  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. We performed 100-fold and
1000-fold simulations of solid tumour systemic therapy RCTs with health
statuses rank ordered from complete response (Stage 0) to death (Stage 4). At
increments of 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)
time-to-first significant efficacy signal. CWTA consistently demonstrated
greater power, and reduced 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 2- to 6-fold. CWTA, by incorporating all efficacy signals in the cancer
treatment trajectory, provides clinically relevant reduction in 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.
