Jamovi v 2

The Statistical Package for Social Sciences Version 25.0 for Windows was used for most calculations. CFA and multigroup CFA were conducted via AMOS (version 24, IBM, Chicago, IL, United States), and McDonald’s ω was calculated via jamovi V.2.2.5. Descriptive statistics [i.e., frequencies and percentages (%), and means ± standard deviations (SD)] were determined to characterize the demographic data of the sample. A value of p of < 0.05 was deemed statistically significant.

Results are presented as the mean ± standard deviation (SD). Normality in the data distribution was evaluated by the Kolmogorov–Smirnov test. Differences in continuous variables pre- and post-treatment were assessed by a parametric paired samples Student’s t-test or a non-parametric paired samples Wilcoxon signed-rank test, as appropriate. Differences in categorical variables were assessed by the Fisher’s exact test or paired samples McNemar’s test, as appropriate. Effect sizes (ES) for significant differences in the values were calculated using Cramer’s V, Cohen’s d, or rank-biserial correlation, as appropriate. Multiple linear regression analysis performed using the enter method was conducted to examine whether changes in predictor variables were associated with changes in PS scores. Statistical significance was set at p < 0.05, and all tests were two-tailed. Data were analyzed using SPSS v.21.0 and Jamovi v.2.2.5.

The data were analysed with the open-source statistical software Jamovi v. 2.2.5 (The jamovi project (2021) [Computer Software]. Retrieved from https://www.jamovi.org (accessed on 21 March 2022), sourced from Bergamo, Italy). Qualitative variables are described as frequencies and percentages. Interobserver agreement rates between Reader 1 and Reader 2 on a DIE location-based level were measured through Cohen’s kappa coefficient. According to Fleiss’s equally arbitrary guidelines, a k-value of less than 0.40 was considered a poor agreement; a k-value ranging from 0.40 to 0.75 was a fair to good agreement, and greater than 0.75 was an excellent agreement. Cohen’s kappa scores were also calculated to measure interobserver agreement between Reader 1 and Reader 3 on locations considered positive for DIE on T2*W imaging. Fisher’s exact test was used to evaluate the prevalence of signal voids assessed by Readers 1 and 3 on these sequences. A p-value < 0.05 was considered significant.

Data were analyzed using SPSS V.25.0, AMOS V.23.0, and jamovi V.2.2.5. Enumeration data was described by frequency and percentage (%), and the measurement data was described by mean and standard deviation (SD). P values < 0.05 were considered statistically significant.

Due to the absence of data on CPET performance and early metabolic syndrome biomarkers in the study population, we set the sample size for this study at n = 14 patients compared to the same number of healthy controls. This number intercepts different expected proportions, with a confidence level of 95% and a margin of error ranging from a minimum of 5.21% (for an expected proportion of 1%) to a maximum of 26.19% (for an expected proportion of 50%). Also, it manages to identify differences in mean values between patients and controls in terms of effect size equal to 0.98, with a power of 80% at a significance level of 5% (calculated with the G*Power 3.1 software. 9.7.).
A descriptive analysis of all the parameters collected was performed. Quantitative variables are reported as means and standard deviations (SD). Qualitative variables are presented as frequencies and absolute percentages (%). Student’s t test was used for the comparison of continuous variable and the Chi squared test was used for the comparison of categorical variables. The Pearson correlation coefficient (r) was used to study the relationship between biomarkers, CPET results, and previous cancer treatment. A p-value < 0.05 was considered statistically significant.
All statistical analyses were performed with Jamovi V.2.2.5 software.

Descriptive statistics were reported as percentages for categorical data, mean ± standard deviation (SD) for normally distributed continuous data, and median (IQR) for non-normally distributed data. The paired comparisons between the case and control groups were done with Independent samples t-test for normally distributed variables and Mann-Whitney U-test for non-normally distributed variables. Additionally, Chi-square test was used to test for significant associations between patients and controls regarding different categorical and ordinal variables. Statistical data processing was performed using the IBM SPSS v.23 statistical package and Jamovi v.22.5. P-value ≤ 0.05 was considered statistically significant.