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1.
J Manag Care Spec Pharm ; 24(12): 1240-1246, 2018 Dec.
Article in English | MEDLINE | ID: mdl-30479201

ABSTRACT

BACKGROUND: FDA-required labeling summarizes certain data that the FDA relies on in its drug approval process. However, when determining coverage of specialty drugs, health care payers may consider dissimilar evidence. OBJECTIVE: To compare evidence cited by the largest U.S. commercial payers in their specialty drug coverage policies with evidence featured in the labeling of the indicated drugs. METHODS: We used the Tufts Medical Center Specialty Drug Evidence and Coverage Database (SPEC)-a database of specialty drug coverage policies issued by 17 of the 20 largest U.S. commercial health care payers-to identify coverage policies for drugs indicated for multiple sclerosis, rheumatoid arthritis, juvenile idiopathic arthritis, ankylosing spondylitis, and non-small cell lung cancer (NSCLC). These disease categories were selected because each was represented by multiple drugs. For each drug, we identified endpoints included in the clinical studies presented in the FDA-required labeling. Using SPEC, we identified randomized controlled trials (RCTs) and other clinical studies that at least 1 payer cited in its coverage policies for the included drugs. We reviewed the full text of each study to identify the endpoints reported. We categorized endpoints as identical to endpoints in the FDA-required labeling of the drugs; similar (e.g., a different measurement scale was used to evaluate the same endpoint); and different (the endpoint was not featured in the FDA-required labeling). RESULTS: We included 41 drugs and reviewed 348 studies (246 RCTs and 102 other clinical studies). Of 2,237 endpoints, 63% were categorized as identical, 26% as similar, and 12% as different. Rheumatoid arthritis was the indication with the largest proportion of endpoints categorized as identical (74% of endpoints in the RCTs cited by payers; 59% of endpoints in the other clinical studies cited by payers). NSCLC was the indication with the largest proportion of endpoints categorized as different (33% of end-points in the RCTs cited by payers; 37% of endpoints in the other clinical studies cited by payers). CONCLUSIONS: Payers often report reviewing clinical evidence that goes beyond information included in FDA-required labeling. Our findings suggest that the FDA should continue engaging with the manufacturer and payer communities to appropriately facilitate communication of information necessary to allow for informed coverage decisions. DISCLOSURES: This study was funded by an unrestricted grant from the Pharmaceutical Research and Manufacturers of America. The authors work with The Center for the Evaluation of Value and Risk in Health, which is partially supported through the CEA Registry Sponsorship program; the CEA Registry has received funding from the National Science Foundation, National Library of Medicine, Agency for Healthcare Research and Quality, Centers for Disease Control and Prevention, and a variety of pharmaceutical and device companies that subscribe to the data. Chambers reports personal fees from Health Advances, Ernst & Young, Magellan Health, Summit Therapeutics, and Sanofi-Aventis, unrelated to this study. Neumann reports past advisory board work with Amgen, Avexis, Axovant, Bayer, Bluebird, Congressional Budget Office, Janssen, Merck, Novo Nordisk, Pacira, Paratek, and Sage; consulting work for Boston Health Economics, GSK, Precision Health Economics, Veritech, and Vertex; speaker fees from AbbVie, Celgene, and Roche; and grants from the Alzheimer's Association, Amgen, Gates, Lundbeck, NIH, NPC, and Sage, all unrelated to this study. The other authors have nothing to disclose.


Subject(s)
Drug Approval/legislation & jurisprudence , Drug Labeling/standards , Insurance Coverage/legislation & jurisprudence , Prescription Drugs/economics , United States Food and Drug Administration/standards , Arthritis, Juvenile/drug therapy , Arthritis, Rheumatoid/drug therapy , Carcinoma, Non-Small-Cell Lung/drug therapy , Decision Making , Drug Labeling/legislation & jurisprudence , Evidence-Based Medicine/standards , Humans , Interdisciplinary Communication , Lung Neoplasms/drug therapy , Multiple Sclerosis/drug therapy , Prescription Drugs/standards , Prescription Drugs/therapeutic use , Randomized Controlled Trials as Topic , Spondylitis, Ankylosing/drug therapy , Treatment Outcome , United States , United States Food and Drug Administration/legislation & jurisprudence
2.
Health Aff (Millwood) ; 37(7): 1041-1047, 2018 07.
Article in English | MEDLINE | ID: mdl-29985695

ABSTRACT

We analyzed specialty drug coverage decisions issued by the largest US commercial health plans to examine variation in coverage and the consistency of those decisions with indications approved by the Food and Drug Administration (FDA). Across 3,417 decisions, 16 percent of the 302 drug-indication pairs were covered the same way by all of the health plans, and 48 percent were covered the same way by 75 percent of the plans. Specifically, 52 percent of the decisions were consistent with the FDA label, 9 percent less restrictive, 2 percent mixed (less restrictive in some ways but more restrictive in others), and 33 percent more restrictive, while 5 percent of the pairs were not covered. Health plans restricted coverage of drugs indicated for cancer less often than they did coverage of drugs indicated for other diseases. Using multivariate regression, we found that several drug-related factors were associated with less restrictive coverage, including indications for orphan diseases or pediatric populations, absence of safety warnings, time on the market, lack of alternatives, and expedited FDA review. Variations in coverage have implications for patients' access to treatment and health system costs.


Subject(s)
Drug Prescriptions/economics , Insurance Coverage/statistics & numerical data , Orphan Drug Production/economics , Orphan Drug Production/statistics & numerical data , Health Benefit Plans, Employee/statistics & numerical data , Health Expenditures/statistics & numerical data , Health Expenditures/trends , Humans
3.
Health Aff (Millwood) ; 36(8): 1408-1415, 2017 08 01.
Article in English | MEDLINE | ID: mdl-28784733

ABSTRACT

We investigated whether drugs approved by the Food and Drug Administration (FDA) through expedited review have offered larger health gains, compared to drugs approved through conventional review processes. We identified published estimates of additional health gains (measured in quality-adjusted life-years, or QALYs) associated with drugs approved in the period 1999-2012 through expedited (seventy-six drugs) versus conventional (fifty-nine) review processes. We found that drugs in at least one expedited review program offered greater gains than drugs reviewed through conventional processes (0.182 versus 0.003 QALYs). We also found that, compared to drugs not included in the same program, greater gains were provided by drugs in the priority review (0.175 versus 0.007 QALYs), accelerated approval (0.370 versus 0.031 QALYs), and fast track (0.254 versus 0.014 QALYs) programs. Our analysis suggests that the FDA has prioritized drugs that offer the largest health gains.


Subject(s)
Drug Approval/statistics & numerical data , Quality-Adjusted Life Years , United States Food and Drug Administration/trends , Drug Discovery/trends , Humans , Time Factors , United States , United States Food and Drug Administration/statistics & numerical data
4.
Expert Rev Pharmacoecon Outcomes Res ; 17(6): 615-623, 2017 Dec.
Article in English | MEDLINE | ID: mdl-28504026

ABSTRACT

BACKGROUND: Debates persist on the appropriate time horizon from a payer's perspective and how the time horizon in cost-effectiveness analysis (CEA) influences the value assessment. METHODS: We systematically reviewed the Tufts Medical Center CEA Registry and identified US-based studies that used a payer perspective from 2005-2014. We classified the identified CEAs as short-term (time horizon ≤ 5 years) and long-term (> 5 years), and examined associations between study characteristics and the specified time horizon. We also developed case studies with selected interventions to further explore the relationship between time horizon and projected costs, benefits, and incremental cost-effectiveness ratios (ICER). RESULTS: Among 782 identified studies that met our inclusion criteria, 552 studies (71%) utilized a long-term time horizon while 198 studies (25%) used a short-term horizon. Among studies that employed multiple time horizons, the extension of the time horizon yielded more favorable ICERs in 19 cases and less favorable ICERs in 4 cases. Case studies showed the use of a longer time horizon also yielded more favorable ICERs. CONCLUSION: The assumed time horizon in CEAs can substantially influence the value assessment of medical interventions. To capture all consequences, we encourage the use of time horizons that extend sufficiently into the future.


Subject(s)
Cost-Benefit Analysis/methods , Decision Making , Research Design , Humans , Registries , Time Factors , United States
5.
Appl Health Econ Health Policy ; 15(2): 227-235, 2017 Apr.
Article in English | MEDLINE | ID: mdl-27832480

ABSTRACT

OBJECTIVE: Compared to traditional drugs, specialty drugs tend to be indicated for lower prevalence diseases. Our objective was to compare the potential population health benefits associated with specialty and traditional drugs in the year following product approval. METHODS: First, we created a dataset of estimates of incremental quality-adjusted life-year (QALY) gains and incremental life-year (LY) gains for US FDA-approved drugs (1999-2011) compared to standard of care at the time of approval identified from a literature search. Second, we categorized each drug as specialty or traditional. Third, for each drug we identified estimates of US disease prevalence for each pertinent indication. Fourth, in order to conservatively estimate the potential population health gains associated with each new drug in the year following its approval we multiplied the health gain estimate by 10% of the identified prevalence. Fifth, we used Mann-Whitney U tests to compare the population health gains for specialty and traditional drugs. RESULTS: We identified QALY gain estimates for 101 drugs, including 56 specialty drugs, and LY gain estimates for 50 drugs, including 34 specialty drugs. The median estimated population QALY gain in the year following approval for specialty drugs was 4200 (IQR = 27,000) and for traditional drugs was 694 (IQR = 24,400) (p = 0.245). The median estimated population LY gain in the year following approval for specialty drugs was 7250 (IQR = 39,200) and for traditional drugs was 2500 (IQR = 58,200) (p = 0.752). CONCLUSIONS: Despite often being indicated for diseases of lower prevalence, we found a trend towards specialty drugs offering larger potential population health gains than traditional drugs, particularly when measured in terms of QALYs.


Subject(s)
Drug Therapy/statistics & numerical data , Drug Approval , Humans , Quality-Adjusted Life Years , Statistics, Nonparametric , Treatment Outcome
6.
Am J Public Health ; 106(12): 2205-2207, 2016 Dec.
Article in English | MEDLINE | ID: mdl-27631752

ABSTRACT

OBJECTIVES: To examine the extent to which recently published cost-utility analyses (cost-effectiveness analyses using quality-adjusted life-years to measure health benefits) have covered the leading health concerns in the US Department of Health and Human Services Healthy People 2020 report. METHODS: We examined data in the Tufts Medical Center Cost-Effectiveness Analysis Registry, a database containing 5000 published cost-utility analyses published in the MEDLINE literature through 2014. We focused on US-based cost-utility analyses published from 2011 through 2014 (n = 687). Two reviewers scanned abstracts and met for a consensus on categorization of cost-utility analyses that addressed the specific priorities listed in the 12 Healthy People 2020 areas (n = 120). RESULTS: Although 7.3% of recently published cost-utility analyses addressed key clinical preventive services, only about 2% of recently published cost-utility analyses covered each of the following Healthy People 2020 topics: reproductive and sexual health, nutrition/physical activity/obesity, maternal and infant health, and tobacco. Fewer than 1% addressed priorities such as injuries and violence, mental health or substance abuse, environmental quality, and oral health. CONCLUSIONS: Few cost-utility analyses have addressed Healthy People 2020 priority areas.


Subject(s)
Cost-Benefit Analysis , Health Services Needs and Demand , Healthy People Programs/economics , Female , Health Priorities , Humans , Male , Registries
7.
J Manag Care Spec Pharm ; 22(10): 1176-81, 2016 Oct.
Article in English | MEDLINE | ID: mdl-27668566

ABSTRACT

BACKGROUND: Payers in the United States issue coverage determinations to guide how their enrolled beneficiaries use prescription drugs. Because payers create their own coverage policies, how they cover drugs can vary, which in turn can affect access to care by beneficiaries. OBJECTIVE: To examine how the largest private payers based on membership cover drugs indicated for rheumatoid arthritis and to determine what evidence the payers reported reviewing when formulating their coverage policies. METHODS: Coverage policies issued by the 10 largest private payers that make their policies publicly available were identified for rheumatoid arthritis drugs. Each coverage determination was compared with the drug's corresponding FDA label and categorized according to the following: (a) consistent with the label, (b) more restrictive than the label, (c) less restrictive than the label, or (d) mixed (i.e., more restrictive than the label in one way but less restrictive in another). Each coverage determination was also compared with the American College of Rheumatology (ACR) 2012 treatment recommendations and categorized using the same relative restrictiveness criteria. The policies were then reviewed to identify the evidence that the payers reported reviewing. The identified evidence was divided into the following 6 categories: randomized controlled trials; other clinical studies (e.g., observational studies); health technology assessments; clinical reviews; cost-effectiveness analyses; and clinical guidelines. RESULTS: Sixty-nine percent of coverage determinations were more restrictive than the corresponding FDA label; 15% were consistent; 3% were less restrictive; and 13% were mixed. Thirty-four percent of coverage determinations were consistent with the ACR recommendations, 33% were more restrictive; 17% were less restrictive; and 17% were mixed. Payers most often reported reviewing randomized controlled trials for their coverage policies (an average of 2.3 per policy). The payers reported reviewing an average of 1.4 clinical guidelines, 1.1 clinical reviews, 0.8 other clinical studies, and 0.5 technology assessments per policy. Only 1 payer reported reviewing cost-effectiveness analyses. The evidence base that the payers reported reviewing varied in terms of volume and composition. CONCLUSIONS: Payers most often covered rheumatoid arthritis drugs more restrictively than the corresponding FDA label indication and the ACR treatment recommendations. Payers reported reviewing a varied evidence base in their coverage policies. DISCLOSURES: Funding for this study was provided by Genentech. Chambers has participated in a Sanofi advisory board, unrelated to this study. The authors report no other potential conflicts of interest. Study concept and design were contributed by Chambers. Anderson, Wilkinson, and Chenoweth collected the data, assisted by Chambers, and data interpretation was primarily performed by Chambers, along with Anderson and with assistance from Wilkinson and Chenoweth. The manuscript was written primarily by Chambers, along with Wilkinson and with assistance from Anderson and Chenoweth. Chambers, Chenoweth, Wilkinson, and Anderson revised the manuscript.


Subject(s)
Antirheumatic Agents/therapeutic use , Arthritis, Rheumatoid/drug therapy , Insurance Coverage/statistics & numerical data , Biomedical Technology , Cost-Benefit Analysis , Drug Labeling , Drug Utilization , Evidence-Based Medicine , Guidelines as Topic , Humans , Insurance, Pharmaceutical Services , Prescription Drugs , Randomized Controlled Trials as Topic , United States , United States Food and Drug Administration
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