Neoadjuvant Ipilimumab Nivolumab Cutaneous Squamous Cell Carcinoma Trial
Okay, here’s a breakdown of the statistical analysis methods used in the study, based on the provided text. I’ll categorize it for clarity:
1. Sample Size & Power:
* The study aimed for 20 patients per treatment arm.
* This sample size was calculated to achieve:
* 94% probability of observing 8 or more patients with a pathological complete response (PCR) in each arm.
* 89% probability of observing 4 or more patients with a non-pathological response (NPR) in each arm.
* The calculations were based on data from Gross et al. (ref. 30).
* Crucial Note: The study was not designed or powered to directly compare the efficacy of the two treatment arms.
2. Comparing Treatment Responses (Categorical & Continuous):
* Categorical Variables: Two-sided Fisher’s exact test.
* Continuous Variables:
* Linear-to-linear test (for comparing treatment responses)
* Mann-whitney *U*-test (for independent groups)
* Wilcoxon’s rank-sum test (for continuous variables across ICB response categories)
* wilcoxon’s signed-rank test (for paired comparisons within the same patient)
3. Survival Analysis:
* Kaplan-Meier curves were used to estimate survival probabilities.
* Two-sided log-rank tests were used to compare survival curves between groups.
* Analyses were performed in RStudio (R, v.4.3.2) using the ‘ggplot2’ package (v.3.4.2) for plotting.
4. whole Exome Sequencing (WES) Analysis:
* Performed in RStudio (R, v.4.0.5).
* Packages used:
* tidyverse (v.1.3.0) and broom (v.1.0.5) for data handling.
* Maftools (v.2.6.05) (ref. 69) for analyzing somatic mutations.
* ggplot2 (v.3.4.2) for plotting.
5. Bulk RNA-seq Analysis:
* Count data were normalized using the DESeq2 R package (v.1.30.1).
6. Data Cutoff:
* The data cutoff date for the analyses was September 30, 2024.
Let me no if you’d like me to elaborate on any specific aspect of these methods!