Jmp version 16

Overall survival was defined as the time from the initial treatment date to the date of death. Overall survival was estimated using Kaplan‐Meier curves, and the log‐rank test was used to compare differences in OS. Wald Chi‐Square tests were used for multivariate analyses for OS and DDT (paclitaxel vs. docetaxel, tumour size, intensity modulated radiation therapy vs. stereotactic radiotherapy, dose of radiotherapy, metastasis, age, sex, and AEs). Each median was used for the cut off of tumour size, dose of radiotherapy and age. The 95% confidence interval (95% CI) for response was based on the binominal distribution. All statistical analyses were performed using JMP version 16.1 software (SAS Institute). The level of significance was set at p < 0.05.

Pearson’s correlation coefficient was used to investigate the correlation between the therapeutic effect and PAI-1 expression levels. Receiver operating characteristic (ROC) curves were used to calculate cut-off values for serum levels of PAI-1 and areas under the curve (AUCs). Cut-offs were determined using Youden’s index (sensitivity + specificity -1) to determine the maximum index value. ROC curves were established to evaluate serum levels of PAI-1 in patients administered nivolumab. For a single comparison between two groups, the Mann-Whitney U-test was used. All statistical analyses were performed using JMP version 16.1 software (SAS Institute, Tokyo, Japan). The level of significance was set at p<0.05.

The primary endpoint of OS and the secondary endpoints of DFS, response rate, pathologic response, R0 resection rate, surgical morbidity, and acute and late toxicity were evaluated 6 months after the completion of enrollment. The final dataset was carefully reviewed for clerical errors by three physicians (T.M., K.N., and T.A.). Data for continuous variables were expressed as median and range. Fisher's exact test and the Mann–Whitney U test were used for categorical and continuous data, respectively. Kaplan–Meier curves were created to estimate OS, and comparisons between groups were estimated using log‐rank tests. Multivariate Cox proportional hazards regression analysis was used to identify prognostic factors independently associated with survival. p < 0.05 was considered significant. In the regression analysis model for OS, multivariate analysis was performed using diameter, CEA, and CA19‐9, which have been reported as factors associated with OS. For DFS, multivariate analysis was performed using the forward selection method, and variables with p values less than 0.1 in univariate analysis were entered in addition to previously reported factors. All statistical analyses were performed on an intention‐to‐treat basis using JMP version 16.0 software (SAS Institute).

The primary endpoint of OS and the secondary endpoints of DFS, response rate, pathologic response, R0 resection rate, surgical morbidity, and acute and late toxicity were evaluated 6 months after the completion of enrollment. The final dataset was carefully reviewed for clerical errors by three physicians (T.M., K.N., and T.A.). Data for continuous variables were expressed as median and range. Fisher's exact test and the Mann–Whitney U test were used for categorical and continuous data, respectively. Kaplan–Meier curves were created to estimate OS, and comparisons between groups were estimated using log‐rank tests. Multivariate Cox proportional hazards regression analysis was used to identify prognostic factors independently associated with survival. p < 0.05 was considered significant. In the regression analysis model for OS, multivariate analysis was performed using diameter, CEA, and CA19‐9, which have been reported as factors associated with OS. For DFS, multivariate analysis was performed using the forward selection method, and variables with p values less than 0.1 in univariate analysis were entered in addition to previously reported factors. All statistical analyses were performed on an intention‐to‐treat basis using JMP version 16.0 software (SAS Institute).

Data are expressed as mean ± standard deviation (SD) for continuous variables and as frequencies and percentages for discrete variables. The statistical significance of intergroup differences was assessed using the χ² test, unpaired t-test, and Mann–Whitney U test where appropriate. First, variables with P < 0.10 in the univariate analysis were adjusted for age (model 1). Next, to determine the indicators for driving cessation, multivariable logistic regression models were performed using variables with P < 0.10 in the univariate analysis (model 2). In all analyses, a P value <0.05 was considered significant. All analyses were performed using JMP, Version 16.0 (SAS Institute, Inc., Cary, NC, USA).

Numerical data were presented as the mean ± SD, while categorical data were expressed as numbers and proportions (%). The baseline age, body mass index, BMD, and bone parameters were compared using analysis of variance or χ² test between participants with or without incident vertebral fracture. In the longitudinal analysis, the Cox proportional hazards model was used to estimate the HRs and 95% CIs of vertebral fracture incidence, with adjustments for candidate risk factors. Candidate factors were selected from those that were significantly different (p < 0.05) between patients with or without incident fractures and were finally extracted using the stepwise method. The Kaplan–Meier curves were plotted to illustrate the survival curve of the incidence of fractures during the observation period, and a log-rank test was used to assess the statistical significance of the differences between patients with and without baseline spinal OA. The relationship between KL grade and the time of incident fracture was evaluated by median survival time. To determine the fracture thresholds of baseline L-BMD in patients with or without spinal OA, a receiver operating characteristic (ROC) analysis was conducted. All comparisons were two-sided, and p values < 0.05 were considered statistically significant. Data were analyzed using JMP version 16.0 (SAS Institute, Cary, NC, USA).

Contingency table analysis was used to compare relative abundance of individual species between outbreak and post-outbreak periods and among the three sampling sectors. Data were transformed by adding 1 to the total number of each species count at each river section to avoid zero values.
To test for differences in black fly abundance across seasons, the mean number of black flies sampled per day was calculated for each transect. A log₁₀ + 1 transformation was used to render these values normally distributed. A one-way ANOVA was run for each season (spring, summer or fall), and the Tukey-Kramer Honest Significant Difference (HSD) test was used to identify statistically significant pairwise differences. A two-factor (month and year) ANOVA was used to compare environmental variables among years. A generalized linear model (GLM) with normal distribution and maximum likelihood estimation was used to test associations in the absolute abundance of individual species per trap with environmental variables or total black fly abundance. All analyses were run in JMP version 16.0 (SAS Institute Inc., Cary, NC, USA). Shannon Diversity Index was calculated using the "vegan" package in R [34 ], and Shannon Equitability Index (H) was calculated by dividing Shannon Diversity Index (H) values by the natural log of number of unique species.