Spss version 26.0 statistical software

OS was defined as the time interval from the first NIVO+IPI treatment to the date of death from any cause, with censoring at the last follow‐up. PFS was defined as the time from the first induction of immunotherapy to disease progression or date of death (whichever occurred first), with censoring at the time of the last follow‐up. The database record was closed upon patient death or at the final follow‐up. Data were expressed as the median and interquartile range (IQR), and statistical significance was set at p < 0.05. The frequencies of categorical variables were compared using the Pearson chi‐square or Fisher's exact test, whichever was appropriate, and the odds ratio (OR) was estimated in proportions. Survival curves were generated using the Kaplan–Meier method and compared using Cox proportional hazard regression analysis. The Cox hazard analysis was also applied to investigate hazard ratio (HR) and 95% confidence interval (CI) in univariate and multivariable analyses. Clinical factors were included in the multivariable analysis if their univariate p‐value was <0.1. All data were analyzed using the SPSS version 26.0 statistical software (SPSS Japan Inc.).

CSS was defined as the time between the initiation of VEGFR‐TKI treatment and  death because of progressive disease (PD). OS was defined as the time from VEGFR‐TKI start to death from any cause. The database record was closed upon patient death or the final follow‐up. Data were expressed as the median and interquartile range (IQR), and a p‐value less than 0.05 hac to be considered significant statistically. The chi‐square test was used to estimate the odds ratio (OR) in proportions on categorical factors. The survival curves were visualized by the Kaplan–Meier method to compare CSS and OS. The Cox proportional hazard regression analysis was applied for the investigation of hazard ratio (HR) and 95% confidence interval (CI). Multivariable analyses were performed by a logistic regression analysis. Clinical variables were included in the multivariable analysis if their univariate P‐value was less than 0.05. All data were analyzed by using SPSS version 26.0 statistical software (SPSS Japan Inc., Tokyo, Japan).

SPSS Version 26.0 statistical software (SPSS Inc., Chicago, Illinois) was used for data analysis. Results were expressed as mean value ± standard deviation. Two-factor ANOVA was used for comparisons between the four groups (sex and the status of normal triglyceridemia or hypertriglyceridemia). When there was a significant F value, a post hoc test was then performed with the Newman–Keuls method to identify significant differences among mean values. Univariate correlations were analyzed by Pearson's coefficient (r). P < 0.05 was considered as statistically significant.

Data of numerical variables were summarised by their mean (95% confidence interval, 95% CI). The reliability of the measurement of tooth size error was calculated by determining the intraclass correlation coefficient (ICC, two-way random model). Cohen’s kappa determined the reliability of success and failure of tooth segmentation with nominal variables. Differences in variables across groups were compared with Friedman’s test or Cochran’s Q test as appropriate. We used the Shapiro–Wilk test to verify whether the data followed a normal distribution. Independent variables affecting the response (tooth size error) were simultaneously evaluated by a GLMM. GLMM jointly considered the main and the first-order interaction effects. Bonferroni’s test was used for post hoc multiple comparisons. All statistical analyses were performed using SPSS version 26.0 statistical software, and p values of less than 0.05 were considered as indicating statistical significance.

All statistical analyses were performed with SPSS version 26.0 statistical software (SPSS, Inc., Chicago, IL, USA). The data conforming to a normal distribution are expressed as the mean ± standard deviation and not conforming as the median ± interquartile range. Clinical outcome assessments and radiological assessments were performed using repeated analysis of variance (ANOVA). The Pfirrmann grading of intervertebral discs was analyzed by the chi-square test. Values of P < 0.05 were considered statistically significant.

Statistical analyses were performed using SPSS version 26.0 statistical software (SPSS Inc., Chicago, IL, USA). Quantitative variables are expressed as median (centile 25; centile 75). Categorical variables were expressed as numbers (%). Mann–Whitney U test, Kruskal-Wallis Test and Dunn’s test were used to compare the quantitative variables. The chi-square test was used to compare the categorical variables. The Spearman’s rank correlation test was used to analyze the relationship between GPX4 promoter methylation level and quantitative clinical data as well as GPX4 mRNA expression level, STING mRNA expression level, serum GPX4, IFN-β, ROS, SOD, MDA, TNF-α, IL-1β and IL-6 levels. The gender and all other statistical analyses were dichotomous variables. All statistical analyses were 2-sided, and P value < 0.05 was considered statistically significant.

All data were analyzed with SPSS version 26.0 statistical software (Chicago, Illinois, USA). Descriptive statistics were used to assess study characteristics and proportions of delivery and pregnancy outcome data in the different smoking groups. Categorical variables were expressed as frequency distributions and cross-tabulations and were compared using the chi-squared test or Fisher’s exact test. Continuous data were expressed as mean and standard deviation and compared using ANOVA. Binary logistic regression was used to examine the association between fetal growth <10th percentile or <5th percentile and smoking status. Covariates with p<0.005 were included in an adjusted regression model. The final model was obtained using a stepwise inverse procedure. Results are presented as rates with associated p values, or odds ratios with 95% confidence intervals. A significance level of p<0.05 was considered. Birth weight took into account gestational age, sex, birth rank of the child, and maternal body mass index.