We consider five asymptotically unbiased estimators of intervention effects on event rates in non-matched and matched-pair cluster randomized trials, including ratio of mean counts r 1 , ratio of mean cluster-level event rates r 2 , ratio of event rates r 3 , double ratio of counts r 4 , and double ratio of event rates r 5 . In the absence of an indirect effect, they all estimate the direct effect of the intervention. Otherwise, r 1 , r 2 , and r 3 estimate the total effect, which comprises the direct and indirect effects, whereas r 4 and r 5 estimate the direct effect only. We derive the conditions under which each estimator is more precise or powerful than its alternatives. To control bias in studies with a small number of clusters, we propose a set of approximately unbiased estimators. We evaluate their properties by simulation and apply the methods to a trial of seasonal malaria chemoprevention. The approximately unbiased estimators are practically unbiased and their confidence intervals usually have coverage probability close to the nominal level; the asymptotically unbiased estimators perform well when the number of clusters is approximately 32 or more per trial arm. Despite its simplicity, r 1 performs comparably with r 2 and r 3 in trials with a large but realistic number of clusters. When the variability of baseline event rate is large and there is no indirect effect, r 4 and r 5 tend to offer higher power than r 1 , r 2 , and r 3 . We discuss the implications of these findings to the planning and analysis of cluster randomized trials.

OBJECTIVE: To identify potential bias in non-inferiority design of published cancer trials, and to provide suggestions for future practice.
METHODS: We systematically searched MEDLINE, Embase and CENTRAL databases (until April 17, 2020) to obtain non-inferiority phase III cancer trials and protocols. Distribution of essential characteristics and study design parameters was compared between trials with and without concluding non-inferiority using multivariable logistic regression.
RESULTS: A total of 291 eligible trials were included. We observed that increased odds of concluding non-inferiority was significantly associated with more lenient non-inferiority margins (OR = 1•94, 95% CI 1•02-3•69) and higher hypothesized event rate (OR = 1•24, 95% CI 1•06-1•47). Trials that established non-inferiority adopted margins that were more dispersedly distributed (dispersion OR = 2•90, 95% CI 1•88-4.48).
CONCLUSIONS: Although limited by the exploratory nature, our study demonstrated existence of possible distorted non-inferiority design which could incur excess non-inferiority in cancer clinical trials. Pre-registration and transparent reporting of detailed non-inferiority design is imperative for future research.