Secondary analyses: cohort selection and model choice
NSCLC cancer
REGRESSION
We assessed the robustness of these findings to cohort selection and choice of predictive model. First, we included all patients diagnosed with NSCLC cancer at any point in the active screening intervention period, as well as the extended follow-up of the trial. This is referred to as the Extended Cohort. Our primary analysis, restricted to subjects diagnosed within 4 years of randomization, is referred to as the 4-Year Cohort.Supplementary Table Permutation variable importance in random survival forests models.Detection is the second most important variable, after Stage, in the 4-Year Cohort. In the Extended Cohort, Detection is more important than both Sex and Smoked. These results show that method of detection has independent prognostic value in models other than CoxPH.Next we considered robustness with respect to choice of the predictive model. While the CoxPH model is the most used regression model for right censored data, it assumes proportional hazards across time for different values of the covariates and that covariates have a linear effect on the log hazard functionTo check whether our conclusions hold for other statistical models, we fit Random Survival Forests (RSF) to the 4-Year Cohort and the Extended Cohort, using the same variables as in the CoxPH model in Table 