Abstract 5718: Additivity predicts the clinical efficacy of most approved combination therapies for advanced cancer

Abstract

Abstract Most advanced cancers are treated with drug combinations. Rational designs aim to identify synergistic drug interactions to produce superior treatments. However, metrics of drug interaction (i.e., synergy, additivity, antagonism) apply to pre-clinical experiments, and there has been no established method to quantify synergy versus additivity in clinical settings. Here, we propose and apply a model of drug additivity for progression-free survival (PFS) to assess if the clinical efficacies of approved drug combinations are more than, or equal to, the sum of their parts. This model accounts for the benefit from patient-to-patient variability in the best single drug response, plus the added benefit of the weaker drug per patient. Among all FDA approvals of combination therapies for advanced cancer between 1995 and 2020, we identified 37 combinations across 13 cancer types (24,723 patients) where the efficacies of monotherapies and combination therapies could be analyzed at matched doses. 95% of combination therapies exhibited progression-free survival times that were additive, or less than additive. Across all trials and follow-up times, the coefficient of determination of the additivity model was R2=0.90, with no fitting or training, only the operation of addition. While there were deviations from additivity, with several combinations being less than additive, 100% of the approved combinations studied would have been predicted to succeed by the additivity model. This study has two key findings. First, a synergistic effect (more than additive) is neither a necessary nor even common property of clinically effective drug combinations. Second, the predictable efficacy of many of the best drug combinations established over the past 25 years suggests that additivity can be used as a design principle for novel drug combinations and clinical trials, which could be helpful as the number of possible therapies grows and as cancers are increasingly divided into subtypes with distinct drug sensitivities. Citation Format: Haeun Hwangbo, Sarah Patterson, Andy Dai, Deborah Plana, Adam C. Palmer. Additivity predicts the clinical efficacy of most approved combination therapies for advanced cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5718.