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Gardea-Resendez M, Ortiz-Orendain J, Miola A, Fuentes Salgado M, Ercis M, Coombes BJ, Gruhlke PM, Bostwick JM, Michel I, Vande Voort JL, Ozerdem A, McKean A, Frye MA, Taylor-Desir M. Racial differences in pathways to care preceding first episode mania or psychosis: a historical cohort prodromal study. Front Psychiatry 2023; 14:1241071. [PMID: 37732076 PMCID: PMC10507622 DOI: 10.3389/fpsyt.2023.1241071] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 08/16/2023] [Indexed: 09/22/2023] Open
Abstract
Background There is evidence suggesting racial disparities in diagnosis and treatment in bipolar disorder (BD) and schizophrenia (SZ). The purpose of this study is to compare psychiatric diagnoses and psychotropic use preceding a first episode of mania (FEM) or psychosis (FEP) in racially diverse patients. Methods Using a comprehensive medical records linkage system (Rochester Epidemiology Project, REP), we retrospectively identified individuals diagnosed with BD or SZ and a documented first episode of mania or psychosis. Illness trajectory before FEP/FEM were characterized as the time from first visit for a mental health complaint to incident case. Pathways to care and clinical events preceding FEP/FEM were compared based on subsequent incident case diagnosis (BD or SZ) and self-reported race (White vs. non-White). Results A total of 205 (FEM = 74; FEP = 131) incident cases were identified in the REP. Duration of psychiatric antecedents was significantly shorter in non-White patients, compared to White patients (2.2 ± 4.3 vs. 7.4 ± 6.6 years; p < 0.001) with an older age at time of first visit for a mental health complaint (15.7 ± 6.3 vs. 11.1 ± 6.0 years; p = 0.005). There were no significant differences by race in FEM pathway to care or age of first seeking mental health. Overall non-White patients had lower rates of psychotropic use. Conclusion These data are unable to ascertain reasons for shorter duration of psychiatric antecedents and later age of seeking care, and more broadly first age of initial symptom presentation. If symptoms are confirmed to be earlier than first time seeking care in both groups, it would be important to identify barriers that racial minorities face to access timely psychiatric care and optimize early intervention strategies.
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Affiliation(s)
- Manuel Gardea-Resendez
- Department of Psychiatry, Universidad Autónoma de Nuevo León, Monterrey, Mexico
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States
| | - Javier Ortiz-Orendain
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States
- Department of Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, NM, United States
| | - Alessandro Miola
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
| | | | - Mete Ercis
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States
| | - Brandon J. Coombes
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States
| | - Peggy M. Gruhlke
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States
| | - J. Michael Bostwick
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States
| | - Ian Michel
- Mayo Clinic Alix School of Medicine, Mayo Clinic, Rochester, MN, United States
| | | | - Aysegul Ozerdem
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States
| | - Alastair McKean
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States
| | - Mark A. Frye
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States
| | - Monica Taylor-Desir
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States
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Kowalski EN, Qian G, Vanni KMM, Sparks JA. A Roadmap for Investigating Preclinical Autoimmunity Using Patient-Oriented and Epidemiologic Study Designs: Example of Rheumatoid Arthritis. Front Immunol 2022; 13:890996. [PMID: 35693829 PMCID: PMC9175569 DOI: 10.3389/fimmu.2022.890996] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 04/26/2022] [Indexed: 11/26/2022] Open
Abstract
Background & Aims Rheumatoid arthritis (RA) is a prototypic autoimmune disease causing inflammatory polyarthritis that affects nearly 1% of the population. RA can lead to joint destruction and disability along with increased morbidity and mortality. Similar to other autoimmune diseases, RA has distinct preclinical phases corresponding to genetic risk, lifestyle risk factors, autoantibody development, and non-specific symptoms prior to clinical diagnosis. This narrative review will detail observational studies for RA risk and clinical trials for RA prevention as a roadmap to investigating preclinical autoimmunity that could be applied to other diseases. Methods In this narrative review, we summarized previous and ongoing research studies investigating RA risk and prevention, categorizing them related to their design and preclinical phases. Results We detailed the following types of studies investigating RA risk and prevention: retrospective population-based and administrative datasets; prospective studies (case-control and cohort; some enrolling based on genetics, first-degree relative status, elevated biomarkers, or early symptoms/arthritis); and randomized clinical trials. These correspond to all preclinical RA phases (genetic, lifestyle, autoimmunity, early signs/symptoms). Previous and ongoing randomized controlled trials have enrolled individuals at very elevated risk for RA based on biomarkers, symptoms, imaging abnormalities, or early signs/symptoms. Conclusion We detailed the rich variety of study designs that is necessary to investigate distinct preclinical phases of an autoimmune disease such as RA. However, further progress is needed to fully elucidate the pathogenesis of RA that may ultimately lead to prevention or delay of disease onset.
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Affiliation(s)
- Emily N Kowalski
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, United States
| | - Grace Qian
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, United States
| | - Kathleen M M Vanni
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, United States
| | - Jeffrey A Sparks
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, MA, United States.,Department of Medicine, Harvard Medical School, Boston, MA, United States
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Sacks HS, Smirnoff M, Carson D, Cooney ML, Shapiro MZ, Hahn CJ, Dasaro CR, Crowson C, Tassiulas I, Hirten RP, Cohen BL, Haber RS, Davies TF, Simpson DM, Crane MA, Harrison DJ, Luft BJ, Moline JM, Udasin IG, Todd AC, Sloan NL, Teitelbaum SL. Autoimmune conditions in the World Trade Center general responder cohort: A nested case-control and standardized incidence ratio analysis. Am J Ind Med 2022; 65:117-131. [PMID: 34825393 DOI: 10.1002/ajim.23313] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Revised: 10/26/2021] [Accepted: 11/02/2021] [Indexed: 12/22/2022]
Abstract
BACKGROUND The World Trade Center (WTC) general responder cohort (GRC) was exposed to environmental toxins possibly associated with increased risk of developing autoimmune conditions. OBJECTIVES Two study designs were used to assess incidence and risks of autoimmune conditions in the GRC. METHODS Three clinically trained professionals established the status of possible GRC cases of autoimmune disorders adhering to diagnostic criteria, supplemented, as needed, by specialists' review of consenting responders' medical records. Nested case-control analyses using conditional logistic regression estimated the risk associated with high WTC exposure (being in the 9/11/2001 dust cloud or ≥median days' response worked) compared with low WTC exposure (all other GRC members'). Four controls were matched to each case on age at case diagnosis (±2 years), sex, race/ethnicity, and year of program enrollment. Sex-specific and sensitivity analyses were performed. GRC age- and sex-adjusted standardized incidence ratios (SIRs) were compared with the Rochester Epidemiology Project (REP). Complete REP inpatient and outpatient medical records were reviewed by specialists. Conditions meeting standardized criteria on ≥2 visits were classified as REP confirmed cases. RESULTS Six hundred and twenty-eight responders were diagnosed with autoimmune conditions between 2002 and 2017. In the nested case-control analyses, high WTC exposure was not associated with autoimmune domains and conditions (rheumatologic domain odds ratio [OR] = 1.03, 95% confidence interval [CI] = 0.77, 1.37; rheumatoid arthritis OR = 1.12, 95% CI = 0.70, 1.77). GRC members had lower SIR than REP. Women's risks were generally greater than men's. CONCLUSIONS The study found no statistically significant increased risk of autoimmune conditions with WTC exposures.
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Affiliation(s)
- Henry S. Sacks
- Department of Environmental Medicine and Public Health Icahn School of Medicine at Mount Sinai New York New York USA
| | - Margaret Smirnoff
- Department of Environmental Medicine and Public Health Icahn School of Medicine at Mount Sinai New York New York USA
| | - Deborah Carson
- Department of Environmental Medicine and Public Health Icahn School of Medicine at Mount Sinai New York New York USA
| | - Michael L. Cooney
- Department of Environmental Medicine and Public Health Icahn School of Medicine at Mount Sinai New York New York USA
| | - Moshe Z. Shapiro
- Department of Environmental Medicine and Public Health Icahn School of Medicine at Mount Sinai New York New York USA
| | - Christopher J. Hahn
- Department of Environmental Medicine and Public Health Icahn School of Medicine at Mount Sinai New York New York USA
| | - Christopher R. Dasaro
- Department of Environmental Medicine and Public Health Icahn School of Medicine at Mount Sinai New York New York USA
| | - Cynthia Crowson
- Division of Biomedical Statistics and Informatics Mayo Clinic College of Medicine Rochester Minnesota USA
| | - Ioannis Tassiulas
- Rheumatology Department Icahn School of Medicine at Mount Sinai New York New York USA
| | - Robert P. Hirten
- Rheumatology Department Icahn School of Medicine at Mount Sinai New York New York USA
| | - Benjamin L. Cohen
- Rheumatology Department Icahn School of Medicine at Mount Sinai New York New York USA
- Department of Gastroenterology, Hepatology, and Nutrition Cleveland Clinic Foundation Cleveland Ohio USA
| | - Richard S. Haber
- Rheumatology Department Icahn School of Medicine at Mount Sinai New York New York USA
| | - Terry F. Davies
- Rheumatology Department Icahn School of Medicine at Mount Sinai New York New York USA
| | - David M. Simpson
- Rheumatology Department Icahn School of Medicine at Mount Sinai New York New York USA
| | - Michael A. Crane
- Department of Environmental Medicine and Public Health, World Trade Center Health Program Clinical Center of Excellence Icahn School of Medicine at Mount Sinai New York New York USA
| | - Denise J. Harrison
- Department of Medicine, Department of Environmental Medicine, World Trade Center Health Program Clinical Center of Excellence, NYU Langone Medical Center New York University School of Medicine New York New York USA
| | - Benjamin J. Luft
- Department of Medicine, World Trade Center Health Program Clinical Center of Excellence Stony Brook University Medical Center Stony Brook New York USA
| | - Jacqueline M. Moline
- Department of Occupational Medicine, Epidemiology and Prevention, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell World Trade Center Health Program Clinical Center of Excellence Hempstead New York USA
| | - Iris G. Udasin
- Department of Environmental and Occupational Medicine, World Trade Center Health Program Clinical Center of Excellence, Environmental and Occupational Health Sciences Institute Rutgers University Biomedical Sciences Piscataway New Jersey USA
| | - Andrew C. Todd
- Department of Environmental Medicine and Public Health Icahn School of Medicine at Mount Sinai New York New York USA
| | - Nancy L. Sloan
- Department of Environmental Medicine and Public Health Icahn School of Medicine at Mount Sinai New York New York USA
| | - Susan L. Teitelbaum
- Department of Environmental Medicine and Public Health Icahn School of Medicine at Mount Sinai New York New York USA
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Challener GJ, Myasoedova E, Crowson CS, Giblon RE, Atkinson EJ, Davis JM. Body mass index trend and variability in rheumatoid arthritis. Clin Rheumatol 2022; 41:349-355. [PMID: 34510294 PMCID: PMC10440724 DOI: 10.1007/s10067-021-05919-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 08/16/2021] [Accepted: 09/07/2021] [Indexed: 11/25/2022]
Abstract
OBJECTIVE To characterize and compare trends in body mass index (BMI) and variability in BMI between subjects with rheumatoid arthritis (RA) and matched non-RA subjects and to determine predictors of BMI trends and variability within RA subjects. METHODS This retrospective population-based cohort study included 1114 Olmsted County, Minnesota residents, 558 with incident RA (age ≥ 18 years, 1987 ACR criteria met in 1995-2009) and 556 non-RA subjects from the same underlying population with similar age, sex, and index calendar year. All subjects were followed until death, migration, or 12/31/2018. Generalized linear models with smoothing splines and random effects to account for multiple measurements per subject were used to examine trends in BMI measurements over time. RESULTS Mean BMI of patients with incident RA (28.8 kg/m2) was not significantly different from that of non-RA subjects (28.9 kg/m2). There was no significant difference in BMI trends over time between RA and non-RA cohorts, or between seropositive for rheumatoid factor (RF) and/or citrullinated antibody (CCP-antibody) and seronegative RA patients, or between male and female subjects. RA subjects were noted to have significantly higher BMI variability following diagnosis compared to non-RA subjects [difference in standard deviation between RA and non-RA subjects prior to index (p = 0.12), 0-5 years after index (p = 0.044), and 5-15 years after index (p = 0.013)]. CONCLUSION The BMI trajectory of the RA population is not significantly different compared to that of the non-RA population, but patients with RA demonstrate higher variability in BMI following diagnosis compared to the non-RA population. Key Points • This study uniquely characterizes longitudinal trajectory in BMI measures and their variability in the RA population versus the non-RA population • This study suggests that RA patients have greater BMI variability compared to the non-RA population, which is highly relevant as BMI variability is increasingly understood as a cardiovascular risk factor.
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Affiliation(s)
- Gregory J Challener
- Division of Rheumatology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA.
| | - Elena Myasoedova
- Division of Rheumatology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Cynthia S Crowson
- Division of Rheumatology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Rachel E Giblon
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | - John M Davis
- Division of Rheumatology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
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The point of no return? Functional disability transitions in patients with and without rheumatoid arthritis: A population-based cohort study. Semin Arthritis Rheum 2022; 52:151941. [PMID: 35000788 PMCID: PMC8810705 DOI: 10.1016/j.semarthrit.2021.12.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 11/03/2021] [Accepted: 12/07/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To assess transition probability between different levels of functional disability (FD) and time spent with FD in patients with versus without rheumatoid arthritis (RA) after RA incidence/index date. METHODS This retrospective population-based cohort study included Olmsted County, Minnesota residents (1987 ACR criteria met in 1999-2013) and comparators without RA from the same area with similar age, sex and RA incidence/index date. Activities of Daily Living (ADL) were obtained by self-report questionnaires annually since 1999. FD was defined as having difficulty with ≥1 ADL. Multistate modeling was used to estimate the probability of transitioning between FD states. RESULTS Five hundred fifty-eight patients with RA and 457 comparators completed ≥2 questionnaires and were included. Patients with RA had increased risk of transitioning from no FD to FD: Hazard Ratio (HR) 2.4; 95%CI:1.9-3.0. Each additional FD at RA onset reduced the probability of returning to no FD by 14%. However, the probability of having ≥1 FD was stable between RA incidence and 10-year follow-up. In the first 15 years of disease, patients with RA spent on average 10.1 years without FD and 3.4 years with ≥1 FD versus 11.6 years and 2.0 years (p<0.001) in comparators. CONCLUSION Patients with RA remain functionally disadvantaged compared to individuals without RA. The likelihood of returning to no FD in RA decreases with each additional preexisting FD. However, the probability of FD does not increase within 10 years of RA onset, potentially reflective of the benefits of disease-modifying treatments in RA.
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Zhang S, Rong G, Xu Y, Jing J. Elevated Nesfatin-1 Level in Synovium and Synovial Fluid is Associated with Pro-Inflammatory Cytokines in Patients with Rheumatoid Arthritis. Int J Gen Med 2021; 14:5269-5278. [PMID: 34522126 PMCID: PMC8434879 DOI: 10.2147/ijgm.s330099] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 08/24/2021] [Indexed: 12/11/2022] Open
Abstract
Background Adipocytokines have been proven to be involved in the progression of autoimmune diseases, including rheumatoid arthritis (RA). Nesfatin-1, a newly discovered adipokine, has recently been reported to possess potent anti-inflammatory, antiapoptotic, and antioxidative properties. However, its role in RA has not yet been reported. Therefore, this study aimed to determine nesfatin-1 levels in the synovium and synovial fluid (SF) of patients with RA and examine their correlation with clinical manifestations and proinflammatory cytokine levels. Methods Synovium and SF samples were collected from patients with RA and non-RA patients during joint surgery. Immunohistochemistry was used to measure nesfatin-1 protein expression in the synovium. Enzyme-linked immunosorbent assay was used to measure nesfatin-1, interleukin-1β (IL-1β), and tumor necrosis factor-α (TNF-α) levels in the synovium and SF. Pearson correlation analysis was used to evaluate the correlations between nesfatin-1 levels, RA clinical features, and proinflammatory cytokines. The diagnostic value of synovium nesfatin-1 for RA was assessed using receiver operating characteristic (ROC) curve analysis. Results The results showed that nesfatin-1, IL-1β, and TNF-α levels in the synovium were significantly higher in patients with RA than in controls, with age and body mass index as covariates. Moreover, the results of Pearson correlation analysis showed that nesfatin-1 levels were positively correlated with IL-1β and TNF-α levels in the synovium of patients with RA. Furthermore, there was a positive relationship between synovium nesfatin-1 levels and rheumatoid factor in patients with RA. Additionally, the results of the ROC curve analysis revealed an area under the curve of 0.733 with 77.5% sensitivity and 60.0% specificity for synovium nesfatin-1 in discriminating patients with RA from controls. Conclusion These findings suggest that increased nesfatin-1 levels in the synovium may be associated with proinflammatory cytokines and RA severity.
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Affiliation(s)
- Shuo Zhang
- Department of Orthopedics, The Second Affiliated Hospital of Anhui Medical University, Hefei, People's Republic of China
| | - Genxiang Rong
- Department of Orthopedics, The First Affiliated Hospital of Anhui Medical University, Hefei, People's Republic of China
| | - Yayun Xu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, People's Republic of China
| | - Juehua Jing
- Department of Orthopedics, The Second Affiliated Hospital of Anhui Medical University, Hefei, People's Republic of China
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Myasoedova E, Davis JM, Roger VL, Achenbach SJ, Crowson CS. Improved Incidence of Cardiovascular Disease in Patients With Incident Rheumatoid Arthritis in the 2000s: A Population-based Cohort Study. J Rheumatol 2021; 48:1379-1387. [PMID: 33589553 DOI: 10.3899/jrheum.200842] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/29/2021] [Indexed: 12/11/2022]
Abstract
OBJECTIVE To assess trends in incidence of cardiovascular disease (CVD) and mortality following incident CVD events in patients with rheumatoid arthritis (RA) onset in 1980-2009 vs non-RA subjects. METHODS We studied Olmsted County, Minnesota residents with incident RA (aged > 18 yrs, 1987 American College of Rheumatology criteria met in 1980-2009) and non-RA subjects from the same source population with similar age, sex, and calendar year of index. All subjects were followed until death, migration, or December 31, 2016. Incident CVD events included myocardial infarction and stroke. Patients with CVD before RA incidence/index date were excluded. Cox models were used to compare incident CVD events by decade, adjusting for age, sex, and CVD risk factors. RESULTS The study included 905 patients with RA and 904 non-RA subjects. Cumulative incidence of any CVD event was lower in patients with incident RA in the 2000s vs the 1980s. The HR for any incident CVD in the 2000s vs 1980s was 0.53 (95% CI 0.31-0.93). The strength of association attenuated after adjustment for anti-rheumatic medication use (HR 0.64, 95% CI 0.34-1.22). Patients with RA in the 2000s had no excess in CVD over non-RA subjects (HR 0.71, 95% CI 0.42-1.19). Risk of death after a CVD event was somewhat lower in patients with RA after the 1980s with an HR of 0.54 (95% CI 0.33-0.90) in the 1990s vs 1980s and 0.68 (95% CI 0.33-1.41) in the 2000s vs 1980s. CONCLUSION The incidence of major CVD events in RA has declined in recent decades. The gap in CVD occurrence between patients with RA and the general population is closing. Mortality after CVD events in RA may be improving.
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Affiliation(s)
- Elena Myasoedova
- E. Myasoedova, MD, PhD, Division of Rheumatology, Department of Internal Medicine, and Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic;
| | - John M Davis
- J.M. Davis III, MD, MS, Division of Rheumatology, Department of Internal Medicine, Mayo Clinic
| | - Veronique L Roger
- V.L. Roger, MD, MPH, Division of Epidemiology, Department of Health Sciences Research, and Division of Circulatory Failure, Department of Cardiovascular Disease, Mayo Clinic
| | - Sara J Achenbach
- S.J. Achenbach, MS, Division of Medical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic
| | - Cynthia S Crowson
- C.S. Crowson, PhD, Division of Rheumatology, Department of Internal Medicine, and Division of Medical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
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Sorour AA, Kurmann RD, Shahin YE, Crowson CS, Achenbach SJ, Mankad R, Myasoedova E. Use of Hydroxychloroquine and Risk of Heart Failure in Patients With Rheumatoid Arthritis. J Rheumatol 2021; 48:1508-1511. [PMID: 33452171 DOI: 10.3899/jrheum.201180] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/08/2021] [Indexed: 11/22/2022]
Abstract
OBJECTIVE To examine the relationship between the use of hydroxychloroquine (HCQ) and risk of developing heart failure (HF) in rheumatoid arthritis (RA). METHODS In this nested case-control study, cases were Olmsted County, Minnesota residents with incident RA (based on 1987 American College of Rheumatology criteria) from 1980 to 2013 who developed HF after RA incidence. Each case was matched on year of birth, sex, and year of RA incidence with an RA control who did not develop HF. Data on HCQ use including start and stop dates, as well as dose changes, were reviewed and used to calculate HCQ duration and cumulative dose. Age-adjusted logistic regression models were used to examine the association between HCQ and HF. RESULTS The study identified 143 RA cases diagnosed with HF (mean age 65.8 yrs, 62% females) and 143 non-HF RA controls (mean age 64.5, 62% female). HCQ cumulative dose was not associated with HF (OR 0.96 per 100-g increase in cumulative dose, 95% CI 0.90-1.03). Likewise, no association was found for patients with a cumulative dose ≥ 300 g (OR 0.92, 95% CI 0.41-2.08). The HCQ duration of intake in years prior to index was not associated with HF (OR 0.98, 95% CI 0.91-1.05). CONCLUSION Use of HCQ was not associated with development of HF in patients with RA in this study. Further studies are needed to understand the effect of higher doses of HCQ on the development of HF in RA.
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Affiliation(s)
- Ahmed A Sorour
- A.A. Sorour, MD, R.D. Kurmann, MD, Y.E. Shahin, R. Mankad, MD, Department of Cardiovascular Medicine, Mayo Clinic
| | - Reto D Kurmann
- A.A. Sorour, MD, R.D. Kurmann, MD, Y.E. Shahin, R. Mankad, MD, Department of Cardiovascular Medicine, Mayo Clinic
| | - Youssef E Shahin
- A.A. Sorour, MD, R.D. Kurmann, MD, Y.E. Shahin, R. Mankad, MD, Department of Cardiovascular Medicine, Mayo Clinic
| | - Cynthia S Crowson
- C.S. Crowson, PhD, Division of Biomedical Statistics and Informatics, and Department of Rheumatology, Mayo Clinic
| | - Sara J Achenbach
- S.J. Achenbach, MS, Division of Biomedical Statistics and Informatics, Mayo Clinic
| | - Rekha Mankad
- A.A. Sorour, MD, R.D. Kurmann, MD, Y.E. Shahin, R. Mankad, MD, Department of Cardiovascular Medicine, Mayo Clinic
| | - Elena Myasoedova
- E. Myasoedova, MD, PhD, Department of Rheumatology, Mayo Clinic, Rochester, Minnesota, USA.
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Multimorbidity and Fatigue in Rheumatoid Arthritis: A Cross-Sectional Study of a Population-Based Cohort. Rheumatol Ther 2020; 7:979-991. [PMID: 33113092 PMCID: PMC7695756 DOI: 10.1007/s40744-020-00247-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Accepted: 10/14/2020] [Indexed: 11/17/2022] Open
Abstract
Introduction The objective was to evaluate the relationships between multimorbidity and overall fatigue as well as fatigue subdomains in patients with rheumatoid arthritis (RA). Methods A cross-sectional study of a population-based cohort of patients with RA was performed. Fatigue was assessed using the Bristol Rheumatoid Arthritis Fatigue Multidimensional Questionnaire (BRAF-MDQ). Patients’ medical records were reviewed for 25 chronic comorbidities prior to the BRAF-MDQ. Linear and logistic regression models were used to estimate the differences in BRAF-MDQ total and subdomain (physical, living, cognitive, and emotional) scores associated with multimorbidity, adjusting for age, sex, disease duration, obesity, smoking, C-reactive protein, and RA autoantibodies. Higher BRAF-MDQ scores indicate greater fatigue severity. Results The cohort included 192 patients, median age 62 years, and median RA duration 13 years. Multimorbidity was common with 93 (48%) having ≥ 2 comorbidities, and 27 (14%) having ≥ 4 comorbidities. The median BRAF-MDQ total score was 9 (interquartile range 3–18), with higher scores indicating greater fatigue. Patients with ≥ 4 comorbidities had higher total BRAF-MDQ scores (median 16.5, interquartile range: 6.8–24.8) than patients with < 4 comorbidities (7.5, 2.8–16.0; p = 0.014). Each additional comorbidity was associated with a 2.33 (95% confidence interval [CI] 1.10–3.56) unit increase in total BRAF-MDQ score (p < 0.001), and the presence of ≥ 4 comorbidities was associated with a 9.33 (95% CI 3.92–14.7) unit increase in total BRAF-MDQ score. Multimorbidity was significantly associated with all four fatigue subdomains in adjusted models. Conclusions Multimorbidity is associated with increased fatigue in patients with RA. The findings suggest that interventions targeting multimorbidity could help alleviate treatment-refractory fatigue in patients with RA and other rheumatic diseases. Electronic Supplementary Material The online version of this article (10.1007/s40744-020-00247-y) contains supplementary material, which is available to authorized users.
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Myasoedova E, Davis JM, Achenbach SJ, Matteson EL, Crowson CS. Trends in Prevalence of Functional Disability in Rheumatoid Arthritis Compared With the General Population. Mayo Clin Proc 2019; 94:1035-1039. [PMID: 31054771 PMCID: PMC6555684 DOI: 10.1016/j.mayocp.2019.01.002] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Accepted: 01/03/2019] [Indexed: 01/04/2023]
Abstract
The objective of the study was to assess trends in functional disability (FD) in patients with rheumatoid arthritis (RA) vs individuals without RA. This retrospective population-based study included 586 patients with RA and 531 individuals without RA. Information on activities of daily living was obtained from self-report questionnaires. The prevalence of FD was higher in those with RA (586 [26%]) vs those without RA (531 [11%]) at RA incidence/index date (P<.001), with persistent excess over the follow-up and calendar time. Patients with RA had a 15% or higher prevalence of FD than individuals without RA in most age groups. Patients with RA have a higher prevalence of FD across RA duration, age, and calendar time than those without RA.
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Affiliation(s)
- Elena Myasoedova
- Division of Rheumatology, Department of Internal Medicine, Mayo Clinic, Rochester, MN.
| | - John M Davis
- Division of Rheumatology, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | - Sara J Achenbach
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Eric L Matteson
- Division of Rheumatology, Department of Internal Medicine, Mayo Clinic, Rochester, MN; Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Cynthia S Crowson
- Division of Rheumatology, Department of Internal Medicine, Mayo Clinic, Rochester, MN; Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
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Myasoedova E, Gabriel SE, Matteson EL, Davis JM, Therneau TM, Crowson CS. Decreased Cardiovascular Mortality in Patients with Incident Rheumatoid Arthritis (RA) in Recent Years: Dawn of a New Era in Cardiovascular Disease in RA? J Rheumatol 2017; 44:732-739. [PMID: 28365576 PMCID: PMC5457313 DOI: 10.3899/jrheum.161154] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/17/2017] [Indexed: 12/25/2022]
Abstract
OBJECTIVE To assess trends in cardiovascular (CV) mortality in patients with incident rheumatoid arthritis (RA) in 2000-07 versus the previous decades, compared with non-RA subjects. METHODS The study population consisted of Olmsted County, Minnesota, USA residents with incident RA (age ≥ 18 yrs, 1987 American College of Rheumatology criteria was met in 1980-2007) and non-RA subjects from the same underlying population with similar age, sex, and calendar year of index. All subjects were followed until death, migration, or December 31, 2014. Followup was truncated for comparability. Aalen-Johansen methods were used to estimate CV mortality rates, adjusting for competing risk of other causes. Cox proportional hazards models were used to compare CV mortality by decade. RESULTS The study included 813 patients with RA and 813 non-RA subjects (mean age 55.9 yrs; 68% women for both groups). Patients with incident RA in 2000-07 had markedly lower 10-year overall CV mortality (2.7%, 95% CI 0.6-4.9%) and coronary heart disease (CHD) mortality (1.1%, 95% CI 0.0-2.7%) than patients diagnosed in 1990-99 (7.1%, 95% CI 3.9-10.1% and 4.5%, 95% CI 1.9-7.1%, respectively; HR for overall CV death: 0.43, 95% CI 0.19-0.94; CHD death: HR 0.21, 95% CI 0.05-0.95). This improvement in CV mortality persisted after accounting for CV risk factors. Ten-year overall CV mortality and CHD mortality in 2000-07 RA incidence cohort was similar to non-RA subjects (p = 0.95 and p = 0.79, respectively). CONCLUSION Our findings suggest significantly improved overall CV mortality, particularly CHD mortality, in patients with RA in recent years. Further studies are needed to examine the reasons for this improvement.
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Affiliation(s)
- Elena Myasoedova
- From the Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science; Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science; Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science, Rochester, Minnesota; Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA.
- E. Myasoedova, MD, PhD, Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science; C.S. Crowson, MS, Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science, and Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science; E.L. Matteson, MD MPH, Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science, and Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science; J.M. Davis III, MD, MS, Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science; T.M. Therneau, PhD, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science; S.E. Gabriel, MD, MSc, Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science, and Rutgers Robert Wood Johnson Medical School.
| | - Sherine E Gabriel
- From the Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science; Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science; Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science, Rochester, Minnesota; Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA
- E. Myasoedova, MD, PhD, Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science; C.S. Crowson, MS, Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science, and Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science; E.L. Matteson, MD MPH, Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science, and Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science; J.M. Davis III, MD, MS, Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science; T.M. Therneau, PhD, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science; S.E. Gabriel, MD, MSc, Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science, and Rutgers Robert Wood Johnson Medical School
| | - Eric L Matteson
- From the Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science; Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science; Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science, Rochester, Minnesota; Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA
- E. Myasoedova, MD, PhD, Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science; C.S. Crowson, MS, Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science, and Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science; E.L. Matteson, MD MPH, Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science, and Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science; J.M. Davis III, MD, MS, Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science; T.M. Therneau, PhD, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science; S.E. Gabriel, MD, MSc, Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science, and Rutgers Robert Wood Johnson Medical School
| | - John M Davis
- From the Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science; Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science; Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science, Rochester, Minnesota; Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA
- E. Myasoedova, MD, PhD, Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science; C.S. Crowson, MS, Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science, and Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science; E.L. Matteson, MD MPH, Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science, and Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science; J.M. Davis III, MD, MS, Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science; T.M. Therneau, PhD, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science; S.E. Gabriel, MD, MSc, Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science, and Rutgers Robert Wood Johnson Medical School
| | - Terry M Therneau
- From the Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science; Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science; Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science, Rochester, Minnesota; Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA
- E. Myasoedova, MD, PhD, Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science; C.S. Crowson, MS, Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science, and Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science; E.L. Matteson, MD MPH, Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science, and Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science; J.M. Davis III, MD, MS, Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science; T.M. Therneau, PhD, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science; S.E. Gabriel, MD, MSc, Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science, and Rutgers Robert Wood Johnson Medical School
| | - Cynthia S Crowson
- From the Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science; Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science; Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science, Rochester, Minnesota; Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA
- E. Myasoedova, MD, PhD, Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science; C.S. Crowson, MS, Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science, and Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science; E.L. Matteson, MD MPH, Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science, and Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science; J.M. Davis III, MD, MS, Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine and Science; T.M. Therneau, PhD, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science; S.E. Gabriel, MD, MSc, Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine and Science, and Rutgers Robert Wood Johnson Medical School
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12
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Davis JM, Lin G, Oh JK, Crowson CS, Achenbach SJ, Therneau TM, Matteson EL, Rodeheffer RJ, Gabriel SE. Five-year changes in cardiac structure and function in patients with rheumatoid arthritis compared with the general population. Int J Cardiol 2017; 240:379-385. [PMID: 28427850 DOI: 10.1016/j.ijcard.2017.03.108] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2016] [Revised: 03/16/2017] [Accepted: 03/23/2017] [Indexed: 12/18/2022]
Abstract
BACKGROUND Patients with rheumatoid arthritis (RA) have increased risk of heart failure with preserved ejection fraction. The development and progression of left ventricular dysfunction before onset of clinical heart failure are unknown. The objective of this study was to evaluate longitudinal changes in cardiac structure and function of patients with RA compared with persons in the general population. METHODS A prospective longitudinal study of a population-based cohort of 160 patients with RA and a population-based cohort of 1391 persons without RA (non-RA cohort) was performed. Each participant underwent 2-dimensional, pulsed-wave tissue Doppler echocardiography at baseline and after 4 to 5years of follow-up. Age- and sex-adjusted linear regression models were used to test for differences between the RA and non-RA cohorts in annualized rates of change for echocardiographic parameters. RESULTS Mitral A velocity increased more rapidly among the patients with RA than the non-RA cohort (age- and sex-adjusted parameter estimate, 0.030; P<0.001). Correspondingly, the mean mitral inflow E/A ratio decreased faster in the RA cohort than the non-RA cohort (adjusted parameter estimate, -0.096; P<0.001). The left atrial volume index increased at a higher rate in the RA cohort than the non-RA cohort (adjusted parameter estimate, 0.150; P<0.001). CONCLUSIONS This pattern of echocardiographic findings confirms previous cross-sectional studies and indicates that subclinical changes in diastolic function occur more rapidly over 5years in RA patients than in the general population. Further research into the mechanisms of myocardial disease in these patients and the relationship with disease activity and treatment is warranted.
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Affiliation(s)
- John M Davis
- Division of Rheumatology, Mayo Clinic, Rochester, MN, United States.
| | - Grace Lin
- Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, United States
| | - Jae K Oh
- Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, United States
| | - Cynthia S Crowson
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, United States
| | - Sara J Achenbach
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, United States
| | - Terry M Therneau
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, United States
| | - Eric L Matteson
- Division of Rheumatology, Mayo Clinic, Rochester, MN, United States
| | | | - Sherine E Gabriel
- Division of Epidemiology, Mayo Clinic, Rochester, MN, United States; Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, United States
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Crow SS, Undavalli C, Warner DO, Katusic SK, Kandel P, Murphy SL, Schroeder DR, Watson RS. Epidemiology of Pediatric Critical Illness in a Population-Based Birth Cohort in Olmsted County, MN. Pediatr Crit Care Med 2017; 18:e137-e145. [PMID: 28125547 PMCID: PMC5336468 DOI: 10.1097/pcc.0000000000001084] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVES Investigations of pediatric critical illness typically focus on inpatient cohorts drawn from wide referral areas and diverse healthcare systems. Cohorts amenable to investigating the full spectrum of critical illness as it develops within a community have yet to be studied in the United States. Our objective was to provide the first epidemiologic report of the incidence and presentation of pediatric critical illness within a U.S. population-based birth cohort. DESIGN Retrospective cohort study. SETTING A geographically defined community (Olmsted, MN) with medical record linkage across all health systems. All ICU services are provided within a single children's hospital. PATIENTS A birth cohort of children (n =9,441) born 2003-2007 in Olmsted County, MN. MEASUREMENTS AND MAIN RESULTS During the study period, there were a total of 15,277 ICU admissions to Mayo Clinic Children's Hospital. A total of 577 birth cohort children accounted for 824 of these admissions during the 61,770 person-years of follow-up accumulated. Incidence of first-time ICU admission was 9.3 admits per 1,000 person-years. Admission rates were highest in the first year of life and then declined steadily. Respiratory problems were among the most common reasons for admission at any age and diagnoses reflect changes in health risk factors as children grow and develop over time. After 1 year old, a majority of children admitted have preexisting chronic comorbidities and/or prior ICU stays. In-hospital mortality occurred exclusively in children admitted prior to 5 days of age (n = 4). Seven children died after hospital discharge. CONCLUSIONS This is the first report characterizing critical illness within a population-based birth cohort of U.S. children. The results demonstrate the changing incidence, presentation, and healthcare requirements associated with critical illness across the developmental spectrum as a population of children ages.
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Affiliation(s)
- Sheri S Crow
- 1Division of Pediatric Critical Care, Department of Pediatrics and Adolescent Medicine, Department of Health Services Research, Mayo Clinic College of Medicine, Rochester, MN. 2Division of Pediatric Critical Care, Department of Pediatrics and Adolescent Medicine, Mayo Clinic College of Medicine, Rochester, MN. 3Department of Anesthesiology, Mayo Clinic College of Medicine, Rochester, MN. 4Department of Epidemiology and Pediatrics and Adolescent Medicine, Mayo Clinic College of Medicine, Rochester, MN. 5Division of Gastroenterology, Department of Internal Medicine, Mayo Clinic College of Medicine, Rochester, MN. 6Mayo Medical School, Mayo Clinic College of Medicine, Rochester, MN. 7Department of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine, Rochester, MN. 8Division of Pediatric Critical Care Medicine, Department of Pediatrics, University of Washington School of Medicine, and Center for Child Health, Behavior, and Development, Seattle Children's Research Institute, Seattle, WA
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Krause ML, Zamora-Legoff JA, Crowson CS, Muskardin TW, Mason T, Matteson EL. Population-based study of outcomes of patients with juvenile idiopathic arthritis (JIA) compared to non-JIA subjects. Semin Arthritis Rheum 2016; 46:439-443. [PMID: 27522464 DOI: 10.1016/j.semarthrit.2016.07.003] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2016] [Revised: 06/07/2016] [Accepted: 07/14/2016] [Indexed: 01/22/2023]
Abstract
OBJECTIVE Evaluate healthcare utilization and occurrence of comorbidities in a population-based cohort of patients of juvenile idiopathic arthritis (JIA) with an age- and sex-matched comparator group. METHODS Prevalent cases of JIA in 1994-2013 were identified in Olmsted County, Minnesota, along with age- and sex-matched non-JIA comparators. Surgeries, hospitalizations, pregnancies, and comorbidities were identified by medical record review. Poisson methods were used to generate rate ratios (RR) with 95% confidence intervals (CI) to compare outcomes between JIA and non-JIA cohorts separately during childhood (age < 18 years) and adulthood (age ≥ 18 years). RESULTS A total of 89 JIA and 89 non-JIA comparators were identified [64% female; mean (SD) age 8.6 (5.1) years at JIA incidence/index date and mean follow-up in childhood 6.3 (4.4) years for JIA; similar for comparators]. Among them, 38 pairs had follow-up into adulthood with mean follow-up of 8.0 (5.5) years for JIA. Children with JIA were more likely to have joint surgery (RR = 3.93, 95% CI: 1.18-24.94), non-joint surgery (RR = 1.90, 95% CI: 1.05-3.67), and hospitalizations (RR = 2.25, 95% CI: 1.04-5.53) than non-JIA comparators. As adults only joint surgeries remained significantly different (RR = 8.5, 95% CI: 2.27-120.1). Depression during childhood was more common in JIA (RR = 2.49, 95% CI: 1.01-6.13). There were no differences in educational achievement, employment status, or pregnancy outcomes between the 2 groups. CONCLUSIONS In a population-based cohort, inpatient healthcare utilization is higher for patients with JIA including surgery and hospitalization during childhood but not extending into adulthood. Understanding long-term comorbidities and healthcare needs for patients with JIA is necessary to provide comprehensive care.
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Affiliation(s)
- Megan L Krause
- Division of Rheumatology, Mayo Clinic College of Medicine, 200 First St SW, Rochester, MN 55905.
| | - Jorge A Zamora-Legoff
- Division of Rheumatology, Mayo Clinic College of Medicine, 200 First St SW, Rochester, MN 55905
| | - Cynthia S Crowson
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN
| | | | - Thomas Mason
- Division of Rheumatology, Mayo Clinic College of Medicine, 200 First St SW, Rochester, MN 55905
| | - Eric L Matteson
- Division of Rheumatology, Mayo Clinic College of Medicine, 200 First St SW, Rochester, MN 55905; Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN
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Zamora-Legoff JA, Krause ML, Crowson CS, Muskardin TW, Mason T, Matteson EL. Treatment of patients with juvenile idiopathic arthritis (JIA) in a population-based cohort. Clin Rheumatol 2016; 35:1493-9. [PMID: 26825065 DOI: 10.1007/s10067-016-3190-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2016] [Accepted: 01/23/2016] [Indexed: 11/28/2022]
Abstract
A population-based cohort was utilized to evaluate medications and intra-articular injection utilization for patients with juvenile idiopathic arthritis (JIA) to inform clinical practice and further research. In a geographically defined population, all incident cases of JIA cases were identified between January 1, 1994 and December 31, 2013 based first on diagnosis code followed by medical chart confirmation. Medications and intra-articular glucocorticoid injections were abstracted. Predictors of the first disease-modifying antirheumatic drug (DMARD)/biologic and injections were reported as a hazard ratio (HR) with 95 % confidence intervals (CIs) adjusted for age and sex. Kaplan-Meier methods evaluated therapy at 6 months and 1 year. Injections were reported per 100 person-years (py) with 95 % CI using the Poisson methods. Seventy-one incident cases were identified. Forty-two (59 %) were female with mean age (standard deviation) at diagnosis of 8.2 (5.3) years. Twenty-six (37 %) utilized at least one DMARD or biologic, in which 77 % of these were prescribed in the first 6 months. Subtype of JIA was significantly associated with DMARDs/biologics (p < 0.001). Intra-articular injections were performed in 48 %. The rate of intra-articular injections was 20.7 per 100 py (95 % CI 16.5, 25.6). The rate of joint injections was higher in the first year after diagnosis (p < 0.001) and more common in recent years (p < 0.001). The majority of patients with JIA in a modern population-based cohort do not require DMARDs or biologics. In those who do, the majority receives these within the first 6 months. Intra-articular injections were utilized in almost half of patients with JIA and were increasingly used.
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Affiliation(s)
- Jorge A Zamora-Legoff
- Division of Rheumatology, Department of Health Sciences Research, Mayo Clinic College of Medicine, Mayo Clinic, Rochester, MN, USA. .,Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
| | - Megan L Krause
- Division of Rheumatology, Department of Health Sciences Research, Mayo Clinic College of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Cynthia S Crowson
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Theresa Wampler Muskardin
- Division of Rheumatology, Department of Health Sciences Research, Mayo Clinic College of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Thomas Mason
- Division of Rheumatology, Department of Health Sciences Research, Mayo Clinic College of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Eric L Matteson
- Division of Rheumatology, Department of Health Sciences Research, Mayo Clinic College of Medicine, Mayo Clinic, Rochester, MN, USA.,Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine, Mayo Clinic, Rochester, MN, USA
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Wright KA, Crowson CS, Michet CJ, Matteson EL. Time trends in incidence, clinical features, and cardiovascular disease in ankylosing spondylitis over three decades: a population-based study. Arthritis Care Res (Hoboken) 2015; 67:836-41. [PMID: 25384671 PMCID: PMC4550091 DOI: 10.1002/acr.22512] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2014] [Revised: 09/29/2014] [Accepted: 11/04/2014] [Indexed: 12/17/2022]
Abstract
OBJECTIVE To determine trends in the incidence and clinical presentation of ankylosing spondylitis (AS), the incidence of cardiovascular disease (CVD), and cardiovascular (CV) risk factors among patients with AS and compare the observed incidence of CVD with that predicted by the Framingham Risk Score (FRS). METHODS A population-based inception cohort of residents of Olmsted County, Minnesota age ≥18 years who fulfilled Modified New York Criteria for AS in 1980-2009 was assembled. Clinical features at presentation were recorded. Age- and sex-adjusted incidence rates and survival were estimated. Incident CVD and CV risk factors were identified. The 10-year CVD risk was calculated using the FRS. Standardized incidence ratios (ratios of observed CVD in AS to that predicted by the FRS) were calculated. RESULTS Eighty-six patients were diagnosed with AS over the study period with an age- and sex-adjusted incidence of 3.1 per 100,000 (95% confidence interval [95% CI] 2.5-3.8). The mean age at diagnosis was 35 years (range 19-69 years). Inflammatory back pain, seen in 90% of patients, was the most common presenting manifestation. The 10-year mean ± SD cumulative incidence of CVD was 15.8% ± 6.1%, three times higher than the predicted events based on the FRS (standardized incidence ratio 3.01, 95% CI 1.35-6.69; P = 0.007). Overall survival was similar to the general population. CONCLUSION AS occurs in approximately 3 persons per 100,000 per year. Clinical features, extraarticular manifestations, and interval from symptom onset to diagnosis have remained constant in this population over the study period. The CVD risk in these patients is higher than expected and underestimated by the FRS.
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Affiliation(s)
- Kerry A. Wright
- Division of Rheumatology, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Cynthia S. Crowson
- Division of Rheumatology, Mayo Clinic College of Medicine, Rochester, MN, USA
- Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Clement J. Michet
- Division of Rheumatology, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Eric L. Matteson
- Division of Rheumatology, Mayo Clinic College of Medicine, Rochester, MN, USA
- Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA
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Deng X, Crowson CS, Rajkumar SV, Dispenzieri A, Larson DR, Therneau TM, Matteson EL, Kyle RA, Katzmann JA, Gabriel SE, Davis JM. Elevation of serum immunoglobulin free light chains during the preclinical period of rheumatoid arthritis. J Rheumatol 2015; 42:181-7. [PMID: 25593227 DOI: 10.3899/jrheum.140543] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
OBJECTIVE Immunoglobulin free light chains (FLC) represent biomarkers of B cell activity in rheumatoid arthritis (RA) and are associated with all-cause mortality in the general population. Our objective was to evaluate the relationships of serum FLC to preclinical disease, RA characteristics, and mortality in RA compared to non-RA subjects. METHODS A population-based study in Olmsted County, Minnesota, USA, was performed by crosslinking a large cohort in the general population having available serum FLC measurements with established RA incidence and prevalence cohorts. Serum κ, λ, and total FLC and their trends relative to RA incidence were compared between RA and non-RA subjects. Regression models were used to determine the associations between FLC, disease characteristics, and mortality, testing for differential effects of FLC on mortality in RA. RESULTS Among 16,609 subjects, 270 fulfilled the criteria for RA at the time of FLC measurement. Mean total FLC were significantly higher in RA compared to non-RA subjects (4.2 vs 3.3 mg/dl, p < 0.001). FLC became elevated 3-5 years before the clinical onset of RA and remained elevated during followup. Polyclonal FLC were found to predict higher mortality in persons with RA, though elevation to the highest decile had a relatively lower effect on mortality in RA compared to non-RA subjects. CONCLUSION Elevation of serum FLC precedes the development of RA and may be useful in monitoring B cell activity and disease progression. FLC are associated with mortality among patients with RA as well as the general population.
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Affiliation(s)
- Xiaoli Deng
- From the Department of Rheumatology and Immunology, Peking University Third Hospital, Beijing, China; Department of Health Sciences Research, Department of Medicine, and Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.X. Deng, MD, Department of Rheumatology and Immunology, Peking University Third Hospital, and formerly Research Trainee, Division of Rheumatology, Departments of Medicine and Immunology, Mayo Clinic; C.S. Crowson, MS, Associate Professor of Medicine, Assistant Professor of Biostatistics; T.M. Therneau, PhD, Professor of Biostatistics, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research; S.V. Rajkumar, MD, Professor of Medicine, Division of Hematology, Department of Medicine; A. Dispenzieri, MD, Professor of Medicine, Professor of Laboratory Medicine and Pathology; R.A. Kyle, MD, Professor of Medicine, Professor of Laboratory Medicine and Pathology, Division of Hematology, Department of Medicine; E.L. Matteson, MD, MPH, Professor of Medicine; S.E. Gabriel, MD, MSc, Professor of Epidemiology, Professor of Medicine, Division of Rheumatology, Department of Medicine, Division of Epidemiology, Department of Health Sciences Research; J.M. Davis III, MD, MS, Associate Professor of Medicine, Division of Rheumatology, Department of Medicine; J.A. Katzmann, PhD, Assistant Professor of Microbiology, Associate Professor of Laboratory Medicine and Pathology, Division of Clinical Biochemistry and Immunology, Department of Laboratory Medicine and Pathology, Mayo Clinic, and the Mayo Clinic College of Medicine; D.R. Larson, MS, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic
| | - Cynthia S Crowson
- From the Department of Rheumatology and Immunology, Peking University Third Hospital, Beijing, China; Department of Health Sciences Research, Department of Medicine, and Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.X. Deng, MD, Department of Rheumatology and Immunology, Peking University Third Hospital, and formerly Research Trainee, Division of Rheumatology, Departments of Medicine and Immunology, Mayo Clinic; C.S. Crowson, MS, Associate Professor of Medicine, Assistant Professor of Biostatistics; T.M. Therneau, PhD, Professor of Biostatistics, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research; S.V. Rajkumar, MD, Professor of Medicine, Division of Hematology, Department of Medicine; A. Dispenzieri, MD, Professor of Medicine, Professor of Laboratory Medicine and Pathology; R.A. Kyle, MD, Professor of Medicine, Professor of Laboratory Medicine and Pathology, Division of Hematology, Department of Medicine; E.L. Matteson, MD, MPH, Professor of Medicine; S.E. Gabriel, MD, MSc, Professor of Epidemiology, Professor of Medicine, Division of Rheumatology, Department of Medicine, Division of Epidemiology, Department of Health Sciences Research; J.M. Davis III, MD, MS, Associate Professor of Medicine, Division of Rheumatology, Department of Medicine; J.A. Katzmann, PhD, Assistant Professor of Microbiology, Associate Professor of Laboratory Medicine and Pathology, Division of Clinical Biochemistry and Immunology, Department of Laboratory Medicine and Pathology, Mayo Clinic, and the Mayo Clinic College of Medicine; D.R. Larson, MS, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic
| | - S Vincent Rajkumar
- From the Department of Rheumatology and Immunology, Peking University Third Hospital, Beijing, China; Department of Health Sciences Research, Department of Medicine, and Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.X. Deng, MD, Department of Rheumatology and Immunology, Peking University Third Hospital, and formerly Research Trainee, Division of Rheumatology, Departments of Medicine and Immunology, Mayo Clinic; C.S. Crowson, MS, Associate Professor of Medicine, Assistant Professor of Biostatistics; T.M. Therneau, PhD, Professor of Biostatistics, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research; S.V. Rajkumar, MD, Professor of Medicine, Division of Hematology, Department of Medicine; A. Dispenzieri, MD, Professor of Medicine, Professor of Laboratory Medicine and Pathology; R.A. Kyle, MD, Professor of Medicine, Professor of Laboratory Medicine and Pathology, Division of Hematology, Department of Medicine; E.L. Matteson, MD, MPH, Professor of Medicine; S.E. Gabriel, MD, MSc, Professor of Epidemiology, Professor of Medicine, Division of Rheumatology, Department of Medicine, Division of Epidemiology, Department of Health Sciences Research; J.M. Davis III, MD, MS, Associate Professor of Medicine, Division of Rheumatology, Department of Medicine; J.A. Katzmann, PhD, Assistant Professor of Microbiology, Associate Professor of Laboratory Medicine and Pathology, Division of Clinical Biochemistry and Immunology, Department of Laboratory Medicine and Pathology, Mayo Clinic, and the Mayo Clinic College of Medicine; D.R. Larson, MS, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic
| | - Angela Dispenzieri
- From the Department of Rheumatology and Immunology, Peking University Third Hospital, Beijing, China; Department of Health Sciences Research, Department of Medicine, and Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.X. Deng, MD, Department of Rheumatology and Immunology, Peking University Third Hospital, and formerly Research Trainee, Division of Rheumatology, Departments of Medicine and Immunology, Mayo Clinic; C.S. Crowson, MS, Associate Professor of Medicine, Assistant Professor of Biostatistics; T.M. Therneau, PhD, Professor of Biostatistics, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research; S.V. Rajkumar, MD, Professor of Medicine, Division of Hematology, Department of Medicine; A. Dispenzieri, MD, Professor of Medicine, Professor of Laboratory Medicine and Pathology; R.A. Kyle, MD, Professor of Medicine, Professor of Laboratory Medicine and Pathology, Division of Hematology, Department of Medicine; E.L. Matteson, MD, MPH, Professor of Medicine; S.E. Gabriel, MD, MSc, Professor of Epidemiology, Professor of Medicine, Division of Rheumatology, Department of Medicine, Division of Epidemiology, Department of Health Sciences Research; J.M. Davis III, MD, MS, Associate Professor of Medicine, Division of Rheumatology, Department of Medicine; J.A. Katzmann, PhD, Assistant Professor of Microbiology, Associate Professor of Laboratory Medicine and Pathology, Division of Clinical Biochemistry and Immunology, Department of Laboratory Medicine and Pathology, Mayo Clinic, and the Mayo Clinic College of Medicine; D.R. Larson, MS, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic
| | - Dirk R Larson
- From the Department of Rheumatology and Immunology, Peking University Third Hospital, Beijing, China; Department of Health Sciences Research, Department of Medicine, and Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.X. Deng, MD, Department of Rheumatology and Immunology, Peking University Third Hospital, and formerly Research Trainee, Division of Rheumatology, Departments of Medicine and Immunology, Mayo Clinic; C.S. Crowson, MS, Associate Professor of Medicine, Assistant Professor of Biostatistics; T.M. Therneau, PhD, Professor of Biostatistics, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research; S.V. Rajkumar, MD, Professor of Medicine, Division of Hematology, Department of Medicine; A. Dispenzieri, MD, Professor of Medicine, Professor of Laboratory Medicine and Pathology; R.A. Kyle, MD, Professor of Medicine, Professor of Laboratory Medicine and Pathology, Division of Hematology, Department of Medicine; E.L. Matteson, MD, MPH, Professor of Medicine; S.E. Gabriel, MD, MSc, Professor of Epidemiology, Professor of Medicine, Division of Rheumatology, Department of Medicine, Division of Epidemiology, Department of Health Sciences Research; J.M. Davis III, MD, MS, Associate Professor of Medicine, Division of Rheumatology, Department of Medicine; J.A. Katzmann, PhD, Assistant Professor of Microbiology, Associate Professor of Laboratory Medicine and Pathology, Division of Clinical Biochemistry and Immunology, Department of Laboratory Medicine and Pathology, Mayo Clinic, and the Mayo Clinic College of Medicine; D.R. Larson, MS, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic
| | - Terry M Therneau
- From the Department of Rheumatology and Immunology, Peking University Third Hospital, Beijing, China; Department of Health Sciences Research, Department of Medicine, and Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.X. Deng, MD, Department of Rheumatology and Immunology, Peking University Third Hospital, and formerly Research Trainee, Division of Rheumatology, Departments of Medicine and Immunology, Mayo Clinic; C.S. Crowson, MS, Associate Professor of Medicine, Assistant Professor of Biostatistics; T.M. Therneau, PhD, Professor of Biostatistics, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research; S.V. Rajkumar, MD, Professor of Medicine, Division of Hematology, Department of Medicine; A. Dispenzieri, MD, Professor of Medicine, Professor of Laboratory Medicine and Pathology; R.A. Kyle, MD, Professor of Medicine, Professor of Laboratory Medicine and Pathology, Division of Hematology, Department of Medicine; E.L. Matteson, MD, MPH, Professor of Medicine; S.E. Gabriel, MD, MSc, Professor of Epidemiology, Professor of Medicine, Division of Rheumatology, Department of Medicine, Division of Epidemiology, Department of Health Sciences Research; J.M. Davis III, MD, MS, Associate Professor of Medicine, Division of Rheumatology, Department of Medicine; J.A. Katzmann, PhD, Assistant Professor of Microbiology, Associate Professor of Laboratory Medicine and Pathology, Division of Clinical Biochemistry and Immunology, Department of Laboratory Medicine and Pathology, Mayo Clinic, and the Mayo Clinic College of Medicine; D.R. Larson, MS, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic
| | - Eric L Matteson
- From the Department of Rheumatology and Immunology, Peking University Third Hospital, Beijing, China; Department of Health Sciences Research, Department of Medicine, and Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.X. Deng, MD, Department of Rheumatology and Immunology, Peking University Third Hospital, and formerly Research Trainee, Division of Rheumatology, Departments of Medicine and Immunology, Mayo Clinic; C.S. Crowson, MS, Associate Professor of Medicine, Assistant Professor of Biostatistics; T.M. Therneau, PhD, Professor of Biostatistics, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research; S.V. Rajkumar, MD, Professor of Medicine, Division of Hematology, Department of Medicine; A. Dispenzieri, MD, Professor of Medicine, Professor of Laboratory Medicine and Pathology; R.A. Kyle, MD, Professor of Medicine, Professor of Laboratory Medicine and Pathology, Division of Hematology, Department of Medicine; E.L. Matteson, MD, MPH, Professor of Medicine; S.E. Gabriel, MD, MSc, Professor of Epidemiology, Professor of Medicine, Division of Rheumatology, Department of Medicine, Division of Epidemiology, Department of Health Sciences Research; J.M. Davis III, MD, MS, Associate Professor of Medicine, Division of Rheumatology, Department of Medicine; J.A. Katzmann, PhD, Assistant Professor of Microbiology, Associate Professor of Laboratory Medicine and Pathology, Division of Clinical Biochemistry and Immunology, Department of Laboratory Medicine and Pathology, Mayo Clinic, and the Mayo Clinic College of Medicine; D.R. Larson, MS, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic
| | - Robert A Kyle
- From the Department of Rheumatology and Immunology, Peking University Third Hospital, Beijing, China; Department of Health Sciences Research, Department of Medicine, and Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.X. Deng, MD, Department of Rheumatology and Immunology, Peking University Third Hospital, and formerly Research Trainee, Division of Rheumatology, Departments of Medicine and Immunology, Mayo Clinic; C.S. Crowson, MS, Associate Professor of Medicine, Assistant Professor of Biostatistics; T.M. Therneau, PhD, Professor of Biostatistics, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research; S.V. Rajkumar, MD, Professor of Medicine, Division of Hematology, Department of Medicine; A. Dispenzieri, MD, Professor of Medicine, Professor of Laboratory Medicine and Pathology; R.A. Kyle, MD, Professor of Medicine, Professor of Laboratory Medicine and Pathology, Division of Hematology, Department of Medicine; E.L. Matteson, MD, MPH, Professor of Medicine; S.E. Gabriel, MD, MSc, Professor of Epidemiology, Professor of Medicine, Division of Rheumatology, Department of Medicine, Division of Epidemiology, Department of Health Sciences Research; J.M. Davis III, MD, MS, Associate Professor of Medicine, Division of Rheumatology, Department of Medicine; J.A. Katzmann, PhD, Assistant Professor of Microbiology, Associate Professor of Laboratory Medicine and Pathology, Division of Clinical Biochemistry and Immunology, Department of Laboratory Medicine and Pathology, Mayo Clinic, and the Mayo Clinic College of Medicine; D.R. Larson, MS, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic
| | - Jerry A Katzmann
- From the Department of Rheumatology and Immunology, Peking University Third Hospital, Beijing, China; Department of Health Sciences Research, Department of Medicine, and Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.X. Deng, MD, Department of Rheumatology and Immunology, Peking University Third Hospital, and formerly Research Trainee, Division of Rheumatology, Departments of Medicine and Immunology, Mayo Clinic; C.S. Crowson, MS, Associate Professor of Medicine, Assistant Professor of Biostatistics; T.M. Therneau, PhD, Professor of Biostatistics, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research; S.V. Rajkumar, MD, Professor of Medicine, Division of Hematology, Department of Medicine; A. Dispenzieri, MD, Professor of Medicine, Professor of Laboratory Medicine and Pathology; R.A. Kyle, MD, Professor of Medicine, Professor of Laboratory Medicine and Pathology, Division of Hematology, Department of Medicine; E.L. Matteson, MD, MPH, Professor of Medicine; S.E. Gabriel, MD, MSc, Professor of Epidemiology, Professor of Medicine, Division of Rheumatology, Department of Medicine, Division of Epidemiology, Department of Health Sciences Research; J.M. Davis III, MD, MS, Associate Professor of Medicine, Division of Rheumatology, Department of Medicine; J.A. Katzmann, PhD, Assistant Professor of Microbiology, Associate Professor of Laboratory Medicine and Pathology, Division of Clinical Biochemistry and Immunology, Department of Laboratory Medicine and Pathology, Mayo Clinic, and the Mayo Clinic College of Medicine; D.R. Larson, MS, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic
| | - Sherine E Gabriel
- From the Department of Rheumatology and Immunology, Peking University Third Hospital, Beijing, China; Department of Health Sciences Research, Department of Medicine, and Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.X. Deng, MD, Department of Rheumatology and Immunology, Peking University Third Hospital, and formerly Research Trainee, Division of Rheumatology, Departments of Medicine and Immunology, Mayo Clinic; C.S. Crowson, MS, Associate Professor of Medicine, Assistant Professor of Biostatistics; T.M. Therneau, PhD, Professor of Biostatistics, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research; S.V. Rajkumar, MD, Professor of Medicine, Division of Hematology, Department of Medicine; A. Dispenzieri, MD, Professor of Medicine, Professor of Laboratory Medicine and Pathology; R.A. Kyle, MD, Professor of Medicine, Professor of Laboratory Medicine and Pathology, Division of Hematology, Department of Medicine; E.L. Matteson, MD, MPH, Professor of Medicine; S.E. Gabriel, MD, MSc, Professor of Epidemiology, Professor of Medicine, Division of Rheumatology, Department of Medicine, Division of Epidemiology, Department of Health Sciences Research; J.M. Davis III, MD, MS, Associate Professor of Medicine, Division of Rheumatology, Department of Medicine; J.A. Katzmann, PhD, Assistant Professor of Microbiology, Associate Professor of Laboratory Medicine and Pathology, Division of Clinical Biochemistry and Immunology, Department of Laboratory Medicine and Pathology, Mayo Clinic, and the Mayo Clinic College of Medicine; D.R. Larson, MS, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic
| | - John M Davis
- From the Department of Rheumatology and Immunology, Peking University Third Hospital, Beijing, China; Department of Health Sciences Research, Department of Medicine, and Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.X. Deng, MD, Department of Rheumatology and Immunology, Peking University Third Hospital, and formerly Research Trainee, Division of Rheumatology, Departments of Medicine and Immunology, Mayo Clinic; C.S. Crowson, MS, Associate Professor of Medicine, Assistant Professor of Biostatistics; T.M. Therneau, PhD, Professor of Biostatistics, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research; S.V. Rajkumar, MD, Professor of Medicine, Division of Hematology, Department of Medicine; A. Dispenzieri, MD, Professor of Medicine, Professor of Laboratory Medicine and Pathology; R.A. Kyle, MD, Professor of Medicine, Professor of Laboratory Medicine and Pathology, Division of Hematology, Department of Medicine; E.L. Matteson, MD, MPH, Professor of Medicine; S.E. Gabriel, MD, MSc, Professor of Epidemiology, Professor of Medicine, Division of Rheumatology, Department of Medicine, Division of Epidemiology, Department of Health Sciences Research; J.M. Davis III, MD, MS, Associate Professor of Medicine, Division of Rheumatology, Department of Medicine; J.A. Katzmann, PhD, Assistant Professor of Microbiology, Associate Professor of Laboratory Medicine and Pathology, Division of Clinical Biochemistry and Immunology, Department of Laboratory Medicine and Pathology, Mayo Clinic, and the Mayo Clinic College of Medicine; D.R. Larson, MS, Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic.
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18
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Epidemiologic concepts and classification of rheumatic and musculoskeletal conditions. Rheumatology (Oxford) 2015. [DOI: 10.1016/b978-0-323-09138-1.00001-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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Bobo WV, Pathak J, Kremers HM, Yawn BP, Brue SM, Stoppel CJ, Croarkin PE, St Sauver J, Frye MA, Rocca WA. An electronic health record driven algorithm to identify incident antidepressant medication users. J Am Med Inform Assoc 2014; 21:785-91. [PMID: 24780720 PMCID: PMC4147111 DOI: 10.1136/amiajnl-2014-002699] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2014] [Revised: 04/16/2014] [Accepted: 04/18/2014] [Indexed: 11/25/2022] Open
Abstract
OBJECTIVE We validated an algorithm designed to identify new or prevalent users of antidepressant medications via population-based drug prescription records. PATIENTS AND METHODS We obtained population-based drug prescription records for the entire Olmsted County, Minnesota, population from 2011 to 2012 (N=149,629) using the existing electronic medical records linkage infrastructure of the Rochester Epidemiology Project (REP). We selected electronically a random sample of 200 new antidepressant users stratified by age and sex. The algorithm required the exclusion of antidepressant use in the 6 months preceding the date of the first qualifying antidepressant prescription (index date). Medical records were manually reviewed and adjudicated to calculate the positive predictive value (PPV). We also manually reviewed the records of a random sample of 200 antihistamine users who did not meet the case definition of new antidepressant user to estimate the negative predictive value (NPV). RESULTS 161 of the 198 subjects electronically identified as new antidepressant users were confirmed by manual record review (PPV 81.3%). Restricting the definition of new users to subjects who were prescribed typical starting doses of each agent for treating major depression in non-geriatric adults resulted in an increase in the PPV (90.9%). Extending the time windows with no antidepressant use preceding the index date resulted in only modest increases in PPV. The manual abstraction of medical records of 200 antihistamine users yielded an NPV of 98.5%. CONCLUSIONS Our study confirms that REP prescription records can be used to identify prevalent and incident users of antidepressants in the Olmsted County, Minnesota, population.
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Affiliation(s)
- William V Bobo
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota, USA
| | - Jyotishman Pathak
- Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Hilal Maradit Kremers
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Barbara P Yawn
- Division of Research, Olmsted Medical Center, Rochester, Minnesota, USA
| | - Scott M Brue
- Biomedical Informatics Support System, Mayo Clinic, Rochester, Minnesota, USA
| | - Cynthia J Stoppel
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota, USA
| | - Paul E Croarkin
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota, USA
| | - Jennifer St Sauver
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Mark A Frye
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota, USA
| | - Walter A Rocca
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
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Myasoedova E, Crowson CS, Green AB, Matteson EL, Gabriel SE. Longterm blood pressure variability in patients with rheumatoid arthritis and its effect on cardiovascular events and all-cause mortality in RA: a population-based comparative cohort study. J Rheumatol 2014; 41:1638-44. [PMID: 24986852 DOI: 10.3899/jrheum.131170] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
OBJECTIVE To examine longterm visit-to-visit blood pressure (BP) variability in patients with rheumatoid arthritis (RA) versus non-RA subjects and to assess its effect on cardiovascular (CV) events and mortality in RA. METHODS Clinic BP measures were collected in a population-based incident cohort of patients with RA (1987 American College of Rheumatology criteria met between January 1, 1995, and January 1, 2008) and non-RA subjects. BP variability was defined as within-subject SD in systolic and diastolic BP. RESULTS The study included 442 patients with RA (mean age 55.5 yrs, 70% females) and 424 non-RA subjects (mean age 55.7 yrs, 69% females). Patients with RA had higher visit-to-visit variability in systolic BP (13.8 ± 4.7 mm Hg) than did non-RA subjects (13.0 ± 5.2 mm Hg, p = 0.004). Systolic BP variability declined after the index date in RA (p < 0.001) but not in the non-RA cohort (p = 0.73), adjusting for age, sex, and calendar year of RA. During the mean followup of 7.1 years, 33 CV events and 57 deaths occurred in the RA cohort. Visit-to-visit systolic BP variability was associated with increased risk of CV events (HR per 1 mm Hg increase in BP variability 1.12, 95% CI 1.01-1.25). Diastolic BP variability was associated with all-cause mortality in RA (HR 1.14, 95% CI 1.03-1.27), adjusting for systolic and diastolic BP, body mass index, smoking, diabetes, dyslipidemia, and use of antihypertensives. CONCLUSION Patients with RA had higher visit-to-visit systolic BP variability than did non-RA subjects. There was a significant decline in systolic BP variability after RA incidence. Higher visit-to-visit BP variability was associated with adverse CV outcomes and all-cause mortality in RA.
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Affiliation(s)
- Elena Myasoedova
- From the Department of Health Sciences Research, and the Division of Rheumatology, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.E. Myasoedova, MD, PhD; C.S. Crowson, MS, Department of Health Sciences Research, and the Division of Rheumatology; A.B. Green, MS, Department of Health Sciences Research; E.L. Matteson, MD, MPH; S.E. Gabriel, MD, MSc, Department of Health Sciences Research, and the Division of Rheumatology, Mayo Clinic College of Medicine
| | - Cynthia S Crowson
- From the Department of Health Sciences Research, and the Division of Rheumatology, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.E. Myasoedova, MD, PhD; C.S. Crowson, MS, Department of Health Sciences Research, and the Division of Rheumatology; A.B. Green, MS, Department of Health Sciences Research; E.L. Matteson, MD, MPH; S.E. Gabriel, MD, MSc, Department of Health Sciences Research, and the Division of Rheumatology, Mayo Clinic College of Medicine.
| | - Abigail B Green
- From the Department of Health Sciences Research, and the Division of Rheumatology, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.E. Myasoedova, MD, PhD; C.S. Crowson, MS, Department of Health Sciences Research, and the Division of Rheumatology; A.B. Green, MS, Department of Health Sciences Research; E.L. Matteson, MD, MPH; S.E. Gabriel, MD, MSc, Department of Health Sciences Research, and the Division of Rheumatology, Mayo Clinic College of Medicine
| | - Eric L Matteson
- From the Department of Health Sciences Research, and the Division of Rheumatology, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.E. Myasoedova, MD, PhD; C.S. Crowson, MS, Department of Health Sciences Research, and the Division of Rheumatology; A.B. Green, MS, Department of Health Sciences Research; E.L. Matteson, MD, MPH; S.E. Gabriel, MD, MSc, Department of Health Sciences Research, and the Division of Rheumatology, Mayo Clinic College of Medicine
| | - Sherine E Gabriel
- From the Department of Health Sciences Research, and the Division of Rheumatology, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.E. Myasoedova, MD, PhD; C.S. Crowson, MS, Department of Health Sciences Research, and the Division of Rheumatology; A.B. Green, MS, Department of Health Sciences Research; E.L. Matteson, MD, MPH; S.E. Gabriel, MD, MSc, Department of Health Sciences Research, and the Division of Rheumatology, Mayo Clinic College of Medicine
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21
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The global shift: Shadows of identifiability. Behav Brain Sci 2014; 37:99-100. [DOI: 10.1017/s0140525x1300188x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
AbstractThe presence of overwhelming amounts of information in our big-data era society is growing. Globalisation is increasingly giving these solicitations (regarding information) a more social aspect causing behavioural changes. While restricting my focus on this aspect of the Bentley et al article, I address related medical questions and pin-point the conceptual interest of the roadmap given therein.
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Jebakumar AJ, Udayakumar PD, Crowson CS, Gabriel SE, Matteson EL. Occurrence and effect of lower extremity ulcer in rheumatoid arthritis -- a population-based Study. J Rheumatol 2014; 41:437-43. [PMID: 24429171 DOI: 10.3899/jrheum.130392] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
OBJECTIVE To assess the occurrence, risk factors, morbidity, and mortality associated with lower extremity (LE) ulcers in patients with rheumatoid arthritis (RA). METHODS Retrospective review of Olmsted County, Minnesota, USA, residents who first fulfilled the 1987 American College of Rheumatology criteria for RA in 1980-2007 with followup to death, migration, or April 2012. Only LE ulcers that developed after the diagnosis of RA were included. RESULTS The study included 813 patients with 9771 total person-years of followup. Of them, 125 developed LE ulcers (total of 171 episodes), corresponding to a rate of occurrence of 1.8 episodes per 100 person-years (95% CI: 1.5, 2.0 per 100 person-yrs). The cumulative incidence of first LE ulcers was 4.8% at 5 years after diagnosis of RA and increased to 26.2% by 25 years. Median time for the LE ulcer to heal was 30 days. Ten of 171 episodes (6%) led to amputation. LE ulcers in RA were associated with increased mortality (HR 2.42; 95% CI 1.71, 3.42), adjusted for age, sex, and calendar year. Risk factors for LE ulcers included age (HR 1.73 per 10-yr increase; 95% CI 1.47, 2.04), rheumatoid factor positivity (HR 1.63; 95% CI 1.05, 2.53), presence of rheumatoid nodules (HR 2.14; 95% CI 1.39, 3.31), and venous thromboembolism (HR 2.16; 95% CI 1.07, 4.36). CONCLUSION LE ulcers are common among patients with RA. The cumulative incidence increased by 1% per year. A significant number require amputation. Patients with RA who have LE ulcers are at a 2-fold risk for premature mortality.
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Affiliation(s)
- Adlene J Jebakumar
- From the Department of Health Sciences Research and the Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
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Barrick BJ, Lohse CM, Lehman JS. Specific causes of death in patients with bullous pemphigoid as measured by death certificate data: a retrospective cohort study. Int J Dermatol 2013; 54:56-61. [PMID: 24372100 DOI: 10.1111/ijd.12243] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
BACKGROUND Mortality rates in patients with bullous pemphigoid (BP) are higher than those in age-matched counterparts. However, the specific causes of death in BP subjects have not been evaluated systematically. OBJECTIVES We sought to characterize the causes of death in patients with BP as recorded by death certificate and to compare these with death data for age- and location-matched control subjects. METHODS This was a retrospective cohort analysis conducted in a large tertiary referral center. Twenty-seven participants who had a confirmed antemortem diagnosis of BP, were residents of Olmsted County, Minnesota, and had died between January 1, 1999, and January 1, 2009, were included in the study. Underlying cause of death and multiple causes of death data for the study population were compared with data sourced from the Centers for Disease Control and Prevention (CDC) for a control group matched by age and geographic location of origin by International Classification of Diseases, 10th Revision (ICD-10) block, and specific ICD-10 codes. RESULTS Comparisons of specific ICD-10 codes revealed increased rates of sepsis (P = 0.031), dementia (P = 0.049), and major depressive disorder (P = 0.005) in the study group. The collective incidence of ICD-10 codes for infections indicated that infections were more frequent contributors to death in the study group (P = 0.035). CONCLUSIONS Clinicians should be mindful of contributors to death in patients with BP and might consider screening for mental health issues, educating patients on the early symptoms of sepsis, and minimizing risk factors for infection.
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Affiliation(s)
- Benjamin J Barrick
- Kansas City University of Medicine and Biosciences, Kansas City, MO, USA
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Myasoedova E, Gabriel SE, Green AB, Matteson EL, Crowson CS. Impact of statin use on lipid levels in statin-naive patients with rheumatoid arthritis versus non-rheumatoid arthritis subjects: results from a population-based study. Arthritis Care Res (Hoboken) 2013; 65:1592-9. [PMID: 23592565 DOI: 10.1002/acr.22029] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2012] [Accepted: 03/27/2013] [Indexed: 01/04/2023]
Abstract
OBJECTIVE To examine lipid profiles among statin-naive patients with rheumatoid arthritis (RA) and those without RA before and after the initiation of statins. METHODS Information regarding lipid measures and statin use was gathered in a population-based incident cohort of patients with RA (1987 American College of Rheumatology criteria first met between January 1, 1988 and January 1, 2008) and in a cohort of non-RA subjects from the same underlying population. Only patients with no prior history of statin use were included. RESULTS The study included 161 patients with RA (mean age 56.3 years, 57% female) and 221 non-RA subjects (mean age 56.0 years, 66% female). Prior to the start of statins, the levels of total cholesterol and low-density lipoprotein (LDL) cholesterol were lower in the RA versus the non-RA cohort (P < 0.001 and P = 0.003, respectively). The absolute and percentage change in LDL cholesterol after at least 90 days of statin use tended to be smaller in the RA versus the non-RA cohort (P = 0.03 and P = 0.09, respectively). After at least 90 days of statin use, patients with RA were less likely to achieve therapeutic goals for LDL cholesterol than the non-RA subjects (P = 0.046). Increased erythrocyte sedimentation rate (ESR) at baseline (odds ratio 0.47, 95% confidence interval 0.26-0.85) was associated with lower likelihood of achieving therapeutic LDL goals. CONCLUSION Patients with RA had lower total cholesterol and LDL cholesterol levels before statin initiation and lower likelihood of achieving therapeutic LDL goals following statin use than the non-RA subjects. Some RA disease characteristics, in particular ESR at baseline, may have an adverse impact on achieving therapeutic LDL goals.
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Myasoedova E, Davis JM, Crowson CS, Roger VL, Karon BL, Borgeson DD, Therneau TM, Matteson EL, Rodeheffer RJ, Gabriel SE. Brief report: rheumatoid arthritis is associated with left ventricular concentric remodeling: results of a population-based cross-sectional study. ACTA ACUST UNITED AC 2013; 65:1713-8. [PMID: 23553738 DOI: 10.1002/art.37949] [Citation(s) in RCA: 50] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2012] [Accepted: 03/19/2013] [Indexed: 11/08/2022]
Abstract
OBJECTIVE To study left ventricular (LV) geometry in patients with rheumatoid arthritis (RA) and no history of heart failure compared with that in subjects with neither RA nor a history of heart failure, and to determine the impact of RA on LV remodeling. METHODS A cross-sectional, community-based study was conducted among adult (age ≥50 years) patients with RA and age- and sex-matched subjects with neither RA nor a history of heart failure. All participants underwent standard 2-dimensional Doppler echocardiography. LV geometry was classified into the following 4 categories based on relative wall thickness and sex-specific cutoffs for the LV mass index: concentric remodeling, concentric hypertrophy, eccentric hypertrophy, or normal geometry. RESULTS Among 200 patients with RA and 600 age- and sex-matched subjects without RA, the mean age was 65 years, and 74% of the individuals in both cohorts were female. Compared with subjects without RA, patients with RA were significantly more likely to have abnormal LV geometry (odds ratio [OR] 1.44, 95% confidence interval [95% CI] 1.03-2.00), even after adjusting for cardiovascular risk factors and comorbidities. Among subjects with abnormal LV geometry, the odds of concentric LV remodeling were significantly increased in patients with RA (OR 4.73, 95% CI 2.85-7.83). In linear regression analyses, the LV mass index appeared to be lower in patients with RA who were currently receiving corticosteroids (β ± SE -0.082 ± 0.027, P = 0.002), even after adjusting for cardiovascular risk factors and comorbidities. CONCLUSION RA was strongly associated with abnormal LV remodeling (particularly concentric LV remodeling) among RA patients without heart failure. This association remained significant after adjustment for cardiovascular risk factors and comorbidities. RA disease-related factors may promote changes in LV geometry. The biologic mechanisms underlying LV remodeling warrant further investigation.
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Akkara Veetil BM, Myasoedova E, Matteson EL, Gabriel SE, Crowson CS. Use of lipid-lowering agents in rheumatoid arthritis: a population-based cohort study. J Rheumatol 2013; 40:1082-8. [PMID: 23637326 DOI: 10.3899/jrheum.121302] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
OBJECTIVE Rheumatoid arthritis (RA) is associated with an increased risk of cardiovascular disease and mortality. Lipid-lowering therapy is reportedly underused in patients with RA. Longitudinal cohort studies comparing use of lipid-lowering medications in patients with RA versus the general population are lacking. METHODS Cardiovascular risk factors, lipid measures, and use of lipid-lowering agents were assessed in a population-based inception cohort of patients with RA and a cohort of non-RA subjects followed from January 1, 1988, to December 31, 2008. The National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATPIII) guidelines were assessed at the time of each lipid measure throughout followup. Time from meeting guidelines to initiation of lipid-lowering agents was assessed using Kaplan-Meier methods. RESULTS The study population included 412 RA and 438 non-RA patients with ≥ 1 lipid measure during followup and no prior use of lipid-lowering agents. Rates of lipid testing were lower among patients with RA compared to non-RA subjects. Among patients who met NCEP ATPIII criteria for lipid-lowering therapy (n = 106 RA; n = 120 non-RA), only 27% of RA and 26% of non-RA subjects initiated lipid-lowering agents within 2 years of meeting the guidelines for initiation. CONCLUSION There was substantial undertreatment in both the RA and the non-RA cohorts who met NCEP ATPIII criteria for initiation of lipid-lowering agents. Patients with RA did not have as frequent lipid testing as individuals in the general population.
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Affiliation(s)
- Bharath Manu Akkara Veetil
- Division of Rheumatology and Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota 55905, USA
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Myasoedova E, Akkara Veetil BM, Matteson EL, Kremers HM, McEvoy MT, Crowson CS. Cardiovascular risk in psoriasis: a population-based analysis with assessment of the framingham risk score. SCIENTIFICA 2013; 2013:371569. [PMID: 24278773 PMCID: PMC3820308 DOI: 10.1155/2013/371569] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2012] [Accepted: 01/07/2013] [Indexed: 06/02/2023]
Abstract
Objective. To examine the utility of the Framingham risk score (FRS) in estimating cardiovascular risk in psoriasis. Methods. We compared the predicted 10-year risk of cardiovascular events, namely, cardiovascular death, myocardial infarction, heart failure, percutaneous transluminal coronary angioplasty, and coronary artery bypass grafting using the FRS, to the observed risk of cardiovascular events in a population-based cohort of patients with psoriasis. Patients with incident or prevalent adult-onset psoriasis aged 30-79 years without prior history of cardiovascular disease were included. Results. Among the 1197 patients with predicted risk scores, the median FRS was 6.0%, while the observed 10-year cardiovascular risk was 6.9% (standardized incidence ratio (SIR): 1.14; 95% confidence interval (CI): 0.92-1.42). The SIR was not elevated for women nor for men. The differences between observed and predicted cardiovascular risks in patients <60 years (SIR: 1.01; 95% CI: 0.73-1.41) or ≥60 years (SIR: 1.26; 95% CI: 0.95-1.68) were not statistically significant. Conclusion. There was no apparent difference between observed and predicted cardiovascular risks in patients with psoriasis in our study. FRS reasonably estimated cardiovascular risk in both men and women as well as in younger and older psoriasis patients, suggesting that FRS can be used in risk stratification in psoriasis without further adjustment.
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Affiliation(s)
- Elena Myasoedova
- Division of Rheumatology, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
- Department of Health Sciences Research, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
| | - Bharath Manu Akkara Veetil
- Division of Rheumatology, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
| | - Eric L. Matteson
- Division of Rheumatology, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
- Department of Health Sciences Research, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
| | - Hilal Maradit Kremers
- Department of Health Sciences Research, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
| | - Marian T. McEvoy
- Department of Dermatology, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
| | - Cynthia S. Crowson
- Division of Rheumatology, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
- Department of Health Sciences Research, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
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Epling-Burnette PK, McDaniel J, Wei S, List AF. Emerging immunosuppressive drugs in myelodysplastic syndromes. Expert Opin Emerg Drugs 2012; 17:519-41. [PMID: 23163589 DOI: 10.1517/14728214.2012.736487] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
INTRODUCTION Myelodysplastic syndromes (MDS) are characterized by dysplastic morphologic features and ineffective hematopoiesis. Pathophysiological characteristics change over time making therapeutic development a major challenge. In early MDS, cytopenias arise or are exacerbated by humoral and cellular immune-mediators that suppress hematopoietic progenitor survival and alter the bone marrow microenvironment. AREAS COVERED In this review, current immunosuppressive regimens are described. To identify new therapies that may enhance immunosuppressive therapy (IST) response and identify pharmacodynamic biomarkers for patient selection, the inflammasome, cytokines, metabolic pathways and signaling events are described. EXPERT OPINION Agents with the potential to induce early, durable hematologic remissions are needed and many new immunosuppressive agents are available for investigation. An immune-mediated mechanism is likely to contribute to MDS early after diagnosis. New approaches that interfere with inflammatory pathways in the bone marrow microenvironment may move closer toward sustained disease control in MDS.
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Affiliation(s)
- Pearlie K Epling-Burnette
- H. Lee Moffitt Cancer Center & Research Institute, Immunology Department, SRB 23033, 12902 Magnolia Dr, Tampa, FL 33612, USA.
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Akkara Veetil BM, Matteson EL, Maradit-Kremers H, McEvoy MT, Crowson CS. Trends in lipid profiles in patients with psoriasis: a population-based analysis. BMC DERMATOLOGY 2012; 12:20. [PMID: 23110323 PMCID: PMC3520693 DOI: 10.1186/1471-5945-12-20] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/29/2012] [Accepted: 10/08/2012] [Indexed: 11/10/2022]
Abstract
BACKGROUND Psoriasis is associated with an atherogenic lipid profile but longitudinal changes in lipids around disease onset are unknown. The purpose of our study is to examine the effect of psoriasis onset on serum lipid profiles. METHODS We compared changes in lipid profiles in a population based incident cohort of 689 patients with psoriasis and 717 non-psoriasis subjects. All lipid measures performed 5 years before and after psoriasis incidence/index date were abstracted. Random-effects models adjusting for age, sex and calendar year were used to examine trends in lipid profiles. RESULTS There were significant declines in total cholesterol (TC) and low-density lipoprotein (LDL) levels during the 5 years before and after psoriasis incidence/index date in both the psoriasis and the non-psoriasis cohorts, with a greater decrease noted in the TC levels (p=0.022) and LDL (p=0.054) in the non-psoriasis cohort. High-density lipoprotein (HDL) levels increased significantly both before and after psoriasis incidence date in the psoriasis cohort. Triglyceride (TG) levels were significantly higher (p<0.001), and HDL levels significantly lower (p=0.013) in patients with psoriasis compared to non-psoriasis subjects. There were no differences in prescriptions for lipid lowering drugs between the two cohorts. CONCLUSIONS Patients with psoriasis had a significant decrease in TC and LDL levels during the 5 years before psoriasis incidence. Higher mean TG and lower mean HDL levels were noted in the 5 years before psoriasis incidence. These changes are unlikely to be caused by lipid lowering treatment alone and require further exploration.
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Myasoedova E, Matteson EL, Talley NJ, Crowson CS. Increased incidence and impact of upper and lower gastrointestinal events in patients with rheumatoid arthritis in Olmsted County, Minnesota: a longitudinal population-based study. J Rheumatol 2012; 39:1355-62. [PMID: 22467929 DOI: 10.3899/jrheum.111311] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
OBJECTIVE To assess the incidence and mortality impact of upper and lower gastrointestinal (GI) events in rheumatoid arthritis (RA) compared to non-RA subjects. METHODS We identified incident upper and lower GI events and estimated their incidence rates using person-year methods in a population-based incident RA cohort of residents of Olmsted County, Minnesota, USA (1987 American College of Rheumatology criteria first fulfilled between January 1, 1980, and January 1, 2008) and non-RA subjects from the same population. RESULTS The study included 813 patients with RA and 813 non-RA subjects (mean followup 10.3 and 10.8 yrs, respectively); 68% women; mean age 55.9 yrs in both cohorts. The rate of upper GI events/100 person-years was 2.9 in RA versus 1.7 in the non-RA cohort (rate ratio 1.7, 95% CI 1.4, 2.2); for lower GI events, the rates were 2.1 in RA versus 1.4 in the non-RA cohort (rate ratio 1.5, 95% CI 1.1, 1.9). The incidence of upper GI bleed, perforation, ulcer, obstruction, and any upper GI event in RA declined over calendar time; the incidence of lower GI events remained unchanged. Exposure to glucocorticoids, prior upper GI disease, abdominal surgery, and smoking were associated with lower GI events in RA. Both upper and lower GI events were associated with increased mortality risk in RA. CONCLUSION There is increased risk of serious upper and lower GI events in RA compared to non-RA subjects, and increased GI-related mortality in RA. Prominent declines in incidence of upper, but not lower GI events in RA highlight the need for studies investigating lower GI disease in patients with RA.
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Affiliation(s)
- Elena Myasoedova
- Department of Health Sciences Research and Division of Rheumatology, Department of Internal Medicine, Mayo Clinic College of Medicine, Rochester, Minnesota 55905, USA
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Singh JA, Jensen MR, Harmsen WS, Gabriel SE, Lewallen DG. Cardiac and thromboembolic complications and mortality in patients undergoing total hip and total knee arthroplasty. Ann Rheum Dis 2011; 70:2082-8. [PMID: 22021865 PMCID: PMC3315837 DOI: 10.1136/ard.2010.148726] [Citation(s) in RCA: 75] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
OBJECTIVE To study 90-day complications following total hip arthroplasty (THA) or total knee arthroplasty (TKA). METHOD In a population-based cohort of all Olmsted County residents who underwent a THA or TKA (1994-2008), we assessed 90-day occurrence and predictors of cardiac complications (myocardial infarction, cardiac arrhythmia or congestive heart failure), thromboembolic complications (deep venous thrombosis or pulmonary embolism) and mortality. RESULTS 90-day complication rates after THA and TKA were: cardiac, 6.9% and 6.7%; thromboembolic, 4.0% and 4.9%; and mortality, 0.7% and 0.4%, respectively. In multivariable-adjusted logistic regression analyses, ASA class III-IV (OR 6.1, 95% CI:1.6-22.8) and higher Deyo-Charlson comorbidity score (OR 1.2, 95% CI:1.0-1.4) were significantly associated with odds of 90-day cardiac event post-THA in patients with no known previous cardiac event. In those with known previous cardiac disease, ASA class III-IV (OR 4.4, 95% CI:2.0-9.9), male gender (OR 0.5, 95% CI:0.3-0.9) and history of thromboembolic disease (OR 3.2; 95% CI:1.4-7.0) were significantly associated with odds of cardiac complication 90 days post-THA. No significant predictors of thromboembolism were found in THA patients. In TKA patients with no previous cardiac history, age >65 years (OR 4.1, 95% CI:1.2-14.0) and in TKA patients with known cardiac disease, ASA class III-IV (OR 3.2, 95% CI:1.8-5.7) was significantly associated with odds of 90-day cardiac events. In TKA patients with no previous thromboembolic disease, male gender (OR 0.5, 95% CI:0.2-0.9) and higher Charlson index (OR 1.2, 95% CI:1.1-1.3) and in patients with known thromboembolic disease, higher Charlson index score (OR 1.2, 95% CI:1.1-1.4) was associated with odds of 90-day thromboembolic events. CONCLUSION Older age, higher comorbidity, higher ASA class and previous history of cardiac/thromboembolic disease were associated with an increased risk.
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Affiliation(s)
- Jasvinder A Singh
- Department of Health Sciences Research, Mayo Clinic School of Medicine, Rochester, Minnesota, USA.
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Aponte EP, Diehl N, Mohney BG. Medical and surgical outcomes in childhood glaucoma: a population-based study. J AAPOS 2011; 15:263-7. [PMID: 21652244 PMCID: PMC3175405 DOI: 10.1016/j.jaapos.2011.02.015] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2010] [Revised: 01/30/2011] [Accepted: 02/05/2011] [Indexed: 11/17/2022]
Abstract
INTRODUCTION To describe the clinical and surgical outcomes among patients younger than 20 years of age diagnosed with glaucoma in a defined population during a 40-year period. METHODS The medical records of all patients (<20 years) diagnosed with glaucoma in Olmsted County, Minnesota, from January 1, 1965, through December 31, 2004, were retrospectively reviewed. RESULTS Thirty children (45 eyes) were diagnosed with various forms of glaucoma during the 40-year study period. During a mean follow-up of 12.5 years (range, 7 days to 32 years), 18 (60%) of the 30 children underwent a mean of 2.7 surgeries (range, 1 to 10), including 6 (20%) patients whose sole surgery consisted of enucleation or evisceration for a blind, painful eye. Twenty-eight (93%) of the 30 children required medical management during the follow-up period, including 14 (47%) treated before their first surgery. At the final follow-up examination, 11 (37%) had a visual acuity of 20/200 or worse. The 10-year Kaplan-Meier risk of vision decreasing less than 20/200 in all glaucoma patients was 22.7% (95% CI, 0-40.9), and patients requiring any glaucoma surgery was 68.3% (95% CI, 42.4-82.6). CONCLUSIONS In this population-based study of children diagnosed with glaucoma during a 40-year period, most patients required surgery, with few being successfully controlled by medications alone. A poor visual outcome or the loss of an eye was relatively common.
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Affiliation(s)
| | - Nancy Diehl
- Mayo Clinic Division of Biostatistics, Rochester, Minnesota
| | - Brian G. Mohney
- Mayo Clinic Department of Ophthalmology, Rochester, Minnesota
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