R software version 3

Continuous variables were compared using an independent-sample, unpaired two-tailed t test or Mann−Whitney H test, as appropriate. Differences in categorical variables were compared using the chi-square or Fisher’s exact test. A logistic regression model was used to estimate the odds ratio (OR) and 95% CI and identify the independent predictors of LN metastasis. Survival curves were generated by using Kaplan–Meier survival analysis, and the differences in survival distributions were tested using the log-rank test. The Cox proportional hazard model was used to determine the hazard ratio (HR) of preoperative variables for OS and DFS. All statistical analyses were conducted using the R software (version 3.4.2) and SPSS (version 19.0), and a two-sided P-value  < 0.05 was considered as statistically significant.

The detailed methods for the assessment of disease DALYs have been described previously^{9 (link),10 (link)}. Differences in DALYs number (men minus women) and ASDR (men to women’s ASDR ratio) were used to compare the relative levels of IS DALYS between sexes. We used percentage changes and estimated annual percentage change (EAPC) to assess the trends in DALYs number and ASDR. It is assumed that the natural logarithm of ASDR follows a regression line. Thus, Y = α + βX + ε, where Y denotes ln (ASDR), X means a calendar year, and ε refers to the error term. Herein, β determines the positive or negative trends of ASDR. Then, EAPC = 100*(exp(β)− 1). Its 95% confidence intervals are also obtained from the linear model. When the EAPC value and its upper boundary of the confidence interval are positive, the trend in ASDR is increasing. Instead, when the EAPC value and its lower boundary of the confidence interval are negative, the trend in ASDR is decreasing. Pearson correlation and linear regression analyses were conducted to identify the correlations between ASDR ratio and SDI. R software version 3.5.2 (https://cran.r-project.org/doc/FAQ/R-FAQ.html#Citing-R) and SPSS software version 21.0 (https://www.ibm.com/products/spss-statistics) were used for charting and analysis. A two-tailed P value less than 0.05 was considered statistically significant.

The QoLR package was used to calculate the HRQoL scores and determine the TTD events in EORTC QLQ-C30 and EORTC QLQ-LC13. Median and interquartile range were used to describe the HRQoL scores and TTD. And chi-squared test was performed to assess the differences in sociodemographic, clinical characteristics, and incidence rate of TTD events between patients with different levels of physical activity. Baseline HRQoL scores of three physical activity levels were compared using the Kruskal-Wallis test. Survival analysis was performed using the univariate and multiple Cox regression analysis after controlling for confounding factors; the results are shown as hazard ratios (HRs) with 95% confidence intervals (CIs). All statistical analyses were performed using R software (version 3.5.2) and Statistical Product and Service Solutions version 20.0 (SPSS 20.0).

Statistical significance of differences among variables with normal distribution was estimated by Student's t-test, while non-normal distribution variables were analyzed by Mann-Whitney U test. Qualitative variables were analyzed by Pearson χ2 test or Fisher’s exact test. Correlation was calculated using Pearson’s and distance correlation analysis. Survival probability was calculated by Kaplan–Meier method, and Log-rank test was used to test the significance of differences in survival curves. Multivariate analysis adopted Cox proportional hazards regression model, and methods of variable filtering were likelihood ratio test of maximum partial likelihood estimation (both forward: LR and backward: LR). Accuracy of survival prediction was evaluated by receiver operating characteristic curve (ROC) analysis and Harrell's concordance index (C-index) analysis. All statistical analyses were performed using R software (version 3.6.2) and SPSS software (version 26.0). Tow-tailed P < 0.05 was considered statistically significant.

Nominal variables were analyzed using a two-tailed Fisher's exact test or chi-square test followed by post hoc two-tailed Fisher's exact tests when applicable. Ordinal and continuous variables were analyzed with the Mann–Whitney U test. P-values with corresponding odds ratios (OR) were presented in the tables. P < 0.05 was considered statistically significant. Tests were performed using R software version 3.6.2 and SPSS software (v24.0).