Chauhan Weighted Trajectory Analysis Reduces Sample Size Requirements and Expedites Time-to-Efficacy Signals in Advanced Cancer Clinical Trials

Abstract

(1) Background: As Kaplan–Meier (KM) analysis is limited to single unidirectional endpoints, most advanced cancer randomized clinical trials (RCTs) are powered for either progression-free survival (PFS) or overall survival (OS). This discards efficacy information carried by partial responses, complete responses, and stable disease that frequently precede progressive disease and death. Chauhan Weighted Trajectory Analysis (CWTA) is a generalization of KM that simultaneously assesses multiple rank-ordered endpoints. We hypothesized that CWTA could use this efficacy information to reduce sample size requirements and expedite efficacy signals in advanced cancer trials. (2) Methods: We performed 100-fold and 1000-fold simulations of solid tumor systemic therapy RCTs with health statuses rank-ordered from complete response (Stage 0) to death (Stage 4). At increments of the sample size and hazard ratio, we compared KM PFS and OS with CWTA for (i) sample size requirements to achieve a power of 0.8 and (ii) the time to first significant efficacy signal. (3) Results: CWTA consistently demonstrated greater power, and it reduced the sample size requirements by 18% to 35% compared to KM PFS and 14% to 20% compared to KM OS. CWTA also expedited time-to-efficacy signals by 2- to 6-fold. (4) Conclusions: CWTA, by incorporating all efficacy signals in the cancer treatment trajectory, provides a clinically relevant reduction in the required sample size and meaningfully expedites the efficacy signals of cancer treatments compared to KM PFS and KM OS. Using CWTA rather than KM as the primary trial outcome has the potential to meaningfully reduce the numbers of patients, trial duration, and costs to evaluate therapies in advanced cancer.