On the Translation of a Treatment's Effect on Disease Progression Into an Effect on Overall Survival

Abstract

There are many examples of treatments for cancer that show a large and statistically significant improvement in progression-free survival (PFS) but fail to show a benefit in overall survival (OS). One recent example that has received considerable attention involves bevacizumab (Avastin) for the treatment of breast cancer. While it seems logical that slowing the rate of progression of a fatal disease would translate into an increase in survival, it is not clear what relative magnitudes of these two effects one should expect. One potential model for the translation of a benefit on disease progression into an OS benefit assumes that patients transition from a low-risk state (pre-progression) into a high-risk state (post-progression), and that the only impact of the treatment is to alter the rate of this transition. In this paper we describe this model and present quantitative results, using an assumption of constant hazards both pre-progression and post-progression. We find that an effect on progression translates into an effect on survival of a smaller magnitude, and that two key factors influence that relationship: the magnitude of the difference between the hazard rate for death in the pre- and post-progression states, and the duration of follow-up.