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!