Issues in using progression-free survival when evaluating oncology products

Abstract

Several challenging and often controversial issues arise in oncology trials with the use of the end point progression-free survival (PFS), defined to be the time to detection of progressive disease or death. While this end point does not directly measure how a patient feels, functions, or survives, it does provide insights about whether an intervention affects the tumor burden process, the intended mechanism through which it is hoped that most anticancer agents will provide benefit. However, simply achieving statistically significant effects on PFS is insufficient to obtaining reliable evidence of important clinical benefit, and even is insufficient to justifying the conclusion that the experimental intervention is "reasonably likely to provide clinical benefit." The magnitude of the effect on PFS in addition to the statistical strength of evidence is of great importance in interpreting the reliability of the evidence regarding clinical efficacy. PFS has several important properties, including being a direct measure of the effect of treatment on the tumor burden process, being sensitive to cytostatic as well as cytotoxic mechanisms of interventions, and incorporating the clinically relevant event of death, increasing its sensitivity to influential harmful mechanisms and avoiding substantial bias that arises when deaths are censored. To obtain reliable evidence about the effect of an intervention on PFS and patient survival, randomized trials should be conducted where all patients are followed to progression and death, and where patients in a control arm do not cross-in at progression unless the experimental regimen has already been established to be effective rescue treatment.

Fig 1.

An approach is illustrated to achieve the timely completion of validation trials when pursuing accelerated approval in the oncology setting. EXP, the experimental regimen; L*, the number of patients experiencing progression-free survival (PFS) events; L, the number of patients experiencing overall survival (OS) events; SOE, strength of evidence required to rule out an hypothesis.