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How To Conduct Economic Evaluations Of New Treatments For Advanced Cancer When Overall Survival Data Are Not Available? Results From A Systematic Literature Review

      Objectives

      Use of surrogate endpoints like progression-free survival (PFS) and time to progression (TTP) instead of overall survival (OS) in clinical trials for advanced cancer remains challenging from a health economic standpoint. This study assessed the use of surrogate endpoints in economic evaluations of anticancer drugs and methodological approaches adopted when reliable OS data are unavailable.

      Methods

      A systematic literature review was conducted to identify economic evaluations of treatments for advanced cancer published between January 2003 and October 2013. Cost-effectiveness and cost-utility analyses expressed in terms of cost per life-year gained and cost per quality-adjusted life-year using a surrogate endpoint as an outcome measure were eligible. Characteristics of selected studies were extracted and comprised: population, treatment of interest, comparator, line-of-treatment, study perspective, and time horizon. Use of surrogate endpoints and methods adopted when OS data were lacking were analyzed. Two reviewers independently selected studies and extracted data.

      Results

      In total, 7,219 studies were identified and 100 fulfilled the eligibility criteria. Most included studies assessed the cost-effectiveness of a biological therapy (65%) in the first-line setting (56%) and in the context of advanced non-small cell lung cancer (24%) or advanced breast cancer (22%). Surrogate endpoints mostly used were PFS and TTP, accounting for 92% of included studies. OS data were unavailable for analysis in nearly 25% of economic evaluations. In the absence of OS data, studies most commonly assumed an equal risk of death for all treatment groups. Other methods included use of indirect comparison based on numerous assumptions, use of a surrogate endpoint as a proxy for OS, consultation with clinical experts, and use of OS data associated with different patient populations or treatment-line.

      Conclusions

      Although several approaches are used, there is no consensus method to estimate the cost-effectiveness of new anticancer drugs in the absence of reliable OS data.