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Adherence patterns in naïve and prevalent use of infliximab and its biosimilar. BMC Rheumatol 2022; 6:65. [PMID: 36316762 PMCID: PMC9623955 DOI: 10.1186/s41927-022-00295-7] [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: 02/21/2022] [Accepted: 07/22/2022] [Indexed: 11/05/2022] Open
Abstract
Introduction Although short-term clinical trials have demonstrated that switching from infliximab (INF) bio-originator to its biosimilar is safe with no significant loss of efficacy, there are limited real-world data comparing their patterns of use and adherence. Methods Using 2015–2018 IBM Marketscan data, we established 4 cohorts of patients with at least one administration or pharmacy claim for INF bio-originator or biosimilar in 2017, including INF naïve biosimilar users, INF prevalent biosimilar users, INF naïve bio-originator users, and INF prevalent bio-originator users, defined according to their prior use of INF from 2015 to their first INF administration in 2017. The proportion of days covered (PDC) was calculated for patients with at least 6, 12, or 18 months of follow-up time. Factors associated with optimal adherence (PDC > 80%) were evaluated using log-binomial models. Results We identified 96 INF naïve biosimilar users, 223 INF prevalent biosimilar users, 2,149 INF naïve bio-originator users, and 10,970 INF prevalent bio-originator users. At the end of 18 months of follow-up, 64% of INF prevalent bio-originators, 48% of INF naïve biosimilars, 41% of INF naïve bio-originators, and 36% of INF prevalent biosimilars had optimal adherence. Depression, previous hospitalization, and greater use of prior biologics were negatively associated with adherence, whereas IBD diagnoses (referent to RA) and age 55–64 (referent to < 35) were positively associated with high adherence. Conclusion INF prevalent users had higher adherence in our analyses than INF naïve users. However, further studies with larger sample size are needed to evaluate INF biosimilar users’ adherence.
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Hresko A, Lin TC, Solomon DH. Medical Care Costs Associated With Rheumatoid Arthritis in the US: A Systematic Literature Review and Meta-Analysis. Arthritis Care Res (Hoboken) 2019; 70:1431-1438. [PMID: 29316377 DOI: 10.1002/acr.23512] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2017] [Accepted: 01/02/2018] [Indexed: 12/17/2022]
Abstract
OBJECTIVE Rheumatoid arthritis (RA) is a morbid, mortal, and costly condition without a cure. Treatments for RA have expanded over the last 2 decades, and direct medical costs may differ by types of treatments. There has not been a systematic literature review since the introduction of new RA treatments, including biologic disease-modifying antirheumatic drugs (bDMARDs). METHODS We conducted a systematic literature review with meta-analysis of direct medical costs associated with RA patients cared for in the US since the marketing of the first bDMARD. Standard search strategies and sources were used, and data were extracted independently by 2 reviewers. The methods and quality of included studies were assessed. Total direct medical costs as well as RA-specific costs were calculated using random-effects meta-analysis. Subgroups of interest included Medicare patients and those using bDMARDs. RESULTS We found 541 potentially relevant studies, and 12 articles met the selection criteria. The quality of studies varied: one-third were poor, one-third were fair, and one-third were good. Total direct medical costs were estimated at $12,509 (95% confidence interval [95% CI] 7,451-21,001) for all RA patients using any treatment regimen and $36,053 (95% CI 32,138-40,445) for bDMARD users. RA-specific costs were $3,723 (95% CI 2,408-5,762) for all RA patients using any treatment regimen and $20,262 (95% CI 17,480-23,487) for bDMARD users. CONCLUSION The total and disease-specific direct medical costs for patients with RA is substantial. Among bDMARD users, the cost of RA care is more than half of all direct medical costs.
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Affiliation(s)
- Andrew Hresko
- Tufts University School of Medicine, Boston, Massachusetts
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Thorne C, Boire G, Chow A, Garces K, Liu F, Poulin-Costello M, Walker V, Haraoui B. Dose Escalation and Co-therapy Intensification Between Etanercept, Adalimumab, and Infliximab: The CADURA Study. Open Rheumatol J 2017; 11:123-135. [PMID: 29296125 PMCID: PMC5744265 DOI: 10.2174/1874312901711010123] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2017] [Revised: 09/05/2017] [Accepted: 09/26/2017] [Indexed: 01/04/2023] Open
Abstract
Objective To compare anti-TNF dose escalation, DMARD and/or glucocorticoid intensification, switches to another biologic, and drug and drug-related costs over 12 and 18 months for rheumatoid arthritis (RA) patients initiating etanercept (ETN), adalimumab (ADA), or infliximab (IFX) in routine clinical practice across Canada. Methods A retrospective chart review of biologic-naïve adult RA patients newly initiating ADA, ETN, or IFX between January 01, 2006 and December 31, 2012 from 11 practices across Canada. Results There were 314 patients in the 12-month analysis and 217 in the 18-month analysis. No dose escalation occurred with ETN over 12 and 18 months versus 38% and 32% for IFX (p<0.001) and 2% and 2% for ADA (p=0.199, p=0.218). Over 18 months, dose escalation and/or DMARD and/or glucocorticoid intensification was less frequent among ETN (16%) versus IFX (44%, p=0.005) and ADA (34%, p=0.004). By 18 months, 22% of patients initiating ADA had switched to another biologic compared with 6% of ETN patients (p=0.001).Patients initiating ETN had lower total (drug and drug-related) costs over 12 and 18 months compared to IFX, and no difference compared to ADA when adjusted for potential confounders. Patients with dose escalation had higher costs compared to those with no dose escalation. Conclusion Physicians were more likely to escalate the dose of IFX, but optimize co-therapy with ADA and ETN. ETN patients had no dose escalation and were less likely to have DMARD and/or glucocorticoid intensification than ADA patients. ETN-treated patients had lower costs compared to IFX patients.
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Affiliation(s)
- Carter Thorne
- The Arthritis Program Research Group, Southlake Regional Health Centre, c/o 43 Lundy's Lane, Newmarket, ON, L3Y 3R7, Canada
| | - Gilles Boire
- Centre Hospitalier Universitaire de Sherbrooke (CIUSSS de l'Estrie-CHUS), Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Andrew Chow
- Credit Valley Rheumatology, Mississauga, ON, Canada
| | | | - Fang Liu
- Optum, 5500 North Service Road, Suite 501, Burlington, ON, L7L 6W6, Canada
| | | | - Valery Walker
- Optum, 5500 North Service Road, Suite 501, Burlington, ON, L7L 6W6, Canada
| | - Boulos Haraoui
- Institut de Rhumatologie de Montreal, Montreal, QC, Canada
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Doshi JA, Hu T, Li P, Pettit AR, Yu X, Blum M. Specialty Tier-Level Cost Sharing and Biologic Agent Use in the Medicare Part D Initial Coverage Period Among Beneficiaries With Rheumatoid Arthritis. Arthritis Care Res (Hoboken) 2016; 68:1624-1630. [DOI: 10.1002/acr.22880] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2015] [Revised: 02/18/2016] [Accepted: 03/01/2016] [Indexed: 11/08/2022]
Affiliation(s)
| | | | | | | | - Xinyan Yu
- University of Pennsylvania; Philadelphia
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Krack G, Zeidler H, Zeidler J. Claims Data Analysis of Tumor Necrosis Factor Inhibitor Treatment Dosing Among Patients with Rheumatoid Arthritis: A Systematic Review of Methods. Drugs Real World Outcomes 2016; 3:265-278. [PMID: 27747836 PMCID: PMC5042945 DOI: 10.1007/s40801-016-0089-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Background With tumor necrosis factor inhibitors, changes of dosing, switching between drugs, insufficient adherence, and persistence are frequent in rheumatoid arthritis. Because this is often associated with decreased efficiency and increased costs, dosage analyses based on claims data are of increasing interest for healthcare providers and payers. Nevertheless, no standardized methods exist to ensure high-quality research. Objective In this review, we compare and discuss applied methods in claims data-based dosage analyses of tumor necrosis factor inhibitor prescriptions in patients with rheumatoid arthritis. Methods A systematic review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. The dosage analysis methods performed within the selected studies were classified into switching, persistence, adherence, and dosage-change analyses, and were then compared and finally discussed. Results A total of 45 studies were found to be relevant. In most studies, a change in dose or persistence was evaluated, followed by switching and adherence analyses. Analyses of changed dose exhibit the most extensive variation of methods. We divided them into three principal methods, where a specified reference dose is compared with (1) the last dose, (2) any dose, or (3) all doses. Conclusion The systematic review identified a high variation of methods. Our results may be helpful for choosing appropriate methods in future studies. The results also demonstrate the need for evidence-based recommendations of methods used in claims data research.
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Affiliation(s)
- Gundula Krack
- Munich Center of Health Sciences (MC-Health), Ludwig Maximilian University of Munich, Ludwigstraße 28, 80539, Munich, Germany. .,German Research Center for Environmental Health (GmbH), Institute of Health Economics and Health Care Management, Helmholtz Zentrum München, Neuherberg, Germany.
| | - Henning Zeidler
- Division of Immunology and Rheumatology, Medical School Hannover, Hannover, Germany
| | - Jan Zeidler
- Center for Health Economics Research Hannover (CHERH), Leibniz University Hannover, Hannover, Germany
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Cannon GW, DuVall SL, Haroldsen CL, Caplan L, Curtis JR, Michaud K, Mikuls TR, Reimold A, Collier DH, Joseph GJ, Harrison DJ, Sauer BC. Clinical Outcomes and Biologic Costs of Switching Between Tumor Necrosis Factor Inhibitors in US Veterans with Rheumatoid Arthritis. Adv Ther 2016; 33:1347-59. [PMID: 27352377 PMCID: PMC4969320 DOI: 10.1007/s12325-016-0371-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2016] [Indexed: 11/26/2022]
Abstract
Introduction The purpose of this study was to evaluate clinical outcomes and drug/administration costs of treatment with tumor necrosis factor inhibitor (TNFi) agents in US veterans with rheumatoid arthritis (RA) initiating TNFi therapy. The analysis compared patients initiating and continuing a single TNFi with patients who subsequently switched to a different TNFi. Methods Data from patients enrolled in the Veterans Affairs Rheumatoid Arthritis (VARA) registry who initiated treatment with adalimumab, etanercept, or infliximab from 2003 to 2010 were analyzed. Outcomes included duration of therapy, Disease Activity Score based on 28 joints (DAS28), and direct drug and drug administration costs. Results Of 563 eligible patients, 262 initiated a single TNFi therapy, 142 restarted their initial TNFi after a ≥90-day gap in treatment (interrupted therapy), and 159 switched to a different TNFi. Patients who switched had higher mean DAS28 before starting TNFi therapy than patients with single or interrupted therapy: 5.3 vs 4.5 or 4.6, respectively. Mean duration of the first course was 34.3 months for single therapy, 18.3 months for interrupted therapy, and 17.7 months for switched therapy. Mean post-treatment DAS28 was highest for patients who switched TNFi. Mean annualized costs for first course were $13,800 for single therapy, $13,200 for interrupted therapy, and $14,200 for switched therapy; mean annualized costs for second course were $12,800 for interrupted therapy and $15,100 for switched therapy. Conclusion Patients who switched TNFi had higher pre-treatment DAS28 and higher overall costs than patients who received the same TNFi as either single or interrupted therapy. Funding This research was funded by Immunex Corp., a fully owned subsidiary of Amgen Inc., and by VA HSR&D Grant SHP 08-172.
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Affiliation(s)
- Grant W Cannon
- Veterans Affairs Salt Lake City Health Care System and University of Utah School of Medicine, Salt Lake City, UT, USA.
| | - Scott L DuVall
- Veterans Affairs Salt Lake City Health Care System and University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Candace L Haroldsen
- Veterans Affairs Salt Lake City Health Care System and University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Liron Caplan
- Denver VA and University of Colorado School of Medicine, Denver, CO, USA
| | | | - Kaleb Michaud
- University of Nebraska Medical Center, Omaha, NE, USA
- National Data Bank for Rheumatic Diseases, Wichita, KS, USA
| | - Ted R Mikuls
- VA Nebraska-Western Iowa Health Care System and University of Nebraska Medical Center, Omaha, NE, USA
| | - Andreas Reimold
- Dallas VA and University of Texas Southwestern, Dallas, TX, USA
| | | | | | | | - Brian C Sauer
- Veterans Affairs Salt Lake City Health Care System and University of Utah School of Medicine, Salt Lake City, UT, USA
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Bonafede M, Johnson BH, Princic N, Shah N, Harrison DJ. Cost per patient-year in response using a claims-based algorithm for the 2 years following biologic initiation in patients with rheumatoid arthritis. J Med Econ 2015; 18:376-89. [PMID: 25530318 DOI: 10.3111/13696998.2014.1001849] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
OBJECTIVE To estimate cost per patient-year in response during 2 years following biologic initiation among patients with rheumatoid arthritis (RA). METHODS Adults newly initiating biologics for RA (etanercept, abatacept, adalimumab, certolizumab, golimumab, or infliximab) between January 2009 and July 2011 were identified in the MarketScan Commercial Database. Eligible patients were continuously enrolled 6 months before (pre-index) and 24 months after (post-index) their first (index) biologic claim. Biologic effectiveness was assessed using six criteria during 2-year follow-up: treatment adherence ≥80%, no biologic dose escalation, no biologic switch, no new disease-modifying anti-rheumatic drug, no new/increased glucocorticoid dose, and limited intra-articular joint injections (≤2). After a 90-day period of non-response for a treatment failure, effectiveness or failure of subsequent treatment was assessed again for the index biologic or new biologic (after switching). Post-index RA-related medical, pharmacy, and drug administration costs were attributed to the index biologic. Cost per patient-year in response was calculated as RA-related costs divided by duration of response. RESULTS Overall, 15.0% of patients (1229/8193) did not fail any criterion for 2 years and were effectively treated. Mean duration of response was highest for etanercept (538.3 days), followed by golimumab (537.0 days; p = 0.864), adalimumab (534.7 days; p = 0.301), certolizumab (524.0 days; p = 0.165), infliximab (480.0 days; p < 0.001), and abatacept (482.3 days; p < 0.001). Total disease-related cost per patient-year in response was lower for patients initiated on etanercept ($25,086) than for patients initiated on adalimumab ($25,960), certolizumab ($26,339), golimumab ($26,332), abatacept ($35,581), or infliximab ($36,107). LIMITATIONS This study was limited to employer-paid commercial insurance. Database analyses cannot determine reasons for failing criteria. The algorithm was not designed and validated for 2 years of follow-up. CONCLUSIONS An effectiveness algorithm estimated that initiating etanercept was the most effective treatment during 2 years of follow-up, with the lowest cost per patient-year in response.
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Johnston SS, McMorrow D, Farr AM, Juneau P, Ogale S. Comparison of Healthcare Costs Between Rheumatoid Arthritis Patients Treated with Infused Biologics After Switching from Another Biologic. Drugs Real World Outcomes 2015; 2:99-109. [PMID: 27747619 PMCID: PMC4883205 DOI: 10.1007/s40801-015-0018-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Introduction While there is a substantial body of literature on the comparative healthcare costs of biologics used to treat rheumatoid arthritis (RA), nearly all of these investigations have been exclusively focused on anti-tumor necrosis factor-α (anti-TNF) agents in the setting of first-line biologic treatment. This study compared healthcare costs between RA patients treated with infused biologics after previously using at least one other biologic agent. Methods Using a large US administrative claims dataset, adult RA patients initiating an infused biologic (abatacept, infliximab, tocilizumab) between January 1, 2010 and January 1, 2012 (initiation = index) were identified. Rituximab was excluded because of unique dosing intervals, which make it difficult to determine treatment discontinuation using a claims database. Patients were required to have used one or more other biologic (infused or injected) at any time before index. Patients could contribute multiple observations to the dataset; one for each infused biologic they initiated between January 1, 2010 and January 1, 2012. A 6-month period before index was used to measure patient characteristics. A variable-length follow-up period after index was used to measure per-patient per-month (PPPM) healthcare costs, including biologic costs, RA-related healthcare costs, and all-cause healthcare costs. Generalized estimating equations models compared healthcare costs between the biologic agents, adjusting for patients’ demographics and clinical characteristics. Results The sample comprised 3,771 infused biologic initiations (abatacept = 1,759; infliximab = 922; tocilizumab = 1,090); the mean age of participants was 55 years, 82 % were female, and the median follow-up ranged from 251 to 280 days. Compared with other patients, patients treated with tocilizumab had significantly lower (all P < 0.05) PPPM biologic costs (abatacept = $2,597, infliximab = $3,141, tocilizumab = $1,894), RA-related healthcare costs (abatacept = $2,929, infliximab = $3,598, tocilizumab = $2,236), and all-cause healthcare costs (abatacept = $3,735, infliximab = $4,600, tocilizumab = $3,042). Conclusions Among RA patients treated with infused biologics after previously using at least one other biologic, patients treated with tocilizumab had the lowest real-world healthcare costs, largely driven by lower costs directly related to biologic treatment. Such biologic-related cost differences may be driven by variations in real-world treatment patterns (e.g., dose, escalation, treatment frequency).
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Affiliation(s)
- Stephen S Johnston
- Truven Health Analytics, 7700 Old Georgetown Rd, Ste 650, Bethesda, MD, 20814, USA.
| | - Donna McMorrow
- Truven Health Analytics, 7700 Old Georgetown Rd, Ste 650, Bethesda, MD, 20814, USA
| | - Amanda M Farr
- Truven Health Analytics, 7700 Old Georgetown Rd, Ste 650, Bethesda, MD, 20814, USA
| | - Paul Juneau
- Truven Health Analytics, 7700 Old Georgetown Rd, Ste 650, Bethesda, MD, 20814, USA
| | - Sarika Ogale
- Genentech, Inc, 1 DNA Way, South San Francisco, CA, 94080, USA
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Cannon GW, DuVall SL, Haroldsen CL, Caplan L, Curtis JR, Michaud K, Mikuls TR, Reimold A, Collier DH, Harrison DJ, Joseph GJ, Sauer BC. Persistence and dose escalation of tumor necrosis factor inhibitors in US veterans with rheumatoid arthritis. J Rheumatol 2014; 41:1935-43. [PMID: 25128516 DOI: 10.3899/jrheum.140164] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
OBJECTIVE Limited evidence exists comparing the persistence, effectiveness, and costs of biologic therapies for rheumatoid arthritis in clinical practice. Comparative effectiveness studies are needed to understand real-world experience with these agents. We evaluated treatment patterns, costs, and effectiveness of tumor necrosis factor inhibitor (TNFi) agents in patients enrolled in the Veterans Affairs Rheumatoid Arthritis (VARA) registry. METHODS Observational data from the VARA registry and linked administrative databases were analyzed. Longitudinal data from VARA patients initiating adalimumab (ADA), etanercept (ETN), or infliximab (IFX) from 2003 (the date all agents were available within the Veteran Affairs) to 2010 were analyzed. Outcomes included Disease Activity Score using 28 joints (DAS28), treatment persistence, dose escalation, and direct costs of drugs and drug administration. RESULTS For 563 eligible patients, baseline DAS28, DAS28 improvements, and persistence on initial treatment were similar across agents. Fewer patients receiving ETN (n = 5/290; 2%) underwent dose escalation than did patients taking ADA (n = 32/204; 16%) or IFX (n = 44/69; 64%). Annual costs for first course of TNFi therapy were lower for injectable ADA ($13,100 US) and ETN ($13,500 US) than for intravenously administered IFX ($16,900 US). CONCLUSION Despite similar persistence and clinical disease activity for these TNFi agents, rates of dose escalation were highest with ADA and IFX. Higher overall costs were noted for IFX without increases in effectiveness.
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Affiliation(s)
- Grant W Cannon
- From the Veterans Affairs Salt Lake City Health Care System; University of Utah School of Medicine, Salt Lake City, Utah; Denver Veterans Affairs (VA); University of Colorado, Denver, Colorado; University of Alabama at Birmingham, Birmingham, Alabama; the University of Nebraska Medical Center; Omaha VA, Omaha, Nebraska; the National Data Bank for Rheumatic Diseases, Wichita, Kansas; Dallas VA; University of Texas Southwestern, Dallas, Texas; Amgen Inc., Thousand Oaks, California, USA.G.W. Cannon, MD, Associate Chief of Staff of Academic Affiliations; S.L. DuVall, PhD, Associate Director, VA Informatics and Computing Infrastructure and Research Assistant Professor; C.L. Haroldsen, MSPH, Senior Programmer/Analyst; B.C. Sauer, PhD, MS, Associate Professor, Veterans Affairs Salt Lake City Health Care System, University of Utah School of Medicine; L. Caplan, MD, PhD, Associate Professor of Medicine/Rheumatology, Denver VA, University of Colorado; J.R. Curtis, MD, MS, MPH, William J. Koopman Endowed Professor in Rheumatology and Immunology, Director, University of Alabama Birmingham (UAB) Arthritis Clinical Intervention Program, Co-director, UAB Center for Education and Research on Therapeutics, Co-director, UAB PharmacoEpidemiology and Economic Research Group, University of Alabama at Birmingham; K. Michaud, PhD, Assistant Professor of Medicine, Co-director, University of Nebraska Medical Center, National Data Bank for Rheumatic Diseases; T.R. Mikuls, MD, Staff Physician and Researcher, Professor of Internal Medicine and Rheumatology, Omaha VA, University of Nebraska Medical Center; A. Reimold, MD, Chief, Rheumatology Section, Associate Professor of Medicine, Dallas VA, University of Texas Southwestern; D.H. Collier, MD, Clinical Research Medical Director; D.J. Harrison, PhD, Health Economics Director, Amgen Inc.; G.J. Joseph, PhD, Health Economics Senior Manager, former employee of Amgen Inc.
| | - Scott L DuVall
- From the Veterans Affairs Salt Lake City Health Care System; University of Utah School of Medicine, Salt Lake City, Utah; Denver Veterans Affairs (VA); University of Colorado, Denver, Colorado; University of Alabama at Birmingham, Birmingham, Alabama; the University of Nebraska Medical Center; Omaha VA, Omaha, Nebraska; the National Data Bank for Rheumatic Diseases, Wichita, Kansas; Dallas VA; University of Texas Southwestern, Dallas, Texas; Amgen Inc., Thousand Oaks, California, USA.G.W. Cannon, MD, Associate Chief of Staff of Academic Affiliations; S.L. DuVall, PhD, Associate Director, VA Informatics and Computing Infrastructure and Research Assistant Professor; C.L. Haroldsen, MSPH, Senior Programmer/Analyst; B.C. Sauer, PhD, MS, Associate Professor, Veterans Affairs Salt Lake City Health Care System, University of Utah School of Medicine; L. Caplan, MD, PhD, Associate Professor of Medicine/Rheumatology, Denver VA, University of Colorado; J.R. Curtis, MD, MS, MPH, William J. Koopman Endowed Professor in Rheumatology and Immunology, Director, University of Alabama Birmingham (UAB) Arthritis Clinical Intervention Program, Co-director, UAB Center for Education and Research on Therapeutics, Co-director, UAB PharmacoEpidemiology and Economic Research Group, University of Alabama at Birmingham; K. Michaud, PhD, Assistant Professor of Medicine, Co-director, University of Nebraska Medical Center, National Data Bank for Rheumatic Diseases; T.R. Mikuls, MD, Staff Physician and Researcher, Professor of Internal Medicine and Rheumatology, Omaha VA, University of Nebraska Medical Center; A. Reimold, MD, Chief, Rheumatology Section, Associate Professor of Medicine, Dallas VA, University of Texas Southwestern; D.H. Collier, MD, Clinical Research Medical Director; D.J. Harrison, PhD, Health Economics Director, Amgen Inc.; G.J. Joseph, PhD, Health Economics Senior Manager, former employee of Amgen Inc
| | - Candace L Haroldsen
- From the Veterans Affairs Salt Lake City Health Care System; University of Utah School of Medicine, Salt Lake City, Utah; Denver Veterans Affairs (VA); University of Colorado, Denver, Colorado; University of Alabama at Birmingham, Birmingham, Alabama; the University of Nebraska Medical Center; Omaha VA, Omaha, Nebraska; the National Data Bank for Rheumatic Diseases, Wichita, Kansas; Dallas VA; University of Texas Southwestern, Dallas, Texas; Amgen Inc., Thousand Oaks, California, USA.G.W. Cannon, MD, Associate Chief of Staff of Academic Affiliations; S.L. DuVall, PhD, Associate Director, VA Informatics and Computing Infrastructure and Research Assistant Professor; C.L. Haroldsen, MSPH, Senior Programmer/Analyst; B.C. Sauer, PhD, MS, Associate Professor, Veterans Affairs Salt Lake City Health Care System, University of Utah School of Medicine; L. Caplan, MD, PhD, Associate Professor of Medicine/Rheumatology, Denver VA, University of Colorado; J.R. Curtis, MD, MS, MPH, William J. Koopman Endowed Professor in Rheumatology and Immunology, Director, University of Alabama Birmingham (UAB) Arthritis Clinical Intervention Program, Co-director, UAB Center for Education and Research on Therapeutics, Co-director, UAB PharmacoEpidemiology and Economic Research Group, University of Alabama at Birmingham; K. Michaud, PhD, Assistant Professor of Medicine, Co-director, University of Nebraska Medical Center, National Data Bank for Rheumatic Diseases; T.R. Mikuls, MD, Staff Physician and Researcher, Professor of Internal Medicine and Rheumatology, Omaha VA, University of Nebraska Medical Center; A. Reimold, MD, Chief, Rheumatology Section, Associate Professor of Medicine, Dallas VA, University of Texas Southwestern; D.H. Collier, MD, Clinical Research Medical Director; D.J. Harrison, PhD, Health Economics Director, Amgen Inc.; G.J. Joseph, PhD, Health Economics Senior Manager, former employee of Amgen Inc
| | - Liron Caplan
- From the Veterans Affairs Salt Lake City Health Care System; University of Utah School of Medicine, Salt Lake City, Utah; Denver Veterans Affairs (VA); University of Colorado, Denver, Colorado; University of Alabama at Birmingham, Birmingham, Alabama; the University of Nebraska Medical Center; Omaha VA, Omaha, Nebraska; the National Data Bank for Rheumatic Diseases, Wichita, Kansas; Dallas VA; University of Texas Southwestern, Dallas, Texas; Amgen Inc., Thousand Oaks, California, USA.G.W. Cannon, MD, Associate Chief of Staff of Academic Affiliations; S.L. DuVall, PhD, Associate Director, VA Informatics and Computing Infrastructure and Research Assistant Professor; C.L. Haroldsen, MSPH, Senior Programmer/Analyst; B.C. Sauer, PhD, MS, Associate Professor, Veterans Affairs Salt Lake City Health Care System, University of Utah School of Medicine; L. Caplan, MD, PhD, Associate Professor of Medicine/Rheumatology, Denver VA, University of Colorado; J.R. Curtis, MD, MS, MPH, William J. Koopman Endowed Professor in Rheumatology and Immunology, Director, University of Alabama Birmingham (UAB) Arthritis Clinical Intervention Program, Co-director, UAB Center for Education and Research on Therapeutics, Co-director, UAB PharmacoEpidemiology and Economic Research Group, University of Alabama at Birmingham; K. Michaud, PhD, Assistant Professor of Medicine, Co-director, University of Nebraska Medical Center, National Data Bank for Rheumatic Diseases; T.R. Mikuls, MD, Staff Physician and Researcher, Professor of Internal Medicine and Rheumatology, Omaha VA, University of Nebraska Medical Center; A. Reimold, MD, Chief, Rheumatology Section, Associate Professor of Medicine, Dallas VA, University of Texas Southwestern; D.H. Collier, MD, Clinical Research Medical Director; D.J. Harrison, PhD, Health Economics Director, Amgen Inc.; G.J. Joseph, PhD, Health Economics Senior Manager, former employee of Amgen Inc
| | - Jeffrey R Curtis
- From the Veterans Affairs Salt Lake City Health Care System; University of Utah School of Medicine, Salt Lake City, Utah; Denver Veterans Affairs (VA); University of Colorado, Denver, Colorado; University of Alabama at Birmingham, Birmingham, Alabama; the University of Nebraska Medical Center; Omaha VA, Omaha, Nebraska; the National Data Bank for Rheumatic Diseases, Wichita, Kansas; Dallas VA; University of Texas Southwestern, Dallas, Texas; Amgen Inc., Thousand Oaks, California, USA.G.W. Cannon, MD, Associate Chief of Staff of Academic Affiliations; S.L. DuVall, PhD, Associate Director, VA Informatics and Computing Infrastructure and Research Assistant Professor; C.L. Haroldsen, MSPH, Senior Programmer/Analyst; B.C. Sauer, PhD, MS, Associate Professor, Veterans Affairs Salt Lake City Health Care System, University of Utah School of Medicine; L. Caplan, MD, PhD, Associate Professor of Medicine/Rheumatology, Denver VA, University of Colorado; J.R. Curtis, MD, MS, MPH, William J. Koopman Endowed Professor in Rheumatology and Immunology, Director, University of Alabama Birmingham (UAB) Arthritis Clinical Intervention Program, Co-director, UAB Center for Education and Research on Therapeutics, Co-director, UAB PharmacoEpidemiology and Economic Research Group, University of Alabama at Birmingham; K. Michaud, PhD, Assistant Professor of Medicine, Co-director, University of Nebraska Medical Center, National Data Bank for Rheumatic Diseases; T.R. Mikuls, MD, Staff Physician and Researcher, Professor of Internal Medicine and Rheumatology, Omaha VA, University of Nebraska Medical Center; A. Reimold, MD, Chief, Rheumatology Section, Associate Professor of Medicine, Dallas VA, University of Texas Southwestern; D.H. Collier, MD, Clinical Research Medical Director; D.J. Harrison, PhD, Health Economics Director, Amgen Inc.; G.J. Joseph, PhD, Health Economics Senior Manager, former employee of Amgen Inc
| | - Kaleb Michaud
- From the Veterans Affairs Salt Lake City Health Care System; University of Utah School of Medicine, Salt Lake City, Utah; Denver Veterans Affairs (VA); University of Colorado, Denver, Colorado; University of Alabama at Birmingham, Birmingham, Alabama; the University of Nebraska Medical Center; Omaha VA, Omaha, Nebraska; the National Data Bank for Rheumatic Diseases, Wichita, Kansas; Dallas VA; University of Texas Southwestern, Dallas, Texas; Amgen Inc., Thousand Oaks, California, USA.G.W. Cannon, MD, Associate Chief of Staff of Academic Affiliations; S.L. DuVall, PhD, Associate Director, VA Informatics and Computing Infrastructure and Research Assistant Professor; C.L. Haroldsen, MSPH, Senior Programmer/Analyst; B.C. Sauer, PhD, MS, Associate Professor, Veterans Affairs Salt Lake City Health Care System, University of Utah School of Medicine; L. Caplan, MD, PhD, Associate Professor of Medicine/Rheumatology, Denver VA, University of Colorado; J.R. Curtis, MD, MS, MPH, William J. Koopman Endowed Professor in Rheumatology and Immunology, Director, University of Alabama Birmingham (UAB) Arthritis Clinical Intervention Program, Co-director, UAB Center for Education and Research on Therapeutics, Co-director, UAB PharmacoEpidemiology and Economic Research Group, University of Alabama at Birmingham; K. Michaud, PhD, Assistant Professor of Medicine, Co-director, University of Nebraska Medical Center, National Data Bank for Rheumatic Diseases; T.R. Mikuls, MD, Staff Physician and Researcher, Professor of Internal Medicine and Rheumatology, Omaha VA, University of Nebraska Medical Center; A. Reimold, MD, Chief, Rheumatology Section, Associate Professor of Medicine, Dallas VA, University of Texas Southwestern; D.H. Collier, MD, Clinical Research Medical Director; D.J. Harrison, PhD, Health Economics Director, Amgen Inc.; G.J. Joseph, PhD, Health Economics Senior Manager, former employee of Amgen Inc
| | - Ted R Mikuls
- From the Veterans Affairs Salt Lake City Health Care System; University of Utah School of Medicine, Salt Lake City, Utah; Denver Veterans Affairs (VA); University of Colorado, Denver, Colorado; University of Alabama at Birmingham, Birmingham, Alabama; the University of Nebraska Medical Center; Omaha VA, Omaha, Nebraska; the National Data Bank for Rheumatic Diseases, Wichita, Kansas; Dallas VA; University of Texas Southwestern, Dallas, Texas; Amgen Inc., Thousand Oaks, California, USA.G.W. Cannon, MD, Associate Chief of Staff of Academic Affiliations; S.L. DuVall, PhD, Associate Director, VA Informatics and Computing Infrastructure and Research Assistant Professor; C.L. Haroldsen, MSPH, Senior Programmer/Analyst; B.C. Sauer, PhD, MS, Associate Professor, Veterans Affairs Salt Lake City Health Care System, University of Utah School of Medicine; L. Caplan, MD, PhD, Associate Professor of Medicine/Rheumatology, Denver VA, University of Colorado; J.R. Curtis, MD, MS, MPH, William J. Koopman Endowed Professor in Rheumatology and Immunology, Director, University of Alabama Birmingham (UAB) Arthritis Clinical Intervention Program, Co-director, UAB Center for Education and Research on Therapeutics, Co-director, UAB PharmacoEpidemiology and Economic Research Group, University of Alabama at Birmingham; K. Michaud, PhD, Assistant Professor of Medicine, Co-director, University of Nebraska Medical Center, National Data Bank for Rheumatic Diseases; T.R. Mikuls, MD, Staff Physician and Researcher, Professor of Internal Medicine and Rheumatology, Omaha VA, University of Nebraska Medical Center; A. Reimold, MD, Chief, Rheumatology Section, Associate Professor of Medicine, Dallas VA, University of Texas Southwestern; D.H. Collier, MD, Clinical Research Medical Director; D.J. Harrison, PhD, Health Economics Director, Amgen Inc.; G.J. Joseph, PhD, Health Economics Senior Manager, former employee of Amgen Inc
| | - Andreas Reimold
- From the Veterans Affairs Salt Lake City Health Care System; University of Utah School of Medicine, Salt Lake City, Utah; Denver Veterans Affairs (VA); University of Colorado, Denver, Colorado; University of Alabama at Birmingham, Birmingham, Alabama; the University of Nebraska Medical Center; Omaha VA, Omaha, Nebraska; the National Data Bank for Rheumatic Diseases, Wichita, Kansas; Dallas VA; University of Texas Southwestern, Dallas, Texas; Amgen Inc., Thousand Oaks, California, USA.G.W. Cannon, MD, Associate Chief of Staff of Academic Affiliations; S.L. DuVall, PhD, Associate Director, VA Informatics and Computing Infrastructure and Research Assistant Professor; C.L. Haroldsen, MSPH, Senior Programmer/Analyst; B.C. Sauer, PhD, MS, Associate Professor, Veterans Affairs Salt Lake City Health Care System, University of Utah School of Medicine; L. Caplan, MD, PhD, Associate Professor of Medicine/Rheumatology, Denver VA, University of Colorado; J.R. Curtis, MD, MS, MPH, William J. Koopman Endowed Professor in Rheumatology and Immunology, Director, University of Alabama Birmingham (UAB) Arthritis Clinical Intervention Program, Co-director, UAB Center for Education and Research on Therapeutics, Co-director, UAB PharmacoEpidemiology and Economic Research Group, University of Alabama at Birmingham; K. Michaud, PhD, Assistant Professor of Medicine, Co-director, University of Nebraska Medical Center, National Data Bank for Rheumatic Diseases; T.R. Mikuls, MD, Staff Physician and Researcher, Professor of Internal Medicine and Rheumatology, Omaha VA, University of Nebraska Medical Center; A. Reimold, MD, Chief, Rheumatology Section, Associate Professor of Medicine, Dallas VA, University of Texas Southwestern; D.H. Collier, MD, Clinical Research Medical Director; D.J. Harrison, PhD, Health Economics Director, Amgen Inc.; G.J. Joseph, PhD, Health Economics Senior Manager, former employee of Amgen Inc
| | - David H Collier
- From the Veterans Affairs Salt Lake City Health Care System; University of Utah School of Medicine, Salt Lake City, Utah; Denver Veterans Affairs (VA); University of Colorado, Denver, Colorado; University of Alabama at Birmingham, Birmingham, Alabama; the University of Nebraska Medical Center; Omaha VA, Omaha, Nebraska; the National Data Bank for Rheumatic Diseases, Wichita, Kansas; Dallas VA; University of Texas Southwestern, Dallas, Texas; Amgen Inc., Thousand Oaks, California, USA.G.W. Cannon, MD, Associate Chief of Staff of Academic Affiliations; S.L. DuVall, PhD, Associate Director, VA Informatics and Computing Infrastructure and Research Assistant Professor; C.L. Haroldsen, MSPH, Senior Programmer/Analyst; B.C. Sauer, PhD, MS, Associate Professor, Veterans Affairs Salt Lake City Health Care System, University of Utah School of Medicine; L. Caplan, MD, PhD, Associate Professor of Medicine/Rheumatology, Denver VA, University of Colorado; J.R. Curtis, MD, MS, MPH, William J. Koopman Endowed Professor in Rheumatology and Immunology, Director, University of Alabama Birmingham (UAB) Arthritis Clinical Intervention Program, Co-director, UAB Center for Education and Research on Therapeutics, Co-director, UAB PharmacoEpidemiology and Economic Research Group, University of Alabama at Birmingham; K. Michaud, PhD, Assistant Professor of Medicine, Co-director, University of Nebraska Medical Center, National Data Bank for Rheumatic Diseases; T.R. Mikuls, MD, Staff Physician and Researcher, Professor of Internal Medicine and Rheumatology, Omaha VA, University of Nebraska Medical Center; A. Reimold, MD, Chief, Rheumatology Section, Associate Professor of Medicine, Dallas VA, University of Texas Southwestern; D.H. Collier, MD, Clinical Research Medical Director; D.J. Harrison, PhD, Health Economics Director, Amgen Inc.; G.J. Joseph, PhD, Health Economics Senior Manager, former employee of Amgen Inc
| | - David J Harrison
- From the Veterans Affairs Salt Lake City Health Care System; University of Utah School of Medicine, Salt Lake City, Utah; Denver Veterans Affairs (VA); University of Colorado, Denver, Colorado; University of Alabama at Birmingham, Birmingham, Alabama; the University of Nebraska Medical Center; Omaha VA, Omaha, Nebraska; the National Data Bank for Rheumatic Diseases, Wichita, Kansas; Dallas VA; University of Texas Southwestern, Dallas, Texas; Amgen Inc., Thousand Oaks, California, USA.G.W. Cannon, MD, Associate Chief of Staff of Academic Affiliations; S.L. DuVall, PhD, Associate Director, VA Informatics and Computing Infrastructure and Research Assistant Professor; C.L. Haroldsen, MSPH, Senior Programmer/Analyst; B.C. Sauer, PhD, MS, Associate Professor, Veterans Affairs Salt Lake City Health Care System, University of Utah School of Medicine; L. Caplan, MD, PhD, Associate Professor of Medicine/Rheumatology, Denver VA, University of Colorado; J.R. Curtis, MD, MS, MPH, William J. Koopman Endowed Professor in Rheumatology and Immunology, Director, University of Alabama Birmingham (UAB) Arthritis Clinical Intervention Program, Co-director, UAB Center for Education and Research on Therapeutics, Co-director, UAB PharmacoEpidemiology and Economic Research Group, University of Alabama at Birmingham; K. Michaud, PhD, Assistant Professor of Medicine, Co-director, University of Nebraska Medical Center, National Data Bank for Rheumatic Diseases; T.R. Mikuls, MD, Staff Physician and Researcher, Professor of Internal Medicine and Rheumatology, Omaha VA, University of Nebraska Medical Center; A. Reimold, MD, Chief, Rheumatology Section, Associate Professor of Medicine, Dallas VA, University of Texas Southwestern; D.H. Collier, MD, Clinical Research Medical Director; D.J. Harrison, PhD, Health Economics Director, Amgen Inc.; G.J. Joseph, PhD, Health Economics Senior Manager, former employee of Amgen Inc
| | - George J Joseph
- From the Veterans Affairs Salt Lake City Health Care System; University of Utah School of Medicine, Salt Lake City, Utah; Denver Veterans Affairs (VA); University of Colorado, Denver, Colorado; University of Alabama at Birmingham, Birmingham, Alabama; the University of Nebraska Medical Center; Omaha VA, Omaha, Nebraska; the National Data Bank for Rheumatic Diseases, Wichita, Kansas; Dallas VA; University of Texas Southwestern, Dallas, Texas; Amgen Inc., Thousand Oaks, California, USA.G.W. Cannon, MD, Associate Chief of Staff of Academic Affiliations; S.L. DuVall, PhD, Associate Director, VA Informatics and Computing Infrastructure and Research Assistant Professor; C.L. Haroldsen, MSPH, Senior Programmer/Analyst; B.C. Sauer, PhD, MS, Associate Professor, Veterans Affairs Salt Lake City Health Care System, University of Utah School of Medicine; L. Caplan, MD, PhD, Associate Professor of Medicine/Rheumatology, Denver VA, University of Colorado; J.R. Curtis, MD, MS, MPH, William J. Koopman Endowed Professor in Rheumatology and Immunology, Director, University of Alabama Birmingham (UAB) Arthritis Clinical Intervention Program, Co-director, UAB Center for Education and Research on Therapeutics, Co-director, UAB PharmacoEpidemiology and Economic Research Group, University of Alabama at Birmingham; K. Michaud, PhD, Assistant Professor of Medicine, Co-director, University of Nebraska Medical Center, National Data Bank for Rheumatic Diseases; T.R. Mikuls, MD, Staff Physician and Researcher, Professor of Internal Medicine and Rheumatology, Omaha VA, University of Nebraska Medical Center; A. Reimold, MD, Chief, Rheumatology Section, Associate Professor of Medicine, Dallas VA, University of Texas Southwestern; D.H. Collier, MD, Clinical Research Medical Director; D.J. Harrison, PhD, Health Economics Director, Amgen Inc.; G.J. Joseph, PhD, Health Economics Senior Manager, former employee of Amgen Inc
| | - Brian C Sauer
- From the Veterans Affairs Salt Lake City Health Care System; University of Utah School of Medicine, Salt Lake City, Utah; Denver Veterans Affairs (VA); University of Colorado, Denver, Colorado; University of Alabama at Birmingham, Birmingham, Alabama; the University of Nebraska Medical Center; Omaha VA, Omaha, Nebraska; the National Data Bank for Rheumatic Diseases, Wichita, Kansas; Dallas VA; University of Texas Southwestern, Dallas, Texas; Amgen Inc., Thousand Oaks, California, USA.G.W. Cannon, MD, Associate Chief of Staff of Academic Affiliations; S.L. DuVall, PhD, Associate Director, VA Informatics and Computing Infrastructure and Research Assistant Professor; C.L. Haroldsen, MSPH, Senior Programmer/Analyst; B.C. Sauer, PhD, MS, Associate Professor, Veterans Affairs Salt Lake City Health Care System, University of Utah School of Medicine; L. Caplan, MD, PhD, Associate Professor of Medicine/Rheumatology, Denver VA, University of Colorado; J.R. Curtis, MD, MS, MPH, William J. Koopman Endowed Professor in Rheumatology and Immunology, Director, University of Alabama Birmingham (UAB) Arthritis Clinical Intervention Program, Co-director, UAB Center for Education and Research on Therapeutics, Co-director, UAB PharmacoEpidemiology and Economic Research Group, University of Alabama at Birmingham; K. Michaud, PhD, Assistant Professor of Medicine, Co-director, University of Nebraska Medical Center, National Data Bank for Rheumatic Diseases; T.R. Mikuls, MD, Staff Physician and Researcher, Professor of Internal Medicine and Rheumatology, Omaha VA, University of Nebraska Medical Center; A. Reimold, MD, Chief, Rheumatology Section, Associate Professor of Medicine, Dallas VA, University of Texas Southwestern; D.H. Collier, MD, Clinical Research Medical Director; D.J. Harrison, PhD, Health Economics Director, Amgen Inc.; G.J. Joseph, PhD, Health Economics Senior Manager, former employee of Amgen Inc
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Curtis JR, Schabert VF, Yeaw J, Korn JR, Quach C, Harrison DJ, Yun H, Joseph GJ, Collier D. Use of a validated algorithm to estimate the annual cost of effective biologic treatment for rheumatoid arthritis. J Med Econ 2014; 17:555-66. [PMID: 24754646 DOI: 10.3111/13696998.2014.914031] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
OBJECTIVES To estimate biologic cost per effectively treated patient with rheumatoid arthritis (RA) using a claims-based algorithm for effectiveness. METHODS Patients with RA aged 18-63 years in the IMS PharMetrics Plus database were categorized as effectively treated if they met all six criteria: (1) a medication possession ratio ≥80% (subcutaneous) or at least as many infusions as specified in US labeling (intravenous); (2) no biologic dose increase; (3) no biologic switch; (4) no new non-biologic disease-modifying anti-rheumatic drug; (5) no new or increased oral glucocorticoid; and (6) ≤1 glucocorticoid injection. Biologic cost per effectively treated patient was defined as total cost of the index biologic (drug plus intravenous administration) divided by the number of patients categorized by the algorithm as effectively treated. Similar methods were used for the index biologic in the second year and for a second biologic after a switch. RESULTS Rates that the index biologic was categorized as effective in the first year were 31.0% etanercept (2243/7247), 28.6% adalimumab (1426/4991), 28.6% abatacept (332/1160), 27.2% golimumab (71/261), and 20.2% infliximab (474/2352). Mean biologic cost per effectively treated patient, per the algorithm, was $50,141 etanercept, $53,386 golimumab, $56,942 adalimumab, $73,516 abatacept, and $114,089 infliximab. Biologic cost per effectively treated patient, using this algorithm, was lower for patients who continued the index biologic in the second year and higher after switching. CONCLUSIONS When a claims-based algorithm was applied to a large commercial claims database, etanercept was categorized as the most effective and had the lowest estimated 1-year biologic cost per effectively treated patient. This proxy for effectiveness from claims databases was validated against a clinical effectiveness scale, but analyses of the second year or the year after a biologic switch were not included in the validation. Costs of other medications were not included in cost calculations.
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Wu N, Lee YCD, Shah N, Harrison DJ. Cost of biologics per treated patient across immune-mediated inflammatory disease indications in a pharmacy benefit management setting: a retrospective cohort study. Clin Ther 2014; 36:1231-41, 1241.e1-3. [PMID: 25062652 DOI: 10.1016/j.clinthera.2014.06.014] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2013] [Revised: 05/13/2014] [Accepted: 06/09/2014] [Indexed: 12/30/2022]
Abstract
PURPOSE Pharmacy benefits management companies have emerged as the national standard for the management of prescription drugs in the United States. The objective of this study was to estimate the annual costs per treated patient of 8 biologics indicated for select immune-mediated inflammatory diseases: moderate to severe rheumatoid arthritis, moderate to severe plaque psoriasis, active psoriatic arthritis, and/or active ankylosing spondylitis. METHODS Using the Medco pharmacy benefits-management database, data from patients aged 18 to 63 years with ≥1 claim for abatacept, adalimumab, certolizumab, etanercept, golimumab, infliximab, rituximab, or ustekinumab, dated between January 1, 2008 and August 31, 2011, were collected. Eligible patients were continuously enrolled for ≥180 days before and 360 days after the date of the first biologic claim (index date), and had ≥1 claim associated with a diagnosis of rheumatoid arthritis, moderate to severe plaque psoriasis, active psoriatic arthritis, and/or active ankylosing spondylitis in the 180 days before or 30 days after the index date. The annual total costs per treated patient were calculated as the total dose of the index biologic and all other biologics for which there was a claim in the postindex period, multiplied by the wholesale acquisition cost as of October 1, 2013, plus the costs associated with administrations (calculated as number of infusions multiplied by the 2013 Medicare Physician Fee Schedule costs). FINDINGS Within the study population (N = 8306; 5356 (64.5%) women, 2950 men (35.5%), average age: 42.3 years (SD: 10.0)), the most commonly used biologics were etanercept (43.1%), adalimumab (31.0%), and infliximab (17.0%), which accounted for 91.1% of all biologic prescriptions. Total costs per treated patient across indications were as follows: adalimumab, $23,427 to $26,304; infliximab, $22,824 to $28,907; and etanercept, $21,468 to $27,748, whereas abatacept, certolizumab, golimumab, rituximab, and ustekinumab were associated with a larger range: $17,017 to $41,888. IMPLICATIONS The present study provides insight into the prescribing patterns and cost differences among 8 biologic agents used for the treatment of immune-mediated inflammatory diseases. This information may prove useful when designing a pharmacy benefits-management formulary.
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Affiliation(s)
- Ning Wu
- Evidera, Lexington, Massachusetts.
| | | | - Neel Shah
- Amgen Inc, Thousand Oaks, California
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Barnabe C, Thanh NX, Ohinmaa A, Homik J, Barr SG, Martin L, Maksymowych WP. Effect of remission definition on healthcare cost savings estimates for patients with rheumatoid arthritis treated with biologic therapies. J Rheumatol 2014; 41:1600-6. [PMID: 25028381 DOI: 10.3899/jrheum.131449] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
OBJECTIVE Sustained remission in rheumatoid arthritis (RA) results in healthcare utilization cost savings. We evaluated the variation in estimates of savings when different definitions of remission [2011 American College of Rheumatology/European League Against Rheumatism Boolean Definition, Simplified Disease Activity Index (SDAI) ≤ 3.3, Clinical Disease Activity Index (CDAI) ≤ 2.8, and Disease Activity Score-28 (DAS28) ≤ 2.6] are applied. METHODS The annual mean healthcare service utilization costs were estimated from provincial physician billing claims, outpatient visits, and hospitalizations, with linkage to clinical data from the Alberta Biologics Pharmacosurveillance Program (ABioPharm). Cost savings in patients who had a 1-year continuous period of remission were compared to those who did not, using 4 definitions of remission. RESULTS In 1086 patients, sustained remission rates were 16.1% for DAS28, 8.8% for Boolean, 5.5% for CDAI, and 4.2% for SDAI. The estimated mean annual healthcare cost savings per patient achieving remission (relative to not) were SDAI $1928 (95% CI 592, 3264), DAS28 $1676 (95% CI 987, 2365), and Boolean $1259 (95% CI 417, 2100). The annual savings by CDAI remission per patient were not significant at $423 (95% CI -1757, 2602). For patients in DAS28, Boolean, and SDAI remission, savings were seen both in costs directly related to RA and its comorbidities, and in costs for non-RA-related conditions. CONCLUSION The magnitude of the healthcare cost savings varies according to the remission definition used in classifying patient disease status. The highest point estimate for cost savings was observed in patients attaining SDAI remission and the least with the CDAI; confidence intervals for these estimates do overlap. Future pharmacoeconomic analyses should employ all response definitions in assessing the influence of treatment.
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Affiliation(s)
- Cheryl Barnabe
- From the Department of Medicine, University of Calgary, Calgary; Department of Community Health Sciences, University of Calgary, Calgary; Institute of Health Economics, Edmonton; School of Public Health, University of Alberta, Edmonton; and Department of Medicine, University of Alberta, Edmonton, Alberta, Canada.C. Barnabe, MD, MSc, FRCPC, Department of Medicine and Department of Community Health Sciences, University of Calgary; N.X. Thanh, MD, PhD, MPH, Institute of Health Economics and School of Public Health, University of Alberta; A. Ohinmaa, PhD, Institute of Health Economics and School of Public Health, University of Alberta; J. Homik, MD, MSc, FRCPC, Department of Medicine, University of Alberta; S.G. Barr, MD, MSc, FRCPC, Department of Medicine, and Department of Community Health Sciences, University of Calgary; L. Martin, MB, ChB, FRCPC, Department of Medicine, University of Calgary; W.P. Maksymowych, MB, ChB, FRCPC, Department of Medicine, University of Alberta.
| | - Nguyen Xuan Thanh
- From the Department of Medicine, University of Calgary, Calgary; Department of Community Health Sciences, University of Calgary, Calgary; Institute of Health Economics, Edmonton; School of Public Health, University of Alberta, Edmonton; and Department of Medicine, University of Alberta, Edmonton, Alberta, Canada.C. Barnabe, MD, MSc, FRCPC, Department of Medicine and Department of Community Health Sciences, University of Calgary; N.X. Thanh, MD, PhD, MPH, Institute of Health Economics and School of Public Health, University of Alberta; A. Ohinmaa, PhD, Institute of Health Economics and School of Public Health, University of Alberta; J. Homik, MD, MSc, FRCPC, Department of Medicine, University of Alberta; S.G. Barr, MD, MSc, FRCPC, Department of Medicine, and Department of Community Health Sciences, University of Calgary; L. Martin, MB, ChB, FRCPC, Department of Medicine, University of Calgary; W.P. Maksymowych, MB, ChB, FRCPC, Department of Medicine, University of Alberta
| | - Arto Ohinmaa
- From the Department of Medicine, University of Calgary, Calgary; Department of Community Health Sciences, University of Calgary, Calgary; Institute of Health Economics, Edmonton; School of Public Health, University of Alberta, Edmonton; and Department of Medicine, University of Alberta, Edmonton, Alberta, Canada.C. Barnabe, MD, MSc, FRCPC, Department of Medicine and Department of Community Health Sciences, University of Calgary; N.X. Thanh, MD, PhD, MPH, Institute of Health Economics and School of Public Health, University of Alberta; A. Ohinmaa, PhD, Institute of Health Economics and School of Public Health, University of Alberta; J. Homik, MD, MSc, FRCPC, Department of Medicine, University of Alberta; S.G. Barr, MD, MSc, FRCPC, Department of Medicine, and Department of Community Health Sciences, University of Calgary; L. Martin, MB, ChB, FRCPC, Department of Medicine, University of Calgary; W.P. Maksymowych, MB, ChB, FRCPC, Department of Medicine, University of Alberta
| | - Joanne Homik
- From the Department of Medicine, University of Calgary, Calgary; Department of Community Health Sciences, University of Calgary, Calgary; Institute of Health Economics, Edmonton; School of Public Health, University of Alberta, Edmonton; and Department of Medicine, University of Alberta, Edmonton, Alberta, Canada.C. Barnabe, MD, MSc, FRCPC, Department of Medicine and Department of Community Health Sciences, University of Calgary; N.X. Thanh, MD, PhD, MPH, Institute of Health Economics and School of Public Health, University of Alberta; A. Ohinmaa, PhD, Institute of Health Economics and School of Public Health, University of Alberta; J. Homik, MD, MSc, FRCPC, Department of Medicine, University of Alberta; S.G. Barr, MD, MSc, FRCPC, Department of Medicine, and Department of Community Health Sciences, University of Calgary; L. Martin, MB, ChB, FRCPC, Department of Medicine, University of Calgary; W.P. Maksymowych, MB, ChB, FRCPC, Department of Medicine, University of Alberta
| | - Susan G Barr
- From the Department of Medicine, University of Calgary, Calgary; Department of Community Health Sciences, University of Calgary, Calgary; Institute of Health Economics, Edmonton; School of Public Health, University of Alberta, Edmonton; and Department of Medicine, University of Alberta, Edmonton, Alberta, Canada.C. Barnabe, MD, MSc, FRCPC, Department of Medicine and Department of Community Health Sciences, University of Calgary; N.X. Thanh, MD, PhD, MPH, Institute of Health Economics and School of Public Health, University of Alberta; A. Ohinmaa, PhD, Institute of Health Economics and School of Public Health, University of Alberta; J. Homik, MD, MSc, FRCPC, Department of Medicine, University of Alberta; S.G. Barr, MD, MSc, FRCPC, Department of Medicine, and Department of Community Health Sciences, University of Calgary; L. Martin, MB, ChB, FRCPC, Department of Medicine, University of Calgary; W.P. Maksymowych, MB, ChB, FRCPC, Department of Medicine, University of Alberta
| | - Liam Martin
- From the Department of Medicine, University of Calgary, Calgary; Department of Community Health Sciences, University of Calgary, Calgary; Institute of Health Economics, Edmonton; School of Public Health, University of Alberta, Edmonton; and Department of Medicine, University of Alberta, Edmonton, Alberta, Canada.C. Barnabe, MD, MSc, FRCPC, Department of Medicine and Department of Community Health Sciences, University of Calgary; N.X. Thanh, MD, PhD, MPH, Institute of Health Economics and School of Public Health, University of Alberta; A. Ohinmaa, PhD, Institute of Health Economics and School of Public Health, University of Alberta; J. Homik, MD, MSc, FRCPC, Department of Medicine, University of Alberta; S.G. Barr, MD, MSc, FRCPC, Department of Medicine, and Department of Community Health Sciences, University of Calgary; L. Martin, MB, ChB, FRCPC, Department of Medicine, University of Calgary; W.P. Maksymowych, MB, ChB, FRCPC, Department of Medicine, University of Alberta
| | - Walter P Maksymowych
- From the Department of Medicine, University of Calgary, Calgary; Department of Community Health Sciences, University of Calgary, Calgary; Institute of Health Economics, Edmonton; School of Public Health, University of Alberta, Edmonton; and Department of Medicine, University of Alberta, Edmonton, Alberta, Canada.C. Barnabe, MD, MSc, FRCPC, Department of Medicine and Department of Community Health Sciences, University of Calgary; N.X. Thanh, MD, PhD, MPH, Institute of Health Economics and School of Public Health, University of Alberta; A. Ohinmaa, PhD, Institute of Health Economics and School of Public Health, University of Alberta; J. Homik, MD, MSc, FRCPC, Department of Medicine, University of Alberta; S.G. Barr, MD, MSc, FRCPC, Department of Medicine, and Department of Community Health Sciences, University of Calgary; L. Martin, MB, ChB, FRCPC, Department of Medicine, University of Calgary; W.P. Maksymowych, MB, ChB, FRCPC, Department of Medicine, University of Alberta
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DeMaria L, Acelajado MC, Luck J, Ta H, Chernoff D, Florentino J, Peabody JW. Variations and practice in the care of patients with rheumatoid arthritis: quality and cost of care. J Clin Rheumatol 2014; 20:79-86. [PMID: 24561410 DOI: 10.1097/rhu.0000000000000076] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
INTRODUCTION Variability in treatment is linked to lower quality of care and higher costs. Rheumatoid arthritis (RA) is a chronic inflammatory disease for which care and management may vary considerably among rheumatologists. The extent of this variability and its cost ramifications have not been widely studied. This prospective study evaluated the quality and variability in care and quantified the potential cost implications. METHODS We used Clinical Performance and Value® vignettes to measure the quality of RA care among community-based rheumatologists. Three online Clinical Performance and Value® vignettes--representing patients likely seen in practice with mild disease activity (case A), worsening disease activity (case B), and stable disease with a complicating comorbidity (case C)--were administered to each rheumatologist. Responses were scored against evidence-based criteria. Costs were computed using current (2011) Medicare pricing. Data were analyzed using t test and fixed-effects analysis of variance. RESULTS One hundred eight board-certified rheumatologists (72% were male; mean age, 49.1 years) completed the study. Overall quality scores averaged 61.3%. Those employed by a health system or in a multispecialty practice were more likely to score higher. Highest combined scores for diagnosis and treatment were evident with case A (61.7%) and lowest with case C (46.7%). Up to 79% of rheumatologists ordered at least 1 laboratory test that was considered unnecessary by study protocol criteria, incurring a mean excess cost of $37.85 per physician per case. Up to 26.9% rheumatologists prescribed biologic agents that were not indicated based on American College of Rheumatology treatment guidelines, resulting in additional costs of $2041 per patient per month. CONCLUSION In this study, we observed a wide range of reported practice variability by rheumatologists in the management of RA. This included unnecessary testing and use of biologic agents that increased the costs of treatment. Opportunities for quality improvement and cost control exist in the management of RA.
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Affiliation(s)
- Lisa DeMaria
- From *QURE Healthcare, San Rafael, CA; †Faculty of Medicine, University of the Philippines, Manila, Philippines; ‡Oregon State University, Corvalis, OR; §Crescendo Biosciences, South San Francisco, CA; ∥School of Economics, University of the Philippines, Quezon City, Philippines; and ¶Global Health Sciences, University of California, San Francisco, CA
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Bonafede M, Joseph GJ, Princic N, Harrison DJ. Annual acquisition and administration cost of biologic response modifiers per patient with rheumatoid arthritis, psoriasis, psoriatic arthritis, or ankylosing spondylitis. J Med Econ 2013; 16:1120-8. [PMID: 23808901 DOI: 10.3111/13696998.2013.820192] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
OBJECTIVE To estimate annual biologic response modifier (BRM) cost per treated patient with rheumatoid arthritis, psoriasis, psoriatic arthritis, and/or ankylosing spondylitis receiving etanercept, abatacept, adalimumab, certolizumab, golimumab, infliximab, rituximab, or ustekinumab. METHODS This was a cohort study of 69,349 commercially insured individuals in a nationwide claims database with one of these conditions that had a claim for one of these BRMs between January 2008 and December 2010 (the index BRM/index date). Cost per treated patient was calculated as the total BRM acquisition and administration cost to the payer in the first year after the index date (including costs of other BRMs after switching) divided by the number of patients who received the index BRM. Etanercept was selected as the reference for comparisons. RESULTS Etanercept was the most commonly used index BRM (n = 32,298; 47%), followed by adalimumab (n = 20,582; 30%), infliximab (n = 11,157; 16%), abatacept (n = 2633; 4%), rituximab (n = 1359; 2%), golimumab (n = 687; <1%), ustekinumab (n = 388; <1%), and certolizumab (n = 245; <1%). Using etanercept as the reference, the cost per treated patient in the first year across all four conditions was 102% for adalimumab and 108% for infliximab. Newer BRMs had costs relative to etanercept that were 90% to 102% for rheumatoid arthritis, 132% for psoriasis, 100% for psoriatic arthritis, and 94% for ankylosing spondylitis. LIMITATIONS Potential study limitations were the lack of clinical information (e.g., disease severity, treatment outcomes) or indirect costs, the inability to compare costs of newer BRMs across all four conditions, and much smaller sample sizes for newer BRMs. CONCLUSIONS Of the BRMs that are approved for indications within all four conditions studied, etanercept had the lowest cost per treated patient when assessed across all four conditions.
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MESH Headings
- Adalimumab
- Adolescent
- Adult
- Antibodies, Monoclonal/economics
- Antibodies, Monoclonal/therapeutic use
- Antibodies, Monoclonal, Humanized/economics
- Antibodies, Monoclonal, Humanized/therapeutic use
- Arthritis, Psoriatic/drug therapy
- Arthritis, Psoriatic/economics
- Arthritis, Rheumatoid/drug therapy
- Arthritis, Rheumatoid/economics
- Biological Products/economics
- Biological Products/therapeutic use
- Cost-Benefit Analysis
- Databases, Factual
- Drug Administration Schedule
- Drug Costs
- Economics, Pharmaceutical
- Etanercept
- Female
- Health Care Costs
- Humans
- Immunoglobulin G/economics
- Immunoglobulin G/therapeutic use
- Injections, Subcutaneous
- Male
- Middle Aged
- Psoriasis/drug therapy
- Psoriasis/economics
- Receptors, Tumor Necrosis Factor/therapeutic use
- Retrospective Studies
- Spondylitis, Ankylosing/drug therapy
- Spondylitis, Ankylosing/economics
- United States
- Ustekinumab
- Young Adult
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Kawatkar AA, Hay JW, Stohl W, Nichol MB. Incremental expenditure of biologic disease modifying antirheumatic treatment using instrumental variables in panel data. HEALTH ECONOMICS 2013; 22:807-823. [PMID: 22718267 DOI: 10.1002/hec.2855] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2012] [Revised: 05/14/2012] [Accepted: 05/28/2012] [Indexed: 06/01/2023]
Abstract
In health care, decision makers are generally interested in simultaneous comparisons among multiple treatments or interventions available as treatment choices in real-world clinical setting. The lack of random assignment to treatment in real-world clinical settings leads to selection-bias issues when evaluating the marginal benefits of treatment. The application of instrumental variables (IV) estimation to mitigate selection bias has traditionally been limited to comparing only two treatments/interventions concurrently. Using the case of biologic treatment in rheumatoid arthritis, we describe a generalized method of moments (GMM)-based panel data IV (IV-GMM) framework, to simultaneously estimate multiple treatment effects in the presence of time-varying selection bias and time-invariant heterogeneity. To satisfy the order and rank conditions for identification with multiple endogeneity, we propose lagged values of each treatment as excluded instruments. We evaluate the validity of the IV estimation assumptions on instrument relevance and exogeneity. Results indicate that the IV-GMM model offers enhanced control over selection bias and heterogeneity, and more importantly the panel data framework can provide valid excluded instruments that satisfy the order and rank conditions for identification when dealing with multiple endogenous variables. The approach outlined in this article has broad application for comparative effectiveness and health technology assessment involving multiple treatments/interventions using real-world nonexperimental data.
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Affiliation(s)
- Aniket A Kawatkar
- Department of Research and Evaluation, Southern California Permanente Medical Group, Pasadena, CA 91101, USA.
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Bonafede MMK, Gandra SR, Watson C, Princic N, Fox KM. Cost per treated patient for etanercept, adalimumab, and infliximab across adult indications: a claims analysis. Adv Ther 2012; 29:234-48. [PMID: 22411424 DOI: 10.1007/s12325-012-0007-y] [Citation(s) in RCA: 44] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2011] [Indexed: 02/07/2023]
Abstract
INTRODUCTION This paper aims to estimate the annual cost of etanercept, adalimumab, and infliximab per treated patient across adult indications using US-managed care drug use data. METHODS Adult patients who used etanercept, adalimumab, or infliximab were identified in the Thomson Reuters MarketScan® Commercial Claims and Encounters Database (Thomson Reuters Healthcare, Ann Arbor, MI, USA) between January 1, 2005 and June 30, 2009. The index event was the first use of etanercept, adalimumab, or infliximab preceded by a diagnosis for rheumatoid arthritis, psoriasis, psoriatic arthritis, or ankylosing spondylitis. Patients were defined as either newly initiating or continuing tumor necrosis factor (TNF) blocker treatment based on their use during the 6 months before the index event. Annual cost per treated patient was the sum of the etanercept, adalimumab, and infliximab medication and administration costs during the 12 months following the index claim. Annual costs were calculated across all patients as well as within each indication group and patient type (new initiator or continuing). RESULTS In total, 21,652 patients met the study criteria (etanercept n = 12,065; adalimumab n = 5,685; infliximab n = 3,902); 43% of patients were new initiators. Patient characteristics were similar across treatment groups in terms of age (mean = 49, SD = 10) and gender (66% female). Across indications, the mean annual TNF-blocker cost per treated patient was $15,345 for etanercept, $18,046 for adalimumab, and $24,018 for infliximab. In new initiators, the TNF-blocker cost per treated patient across indications was $14,543 for etanercept, $16,978 for adalimumab, and $21,086 for infliximab; among patients continuing therapy, annual costs were $15,836 for etanercept, $19,457 for adalimumab, and $25,748 for infliximab. CONCLUSION Patients on etanercept had the lowest TNF-blocker cost per treated patient for adult indications when applying actual drug use from a US-managed care population. TNF-blocker costs per treated patient on adalimumab and infliximab were approximately 18% and 57% higher than etanercept, respectively, using real-world drug use data.
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MESH Headings
- Adalimumab
- Adolescent
- Adult
- Aged
- Antibodies, Monoclonal/economics
- Antibodies, Monoclonal/therapeutic use
- Antibodies, Monoclonal, Humanized/economics
- Antibodies, Monoclonal, Humanized/therapeutic use
- Antirheumatic Agents/economics
- Arthritis, Psoriatic/drug therapy
- Arthritis, Psoriatic/economics
- Arthritis, Rheumatoid/drug therapy
- Arthritis, Rheumatoid/economics
- Etanercept
- Female
- Health Care Costs/statistics & numerical data
- Humans
- Immunoglobulin G/economics
- Immunoglobulin G/therapeutic use
- Infliximab
- Insurance Claim Review
- Male
- Managed Care Programs/statistics & numerical data
- Middle Aged
- Psoriasis/drug therapy
- Psoriasis/economics
- Receptors, Tumor Necrosis Factor/therapeutic use
- Spondylitis, Ankylosing/drug therapy
- Spondylitis, Ankylosing/economics
- United States
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Carter CT, Changolkar AK, Scott McKenzie R. Adalimumab, etanercept, and infliximab utilization patterns and drug costs among rheumatoid arthritis patients. J Med Econ 2012; 15:332-9. [PMID: 22168788 DOI: 10.3111/13696998.2011.649325] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
OBJECTIVES To evaluate the utilization patterns of the anti-tumor necrosis factor (anti-TNF) agents Humira (adalimumab), Enbrel (etanercept), and Remicade (infliximab) in patients with rheumatoid arthritis (RA) and compare medication costs during the first year of treatment. (Humira is a registered trademark of Abbott Laboratories, IL; Enbrel is a registered trademark of Immunex Corporation, CA; and Remicade is a registered trademark of Janssen Biotech, Inc., PA). METHODS This retrospective analysis of medical and pharmacy claims included patients who were aged ≥18 years, had ≥2 RA diagnosis codes, and had ≥365 days of persistence with the index anti-TNF. Patients excluded had claims for anti-TNF agents within 6 months before the index date. Refill patterns for adalimumab and etanercept, number of infliximab infusions, time between infusions, and dose per infusion were analyzed for 12 months. Direct anti-TNF medication costs were compared among anti-TNFs for the initial treatment year. RESULTS Infliximab-treated patients (n = 457) were significantly older than adalimumab- (n = 337) or etanercept-treated patients (n = 902). Time between refills was longer than recommended for 28% and 30% of adalimumab and etanercept refill periods, respectively. Potential cumulative time without therapy was 33 days for adalimumab and 43 days for etanercept. Statistically significant differences in mean per-patient anti-TNF medication costs for the first year were reported for adalimumab, etanercept, and infliximab ($14,991, $13,361, and $18,139, respectively; p < 0.0001); however, a cost assessment using labeled dosing of the anti-TNF agents with optimal treatment compliance yielded comparable annual medication costs. LIMITATIONS This analysis only evaluated utilization patterns for selected anti-TNF agents and was not inclusive of other medications that patients may have been using for RA. Absolute patient adherence could not be assessed due to lack of information on how patients were self-administering adalimumab and etanercept or if samples of the agents were made available. CONCLUSIONS This study identified gaps in patients' refills compared with prescriber recommendations. The infliximab-treated group had infusion patterns consistent with prescribing information. Potential clinical and economic implications of dose attenuation with adalimumab and etanercept should be explored further.
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MESH Headings
- Adalimumab
- Adolescent
- Adult
- Antibodies, Monoclonal/administration & dosage
- Antibodies, Monoclonal/economics
- Antibodies, Monoclonal/therapeutic use
- Antibodies, Monoclonal, Humanized/administration & dosage
- Antibodies, Monoclonal, Humanized/economics
- Antibodies, Monoclonal, Humanized/therapeutic use
- Antirheumatic Agents/economics
- Antirheumatic Agents/therapeutic use
- Arthritis, Rheumatoid/drug therapy
- Arthritis, Rheumatoid/physiopathology
- Comorbidity
- Drug Utilization/statistics & numerical data
- Etanercept
- Female
- Humans
- Immunoglobulin G/administration & dosage
- Immunoglobulin G/economics
- Immunoglobulin G/therapeutic use
- Infliximab
- Insurance Claim Review
- Male
- Middle Aged
- Prescription Fees
- Receptors, Tumor Necrosis Factor/administration & dosage
- Receptors, Tumor Necrosis Factor/therapeutic use
- Retrospective Studies
- United States
- Young Adult
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Ambegaonkar BM, Wentworth C, Allen C, Sazonov V. Association between extended-release niacin treatment and glycemic control in patients with type 2 diabetes mellitus: analysis of an administrative-claims database. Metabolism 2011; 60:1038-44. [PMID: 21185576 DOI: 10.1016/j.metabol.2010.11.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2009] [Revised: 11/09/2010] [Accepted: 11/10/2010] [Indexed: 10/18/2022]
Abstract
The aim of the study was to evaluate trends in antihyperglycemic agents (AHAs) use in patients with type 2 diabetes mellitus (T2DM) newly initiating extended-release niacin (ERN) compared with other lipid-modifying therapy (LMT). United States administrative-claims data identified adults with T2DM on AHAs who received a new prescription for ERN or another LMT between January 2001 and June 2003 (index date), and these adults were followed for 12 months. Inclusion criteria were (1) stable T2DM as defined by International Classification of Diseases, Ninth Revision, codes and also receiving at least 2 AHA prescriptions 12 to 24 months before initiating ERN or LMT treatment and (2) at least 2 prescriptions within 12 months before the onset of ERN or LMT. Trends in AHA prescriptions 12 months before (baseline) and after (follow-up) index date were defined as (1) no change (ie, stable T2DM), (2) increased (ie, worsening T2DM), or (3) reduced (ie, improved T2DM). Among 3799 patients with T2DM, 392 (10.3%) were treated with ERN and 3407 (89.7%) were treated with other LMT. In the ERN cohort, 82.1% of patients experienced no change in AHA prescriptions between baseline and follow-up compared with 79.4% of patients in the LMT cohort (P = .20); 13% of the ERN cohort and 16% of the LMT cohort (P = .17) experienced a dose increase or the addition of another AHA; and 5% of both cohorts were prescribed fewer AHAs or switched to a lower dose (P = .92). Treatment with ERN (vs other types of LMT) did not significantly increase AHA use, implying that T2DM status did not worsen in this cohort.
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Sany J, Cohen JD, Combescure C, Bozonnat MC, Roch-Bras F, Lafon G, Daures JP. Medico-economic evaluation of infliximab in rheumatoid arthritis--prospective French study of a cohort of 635 patients monitored for two years. Rheumatology (Oxford) 2009; 48:1236-41. [DOI: 10.1093/rheumatology/kep198] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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Nair KV, Tang B, Van Den Bos J, Zhang V, Saseen JJ, Naim A, Rahman M. Categorization of infliximab dose changes and healthcare utilization and expenditures for patients with rheumatoid arthritis in commercially insured and Medicare-eligible populations. Curr Med Res Opin 2009; 25:303-14. [PMID: 19192975 DOI: 10.1185/03007990802598736] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
OBJECTIVE To evaluate how changes in infliximab dose influence resource utilization and expenditures for patients with rheumatoid arthritis (RA). RESEARCH DESIGN AND METHODS A retrospective analysis using claims from January 1, 1999 through March 31, 2005 in the MedStat MarketScan databases for RA patients who had an increase, decrease, or no change in infliximab dose within 1 year of initiating therapy. Eligibility criteria included at least one claim with a diagnosis of RA and no biologic treatment within 6 months before the index infliximab claim, continuous health plan enrollment (commercial or Medicare) for 6 months before and 12 months after the index date, and three consecutive infliximab infusions. The index and final infliximab doses were estimated from claims data. RESULTS Data were included for 1678 commercially insured patients and 616 Medicare-eligible patients; 45.4% and 39.3%, respectively, had an increase in dose, 24.7% and 43.2%, respectively, had a decrease in dose, and 29.9% and 17.5%, respectively, had no change in dose. Overall, resource utilization was higher in the increase-in-dose groups and lower in the no change-in-dose groups when compared with the decrease-in-dose groups for both cohorts. Medical costs were also highest for the increase-in-dose groups for both cohorts. Pharmacy expenditures for the no-change-in-dose groups were lower than the decrease-in-dose groups in both cohorts. CONCLUSIONS An increase in dose was the most common dose change for the commercial cohort, while a decrease in dose was the most common dose change for the Medicare-eligible cohort. Patients with an increase in dose had the highest utilization and expenditures while those with no change in dose had the lowest levels. The nature of this utilization needs to be examined to better understand how dosing changes may influence medical utilization. Changes in dose were defined by the difference between the first and final doses and may not have captured changes in interim doses.
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Juillard-Condat B, Constantin A, Cambon-Thomsen A, Bourrel R, Taboulet F. Impact of etanercept on the costs of rheumatoid arthritis (RA): Results from a French observational study. Joint Bone Spine 2008; 75:25-8. [PMID: 17913554 DOI: 10.1016/j.jbspin.2007.04.013] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2006] [Accepted: 04/17/2007] [Indexed: 11/23/2022]
Abstract
INTRODUCTION Economical impact of rheumatoid arthritis (RA) has been widely modified thanks to TNF inhibitors. Our study aims to estimate the impact etanercept prescription, in term of health resources consumption, within a regional cohort of French RA patients. METHODS The study included 148 RA patients, with a mean follow-up duration of 343 days before and after etanercept initiation. Data were anonymously collected from ERASME database of French Health Insurance in Midi-Pyrénées region. A patient-by-patient microcosting approach was performed. RESULTS The average annual cost per patient, attributable to RA, was 2.8 times higher after treatment by etanercept than before (15,148.57euro versus 5248.95euro). We observed a rise in pharmaceutical costs, from 11.7% of direct medical costs before to 69.7% after etanercept initiation (120.12euro versus 9995.23euro). We observed a small decrease particularly for NSAIDs (142.14euro versus 102.21euro) and physiotherapy (286.40euro versus 138.77euro). Attributable act costs and indirect costs did not differ before and after etanercept initiation. DISCUSSION In this short-term study, initiation of etanercept in RA patients did not come along with a decrease of consumption of health resources. Long-term studies are needed to reveal a potential economical advantage as a consequence of the clinical, structural and functional efficacy of anti-TNF.
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