Statistics and reproducibility
tumor, Tumor
REGRESSION, MAY, TUMOR, TUMOR
This is an open-label, phase 1b, dose-escalation and dose-expansion study. No randomization or blinding was involved. Sample size was determined using the normal approximation method. Assuming that the expected ORR is 40%, when the sample size reach 120 in the efficacy population, the probability of observed ORR > 35% by normal approximation method is above 85% (86.8%). No data was excluded from the analyses. Safety and pharmacokinetics were evaluated in patients from all cohorts who received at least one dose of JMT101 plus afatinib or osimertinib during the dose-escalation stage and dose-expansion stage. The efficacy population included patients from the expanding cohort, either enrolled during the escalation stage or expansion stage, who had at least one dose of study treatment by the date of data cutoff (31 May, 2022). Target enrollment at the dose-expansion stage was 12–200 patients to allow preliminary estimation of antitumor activity. Categorical outcomes (eg, ORR, DCR) were presented as percentages and two-sided 95% confidence interval using the Clopper–Pearson method. Time-to-event outcomes (eg, PFS, OS) were estimated using the Kaplan–Meier method. Difference between categorical outcomes were tested using the Chi-square or Fisher’s exact test. Survival curves were compared using the non-parametric log-rank test. Univariate and multivariate Cox regression analyses were performed to identify clinical and genetic factors associated with PFS. Subgroup analyses of efficacy by clinicopathological features and prior treatments were non-prespecified and exploratory. Tumor mutation load was calculated as the number of mutations detected in each sample. The distribution of tumor mutation load in different subsets of patients was presented as mean and standard error of mean. Mann-Whitney U test was used to compare the difference in distribution of tumor mutation load. Mutations that were newly detected or increased in VAF by 1.5 times at progression and defined as pathogenic mutations by OncoKB and COSMIC database were identified as potential resistance mediators that may drive acquired treatment resistance