Durable survival and response rates of modern immuno-oncology agents are rarely recognized as significant by current oncology value frameworks. This may be due to insufficient demonstration of efficacy of such agents or inappropriately calibrated value frameworks.

Introduction Understanding the efficacy of treatments is crucial for patients, physicians, and policymakers. Median survival, the most common measure used in the outcome reporting of oncology clinical trials, is easy to understand; however, it describes only a single time point. The interpretation of the hazard ratio is difficult, and its underlying statistical assumptions are not always met. The objective of this study was to evaluate alternative measures based on the mean benefit of novel oncology treatments. Materials and Methods We reviewed all U.S. Food and Drug Administration (FDA) approvals for oncology agents between 2013 and 2017. We digitized survival curves as reported in the clinical trials used for the FDA approvals and implemented statistical transformations to calculate for each trial the restricted mean survival time (RMST), as well as the mean survival using Weibull distribution. We compared the mean survival with the median survival benefit in each clinical trial. Results The FDA approved 83 solid tumor indications for oncology agents between 2013 and 2017, of which 27 approvals based on response rates, whereas 49 approvals were based on survival endpoints (progression‐free survival and overall survival). The average improvement in median overall survival or progression‐free survival was 4.6 months versus 3.6 months improvement in the average RMST and 6.1 months improvement in mean survival using Weibull distribution. Conclusion Mean survival may supply valuable information for different stakeholders. Its inclusion should be considered in the reporting of prospective clinical trials. Implications for Practice Mean survival may supply valuable information for different stakeholders. Its inclusion should be considered in the reporting of clinical trials.

BackgroundIncreasing health costs in developed countries are a major concern for decision makers. A variety of cost containment tools are used to control this trend, including maximum price regulation and reimbursement methods for health technologies. Information regarding expenditure-related outcomes of these tools is not available.ObjectiveTo evaluate the association between different cost-regulating mechanisms and national health expenditures in selected countries.MethodsPrice-regulating and reimbursement mechanisms for prescription drugs among OECD countries were reviewed. National health expenditure indices for 2008–2012 were extracted from OECD statistical sources. Possible associations between characteristics of different systems for regulation of drug prices and reimbursement and health expenditures were examined.ResultsIn most countries, reimbursement mechanisms are part of publicly financed plans. Maximum price regulation is composed of reference-pricing, either of the same drug in other countries, or of therapeutic alternatives within the country, as well as value-based pricing (VBP). No association was found between price regulation or reimbursement mechanisms and healthcare costs. However, VBP may present a more effective mechanism, leading to reduced costs in the long term.ConclusionsMaximum price and reimbursement mechanism regulations were not found to be associated with cost containment of national health expenditures. VBP may have the potential to do so over the long term.

PURPOSE: A unique feature of immuno-oncology agents is the potential for durable survival for a subset of patients; however, this benefit usually cannot not be seen in the early published data used for regulatory approval. Value frameworks developed by ASCO and the European Society for Medical Oncology (ESMO) assess the clinical benefit demonstrated in clinical trials. Proven benefit may change with time as more mature data are available. Our objective was to evaluate the impact of mature data for immuno-oncology agents on ASCO and ESMO scores and to examine the concordance of these frameworks using more mature data. METHODS: We reviewed Food and Drug Administration (FDA) approvals for immuno-oncology agents between 2011 and 2017, calculated the ASCO-Net Health Benefit (NHB) score and ESMO-Magnitude of Clinical Benefit Score (MCBS), checked which agents fulfilled the criteria of being rewarded for durable survival, assessed the concordance between models using the Spearman correlation test, and compared the initial results of registration studies with mature follow-up data from the same studies. RESULTS: The FDA approved 27 solid tumor indications for immuno-oncology agents between 2011 and 2017. The correlation between ASCO-NHB score and ESMO-MCBS was high (0.88). Mature follow-up data were available for 13 of these indications, in which 6 studies were found to have improved in the grade of ASCO and/or ESMO value frameworks, whereas 2 cases were downgraded in the scale. CONCLUSION: Despite different approaches, the high concordance between ASCO and ESMO value frameworks indicates that both models reward treatments as beneficial for the same immuno-oncology agents. Mature data with longer follow-up reaffirmed most of the findings found in the evaluation in the initially published registration studies.

6624 Background: Patented anti-cancer drugs launch prices have increased in recent years with subsequent increases after launch. Recently, large price increases of generic drugs were at the center of public attention in the United States. Our aim was to assess price changes with time for Medicare part B anti-cancer generic drugs and to understand how drug characteristics and market structure influence price trajectories. Methods: We included all Medicare part B anti-cancer drugs with price reported in both 2006 and 2016. Patent expiration dates were attached using the Medicare Drug Patent Expiration engine and drugs with a patent expiration date later than 2006 were excluded. Generic manufacturers' FDA approvals for each drug were extracted from the FDA Orange Book. For each drug we extracted the Average Sales Price (ASP) history from October 2006 to October 2016, published by the Center for Medicare and Medicaid services (CMS). Prices were adjusted for inflation, using information obtained from the United States Department of Labor. For each drug we calculated the cumulative ASP change during the follow-up period. Data were analyzed using IBM SPSS Statistics software. Results: We identified 31 anti-cancer generic drugs that met the inclusion and exclusion criteria. During the follow-up period, 15 (48%) drugs had increases in price (median 139%, range 18-2632%). Seven (23%) drugs increased by more than 200% (Table 1). Both gradual price and acute price increases were observed. Some of the drugs which had substantial price increases had no market competition market. Conclusions: Generic drug prices may change substantially with time. Gradual or rapid price increases may be due to lack of generic drug competition, substitution shortages or marketing reasons. New regulations may be needed to prevent further increases in generic drug costs, while balancing the need to maintain financial incentives for drug production and competition. [Table: see text]