Abstract:

Objective To apply the competing risk model to the analysis of clinical trials for tumor treatment. Methods A multi-center, randomized, double-blind, prospective, placebo parallel control design, phase Ⅲ clinical trial was preformed to evaluate the clinical synergism of a medicine served as chemosensitizer for the treatment of non-small cell lung cancer and breast cancer. The competing risk model was used to estimate the rates of cumulative remission and cumulative progression in both groups and comparison was conducted between groups with Gray test. The sub-distribution hazard model was used to perform the multivariate analysis. Results For non-small cell lung cancer patients, the differences in rates of cumulative remission and cumulative progression in two groups after chemotherapy were statistically significant (P=0.000，P=0.001). Medications, age, and tumor size were factors influencing the remission after chemotherapy, while medications, sex, age, and tumor size were factors influencing the progression after chemotherapy. For breast cancer patients, the difference in cumulative remission rate in two groups after chemotherapy was statistically significant and the difference in cumulative progression rate in two groups after chemotherapy was not statistically significant. Medications and tumor size were factors influencing the remission after chemotherapy, while age and tumor size were factors influencing the progression after chemotherapy. Conclusion Cumulative incidence function and sub-distribution hazard model should be used if the competing risk exists because the results are more in line with the actual situation.

Key words: competing risk, Gray test, cumulative incidence function； proportional sub-distribution hazard model