Little Consistency In Evidence Cited By Commercial Plans For Specialty Drug Coverage.

We found wide variation in the evidence that US commercial health plans reported reviewing in their specialty drug coverage policies. There was little consistency in the numbers or types of studies cited by health plans. On average, only 15 percent of health plans' coverage policies cited the same study evaluating a specific drug for a specific indication.

Discrepancies Between FDA-Required Labeling and Evidence that Payers Cite in Drug Coverage Policies.

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.

Specialty Drug Coverage Varies Across Commercial Health Plans In The US.

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.

Comparing the cost-per-QALYs gained and cost-per-DALYs averted literatures.

Background: We examined the similarities and differences between studies using two common metrics used in cost-effectiveness analyses (CEAs): cost per quality-adjusted life year (QALY) gained and cost per disability-adjusted life year (DALY) averted. Methods: We used the Tufts Medical Center CEA Registry, which contains English-language cost-per-QALY gained studies, and the Global Cost-Effectiveness Analysis (GHCEA) Registry, which contains cost-per-DALY averted studies. We examined study characteristics, including intervention type, sponsor, country, and primary disease, and also compared the number of published CEAs to disease burden for major diseases and conditions across geographic regions. Results: We identified 6,438 cost-per-QALY and 543 cost-per-DALY studies published through 2016 and observed rapid growth for both literatures. Cost-per-QALY studies most often examined pharmaceuticals and interventions in high-income countries. Cost-per-DALY studies predominantly focused on infectious disease interventions and interventions in low and lower-middle income countries. We found that while diseases imposing a larger burden tend to receive more attention in the cost-effectiveness analysis literature, the number of publications for some diseases and conditions deviates from this pattern, suggesting "under-studied" conditions (e.g., neonatal disorders) and "over-studied" conditions (e.g., HIV and TB). Conclusions: The CEA literature has grown rapidly, with applications to diverse interventions and diseases.  The publication of fewer studies than expected for some diseases given their imposed burden suggests funding opportunities for future cost-effectiveness research.

The influence of time horizon on results of cost-effectiveness analyses.

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.