Population kinetics of progression free survival (PFS).

Abstract

e18251 Background: We assessed drug type impact on whether PFS curves could be fit by 2 phase decay models on nonlinear regression analysis (NLRA). Methods: We digitized 894 published PFS curves for incurable cancers. We used GraphPad Prism 7 for 1 phase and 2 phase decay NLRA, with constraints Y0 = 100 and plateau = 0. We defined curves as fitting 2 phase models if each subpopulation was ≥1% of the entire population and if subpopulation half-lives differed by a factor of ≥2, or if log-linear plots demonstrated unequivocal 2 phase decay. Results: PFS curves for single agents showed either high (≥75%) or low ( < 30%) probability of 2 phase decay, depending on drug type (p < 0.0001, Table). 11/11 PD1/ipilimumab combinations had 2 phase decay vs 36/209 curves (17%) for all other combinations. Conclusions: Drugs have either high or low probability of PFS curve 2 phase decay. Clinical trial methods or some mechanisms of acquired resistance might contribute to 2 phase decay, but 2 phase decay also could indicate a dichotomous factor (eg gene mutation/deletion or complete pathway silencing) producing 2 distinct subpopulations with differing progression rates. Drugs with high 2 phase decay could be prime candidates for RNA & whole genome sequencing, pathway expression studies etc to identify dichotomous predictive factors. Further assessment is needed to better understand why some drugs behave differently when given in combinations vs as single agents. [Table: see text]