End Points in Lung Cancer Clinical Trials: Are we Ready to Step Away from Overall Survival?

Abstract

467 ISSN 1758-1966 10.2217/LMT.13.54 © 2013 Future Medicine Ltd Lung Cancer Manage. (2013) 2(6), 467–470 Overall survival (OS), defined as the time from randomization or registration to death from any cause, is the gold standard end point in clinical trials as it is a measure of direct clinical benefit to a patient. OS as an end point is unambiguous and can unequivocally assess the benefit of a new treatment relative to the current standard of care. While improving OS remains the ultimate goal of new cancer therapy, an intermediate end point, such as progression-free survival (PFS), a composite end point defined as time from randomization to disease progression or death, is commonly used to evaluate the treatment effect of new oncologic products studied in randomized controlled trials (RCTs) [1]. Two major reasons to explore alternate end points to OS are: first, the inability to effectively assess crossover effects and subsequent therapies; and second, the requirement of large patient numbers and extended follow-up, making it a ‘long’ end point to assess, thereby delaying the development, approval and access to potentially efficacious drugs. Korn et al. discussed the influence of effective subsequent therapies on OS comparisons in RCTs where either subsequent therapy is equally effective in both arms of the RCT or where control arm patients crossover to experimental therapy upon disease progression [2]. The authors concluded that while improvement in an intermediate end point, such as PFS or disease-free survival (DFS), could be considered as evidence of true clinical benefit in adjuvant settings (i.e., early-stage disease), use of OS as the primary outcome is appropriate in trials where there is no intermediate end point to assess clinical benefit. This brings up the discussion of an intermediate end point versus a surrogate end point. An intermediate end point as defined by Korn et al. is one that directly measures true clinical benefit, whereas a surrogate end point is one that has been validated as an adequate substitute for the true clinical end point [2]. A valid surrogate end point must, therefore, both correlate with and accurately predict the true outcome of interest, for example, the treatment effect observed on the surrogate end point should reliably and precisely predict the treatment effect on the true clinical end point [3,4]. Shi et al. elegantly outline the issues surrounding the validation of surrogate end points [4], and review meta-analytic approaches