randomized to intensive treatment increased from 132.8 mm Hg (95% CI, 132.0-133.7) at 5 years to 140.4 mm Hg (95% CI, 137.8-143.0) at 10 years following randomization. Conclusions and Relevance The beneficial effect of intensive treatment on cardiovascular and all-cause mortality did not persist after the trial. Given increasing outpatient SBP levels in participants randomized to intensive treatment following the trial, these results highlight the importance of consistent long-term management of hypertension. Trial Registration ClinicalTrials.gov Identifier: NCT01206062.
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Affiliation(s)
- Byron C. Jaeger
- Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, North Carolina
| | - Adam P. Bress
- Informatics, Decision-Enhancement, and Analytic Sciences (IDEAS) Center, Veterans Affairs, Salt Lake City Health Care System, Salt Lake City, Utah
- Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City
| | - Joshua D. Bundy
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana
| | - Alfred K. Cheung
- Renal Section, Veterans Affairs Salt Lake City Healthcare System, Salt Lake City, Utah
- Division of Nephrology and Hypertension, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City
| | - William C. Cushman
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis
| | - Paul E. Drawz
- Division of Renal Diseases and Hypertension, University of Minnesota, Minneapolis
| | - Karen C. Johnson
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis
| | - Cora E. Lewis
- Department of Epidemiology, University of Alabama at Birmingham
| | - Suzanne Oparil
- Division of Cardiovascular Disease, Department of Medicine, University of Alabama at Birmingham
| | - Michael V. Rocco
- Section on Nephrology, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Stephen R. Rapp
- Department of Psychiatry and Behavioral Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina
- Department of Social Science and Health Policy, Wake Forest University School of Medicine, Winston-Salem, North Carolina
| | - Mark A. Supiano
- Division of Geriatrics, University of Utah School of Medicine, Salt Lake City
| | - Paul K. Whelton
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana
| | - Jeff D. Williamson
- Section on Gerontology and Geriatric Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina
| | - Jackson T. Wright
- Division of Nephrology and Hypertension, University Hospitals Cleveland Medical Center, Case Western Reserve University, Cleveland, Ohio
| | - David M. Reboussin
- Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, North Carolina
| | - Nicholas M. Pajewski
- Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, North Carolina
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26
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Marcum ZA, Cohen JB, Larson EB, Williamson J, Bress AP, Bress A. Can Preferentially Prescribing Angiotensin II Receptor Blockers (ARBs) over Angiotensin-Converting Enzyme Inhibitors (ACEIs) Decrease Dementia Risk and Improve Brain Health Equity? NAM Perspect 2022; 2022:10.31478/202205c. [PMID: 36177210 PMCID: PMC9499377 DOI: 10.31478/202205c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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27
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Tajeu GS, Colvin CL, Hardy ST, Bress AP, Gaye B, Jaeger BC, Ogedegbe G, Sakhuja S, Sims M, Shimbo D, O’Brien EC, Spruill TM, Muntner P. Prevalence, risk factors, and cardiovascular disease outcomes associated with persistent blood pressure control: The Jackson Heart Study. PLoS One 2022; 17:e0270675. [PMID: 35930588 PMCID: PMC9355196 DOI: 10.1371/journal.pone.0270675] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Accepted: 06/14/2022] [Indexed: 11/18/2022] Open
Abstract
Background
Maintaining blood pressure (BP) control over time may contribute to lower risk for cardiovascular disease (CVD) among individuals who are taking antihypertensive medication.
Methods
The Jackson Heart Study (JHS) enrolled 5,306 African-American adults ≥21 years of age and was used to determine the proportion of African Americans that maintain persistent BP control, identify factors associated with persistent BP control, and determine the association of persistent BP control with CVD events. This analysis included 1,604 participants who were taking antihypertensive medication at Visit 1 and had BP data at Visits 1 (2000–2004), 2 (2005–2008), and 3 (2009–2013). Persistent BP control was defined as systolic BP <140 mm Hg and diastolic BP <90 mm Hg at all three visits. CVD events were assessed from Visit 3 through December 31, 2016. Hazard ratios (HR) for the association of persistent BP control with CVD outcomes were adjusted for age, sex, systolic BP, smoking, diabetes, and total and high-density lipoprotein cholesterol at Visit 3.
Results
At Visit 1, 1,226 of 1,604 participants (76.4%) with hypertension had controlled BP. Overall, 48.9% of participants taking antihypertensive medication at Visit 1 had persistent BP control. After multivariable adjustment for demographic, socioeconomic, clinical, behavioral, and psychosocial factors, and access-to-care, participants were more likely to have persistent BP control if they were <65 years of age, women, had family income ≥$25,000 at each visit, and visited a health professional in the year prior to each visit. The multivariable adjusted HR (95% confidence interval) comparing participants with versus without persistent BP control was 0.71 (0.46–1.10) for CVD, 0.68 (0.34–1.34) for coronary heart disease, 0.65 (0.27–1.52) for stroke, and 0.55 (0.33–0.90) for heart failure.
Conclusion
Less than half of JHS participants taking antihypertensive medication had persistent BP control, putting them at increased risk for heart failure.
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Affiliation(s)
- Gabriel S. Tajeu
- Department of Health Services Administration and Policy, Temple University, Philadelphia, PA, United States of America
- * E-mail:
| | - Calvin L. Colvin
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, United States of America
| | - Shakia T. Hardy
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, United States of America
| | - Adam P. Bress
- Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, UT, United States of America
| | - Bamba Gaye
- INSERM, U970, Paris Cardiovascular Research Center, Department of Epidemiology, Paris, France
- Sorbonne Paris Cité, Faculté de Médecine, Université Paris Descartes, Paris, France
| | - Byron C. Jaeger
- Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Wake Forest, NC, United States of America
| | - Gbenga Ogedegbe
- Department of Population Health, NYU Grossman School of Medicine, New York, NY, United States of America
| | - Swati Sakhuja
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, United States of America
| | - Mario Sims
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, United States of America
| | - Daichi Shimbo
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, United States of America
| | - Emily C. O’Brien
- Departments of Population Health Sciences and Neurology, Duke University School of Medicine, Durham, NC, United States of America
| | - Tanya M. Spruill
- Department of Population Health, NYU Grossman School of Medicine, New York, NY, United States of America
| | - Paul Muntner
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, United States of America
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28
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Kelly TN, Sun X, He KY, Brown MR, Taliun SAG, Hellwege JN, Irvin MR, Mi X, Brody JA, Franceschini N, Guo X, Hwang SJ, de Vries PS, Gao Y, Moscati A, Nadkarni GN, Yanek LR, Elfassy T, Smith JA, Chung RH, Beitelshees AL, Patki A, Aslibekyan S, Blobner BM, Peralta JM, Assimes TL, Palmas WR, Liu C, Bress AP, Huang Z, Becker LC, Hwa CM, O'Connell JR, Carlson JC, Warren HR, Das S, Giri A, Martin LW, Craig Johnson W, Fox ER, Bottinger EP, Razavi AC, Vaidya D, Chuang LM, Chang YPC, Naseri T, Jain D, Kang HM, Hung AM, Srinivasasainagendra V, Snively BM, Gu D, Montasser ME, Reupena MS, Heavner BD, LeFaive J, Hixson JE, Rice KM, Wang FF, Nielsen JB, Huang J, Khan AT, Zhou W, Nierenberg JL, Laurie CC, Armstrong ND, Shi M, Pan Y, Stilp AM, Emery L, Wong Q, Hawley NL, Minster RL, Curran JE, Munroe PB, Weeks DE, North KE, Tracy RP, Kenny EE, Shimbo D, Chakravarti A, Rich SS, Reiner AP, Blangero J, Redline S, Mitchell BD, Rao DC, Ida Chen YD, Kardia SLR, Kaplan RC, Mathias RA, He J, Psaty BM, Fornage M, Loos RJF, Correa A, Boerwinkle E, Rotter JI, Kooperberg C, Edwards TL, Abecasis GR, Zhu X, Levy D, Arnett DK, Morrison AC. Insights From a Large-Scale Whole-Genome Sequencing Study of Systolic Blood Pressure, Diastolic Blood Pressure, and Hypertension. Hypertension 2022; 79:1656-1667. [PMID: 35652341 PMCID: PMC9593435 DOI: 10.1161/hypertensionaha.122.19324] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
BACKGROUND The availability of whole-genome sequencing data in large studies has enabled the assessment of coding and noncoding variants across the allele frequency spectrum for their associations with blood pressure. METHODS We conducted a multiancestry whole-genome sequencing analysis of blood pressure among 51 456 Trans-Omics for Precision Medicine and Centers for Common Disease Genomics program participants (stage-1). Stage-2 analyses leveraged array data from UK Biobank (N=383 145), Million Veteran Program (N=318 891), and Reasons for Geographic and Racial Differences in Stroke (N=10 643) participants, along with whole-exome sequencing data from UK Biobank (N=199 631) participants. RESULTS Two blood pressure signals achieved genome-wide significance in meta-analyses of stage-1 and stage-2 single variant findings (P<5×10-8). Among them, a rare intergenic variant at novel locus, LOC100506274, was associated with lower systolic blood pressure in stage-1 (beta [SE]=-32.6 [6.0]; P=4.99×10-8) but not stage-2 analysis (P=0.11). Furthermore, a novel common variant at the known INSR locus was suggestively associated with diastolic blood pressure in stage-1 (beta [SE]=-0.36 [0.07]; P=4.18×10-7) and attained genome-wide significance in stage-2 (beta [SE]=-0.29 [0.03]; P=7.28×10-23). Nineteen additional signals suggestively associated with blood pressure in meta-analysis of single and aggregate rare variant findings (P<1×10-6 and P<1×10-4, respectively). DISCUSSION We report one promising but unconfirmed rare variant for blood pressure and, more importantly, contribute insights for future blood pressure sequencing studies. Our findings suggest promise of aggregate analyses to complement single variant analysis strategies and the need for larger, diverse samples, and family studies to enable robust rare variant identification.
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Affiliation(s)
- Tanika N Kelly
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
- Translational Sciences Institute (T.N.K., J.H.), Tulane University, New Orleans, LA
| | - Xiao Sun
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Karen Y He
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH (K.Y.H., X.Z.)
| | - Michael R Brown
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.), The University of Texas Health Science Center at Houston' Houston' TX
| | - Sarah A Gagliano Taliun
- Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor' MI
| | - Jacklyn N Hellwege
- Division of Genetic Medicine, Department of Medicine (J.N.H.), Vanderbilt University Medical Center, Nashville, TN
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville' TN (J.N.H., A.G., A.M.H., T.L.E.)
| | - Marguerite R Irvin
- Department of Epidemiology (M.R.I., S.A., N.D.A.), University of Alabama at Birmingham' AL
| | - Xuenan Mi
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine (J.A.B., K.E.N.), University of Washington, Seattle' WA
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill (N.F.)
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance' CA (X.G., Y.-D.I.C., J.I.R., D.L.)
| | - Shih-Jen Hwang
- National Heart, Lung and Blood Institute, Population Sciences Branch, National Institutes of Health, Framingham, MA (S.-J.H.)
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.), The University of Texas Health Science Center at Houston' Houston' TX
| | - Yan Gao
- Department of Physiology and Biophysics (Y.G., E.E.K., R.J.F.L.), University of Mississippi Medical Center, Jackson' MS
| | - Arden Moscati
- The Charles Bronfman Institute for Personalized Medicine (A.M., G.N.N.), The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Girish N Nadkarni
- The Charles Bronfman Institute for Personalized Medicine (A.M., G.N.N.), The Icahn School of Medicine at Mount Sinai, New York, NY
- Department of Medicine (G.N.N.), The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Lisa R Yanek
- Division of General Internal Medicine, Department of Medicine (L.R.Y., D.V.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Tali Elfassy
- Division of Epidemiology, Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami' FL (T.E.)
| | - Jennifer A Smith
- Department of Epidemiology (J.A.S., S.L.R.K.), University of Michigan, Ann Arbor' MI
| | - Ren-Hua Chung
- Institute of Population Sciences, National Health Research Institutes, Taiwan (R.-H.C.)
| | - Amber L Beitelshees
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore' MD (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.)
| | - Amit Patki
- Department of Biostatistics (A.P., V.S.), University of Alabama at Birmingham' AL
| | - Stella Aslibekyan
- Department of Epidemiology (M.R.I., S.A., N.D.A.), University of Alabama at Birmingham' AL
| | - Brandon M Blobner
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services (B.M.P.), University of Washington, Seattle' WA
- Department of Human Genetics (B.M.B., R.L.M., D.E.W.), University of Pittsburgh, PA
| | - Juan M Peralta
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville' TX (J.M.P., J.E.C., J.B.)
| | - Themistocles L Assimes
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford' CA (T.L.A.)
- Division of Cardiology Medicine, Palo Alto VA HealthCare System, Palo Alto' CA (T.L.A.)
| | - Walter R Palmas
- Division of General Medicine, Department of Medicine, Columbia University, New York, NY (W.R.P.)
| | - Chunyu Liu
- Department of Biostatistics, Boston University, Boston' MA (C.L.)
| | - Adam P Bress
- Division of Health System Innovation and Research, Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City' UT (A.P.B.)
| | - Zhijie Huang
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Lewis C Becker
- Division of Cardiology, Department of Medicine (L.C.B.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Chii-Min Hwa
- Taichung Veterans General Hospital, Taichung, Taiwan (C.-M.H.)
| | - Jeffrey R O'Connell
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore' MD (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.)
| | - Jenna C Carlson
- Department of Biostatistics, Graduate School of Public Health (J.C.C.), University of Pittsburgh, PA
| | - Helen R Warren
- Department of Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry (H.R.W., P.B.M.), Queen Mary University of London, United Kingdom
- National Institute for Health Research Barts Cardiovascular Biomedical Research Centre (H.R.W., P.B.M.), Queen Mary University of London, United Kingdom
| | - Sayantan Das
- Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor' MI
| | - Ayush Giri
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville' TN (J.N.H., A.G., A.M.H., T.L.E.)
- Division of Quantitative Sciences, Department of Obstetrics and Gynecology, Vanderbilt University, Nashville, TN (A.G.)
| | - Lisa W Martin
- Division of Cardiology, Department of Medicine, George Washington University, Washington, DC (L.W.M.)
| | - W Craig Johnson
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Ervin R Fox
- Division of Cardiology, Department of Medicine (E.R.F.), University of Mississippi Medical Center, Jackson' MS
| | - Erwin P Bottinger
- Hasso Plattner Institute for Digital Health at Mount Sinai (E.P.B.), The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Alexander C Razavi
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Dhananjay Vaidya
- Division of General Internal Medicine, Department of Medicine (L.R.Y., D.V.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Lee-Ming Chuang
- Department of Internal Medicine, National Taiwan University Hospital, Taipei' Taiwan (L.-M.C.)
| | - Yen-Pei C Chang
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore' MD (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.)
| | - Take Naseri
- Ministry of Health, Government of Samoa, Apia' Samoa (T.N.)
| | - Deepti Jain
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Hyun Min Kang
- Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor' MI
| | - Adriana M Hung
- Division of Nephrology and Hypertension, Department of Medicine (A.M.H.), Vanderbilt University Medical Center, Nashville, TN
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville' TN (J.N.H., A.G., A.M.H., T.L.E.)
| | | | - Beverly M Snively
- Division of Public Health Sciences, Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC (B.M.S.)
| | - Dongfeng Gu
- Department of Epidemiology and Key Laboratory of Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (D.G., J.H.)
| | - May E Montasser
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore' MD (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.)
| | | | - Benjamin D Heavner
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Jonathon LeFaive
- Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor' MI
| | - James E Hixson
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.), The University of Texas Health Science Center at Houston' Houston' TX
| | - Kenneth M Rice
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Fei Fei Wang
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Jonas B Nielsen
- Department of Internal Medicine: Cardiology (J.B.N.), University of Michigan, Ann Arbor' MI
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark (J.B.N.)
| | - Jianfeng Huang
- Translational Sciences Institute (T.N.K., J.H.), Tulane University, New Orleans, LA
- Department of Epidemiology and Key Laboratory of Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (D.G., J.H.)
| | - Alyna T Khan
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Wei Zhou
- Department of Computational Medicine and Bioinformatics (W.Z.), University of Michigan, Ann Arbor' MI
| | - Jovia L Nierenberg
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Cathy C Laurie
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Nicole D Armstrong
- Department of Epidemiology (M.R.I., S.A., N.D.A.), University of Alabama at Birmingham' AL
| | - Mengyao Shi
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Yang Pan
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Adrienne M Stilp
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Leslie Emery
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Quenna Wong
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Nicola L Hawley
- Department of Chronic Disease Epidemiology, Yale University, New Haven, CT (N.L.H.)
| | - Ryan L Minster
- Department of Human Genetics (B.M.B., R.L.M., D.E.W.), University of Pittsburgh, PA
| | - Joanne E Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville' TX (J.M.P., J.E.C., J.B.)
| | - Patricia B Munroe
- Department of Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry (H.R.W., P.B.M.), Queen Mary University of London, United Kingdom
- National Institute for Health Research Barts Cardiovascular Biomedical Research Centre (H.R.W., P.B.M.), Queen Mary University of London, United Kingdom
| | - Daniel E Weeks
- Department of Human Genetics (B.M.B., R.L.M., D.E.W.), University of Pittsburgh, PA
- Department of Biostatistics (D.E.W.), University of Pittsburgh, PA
| | - Kari E North
- Cardiovascular Health Research Unit, Department of Medicine (J.A.B., K.E.N.), University of Washington, Seattle' WA
| | - Russell P Tracy
- Department of Pathology & Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington' VT (R.P.T.)
| | - Eimear E Kenny
- Department of Physiology and Biophysics (Y.G., E.E.K., R.J.F.L.), University of Mississippi Medical Center, Jackson' MS
- Department of Genetics and Genomics (E.E.K.), The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Daichi Shimbo
- Division of Cardiology, Department of Medicine, Columbia University Medical Center, New York, NY (D.S.)
| | - Aravinda Chakravarti
- Department of Medicine (A.C.), University of Mississippi Medical Center, Jackson' MS
| | - Stephen S Rich
- Center for Public Health, University of Virginia, Charlottesville' VA (S.S.R.)
| | - Alex P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA (A.P.R., C.K.)
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville' TX (J.M.P., J.E.C., J.B.)
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA (S.R.)
| | - Braxton D Mitchell
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore' MD (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.)
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore' MD (B.D.M.)
| | - Dabeeru C Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO (D.C.R.)
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance' CA (X.G., Y.-D.I.C., J.I.R., D.L.)
| | - Sharon L R Kardia
- Department of Epidemiology (J.A.S., S.L.R.K.), University of Michigan, Ann Arbor' MI
| | - Robert C Kaplan
- Division of Social Medicine, Albert Einstein College of Medicine, Bronx, NY (R.C.K.)
| | - Rasika A Mathias
- Division of Allergy & Clinical Immunology, Department of Medicine (R.A.M.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Jiang He
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Bruce M Psaty
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
- Kaiser Permanente Washington Health Research Institute, Seattle' WA (B.M.P.)
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine (M.F.), The University of Texas Health Science Center at Houston' Houston' TX
- Human Genetics Center (M.F.), The University of Texas Health Science Center at Houston' Houston' TX
| | - Ruth J F Loos
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance' CA (X.G., Y.-D.I.C., J.I.R., D.L.)
- The Mindich Child Health and Development Institute (R.J.F.L.), The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Adolfo Correa
- Center for Human Genetics and Genomics, New York University Grossman School of Medicine, New York, NY (A.C.)
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.), The University of Texas Health Science Center at Houston' Houston' TX
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX (E.B.)
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance' CA (X.G., Y.-D.I.C., J.I.R., D.L.)
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA (A.P.R., C.K.)
| | - Todd L Edwards
- Division of Epidemiology, Department of Medicine (T.L.E.), Vanderbilt University Medical Center, Nashville, TN
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville' TN (J.N.H., A.G., A.M.H., T.L.E.)
| | - Gonçalo R Abecasis
- Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor' MI
| | - Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH (K.Y.H., X.Z.)
| | - Daniel Levy
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance' CA (X.G., Y.-D.I.C., J.I.R., D.L.)
| | - Donna K Arnett
- College of Public Health, University of Kentucky, Lexington, KY (D.K.A.)
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.), The University of Texas Health Science Center at Houston' Houston' TX
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Cohen JB, Marcum ZA, Zhang C, Derington CG, Greene TH, Ghazi L, Herrick JS, King JB, Cheung AK, Bryan N, Supiano MA, Sonnen JA, Weintraub WS, Scharfstein D, Williamson J, Pajewski NM, Bress AP. Risk of Mild Cognitive Impairment or Probable Dementia in New Users of Angiotensin II Receptor Blockers and Angiotensin-Converting Enzyme Inhibitors: A Secondary Analysis of Data From the Systolic Blood Pressure Intervention Trial (SPRINT). JAMA Netw Open 2022; 5:e2220680. [PMID: 35834254 PMCID: PMC9284332 DOI: 10.1001/jamanetworkopen.2022.20680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Accepted: 05/20/2022] [Indexed: 11/14/2022] Open
Abstract
Importance The cardiovascular and renal outcomes of angiotensin-II receptor blocker (ARB) and angiotensin-converting enzyme inhibitor (ACEI) treatment are well-known; however, few studies have evaluated initiation of these agents and cognitive impairment. Objective To emulate a target trial to evaluate the cognitive outcomes of initiating an ARB- vs ACEI-based antihypertensive regimen in individuals at risk for mild cognitive impairment (MCI) and probable dementia (PD). Design, Setting, and Participants Active comparator, new-user observational cohort study design using data from the Systolic Blood Pressure Intervention Trial (SPRINT), conducted November 2010 through July 2018. Marginal cause-specific hazard ratios (HRs) and treatment-specific cumulative incidence functions were estimated with inverse probability (IP) weighting to account for confounding. Participants were using neither an ARB nor ACEI at baseline. Data analysis was conducted from April 7, 2021, to April 26, 2022. Exposures New users of ARB vs ACEI during the first 12 months of trial follow-up. Main Outcomes and Measures Composite of adjudicated amnestic MCI or PD. Results Of 9361 participants, 727 and 1313 new users of an ARB or ACEI, respectively, with well-balanced baseline characteristics between medication exposure groups after inverse probability weighting (mean [SD] age, 67 [9.5] years; 1291 ]63%] male; 240 [33%] Black; 89 [12%] Hispanic; 383 [53%] White; and 15 [2%] other race or ethnicity. In the primary analysis, during a median follow-up of 4.9 years, the inverse probability-weighted rate of amnestic MCI or PD was 4.3 vs 4.6 per 100 person-years among participants initiating ARB vs ACEI (HR, 0.93; 95% CI, 0.76-1.13). In subgroup analyses, new users of an ARB vs ACEI had a lower rate of amnestic MCI or PD among those in the standard systolic blood pressure treatment arm (HR, 0.61; 95% CI, 0.41-0.91) but not in the intensive arm (HR, 1.17; 95% CI, 0.90-1.52) (P = .007 for interaction). Conclusions and Relevance In this observational cohort study of US adults at high cardiovascular disease risk, there was no difference in the rate of amnestic MCI or PD among new users of an ARB compared with ACEI, although 95% CIs were wide.
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Affiliation(s)
- Jordana B. Cohen
- Department of Medicine, Renal-Electrolyte and Hypertension Division, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Zachary A. Marcum
- Department of Pharmacy, University of Washington School of Pharmacy, Seattle
| | - Chong Zhang
- Intermountain Healthcare Department of Population Health Sciences, Division of Biostatistics, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Catherine G. Derington
- Intermountain Healthcare Department of Population Health Sciences, Division of Health System Innovation and Research, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Tom H. Greene
- Intermountain Healthcare Department of Population Health Sciences, Division of Health System Innovation and Research, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Lama Ghazi
- Clinical and Translational Research Accelerator, Yale University School of Medicine, New Haven, Connecticut
| | - Jennifer S. Herrick
- Intermountain Healthcare Department of Population Health Sciences, Division of Health System Innovation and Research, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, Utah
| | - Jordan B. King
- Intermountain Healthcare Department of Population Health Sciences, Division of Health System Innovation and Research, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
- Institute for Health Research, Kaiser Permanente Colorado, Aurora
| | - Alfred K. Cheung
- Department of Internal Medicine, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
- Medical Service, Veterans Affairs Salt Lake City Healthcare System, Salt Lake City, Utah
| | - Nick Bryan
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Mark A. Supiano
- Geriatrics Division, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Joshua A. Sonnen
- Departments of Pathology, Neurology, and Neurosurgery, McGill University, Montréal, Québec, Canada
| | | | - Daniel Scharfstein
- Intermountain Healthcare Department of Population Health Sciences, Division of Biostatistics, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
| | - Jeff Williamson
- Sticht Center for Healthy Aging and Alzheimer’s Prevention, Wake Forest University School of Medicine, Winston-Salem, North Carolina
| | - Nicholas M. Pajewski
- Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, North Carolina
| | - Adam P. Bress
- Intermountain Healthcare Department of Population Health Sciences, Division of Health System Innovation and Research, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, Utah
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30
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Bellows BK, Xu J, Sheppard JP, Schwartz JE, Shimbo D, Muntner P, McManus RJ, Moran AE, Bryant KB, Cohen LP, Bress AP, King JB, Shikany JM, Green BB, Yano Y, Clark D, Zhang Y. Predicting Out-of-Office Blood Pressure in a Diverse US Population. Am J Hypertens 2022; 35:533-542. [PMID: 35040867 PMCID: PMC9203065 DOI: 10.1093/ajh/hpac005] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 01/04/2022] [Accepted: 01/14/2022] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND The PRedicting Out-of-OFfice Blood Pressure (PROOF-BP) algorithm accurately predicted out-of-office blood pressure (BP) among adults with suspected high BP in the United Kingdom and Canada. We tested the accuracy of PROOF-BP in a diverse US population and evaluated a newly developed US-specific algorithm (PROOF-BP-US). METHODS Adults with ≥2 office BP readings and ≥10 awake BP readings on 24-hour ambulatory BP monitoring from 4 pooled US studies were included. We compared mean awake BP with predicted out-of-office BP using PROOF-BP and PROOF-BP-US. Our primary outcomes were hypertensive out-of-office systolic BP (SBP) ≥130 mm Hg and diastolic BP (DBP) ≥80 mm Hg. RESULTS We included 3,058 adults, mean (SD) age was 52.0 (11.9) years, 38% were male, and 54% were Black. The area under the receiver-operator characteristic (AUROC) curve (95% confidence interval) for hypertensive out-of-office SBP was 0.81 (0.79-0.82) and DBP was 0.76 (0.74-0.78) for PROOF-BP. For PROOF-BP-US, the AUROC curve for hypertensive out-of-office SBP was 0.82 (0.81-0.83) and for DBP was 0.81 (0.79-0.83). The optimal predicted out-of-office BP ranges for out-of-office BP measurement referral were 120-134/75-84 mm Hg for PROOF-BP and 125-134/75-84 mm Hg for PROOF-BP-US. The 2017 American College of Cardiology/American Heart Association BP guideline (referral range 130-159/80-99 mm Hg) would refer 93.1% of adults not taking antihypertensive medications with office BP ≥130/80 mm Hg in the National Health and Nutrition Examination Survey for out-of-office BP measurement, compared with 53.1% using PROOF-BP and 46.8% using PROOF-BP-US. CONCLUSIONS PROOF-BP and PROOF-BP-US accurately predicted out-of-office hypertension in a diverse sample of US adults.
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Affiliation(s)
- Brandon K Bellows
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Jingyu Xu
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - James P Sheppard
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Joseph E Schwartz
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
- Department of Psychiatry and Behavioral Health, Stony Brook University, Stony Brook, New York, USA
| | - Daichi Shimbo
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Paul Muntner
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Richard J McManus
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Andrew E Moran
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Kelsey B Bryant
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Laura P Cohen
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Adam P Bress
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Jordan B King
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, USA
| | - James M Shikany
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Beverly B Green
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente, Seattle, Washington, USA
| | - Yuichiro Yano
- Department of Family Medicine and Community Health, Duke University, Durham, North Carolina, USA
| | - Donald Clark
- Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, USA
| | - Yiyi Zhang
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
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31
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Green MB, Shimbo D, Schwartz JE, Bress AP, King JB, Muntner P, Sheppard JP, McManus RJ, Kohli-Lynch CN, Zhang Y, Shea S, Moran AE, Bellows BK. Cost-Effectiveness of Masked Hypertension Screening and Treatment in US Adults With Suspected Masked Hypertension: A Simulation Study. Am J Hypertens 2022; 35:752-762. [PMID: 35665802 PMCID: PMC9340638 DOI: 10.1093/ajh/hpac071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Revised: 04/25/2022] [Accepted: 06/01/2022] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND Recent US blood pressure (BP) guidelines recommend using ambulatory BP monitoring (ABPM) or home BP monitoring (HBPM) to screen adults for masked hypertension. However, limited evidence exists of the expected long-term effects of screening for and treating masked hypertension. METHODS We estimated the lifetime health and economic outcomes of screening for and treating masked hypertension using the Cardiovascular Disease (CVD) Policy Model, a validated microsimulation model. We simulated a cohort of 100,000 US adults aged ≥20 years with suspected masked hypertension (i.e., office BP 120-129/<80 mm Hg, not taking antihypertensive medications, without CVD history). We compared usual care only (i.e., no screening), usual care plus ABPM, and usual care plus HBPM. We projected total direct healthcare costs (2021 USD), quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios. Future costs and QALYs were discounted 3% annually. Secondary outcomes included CVD events and serious adverse events. RESULTS Relative to usual care, adding masked hypertension screening and treatment with ABPM and HBPM was projected to prevent 14.3 and 20.5 CVD events per 100,000 person-years, increase the proportion experiencing any treatment-related serious adverse events by 2.7 and 5.1 percentage points, and increase mean total costs by $1,076 and $1,046, respectively. Compared with usual care, adding ABPM was estimated to cost $85,164/QALY gained. HBPM resulted in lower QALYs than usual care due to increased treatment-related adverse events and pill-taking disutility. CONCLUSIONS The results from our simulation study suggest screening with ABPM and treating masked hypertension is cost-effective in US adults with suspected masked hypertension.
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Affiliation(s)
- Matthew B Green
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Daichi Shimbo
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Joseph E Schwartz
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA,Department of Psychiatry and Behavioral Health, Stony Brook University, Stony Brook, New York, USA
| | - Adam P Bress
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Jordan B King
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Paul Muntner
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - James P Sheppard
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Richard J McManus
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Ciaran N Kohli-Lynch
- Center for Health Services and Outcomes Research, Institute of Public Health and Medicine, Northwestern Feinberg School of Medicine, Northwestern University, Chicago, Illinois,USA
| | - Yiyi Zhang
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Steven Shea
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Andrew E Moran
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
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Zheutlin AR, Derington CG, King JB, Berchie RO, Herrick JS, Dixon DL, Cohen JB, Shimbo D, Kronish IM, Saseen JJ, Muntner P, Moran AE, Bress AP. Factors associated with antihypertensive monotherapy among US adults with treated hypertension and uncontrolled blood pressure overall and by race/ethnicity, National Health and Nutrition Examination Survey 2013-2018. Am Heart J 2022; 248:150-159. [PMID: 34662571 PMCID: PMC9012814 DOI: 10.1016/j.ahj.2021.10.184] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 10/05/2021] [Indexed: 12/25/2022]
Abstract
BACKGROUND Treating hypertension with antihypertensive medications combinations, rather than one medication (ie, monotherapy), is underused in the United States, particularly in certain race/ethnic groups. Identifying factors associated with monotherapy use despite uncontrolled blood pressure (BP) overall and within race/ethnic groups may elucidate intervention targets in under-treated populations. METHODS Cross-sectional analysis of National Health and Nutrition Examination Surveys (NHANES; 2013-2014 through 2017-2018). We included participants age ≥20 years with hypertension, taking at least one antihypertensive medication, and uncontrolled BP (systolic BP [SBP] ≥ 140 mmHg or diastolic BP [DBP] ≥ 90 mmHg). Demographic, clinical, and healthcare-access factors associated with antihypertensive monotherapy were determined using multivariable-adjusted Poisson regression. RESULTS Among 1,597 participants with hypertension and uncontrolled BP, age- and sex- adjusted prevalence of monotherapy was 42.6% overall, 45.4% among non-Hispanic White, 31.9% among non-Hispanic Black, 39.6% among Hispanic, and 50.9% among non-Hispanic Asian adults. Overall, higher SBP was associated with higher monotherapy use, while older age, having a healthcare visit in the previous year, higher body mass index, and having heart failure were associated with lower monotherapy use. CONCLUSION Clinical and healthcare-access factors, including a healthcare visit within the previous year and co-morbid conditions were associated with a higher likelihood of combination antihypertensive therapy.
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Affiliation(s)
- Alexander R Zheutlin
- Department of Internal Medicine, University of Utah, School of Medicine, Salt Lake City, UT; Department of Population Health Sciences, University of Utah, School of Medicine, Salt Lake City, UT.
| | - Catherine G Derington
- Department of Population Health Sciences, University of Utah, School of Medicine, Salt Lake City, UT
| | - Jordan B King
- Department of Population Health Sciences, University of Utah, School of Medicine, Salt Lake City, UT; Institute for Health Research, Kaiser Permanente Colorado, Aurora, CO
| | - Ransmond O Berchie
- Department of Population Health Sciences, University of Utah, School of Medicine, Salt Lake City, UT
| | - Jennifer S Herrick
- Department of Population Health Sciences, University of Utah, School of Medicine, Salt Lake City, UT
| | - Dave L Dixon
- Department of Pharmacotherapy and Outcomes Science, Virginia Commonwealth University School of Pharmacy, Richmond, VA
| | - Jordana B Cohen
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA; Renal-Electrolyte and Hypertension Division, Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
| | - Daichi Shimbo
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY
| | - Ian M Kronish
- Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY
| | - Joseph J Saseen
- Department of Clinical Pharmacy, University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences, Aurora, CO; Department of Family Medicine, University of Colorado, School of Medicine, Aurora, CO
| | - Paul Muntner
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL
| | - Andrew E Moran
- Division of General Medicine, Columbia University Irving Medical Center, New York, NY
| | - Adam P Bress
- Department of Population Health Sciences, University of Utah, School of Medicine, Salt Lake City, UT
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Zhang Z, Kolm P, Bhatt D, Dolman S, Bress AP, King JB, Bellows Pharmd BK, Derington C, Jiao L, Philip S, Weintraub WS. Abstract 170: Cost-effectiveness Of Icosapent Ethyl In Reduce-it USA: Results From Patients Randomized In The United States. Circ Cardiovasc Qual Outcomes 2022. [DOI: 10.1161/circoutcomes.15.suppl_1.170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
The Reduction of Cardiovascular Events with Icosapent Ethyl (IE)-Intervention Trial (REDUCE-IT) demonstrated the efficacy of IE among patients with elevated triglyceride levels despite the use of statins. This study aimed to examine the cost-effectiveness (CE) of IE among US adults using both in-trial and lifetime time horizons.
Methods:
US patients in REDUCE-IT were included in the in-trial analysis. We included all cardiovascular and serious adverse events from the REDUCE-IT database where rates differed between the study arms; we used patient-level data from REDUCE-IT USA based on 2019 US costs and $4.16/day for IE. The lifetime analysis used a microsimulation Markov model. Both analyses considered value from a US health sector perspective. The primary result is the incremental CE ratio (ICER), measured as incremental costs divided by incremental quality-adjusted life-years (QALY) of IE compared with placebo. We performed univariate and probabilistic sensitivity analyses (PSA) to capture the uncertainties involved in the estimation of costs and QALYs.
Results:
Based on 3146 REDUCE-IT USA participants, there was an incremental gain in QALYs with IE compared with placebo using in-trial (3.28 vs. 3.13) and lifetime (10.36 vs. 9.83) time horizons. Total healthcare costs were lower with IE compared with placebo for both in-trial ($20,221 vs. $20,357) and lifetime ($201,842 vs. $204,701). IE was a dominant strategy compared to placebo using a lifetime time horizon with a 74.8% probability of being more effective and costing less and had a 99.6% probability of costing below $50,000 per QALY. The lifetime PSA showed that IE was a dominant strategy in 65.6% of simulations and cost-effective in 98.8%, 99.6%, and 99.9% of simulations at the $50,000, $100,000, and $150,000 per QALY gained thresholds, respectively.
Conclusions:
The REDUCE-IT USA cost-effectiveness analysis has shown that IE provides better outcomes with lower costs, dominant both in-trial and lifetime as well in the majority of sensitivity analyses and subgroups, both in primary and secondary prevention. These results, with the clinical evidence of efficacy, suggest that at $4.16 per day, IE therapy should be strongly considered in patients similar to those enrolled in REDUCE-IT USA.
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Affiliation(s)
| | - Paul Kolm
- MedStar Washington Hosp, Washington, DC
| | - Deepak Bhatt
- Brigham and Women’s Hosp Heart and Vascular Cntr, Boston, MA
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Derington CG, Bress AP, Herrick JS, FAN WENJUN, Wong ND, Andrade KE, Johnson J, Philip S, Abrahamson D, Jiao L, Bhatt DL, Weintraub WS. Abstract 244: The Potential Population Health Impact Of Treating US Adults With Icosapent Ethyl. Circ Cardiovasc Qual Outcomes 2022. [DOI: 10.1161/circoutcomes.15.suppl_1.244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
To estimate the population health impact of treating all US adults eligible for the Reduction of Cardiovascular Events with Icosapent Ethyl-Intervention Trial (REDUCE-IT) with icosapent ethyl (IPE), we estimated (1) the number of ASCVD events and healthcare costs that could be prevented; and (2) medication costs.
Methods:
We derived REDUCE-IT eligible cohorts in (1) the National Health and Nutrition Examination Surveys (NHANES) 2009-2014 and (2) the Optum Research Database (ORD). Population sizes were obtained from NHANES and observed first event rates at five years (composite of cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, unstable angina requiring hospitalization, or coronary revascularization) were estimated from ORD. Hazard ratios from REDUCE-IT USA estimated events prevented with IPE. Total (i.e., first and recurrent) event rates were estimated from the REDUCE-IT USA subgroup, applying the treatment effect on total events observed in the entire REDUCE-IT trial. The National Inpatient Sample estimated facility and professional event costs and daily IPE treatment cost was approximated at $4.16.
Results:
We estimate 3.6 million US adults to be REDUCE-IT eligible, and an observed first event rate of 19.0% could be lowered to 13.1% with five years of IPE treatment, preventing 212,000 events (Table). We projected the annual IPE treatment cost for all eligible persons to be $5.5 billion, but saving $1.7 billion annually due to first events prevented (net annual cost $3.8 billion). The total five-year event rate (first and recurrent) could be reduced from 42.5% to 28.9% with five years of IPE therapy, preventing 490,000 events (net annual cost $2.3 billion).
Conclusions:
Treating all REDUCE-IT eligible US adults has substantial medication costs but could prevent a substantial number of ASCVD events and associated direct costs. Indirect cost savings by preventing events could outweigh much of the incurred direct costs.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - Deepak L Bhatt
- Brigham and Women's Hosp Heart and Vascular Cntr, Harvard Med Sch, Boston, MA
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Yang WY, Izzi B, Bress AP, Thijs L, Citterio L, Wei FF, Salvi E, Delli Carpini S, Manunta P, Cusi D, Hoylaerts MF, Luttun A, Verhamme P, Hardikar S, Nawrot TS, Staessen JA, Zhang ZY. Association of colorectal cancer with genetic and epigenetic variation in PEAR1—A population-based cohort study. PLoS One 2022; 17:e0266481. [PMID: 35390065 PMCID: PMC8989234 DOI: 10.1371/journal.pone.0266481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 03/22/2022] [Indexed: 11/19/2022] Open
Abstract
Platelet Endothelial Aggregation Receptor 1 (PEAR1) modulates angiogenesis and platelet contact-induced activation, which play a role in the pathogenesis of colorectal cancer. We therefore tested the association of incident colorectal cancer and genetic and epigenetic variability in PEAR1 among 2532 randomly recruited participants enrolled in the family-based Flemish Study on Environment, Genes and Health Outcomes (51.2% women; mean age 44.8 years). All underwent genotyping of rs12566888 located in intron 1 of the PEAR1 gene; in 926 participants, methylation at 16 CpG sites in the PEAR1 promoter was also assessed. Over 18.1 years (median), 49 colorectal cancers occurred, all in different pedigrees. While accounting for clustering of risk factors within families and adjusting for sex, age, body mass index, the total-to-HDL cholesterol ratio, serum creatinine, plasma glucose, smoking and drinking, use of antiplatelet and nonsteroidal anti-inflammatory drug, the hazard ratio of colorectal cancer contrasting minor-allele (T) carriers vs. major-allele (GG) homozygotes was 2.17 (95% confidence interval, 1.18–3.99; P = 0.013). Bootstrapped analyses, from which we randomly excluded from two to nine cancer cases, provided confirmatory results. In participants with methylation data, we applied partial least square discriminant analysis (PLS-DA) and identified two methylation sites associated with higher colorectal cancer risk and two with lower risk. In-silico analysis suggested that methylation of the PEAR1 promoter at these four sites might affect binding of transcription factors p53, PAX5, and E2F-1, thereby modulating gene expression. In conclusion, our findings suggest that genetic and epigenetic variation in PEAR1 modulates the risk of colorectal cancer in white Flemish. To what extent, environmental factors as exemplified by our methylation data, interact with genetic predisposition and modulate penetrance of colorectal cancer risk is unknown.
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Affiliation(s)
- Wen-Yi Yang
- Department of Cardiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Sciences, University of Leuven, Leuven, Belgium
| | - Benedetta Izzi
- Department of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli, Italy
| | - Adam P Bress
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, United States of America
| | - Lutgarde Thijs
- Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Sciences, University of Leuven, Leuven, Belgium
| | - Lorena Citterio
- Division of Nephrology and Dialysis, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Fang-Fei Wei
- Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Sciences, University of Leuven, Leuven, Belgium
- Department of Cardiology, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Erika Salvi
- Department of Health Sciences, University of Milan, Milan, Italy
| | - Simona Delli Carpini
- Division of Nephrology and Dialysis, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Paolo Manunta
- School of Nephrology, University Vita-Salute San Raffaele, Milan, Italy
| | | | | | - Aernout Luttun
- Center for Molecular and Vascular Biology, KU Leuven Department of Cardiovascular Sciences, University of Leuven, Leuven, Belgium
| | - Peter Verhamme
- Center for Molecular and Vascular Biology, KU Leuven Department of Cardiovascular Sciences, University of Leuven, Leuven, Belgium
| | - Sheetal Hardikar
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, United States of America
- Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah, United States of America
| | - Tim S Nawrot
- Centre for Environmental Sciences, Hasselt University, Hasselt, Belgium
| | - Jan A Staessen
- Biomedical Science Group, University of Leuven, Leuven, Belgium
- Research Institute Association for the Promotion of Preventive Medicine, Mechelen, Belgium
| | - Zhen-Yu Zhang
- Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Sciences, University of Leuven, Leuven, Belgium
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Parcha V, Pampana A, Bress AP, Irvin MR, Arora G, Arora P. Association of Polygenic Risk Score With Blood Pressure and Adverse Cardiovascular Outcomes in Individuals With Type II Diabetes: Insights From the ACCORD Trial. Hypertension 2022; 79:e100-e102. [PMID: 35369713 PMCID: PMC9010352 DOI: 10.1161/hypertensionaha.122.18976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Vibhu Parcha
- Division of Cardiovascular Disease (V.P., A.P., G.A., P.A.), University of Alabama at Birmingham
| | - Akhil Pampana
- Division of Cardiovascular Disease (V.P., A.P., G.A., P.A.), University of Alabama at Birmingham
| | - Adam P Bress
- Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City (A.B.)
| | - Marguerite R Irvin
- Department of Epidemiology, School of Public Health (M.R.I.), University of Alabama at Birmingham
| | - Garima Arora
- Division of Cardiovascular Disease (V.P., A.P., G.A., P.A.), University of Alabama at Birmingham
| | - Pankaj Arora
- Division of Cardiovascular Disease (V.P., A.P., G.A., P.A.), University of Alabama at Birmingham.,Section of Cardiology, Birmingham Veterans Affairs Medical Center, AL (P.A.)
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37
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Shah RU, Bress AP, Vickers AJ. Do Prediction Models Do More Harm Than Good? Circ Cardiovasc Qual Outcomes 2022; 15:e008667. [PMID: 35354281 DOI: 10.1161/circoutcomes.122.008667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Rashmee U Shah
- Division of Cardiovascular Medicine (R.U.S.), University of Utah School of Medicine
| | - Adam P Bress
- Department of Population Health Sciences (A.P.B), University of Utah School of Medicine
| | - Andrew J Vickers
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, (A.J.V.)
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Derington CG, Bress AP, Herrick JS, Fan W, Wong ND, Andrade KE, Johnson J, Philip S, Abrahamson D, Jiao L, Bhatt DL, Weintraub WS. The Potential Population Health Impact of Treating REDUCE-IT eligible US adults with Icosapent Ethyl. Am J Prev Cardiol 2022; 10:100345. [PMID: 35574517 PMCID: PMC9097618 DOI: 10.1016/j.ajpc.2022.100345] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 04/18/2022] [Accepted: 04/25/2022] [Indexed: 11/25/2022] Open
Abstract
An estimated 3.6 million US adults are REDUCE-IT eligible. An estimated 212,000 ASCVD events over five years can be prevented with icosapent ethyl therapy. The estimated annual cost of treating all eligible US adults with icosapent ethyl is $5.5 billion. An estimated $1.8 billion could be saved annually from ASCVD events prevented.
Objective To explore the population health impact of treating all US adults eligible for the Reduction of Cardiovascular Events with Icosapent Ethyl–Intervention Trial (REDUCE-IT) with icosapent ethyl (IPE), we estimated (1) the number of ASCVD events and healthcare costs that could be prevented; and (2) medication costs. Methods We derived REDUCE-IT eligible cohorts in (1) the National Health and Nutrition Examination Surveys (NHANES) 2009-2014 and (2) the Optum Research Database (ORD). Population sizes were obtained from NHANES and observed first event rates (composite of cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, unstable angina requiring hospitalization, or coronary revascularization) were estimated from the ORD. Hazard ratios from REDUCE-IT USA estimated events prevented with IPE therapy. The National Inpatient Sample estimated event costs (facility and professional) and daily IPE treatment cost was approximated at $4.59. Results We estimate 3.6 million US adults to be REDUCE-IT eligible, and the observed five-year first event rate without IPE of 19.0% (95% confidence interval [CI] 16.6%-19.5%) could be lowered to 13.1% (95% CI 12.8%-13.5%) with five years of IPE treatment, preventing 212,000 (uncertainty range 163,000-262,000) events. We projected the annual IPE treatment cost for all eligible persons to be $6.0 billion (95% CI $4.7-$7.5 billion), but saving $1.8 billion annually due to first events prevented (net annual cost $4.3 billion). The total five-year event rate (first and recurrent) could be reduced from 42.5% (95% CI 39.6%-45.4%) to 28.9% (95% CI 26.9-30.9%) with five years of IPE therapy, preventing 490,000 (uncertainty range 370,000-609,000) events (net annual cost $2.6 billion). Conclusions Treating all REDUCE-IT eligible US adults has substantial medication costs but could prevent a substantial number of ASCVD events and associated direct costs. Indirect cost savings by preventing events could outweigh much of the incurred direct costs.
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Dolui S, Detre JA, Gaussoin SA, Herrick JS, Wang DJJ, Tamura MK, Cho ME, Haley WE, Launer LJ, Punzi HA, Rastogi A, Still CH, Weiner DE, Wright JT, Williamson JD, Wright CB, Bryan RN, Bress AP, Pajewski NM, Nasrallah IM. Association of Intensive vs Standard Blood Pressure Control With Cerebral Blood Flow: Secondary Analysis of the SPRINT MIND Randomized Clinical Trial. JAMA Neurol 2022; 79:380-389. [PMID: 35254390 PMCID: PMC8902686 DOI: 10.1001/jamaneurol.2022.0074] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
IMPORTANCE Antihypertensive treatments benefit cerebrovascular health and cognitive function in patients with hypertension, but it is uncertain whether an intensive blood pressure target leads to potentially harmful cerebral hypoperfusion. OBJECTIVE To investigate the association of intensive systolic blood pressure (SBP) control vs standard control with whole-brain cerebral blood flow (CBF). DESIGN, SETTING, AND PARTICIPANTS This substudy of the Systolic Blood Pressure Intervention Trial (SPRINT) randomized clinical trial compared the efficacy of 2 different blood pressure-lowering strategies with longitudinal brain magnetic resonance imaging (MRI) including arterial spin labeled perfusion imaging to quantify CBF. A total of 1267 adults 50 years or older with hypertension and increased cardiovascular risk but free of diabetes or dementia were screened for the SPRINT substudy from 6 sites in the US. Randomization began in November 2010 with final follow-up MRI in July 2016. Analyses were performed from September 2020 through December 2021. INTERVENTIONS Study participants with baseline CBF measures were randomized to an intensive SBP target less than 120 mm Hg or standard SBP target less than 140 mm Hg. MAIN OUTCOMES AND MEASURES The primary outcome was change in whole-brain CBF from baseline. Secondary outcomes were change in gray matter, white matter, and periventricular white matter CBF. RESULTS Among 547 participants with CBF measured at baseline, the mean (SD) age was 67.5 (8.1) years and 219 (40.0%) were women; 315 completed follow-up MRI at a median (IQR) of 4.0 (3.7-4.1) years after randomization. Mean whole-brain CBF increased from 38.90 to 40.36 (difference, 1.46 [95% CI, 0.08-2.83]) mL/100 g/min in the intensive treatment group, with no mean increase in the standard treatment group (37.96 to 37.12; difference, -0.84 [95% CI, -2.30 to 0.61] mL/100 g/min; between-group difference, 2.30 [95% CI, 0.30-4.30; P = .02]). Gray, white, and periventricular white matter CBF showed similar changes. The association of intensive vs standard treatment with CBF was generally similar across subgroups defined by age, sex, race, chronic kidney disease, SBP, orthostatic hypotension, and frailty, with the exception of an indication of larger mean increases in CBF associated with intensive treatment among participants with a history of cardiovascular disease (interaction P = .05). CONCLUSIONS AND RELEVANCE Intensive vs standard antihypertensive treatment was associated with increased, rather than decreased, cerebral perfusion, most notably in participants with a history of cardiovascular disease. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT01206062.
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Affiliation(s)
- Sudipto Dolui
- Department of Radiology, University of Pennsylvania, Philadelphia
| | - John A Detre
- Department of Radiology, University of Pennsylvania, Philadelphia.,Department of Neurology, University of Pennsylvania, Philadelphia
| | - Sarah A Gaussoin
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Jennifer S Herrick
- Department of Population Health Sciences, University of Utah, Salt Lake City
| | - Danny J J Wang
- Laboratory of FMRI Technology, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles.,Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles
| | - Manjula Kurella Tamura
- Geriatric Research and Education Clinical Center, Palo Alto Veterans Affairs Health Care System, Palo Alto, California.,Division of Nephrology, Stanford University School of Medicine, Palo Alto, California
| | - Monique E Cho
- Division of Nephrology and Hypertension, University of Utah, Salt Lake City
| | - William E Haley
- Department of Nephrology and Hypertension, Mayo Clinic, Jacksonville, Florida
| | - Lenore J Launer
- Intramural Research Program, National Institute on Aging, Baltimore, Maryland
| | - Henry A Punzi
- Trinity Hypertension and Metabolic Research Institute, Punzi Medical Center, Carrollton, Texas.,Department of Family and Community Medicine, University of Texas Southwestern Medical Center, Dallas
| | - Anjay Rastogi
- Department of Medicine, University of California at Los Angeles School of Medicine, Los Angeles
| | - Carolyn H Still
- Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, Ohio
| | - Daniel E Weiner
- William B. Schwartz, MD, Division of Nephrology, Tufts Medical Center, Boston, Massachusetts
| | - Jackson T Wright
- Division of Nephrology and Hypertension, University Hospitals Cleveland Medical Center, Case Western Reserve University, Cleveland, Ohio
| | - Jeff D Williamson
- Sticht Center on Healthy Aging and Alzheimer's Prevention, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Clinton B Wright
- Stroke Branch (intramural)/Division of Clinical Research (extramural), National Institute of Neurological Disorders and Stroke, Bethesda, Maryland
| | - R Nick Bryan
- Department of Diagnostic Medicine; Dell Medical School, University of Texas at Austin, Austin
| | - Adam P Bress
- Department of Population Health Sciences, University of Utah, Salt Lake City
| | - Nicholas M Pajewski
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Ilya M Nasrallah
- Department of Radiology, University of Pennsylvania, Philadelphia
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40
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Xu Y, Greene TH, Bress AP, Sauer BC, Bellows BK, Zhang Y, Weintraub WS, Moran AE, Shen J. Estimating the optimal individualized treatment rule from a cost-effectiveness perspective. Biometrics 2022; 78:337-351. [PMID: 33215693 PMCID: PMC8134511 DOI: 10.1111/biom.13406] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 10/30/2020] [Accepted: 11/06/2020] [Indexed: 11/27/2022]
Abstract
Optimal individualized treatment rules (ITRs) provide customized treatment recommendations based on subject characteristics to maximize clinical benefit in accordance with the objectives in precision medicine. As a result, there is growing interest in developing statistical tools for estimating optimal ITRs in evidence-based research. In health economic perspectives, policy makers consider the tradeoff between health gains and incremental costs of interventions to set priorities and allocate resources. However, most work on ITRs has focused on maximizing the effectiveness of treatment without considering costs. In this paper, we jointly consider the impact of effectiveness and cost on treatment decisions and define ITRs under a composite-outcome setting, so that we identify the most cost-effective ITR that accounts for individual-level heterogeneity through direct optimization. In particular, we propose a decision-tree-based statistical learning algorithm that uses a net-monetary-benefit-based reward to provide nonparametric estimations of the optimal ITR. We provide several approaches to estimating the reward underlying the ITR as a function of subject characteristics. We present the strengths and weaknesses of each approach and provide practical guidelines by comparing their performance in simulation studies. We illustrate the top-performing approach from our simulations by evaluating the projected 15-year personalized cost-effectiveness of the intensive blood pressure control of the Systolic Blood Pressure Intervention Trial (SPRINT) study.
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Affiliation(s)
- Yizhe Xu
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah
| | - Tom H. Greene
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah,Department of Internal Medicine, University of Utah, Salt Lake City, Utah,Department of Family and Preventive Medicine, University of Utah, Salt Lake City, Utah
| | - Adam P. Bress
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah
| | - Brian C. Sauer
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah,Department of Family and Preventive Medicine, University of Utah, Salt Lake City, Utah,Salt Lake City Veterans Affairs Medical Center, Salt Lake City, Utah
| | - Brandon K. Bellows
- Department of Medicine, Columbia University Medical Center, New York, New York
| | - Yue Zhang
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah,Department of Internal Medicine, University of Utah, Salt Lake City, Utah,Department of Family and Preventive Medicine, University of Utah, Salt Lake City, Utah
| | | | - Andrew E. Moran
- Department of Medicine, Columbia University Medical Center, New York, New York
| | - Jincheng Shen
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah,Department of Internal Medicine, University of Utah, Salt Lake City, Utah,Department of Family and Preventive Medicine, University of Utah, Salt Lake City, Utah
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41
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He KY, Kelly TN, Wang H, Liang J, Zhu L, Cade BE, Assimes TL, Becker LC, Beitelshees AL, Bielak LF, Bress AP, Brody JA, Chang YPC, Chang YC, de Vries PS, Duggirala R, Fox ER, Franceschini N, Furniss AL, Gao Y, Guo X, Haessler J, Hung YJ, Hwang SJ, Irvin MR, Kalyani RR, Liu CT, Liu C, Martin LW, Montasser ME, Muntner PM, Mwasongwe S, Naseri T, Palmas W, Reupena MS, Rice KM, Sheu WHH, Shimbo D, Smith JA, Snively BM, Yanek LR, Zhao W, Blangero J, Boerwinkle E, Chen YDI, Correa A, Cupples LA, Curran JE, Fornage M, He J, Hou L, Kaplan RC, Kardia SLR, Kenny EE, Kooperberg C, Lloyd-Jones D, Loos RJF, Mathias RA, McGarvey ST, Mitchell BD, North KE, Peyser PA, Psaty BM, Raffield LM, Rao DC, Redline S, Reiner AP, Rich SS, Rotter JI, Taylor KD, Tracy R, Vasan RS, Morrison AC, Levy D, Chakravarti A, Arnett DK, Zhu X. Rare coding variants in RCN3 are associated with blood pressure. BMC Genomics 2022; 23:148. [PMID: 35183128 PMCID: PMC8858539 DOI: 10.1186/s12864-022-08356-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 02/01/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND While large genome-wide association studies have identified nearly one thousand loci associated with variation in blood pressure, rare variant identification is still a challenge. In family-based cohorts, genome-wide linkage scans have been successful in identifying rare genetic variants for blood pressure. This study aims to identify low frequency and rare genetic variants within previously reported linkage regions on chromosomes 1 and 19 in African American families from the Trans-Omics for Precision Medicine (TOPMed) program. Genetic association analyses weighted by linkage evidence were completed with whole genome sequencing data within and across TOPMed ancestral groups consisting of 60,388 individuals of European, African, East Asian, Hispanic, and Samoan ancestries. RESULTS Associations of low frequency and rare variants in RCN3 and multiple other genes were observed for blood pressure traits in TOPMed samples. The association of low frequency and rare coding variants in RCN3 was further replicated in UK Biobank samples (N = 403,522), and reached genome-wide significance for diastolic blood pressure (p = 2.01 × 10- 7). CONCLUSIONS Low frequency and rare variants in RCN3 contributes blood pressure variation. This study demonstrates that focusing association analyses in linkage regions greatly reduces multiple-testing burden and improves power to identify novel rare variants associated with blood pressure traits.
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Affiliation(s)
- Karen Y He
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Wolstein Research Building, 2103 Cornell Road, Cleveland, OH, 44106, USA
| | - Tanika N Kelly
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Heming Wang
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Jingjing Liang
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Wolstein Research Building, 2103 Cornell Road, Cleveland, OH, 44106, USA
| | - Luke Zhu
- Center for Human Genetics & Genomics, New York University Grossman School of Medicine, New York, NY, USA
| | - Brian E Cade
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Themistocles L Assimes
- Department of Medicine (Division of Cardiovascular Medicine), Stanford University, Palo Alto, CA, USA
| | - Lewis C Becker
- GeneSTAR Research Program, Department of Medicine, Divisions of Cardiology and General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Amber L Beitelshees
- Division of Endocrinology, Diabetes, and Nutrition, Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Adam P Bress
- Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Yen-Pei Christy Chang
- Division of Endocrinology, Diabetes, and Nutrition, Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Yi-Cheng Chang
- Graduate Institute of Medical Genomics and Proteomics, National Taiwan University, Taipei City, Taiwan
- Institute of Biomedical Sciences, Academia Sinica, Taipei City, Taiwan
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Ravindranath Duggirala
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Ervin R Fox
- Division of Cardiovascular Diseases, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Nora Franceschini
- Department of Epidemiology, UNC Gillings School of Global Public Health, Chapel Hill, NC, USA
| | - Anna L Furniss
- Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS, USA
| | - Yan Gao
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jeffrey Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Yi-Jen Hung
- Institute of Preventive Medicine, National Defense Medical Center, New Taipei City, Taiwan
| | - Shih-Jen Hwang
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
- Framingham Heart Study, National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, USA
| | - Marguerite Ryan Irvin
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AB, USA
| | - Rita R Kalyani
- GeneSTAR Research Program, Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ching-Ti Liu
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
- Framingham Heart Study, National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, USA
| | - Chunyu Liu
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
- Framingham Heart Study, National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, USA
| | - Lisa Warsinger Martin
- Division of Cardiology, Department of Medicine, George Washington University, Washington, DC, USA
| | - May E Montasser
- Division of Endocrinology, Diabetes, and Nutrition, Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Paul M Muntner
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AB, USA
| | | | - Take Naseri
- Ministry of Health, Government of Samoa, Apia, Samoa
| | - Walter Palmas
- Division of Cardiology, Columbia University Irving Medical Center, New York, NY, USA
| | | | - Kenneth M Rice
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Wayne H-H Sheu
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung City, Taiwan
| | - Daichi Shimbo
- Division of Cardiology, Columbia University Irving Medical Center, New York, NY, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Beverly M Snively
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Lisa R Yanek
- GeneSTAR Research Program, Department of Medicine, Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
- Division of Genomic Outcomes, Department of Pediatrics, Harbor-UCLA Medical Center Professor of Pediatrics, UCLA, Torrance, CA, USA
| | - Adolfo Correa
- Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS, USA
| | - L Adrienne Cupples
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
- Framingham Heart Study, National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, USA
| | - Joanne E Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Myriam Fornage
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University Chicago, Evanston, IL, USA
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Eimear E Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Donald Lloyd-Jones
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Rasika A Mathias
- GeneSTAR Research Program, Department of Medicine, Divisions of Allergy and Clinical Immunology and General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Stephen T McGarvey
- International Health Institute and Department of Epidemiology, School of Public Health, Brown University, Providence, RI, USA
- Department of Anthropology, Brown University, Providence, RI, USA
| | - Braxton D Mitchell
- Division of Endocrinology, Diabetes, and Nutrition, Program for Personalized and Genomic Medicine, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Geriatrics Research and Education Clinical Center, Veterans Affairs Medical Center, Baltimore, MD, USA
| | - Kari E North
- Department of Epidemiology, UNC Gillings School of Global Public Health, Chapel Hill, NC, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - D C Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Alex P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Russell Tracy
- Department of Pathology & Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT, USA
- Department of Biochemistry, University of Vermont, Burlington, VT, USA
| | - Ramachandran S Vasan
- Framingham Heart Study, National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, USA
- Department of Medicine, School of Medicine, Boston University, Boston, MA, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Daniel Levy
- Framingham Heart Study, National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Aravinda Chakravarti
- Center for Human Genetics & Genomics, New York University Grossman School of Medicine, New York, NY, USA
| | - Donna K Arnett
- University of Kentucky College of Public Health, Lexington, KY, USA
| | - Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Wolstein Research Building, 2103 Cornell Road, Cleveland, OH, 44106, USA.
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Sakhuja S, Jaeger BC, Akinyelure OP, Bress AP, Shimbo D, Schwartz JE, Hardy ST, Howard G, Drawz P, Muntner P. Potential impact of systematic and random errors in blood pressure measurement on the prevalence of high office blood pressure in the United States. J Clin Hypertens (Greenwich) 2022; 24:263-270. [PMID: 35137521 PMCID: PMC8925005 DOI: 10.1111/jch.14418] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 11/22/2021] [Accepted: 12/08/2021] [Indexed: 11/29/2022]
Abstract
The authors examined the proportion of US adults that would have their high blood pressure (BP) status changed if systolic BP (SBP) and diastolic BP (DBP) were measured with systematic bias and/or random error versus following a standardized protocol. Data from the 2017-2018 National Health and Nutrition Examination Survey (NHANES; n = 5176) were analyzed. BP was measured up to three times using a mercury sphygmomanometer by a trained physician following a standardized protocol and averaged. High BP was defined as SBP ≥130 mm Hg or DBP ≥80 mm Hg. Among US adults not taking antihypertensive medication, 32.0% (95%CI: 29.6%,34.4%) had high BP. If SBP and DBP were measured with systematic bias, 5 mm Hg for SBP and 3.5 mm Hg for DBP higher and lower than in NHANES, the proportion with high BP was estimated to be 44.4% (95%CI: 42.6%,46.2%) and 21.9% (95%CI 19.5%,24.4%). Among US adults taking antihypertensive medication, 60.6% (95%CI: 57.2%,63.9%) had high BP. If SBP and DBP were measured 5 and 3.5 mm Hg higher and lower than in NHANES, the proportion with high BP was estimated to be 71.8% (95%CI: 68.3%,75.0%) and 48.4% (95%CI: 44.6%,52.2%), respectively. If BP was measured with random error, with standard deviations of 15 mm Hg for SBP and 7 mm Hg for DBP, 21.4% (95%CI: 19.8%,23.0%) of US adults not taking antihypertensive medication and 20.5% (95%CI: 17.7%,23.3%) taking antihypertensive medication had their high BP status re-categorized. In conclusions, measuring BP with systematic or random errors may result in the misclassification of high BP for a substantial proportion of US adults.
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Affiliation(s)
- Swati Sakhuja
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Byron C Jaeger
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | | | - Adam P Bress
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Daichi Shimbo
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA
| | - Joseph E Schwartz
- Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA.,Department of Psychiatry and Behavioral Health, Renaissance School of Medicine, Stony Brook, New York, USA
| | - Shakia T Hardy
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - George Howard
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Paul Drawz
- Division of Nephrology and Hypertension, University of Minnesota, Minneapolis, Minnesota, USA
| | - Paul Muntner
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
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43
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Weintraub WS, Bhatt DL, Zhang Z, Dolman S, Boden WE, Bress AP, King JB, Bellows BK, Tajeu GS, Derington CG, Johnson J, Andrade K, Steg PG, Miller M, Brinton EA, Jacobson TA, Tardif JC, Ballantyne CM, Kolm P. Cost-effectiveness of Icosapent Ethyl for High-risk Patients With Hypertriglyceridemia Despite Statin Treatment. JAMA Netw Open 2022; 5:e2148172. [PMID: 35157055 PMCID: PMC8844997 DOI: 10.1001/jamanetworkopen.2021.48172] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Accepted: 11/02/2021] [Indexed: 12/25/2022] Open
Abstract
Importance The Reduction of Cardiovascular Events With Icosapent Ethyl-Intervention Trial (REDUCE-IT) demonstrated the efficacy of icosapent ethyl (IPE) for high-risk patients with hypertriglyceridemia and known cardiovascular disease or diabetes and at least 1 other risk factor who were treated with statins. Objective To estimate the cost-effectiveness of IPE compared with standard care for high-risk patients with hypertriglyceridemia despite statin treatment. Design, Setting, and Participants An in-trial cost-effectiveness analysis was performed using patient-level study data from REDUCE-IT, and a lifetime analysis was performed using a microsimulation model and data from published literature. The study included 8179 patients with hypertriglyceridemia despite stable statin therapy recruited between November 21, 2011, and May 31, 2018. Analyses were performed from a US health care sector perspective. Statistical analysis was performed from March 1, 2018, to October 31, 2021. Interventions Patients were randomly assigned to IPE, 4 g/d, or placebo and were followed up for a median of 4.9 years (IQR, 3.5-5.3 years). The cost of IPE was $4.16 per day after rebates using SSR Health net cost (SSR cost) and $9.28 per day with wholesale acquisition cost (WAC). Main Outcomes and Measures Main outcomes were incremental quality-adjusted life-years (QALYs), total direct health care costs (2019 US dollars), and cost-effectiveness. Results A total of 4089 patients (2927 men [71.6%]; median age, 64.0 years [IQR, 57.0-69.0 years]) were randomly assigned to receive IPE, and 4090 patients (2895 men [70.8%]; median age, 64.0 years [IQR, 57.0-69.0 years]) were randomly assigned to receive standard care. Treatment with IPE yielded more QALYs than standard care both in trial (3.34 vs 3.27; mean difference, 0.07 [95% CI, 0.01-0.12]) and over a lifetime projection (10.59 vs 10.35; mean difference, 0.24 [95% CI, 0.15-0.33]). In-trial, total health care costs were higher with IPE using either SSR cost ($18 786) or WAC ($24 544) than with standard care ($17 273; mean difference from SSR cost, $1513 [95% CI, $155-$2870]; mean difference from WAC, $7271 [95% CI, $5911-$8630]). Icosapent ethyl cost $22 311 per QALY gained using SSR cost and $107 218 per QALY gained using WAC. Over a lifetime, IPE was projected to be cost saving when using SSR cost ($195 276) compared with standard care ($197 064; mean difference, -$1788 [95% CI, -$9735 to $6159]) but to have higher costs when using WAC ($202 830) compared with standard care (mean difference, $5766 [95% CI, $1094-$10 438]). Compared with standard care, IPE had a 58.4% lifetime probability of costing less and being more effective when using SSR cost and an 89.4% probability of costing less than $50 000 per QALY gained when using SSR cost and a 72.5% probability of costing less than $50 000 per QALY gained when using WAC. Conclusions and Relevance This study suggests that, both in-trial and over the lifetime, IPE offers better cardiovascular outcomes than standard care in REDUCE-IT participants at common willingness-to-pay thresholds.
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Affiliation(s)
- William S. Weintraub
- MedStar Healthcare Delivery Research Network, MedStar Health Research Institute, Washington, DC
| | - Deepak L. Bhatt
- Brigham and Women’s Hospital Heart and Vascular Center, Harvard Medical School, Boston, Massachusetts
| | - Zugui Zhang
- Institute for Research on Equity and Community Health, ChristianaCare Health System, Newark, Delaware
| | - Sarahfaye Dolman
- MedStar Healthcare Delivery Research Network, MedStar Health Research Institute, Washington, DC
| | - William E. Boden
- Department of Medicine, Cardiology Section, Veterans Affairs Boston Healthcare System, Boston, Massachusetts
- Department of Medicine, Boston University School of Medicine, Boston, Massachusetts
| | - Adam P. Bress
- Department of Population Health Sciences, University of Utah, Salt Lake City
| | - Jordan B. King
- Department of Population Health Sciences, University of Utah, Salt Lake City
| | | | - Gabriel S. Tajeu
- Health Services Administration and Policy, Temple University, Philadelphia, Pennsylvania
| | | | - Jonathan Johnson
- Health Economics and Outcomes Research, Optum, Eden Prairie, Minnesota
| | - Katherine Andrade
- Health Economics and Outcomes Research, Optum, Eden Prairie, Minnesota
| | - P. Gabriel Steg
- Medical School of Université de Paris, Paris, France
- Cardiology Department, Assistance Publique-Hôpitaux de Paris, Hôpital Bichat, Paris, France
- French Alliance for Cardiovascular Trials (FACT), INSERM U-1148, Paris, France
| | - Michael Miller
- Department of Medicine, University of Maryland School of Medicine, Baltimore
| | | | - Terry A. Jacobson
- Office of Health Promotion and Disease Prevention, Department of Medicine, Emory University, Atlanta, Georgia
| | - Jean-Claude Tardif
- Montreal Heart Institute, Université de Montréal, Montreal, Quebec, Canada
| | | | - Paul Kolm
- Center of Biostatistics, Informatics, and Data Science, MedStar Health Research Institute, Washington, DC
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Zheutlin AR, Mondesir FL, Derington CG, King JB, Zhang C, Cohen JB, Berlowitz DR, Anstey DE, Cushman WC, Greene TH, Ogedegbe O, Bress AP. Analysis of Therapeutic Inertia and Race and Ethnicity in the Systolic Blood Pressure Intervention Trial: A Secondary Analysis of a Randomized Clinical Trial. JAMA Netw Open 2022; 5:e2143001. [PMID: 35006243 PMCID: PMC8749480 DOI: 10.1001/jamanetworkopen.2021.43001] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 11/15/2021] [Indexed: 12/24/2022] Open
Abstract
Importance Therapeutic inertia may contribute to racial and ethnic differences in blood pressure (BP) control. Objective To determine the association between race and ethnicity and therapeutic inertia in the Systolic Blood Pressure Intervention Trial (SPRINT). Design, Setting, and Participants This cross-sectional study was a secondary analysis of data from SPRINT, a randomized clinical trial comparing intensive (<120 mm Hg) vs standard (<140 mm Hg) systolic BP treatment goals. Participants were enrolled between November 8, 2010, and March 15, 2013, with a median follow-up 3.26 years. Participants included adults aged 50 years or older at high risk for cardiovascular disease but without diabetes, previous stroke, or heart failure. The present analysis was restricted to participant visits with measured BP above the target goal. Analyses for the present study were performed in from October 2020 through March 2021. Exposures Self-reported race and ethnicity, mutually exclusively categorized into groups of Hispanic, non-Hispanic Black, or non-Hispanic White participants. Main Outcomes and Measures Therapeutic inertia, defined as no antihypertensive medication intensification at each study visit where the BP was above target goal. The association between self-reported race and ethnicity and therapeutic inertia was estimated using generalized estimating equations and stratified by treatment group. Antihypertensive medication use was assessed with pill bottle inventories at each visit. Blood pressure was measured using an automated device. Results A total of 8556 participants, including 4141 in the standard group (22 844 participant-visits; median age, 67.0 years [IQR, 61.0-76.0 years]; 1467 women [35.4%]) and 4415 in the intensive group (35 453 participant-visits; median age, 67.0 years [IQR, 61.0-76.0 years]; 1584 women [35.9%]) with at least 1 eligible study visit were included in the present analysis. Among non-Hispanic White, non-Hispanic Black, and Hispanic participants, the overall prevalence of therapeutic inertia in the standard vs intensive groups was 59.8% (95% CI, 58.9%-60.7%) vs 56.0% (95% CI, 55.2%-56.7%), 56.8% (95% CI, 54.4%-59.2%) vs 54.5% (95% CI, 52.4%-56.6%), and 59.7% (95% CI, 56.5%-63.0%) vs 51.0% (95% CI, 47.4%-54.5%), respectively. The adjusted odds ratios in the standard and intensive groups for therapeutic inertia associated with non-Hispanic Black vs non-Hispanic White participants were 0.85 (95% CI, 0.79-0.92) and 0.94 (95% CI, 0.88-1.01), respectively. The adjusted odds ratios for therapeutic inertia comparing Hispanic vs non-Hispanic White participants were 1.00 (95% CI, 0.90-1.13) and 0.89 (95% CI, 0.79-1.00) in the standard and intensive groups, respectively. Conclusions and Relevance Among SPRINT participants above BP target goal, this cross-sectional study found that therapeutic inertia prevalence was similar or lower for non-Hispanic Black and Hispanic participants compared with non-Hispanic White participants. These findings suggest that a standardized approach to BP management, as used in SPRINT, may help ensure equitable care and could reduce the contribution of therapeutic inertia to disparities in hypertension. Trial Registration ClinicalTrials.gov identifier: NCT01206062.
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Affiliation(s)
- Alexander R. Zheutlin
- Department of Internal Medicine, University of Utah, School of Medicine, Salt Lake City
- Department of Population Health Sciences, University of Utah, School of Medicine, Salt Lake City
| | - Favel L. Mondesir
- Department of Biostatistics, School of Public Health, Boston University, Boston, Massachusetts
| | - Catherine G. Derington
- Department of Population Health Sciences, University of Utah, School of Medicine, Salt Lake City
| | - Jordan B. King
- Department of Population Health Sciences, University of Utah, School of Medicine, Salt Lake City
- Institute for Health Research, Kaiser Permanente Colorado, Aurora
| | - Chong Zhang
- Department of Internal Medicine, University of Utah, School of Medicine, Salt Lake City
| | - Jordana B. Cohen
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Renal-Electrolyte and Hypertension Division, Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia
| | - Dan R. Berlowitz
- Department of Public Health, University of Massachusetts-Lowell, Lowell
| | - D. Edmund Anstey
- Division of Cardiology, Columbia University Irving Medical Center, New York, New York
| | - William C. Cushman
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis
- Medical Service, Memphis VA Medical Center, Memphis, Tennessee
| | - Tom H. Greene
- Department of Population Health Sciences, University of Utah, School of Medicine, Salt Lake City
| | - Olugbenga Ogedegbe
- Center for Healthful Behavior Change, Division of Health and Behavior, Department of Population Health, New York University School of Medicine, New York, New York
| | - Adam P. Bress
- Department of Population Health Sciences, University of Utah, School of Medicine, Salt Lake City
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Marcum ZA, Cohen JB, Zhang C, Derington CG, Greene TH, Ghazi L, Herrick JS, King JB, Cheung AK, Bryan N, Supiano MA, Sonnen JA, Weintraub WS, Williamson J, Pajewski NM, Bress AP. Association of Antihypertensives That Stimulate vs Inhibit Types 2 and 4 Angiotensin II Receptors With Cognitive Impairment. JAMA Netw Open 2022; 5:e2145319. [PMID: 35089354 PMCID: PMC8800076 DOI: 10.1001/jamanetworkopen.2021.45319] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 11/29/2021] [Indexed: 01/05/2023] Open
Abstract
Importance Use of antihypertensive medications that stimulate type 2 and 4 angiotensin II receptors, compared with those that do not stimulate these receptors, has been associated with a lower risk of dementia. However, this association with cognitive outcomes in hypertension trials, with blood pressure levels in the range of current guidelines, has not been evaluated. Objective To examine the association between use of exclusively antihypertensive medication regimens that stimulate vs inhibit type 2 and 4 angiotensin II receptors on mild cognitive impairment (MCI) or dementia. Design, Setting, and Participants This cohort study is a secondary analysis (April 2011 to July 2018) of participants in the randomized Systolic Blood Pressure Intervention Trial (SPRINT), which recruited individuals 50 years or older with hypertension and increased cardiovascular risk but without a history of diabetes, stroke, or dementia. Data analysis was conducted from March 16 to July 6, 2021. Exposures Prevalent use of angiotensin II receptor type 2 and 4-stimulating or -inhibiting antihypertensive medication regimens at the 6-month study visit. Main Outcomes and Measures The primary outcome was a composite of adjudicated amnestic MCI or probable dementia. Results Of the 8685 SPRINT participants who were prevalent users of antihypertensive medication regimens at the 6-month study visit (mean [SD] age, 67.7 [11.2] years; 5586 [64.3%] male; and 935 [10.8%] Hispanic, 2605 [30.0%] non-Hispanic Black, 4983 [57.4%] non-Hispanic White, and 162 [1.9%] who responded as other race or ethnicity), 2644 (30.4%) were users of exclusively stimulating, 1536 (17.7%) inhibiting, and 4505 (51.9%) mixed antihypertensive medication regimens. During a median of 4.8 years of follow-up (95% CI, 4.7-4.8 years), there were 45 vs 59 cases per 1000 person-years of amnestic MCI or probable dementia among prevalent users of regimens that contained exclusively stimulating vs inhibiting antihypertensive medications (hazard ratio [HR], 0.76; 95% CI, 0.66-0.87). When comparing stimulating-only vs inhibiting-only users, amnestic MCI occurred at rates of 40 vs 54 cases per 1000 person-years (HR, 0.74; 95% CI, 0.64-0.87) and probable dementia at rates of 8 vs 10 cases per 1000 person-years (HR, 0.80; 95% CI, 0.57-1.14). Negative control outcome analyses suggested the presence of residual confounding. Conclusions and Relevance In this secondary analysis of SPRINT, prevalent users of regimens that contain exclusively antihypertensive medications that stimulate vs inhibit type 2 and 4 angiotensin II receptors had lower rates of incident cognitive impairment. Residual confounding cannot be ruled out. If these results are replicated in randomized clinical trials, certain antihypertensive medications could be prioritized to prevent cognitive decline.
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Affiliation(s)
- Zachary A. Marcum
- Department of Pharmacy, School of Pharmacy, University of Washington, Seattle
| | - Jordana B. Cohen
- Renal-Electrolyte and Hypertension Division, Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Chong Zhang
- Division of Health System Innovation and Research, Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City
| | - Catherine G. Derington
- Division of Health System Innovation and Research, Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City
| | - Tom H. Greene
- Division of Health System Innovation and Research, Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City
| | - Lama Ghazi
- Clinical and Translational Research Accelerator, Yale University School of Medicine, New Haven, Connecticut
| | - Jennifer S. Herrick
- Division of Health System Innovation and Research, Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, Utah
| | - Jordan B. King
- Division of Health System Innovation and Research, Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, Utah
- Institute for Health Research, Kaiser Permanente Colorado, Aurora
| | - Alfred K. Cheung
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, Utah
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City
| | - Nick Bryan
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Mark A. Supiano
- Division of Geriatrics, University of Utah School of Medicine, Salt Lake City
| | - Joshua A. Sonnen
- Department of Pathology and Neurology and Neurosurgery, McGill University School of Medicine, Montreal, Quebec, Canada
| | | | - Jeff Williamson
- Section on Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Nicholas M. Pajewski
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Adam P. Bress
- Division of Health System Innovation and Research, Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, Utah
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City
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46
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King JB, Pinheiro LC, Ringel JB, Bress AP, Shimbo D, Muntner P, Reynolds K, Cushman M, Howard G, Manly JJ, Safford MM. Multiple Social Vulnerabilities to Health Disparities and Hypertension and Death in the REGARDS Study. Hypertension 2022; 79:196-206. [PMID: 34784734 PMCID: PMC8665033 DOI: 10.1161/hypertensionaha.120.15196] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Social vulnerabilities increase the risk of developing hypertension and lower life expectancy, but the effect of an individual's overall vulnerability burden is unknown. Our objective was to determine the association of social vulnerability count and the risk of developing hypertension or dying over 10 years and whether these associations vary by race. We used the REGARDS study (Reasons for Geographic and Racial Differences in Stroke) and included participants without baseline hypertension. The primary exposure was the count of social vulnerabilities defined across economic, education, health and health care, neighborhood and built environment, and social and community context domains. Among 5425 participants of mean age 64±10 SD years of which 24% were Black participants, 1468 (31%) had 1 vulnerability and 717 (15%) had ≥2 vulnerabilities. Compared with participants without vulnerabilities, the adjusted relative risk ratio for developing hypertension was 1.16 (95% CI, 0.99-1.36) and 1.49 (95% CI, 1.20-1.85) for individuals with 1 and ≥2 vulnerabilities, respectively. The adjusted relative risk ratio for death was 1.55 (95% CI, 1.24-1.93) and 2.30 (95% CI, 1.75-3.04) for individuals with 1 and ≥2 vulnerabilities, respectively. A greater proportion of Black participants developed hypertension and died than did White participants (hypertension, 38% versus 31%; death, 25% versus 20%). The vulnerability count association was strongest in White participants (P value for vulnerability count×race interaction: hypertension=0.046, death=0.015). Overall, a greater number of socially determined vulnerabilities was associated with progressively higher risk of developing hypertension, and an even higher risk of dying over 10 years.
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Affiliation(s)
- Jordan B. King
- Department of Population Health Sciences, School of Medicine, University of Utah,Institute for Health Research, Kaiser Permanente Colorado
| | | | | | - Adam P. Bress
- Department of Population Health Sciences, School of Medicine, University of Utah
| | - Daichi Shimbo
- Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons
| | - Paul Muntner
- Department of Epidemiology, Ryals School of Public Health, University of Alabama at Birmingham
| | - Kristi Reynolds
- Department of Research and Evaluation, Kaiser Permanente Southern California,Department of Health Systems Science, Kaiser Permanente School of Medicine
| | - Mary Cushman
- Department of Medicine, Larner College of Medicine, University of Vermont
| | - George Howard
- Department of Biostatistics, Ryals School of Public Health, University of Alabama at Birmingham
| | - Jennifer J. Manly
- Department of Neurology, Columbia University Vagelos College of Physicians and Surgeons
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47
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Smith SM, Desai RA, Walsh MG, Nilles EK, Shaw K, Smith M, Chamberlain AM, Derington CG, Bress AP, Chuang CH, Ford DE, Taylor BW, Chandaka S, Patel LP, McClay J, Priest E, Fuloria J, Doshi K, Ahmad FS, Viera AJ, Faulkner M, O'Brien EC, Pletcher MJ, Cooper-DeHoff RM. Angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, and COVID-19-related outcomes: A patient-level analysis of the PCORnet blood pressure control lab. Am Heart J Plus 2022; 13:100112. [PMID: 35252907 PMCID: PMC8889730 DOI: 10.1016/j.ahjo.2022.100112] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 01/21/2022] [Accepted: 02/11/2022] [Indexed: 12/20/2022]
Abstract
SARS-CoV-2 accesses host cells via angiotensin-converting enzyme-2, which is also affected by commonly used angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs), raising concerns that ACEI or ARB exposure may portend differential COVID-19 outcomes. In parallel cohort studies of outpatient and inpatient COVID-19-diagnosed adults with hypertension, we assessed associations between antihypertensive exposure (ACEI/ARB vs. non-ACEI/ARB antihypertensives, as well as between ACEI- vs. ARB) at the time of COVID-19 diagnosis, using electronic health record data from PCORnet health systems. The primary outcomes were all-cause hospitalization or death (outpatient cohort) or all-cause death (inpatient), analyzed via Cox regression weighted by inverse probability of treatment weights. From February 2020 through December 9, 2020, 11,246 patients (3477 person-years) and 2200 patients (777 person-years) were included from 17 health systems in outpatient and inpatient cohorts, respectively. There were 1015 all-cause hospitalization or deaths in the outpatient cohort (incidence, 29.2 events per 100 person-years), with no significant difference by ACEI/ARB use (adjusted HR 1.01; 95% CI 0.88, 1.15). In the inpatient cohort, there were 218 all-cause deaths (incidence, 28.1 per 100 person-years) and ACEI/ARB exposure was associated with reduced death (adjusted HR, 0.76; 95% CI, 0.57, 0.99). ACEI, versus ARB exposure, was associated with higher risk of hospitalization in the outpatient cohort, but no difference in all-cause death in either cohort. There was no evidence of effect modification across pre-specified baseline characteristics. Our results suggest ACEI and ARB exposure have no detrimental effect on hospitalizations and may reduce death among hypertensive patients diagnosed with COVID-19.
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Affiliation(s)
- Steven M Smith
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, United States of America
- Department of Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida, Gainesville, FL, United States of America
| | - Raj A Desai
- Department of Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida, Gainesville, FL, United States of America
| | - Marta G Walsh
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, United States of America
| | - Ester Kim Nilles
- Duke Clinical Research Institute, Duke University, Durham, NC, United States of America
| | - Katie Shaw
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, United States of America
| | - Myra Smith
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, United States of America
| | - Alanna M Chamberlain
- Departments of Quantitative Health Sciences and Cardiovascular Medicine, Mayo Clinic, Rochester, MN, United States of America
| | - Catherine G Derington
- Department of Population Health Sciences, School of Medicine, University of Utah, Salt Lake City, UT, United States of America
| | - Adam P Bress
- Department of Population Health Sciences, School of Medicine, University of Utah, Salt Lake City, UT, United States of America
| | | | - Daniel E Ford
- Johns Hopkins University, Baltimore, MD, United States of America
| | - Bradley W Taylor
- Medical College of Wisconsin, Milwaukee, WI, United States of America
| | - Sravani Chandaka
- University of Kansas Medical Center, Kansas City, KS, United States of America
| | | | - James McClay
- University of Nebraska, Omaha, NE, United States of America
| | - Elisa Priest
- Baylor Scott & White Health, Dallas, TX, United States of America
| | - Jyotsna Fuloria
- School of Medicine, Louisiana State University, New Orleans, LA, United States of America
| | - Kruti Doshi
- Cook County Health, Chicago, IL, United States of America
| | - Faraz S Ahmad
- Departments of Medicine and Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States of America
| | - Anthony J Viera
- Department of Family Medicine and Community Health, School of Medicine, Duke University, Durham, NC, United States of America
| | - Madelaine Faulkner
- Department of Epidemiology & Biostatistics, School of Medicine, University of California San Francisco, San Francisco, CA, United States of America
| | - Emily C O'Brien
- Duke Clinical Research Institute, Duke University, Durham, NC, United States of America
| | - Mark J Pletcher
- Department of Epidemiology & Biostatistics, School of Medicine, University of California San Francisco, San Francisco, CA, United States of America
| | - Rhonda M Cooper-DeHoff
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, United States of America
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Langford AT, Butler M, Booth JN, Jin P, Bress AP, Tanner RM, Kalinowski J, Blanc J, Seixas A, Shimbo D, Sims M, Ogedegbe G, Spruill TM. Stress and Depression Are Associated With Life's Simple 7 Among African Americans With Hypertension: Findings From the Jackson Heart Study. Am J Hypertens 2021; 34:1311-1321. [PMID: 34272853 DOI: 10.1093/ajh/hpab116] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2021] [Revised: 06/18/2021] [Accepted: 07/15/2021] [Indexed: 01/14/2023] Open
Abstract
BACKGROUND The American Heart Association created the Life's Simple 7 (LS7) metrics to promote cardiovascular health (CVH) by achieving optimal levels of blood pressure, cholesterol, blood sugar, physical activity, diet, weight, and smoking status. The degree to which psychosocial factors such as stress and depression impact one's ability to achieve optimal CVH is unclear, particularly among hypertensive African Americans. METHODS Cross-sectional analyses included 1,819 African Americans with hypertension participating in the Jackson Heart Study (2000-2004). Outcomes were LS7 composite and individual component scores (defined as poor, intermediate, ideal). High perceived chronic stress was defined as the top quartile of Weekly Stress Inventory scores. High depressive symptoms were defined as Center for Epidemiologic Studies Depression scale scores of ≥16. We compared 4 groups: high stress alone; high depressive symptoms alone; high stress and high depressive symptoms; low stress and low depressive symptoms (reference) using linear regression for total LS7 scores and logistic regression for LS7 components. RESULTS Participants with both high stress and depressive symptoms had lower composite LS7 scores (B [95% confidence interval] = -0.34 [-0.65 to -0.02]) than those with low stress and depressive symptoms in unadjusted and age/sex-adjusted models. They also had poorer health status for smoking (odds ratio [95% confidence interval] = 0.52 [0.35-0.78]) and physical activity (odds ratio [95% confidence interval] = 0.71 [0.52-0.95]) after full covariate adjustment. CONCLUSIONS The combination of high stress and high depressive symptoms was associated with poorer LS7 metrics in hypertensive African Americans. Psychosocial interventions may increase the likelihood of engaging in behaviors that promote optimal CVH.
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Affiliation(s)
- Aisha T Langford
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
| | - Mark Butler
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
- Institute of Health System Science, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York, USA
| | - John N Booth
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
- Department of Real-World Evidence and Late Phase, CTI Clinical Trials and Consulting Services, Inc., Covington, Kentucky, USA
| | - Peng Jin
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
| | - Adam P Bress
- Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Rikki M Tanner
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Jolaade Kalinowski
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
- Department of Human Development and Family Sciences, University of Connecticut, Storrs, Connecticut, USA
| | - Judite Blanc
- Department of Psychiatry & Behavioral Sciences, University of Miami, Miami, Florida, USA
| | - Azizi Seixas
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
| | - Daichi Shimbo
- Department of Medicine, Columbia University Medical Center, New York, New York, USA
| | - Mario Sims
- Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, USA
| | - Gbenga Ogedegbe
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
- Institute for Excellence in Health Equity, NYU Grossman School of Medicine, New York, New York, USA
| | - Tanya M Spruill
- Department of Population Health, NYU Grossman School of Medicine, New York, New York, USA
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Mohanty AF, Levitan EB, King JB, Dodson JA, Vardeny O, Cook J, Herrick JS, He T, Patterson OV, Alba PR, Russo PA, Obi EN, Choi ME, Fang JC, Bress AP. Sacubitril/Valsartan Initiation Among Veterans Who Are Renin-Angiotensin-Aldosterone System Inhibitor Naïve With Heart Failure and Reduced Ejection Fraction. J Am Heart Assoc 2021; 10:e020474. [PMID: 34612065 PMCID: PMC8751890 DOI: 10.1161/jaha.120.020474] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background Sacubitril/valsartan, a first‐in‐class angiotensin receptor neprilysin inhibitor, received US Food and Drug Administration approval in 2015 for heart failure with reduced ejection fraction (HFrEF). Our objective was to describe the sacubitril/valsartan initiation rate, associated characteristics, and 6‐month follow‐up dosing among veterans with HFrEF who are renin‐angiotensin‐aldosterone system inhibitor (RAASi) naïve. Methods and Results Retrospective cohort study of veterans with HFrEF who are RAASi naïve defined as left ventricular ejection fraction (LVEF) ≤40%; ≥1 in/outpatient heart failure visit, first RAASi (sacubitril/valsartan, angiotensin‐converting enzyme inhibitor [ACEI]), or angiotensin‐II receptor blocker [ARB]) fill from July 2015 to June 2019. Characteristics associated with sacubitril/valsartan initiation were identified using Poisson regression models. From July 2015 to June 2019, we identified 3458 sacubitril/valsartan and 29 367 ACEI or ARB initiators among veterans with HFrEF who are RAASi naïve. Sacubitril/valsartan initiation increased from 0% to 26.5%. Sacubitril/valsartan (versus ACEI or ARB) initiators were less likely to have histories of stroke, myocardial infarction, or hypertension and more likely to be older and have diabetes mellitus and lower LVEF. At 6‐month follow‐up, the prevalence of ≥50% target daily dose for sacubitril/valsartan, ACEI, and ARB initiators was 23.5%, 43.2%, and 47.1%, respectively. Conclusions Sacubitril/valsartan initiation for HFrEF in the Veterans Administration increased in the 4 years immediately following Food and Drug Administration approval. Sacubitril/valsartan (versus ACEI or ARB) initiators had fewer baseline cardiovascular comorbidities and the lowest proportion on ≥50% target daily dose at 6‐month follow‐up. Identifying the reasons for lower follow‐up dosing of sacubitril/valsartan could support guideline recommendations and quality improvement strategies for patients with HFrEF.
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Affiliation(s)
- April F Mohanty
- Veterans Affairs Salt Lake City Health Care System Salt Lake City UT.,Department of Internal Medicine University of Utah School of Medicine Salt Lake City UT
| | - Emily B Levitan
- Department of Epidemiology University of Alabama at Birmingham School of Public Health Birmingham AL
| | - Jordan B King
- Department of Population Health Sciences University of Utah School of Medicine Salt Lake City UT.,Institute for Health Research Kaiser Permanente Colorado Aurora CO
| | - John A Dodson
- Leon H. Charney Division of Cardiology Department of Medicine New York University School of Medicine New York NY
| | - Orly Vardeny
- University of Minnesota Medical School Minneapolis MN
| | - James Cook
- Veterans Affairs Salt Lake City Health Care System Salt Lake City UT.,Department of Internal Medicine University of Utah School of Medicine Salt Lake City UT
| | - Jennifer S Herrick
- Veterans Affairs Salt Lake City Health Care System Salt Lake City UT.,Department of Internal Medicine University of Utah School of Medicine Salt Lake City UT
| | - Tao He
- Veterans Affairs Salt Lake City Health Care System Salt Lake City UT.,Department of Internal Medicine University of Utah School of Medicine Salt Lake City UT
| | - Olga V Patterson
- Veterans Affairs Salt Lake City Health Care System Salt Lake City UT.,Department of Internal Medicine University of Utah School of Medicine Salt Lake City UT
| | - Patrick R Alba
- Veterans Affairs Salt Lake City Health Care System Salt Lake City UT.,Department of Internal Medicine University of Utah School of Medicine Salt Lake City UT
| | - Patricia A Russo
- US Health Economics & Outcomes Research Novartis Pharmaceuticals CorporationEast Hanover NJ
| | - Engels N Obi
- US Health Economics & Outcomes Research Novartis Pharmaceuticals CorporationEast Hanover NJ
| | | | - James C Fang
- Department of Internal Medicine University of Utah School of Medicine Salt Lake City UT
| | - Adam P Bress
- Veterans Affairs Salt Lake City Health Care System Salt Lake City UT.,Department of Internal Medicine University of Utah School of Medicine Salt Lake City UT.,Department of Population Health Sciences University of Utah School of Medicine Salt Lake City UT
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50
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Derington CG, Bellows B, Tajeu GS, Herrick JS, Berchie RO, Ying J, Sakhuja S, Greene T, Ruiz-negron N, Howard G, Levitan EB, Muntner P, Safford MM, Weintraub WS, Moran AE, Bress AP. Abstract 02: Distribution Of Predicted Cardiovascular And All-cause Mortality Benefit Of Intensive Vs Standard Blood Pressure Control Among Us Adults Eligible For The Systolic Blood Pressure Intervention Trial. Hypertension 2021. [DOI: 10.1161/hyp.78.suppl_1.02] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Introduction:
If resources are scarce, achieving national SBP control goals will require prioritizing treatment among those likely to benefit. To identify patients with greatest predicted benefit with intensive SBP treatment and estimate population sizes, we applied algorithms to community samples who met the SPRINT enrollment criteria.
Methods:
The published algorithms separately predict the absolute risk reduction in CVD events and mortality at 3.26 years with intensive (<120 mm Hg) vs standard (<140 mm Hg) SBP lowering. We applied and calibrated the algorithms to SPRINT standard arm participants (n=4 399) and samples meeting SPRINT enrollment criteria from the National Health and Nutrition Examination Survey (NHANES, n=1 297) and the Reasons for Geographic And Racial Differences in Stroke (REGARDS, n=2 785). Predicted absolute risk reduction estimated number needed to treat (NNT), categorized as <50, 50-100, and ≥100. Observed 3.26 year CVD event (SPRINT, REGARDS) and mortality rates (all cohorts) were calculated.
Results:
The median ages were 67 (SPRINT), 69 (NHANES), and 72 (REGARDS). Greater proportions of NHANES and REGARDS vs SPRINT had predicted NNT <100 for CVD events (NHANES 94.8%, REGARDS 99.2%, SPRINT 87.8%) and mortality (NHANES 64.3%, REGARDS 63.7%, SPRINT 38.8%) (
Table
). Event rates were comparable within NNT groups.
Conclusions:
Predicted NNT distributions differ between cohorts but event rates are similar. Most adults who meet SPRINT enrollment criteria have predicted NNT <100 for CVD and mortality with intensive SBP treatment. These results suggest that published algorithms can identify those most likely to benefit and can guide implementation.
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Affiliation(s)
| | | | | | | | | | | | | | - Tom Greene
- Univ of Utah, Salt Lake City, United States Minor Outlying Islands
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