Spss statistical software for windows version 24

SPSS statistical software for Windows, version 24 (SPSS Inc., Chicago, IL, USA) was used to analyse the data.
Following the user manual for the A-NPC-SF, responses to each skill area were recalculated to a score between 1 and 100, with 100 being the highest skill and 1 being the lowest. The same is true for the A-NPSES scale; responses to each area of self-efficacy were recalculated on a score ranging from 1 to 100, where 100 represents the highest self-efficacy, and 1 is the lowest.
Descriptive statistics were calculated, including means and standard deviations (SD), frequency, and percentages. Inferential statistics via one-way analysis of variance (ANOVA) were used to analyse the between-group means. Pearson’s correlation coefficient was calculated for the relationships between the A-NPC-SF factor scores to assess whether the tested sample exhibited the appropriate job skills based on their process. Pearson’s correlation was used to correlate continuous data.
A p-value less than 0.05 was considered statistically significant. Internal consistency of each skill area and full scale were calculated using Cronbach’s alpha. The missing values were replaced with the obtained mean of the missing elements. Cases with missing values for more than 50% of the responses were excluded from the study. The analyses were conducted independently by three authors.

All values are expressed as the mean ± SD, number, or percentage, as appropriate. Differences in continuous variables between two groups were analyzed by t test or chi-square test, when it is appropriate. Continuous variables at different time points in each group were compared using Friedman test followed by Wilcoxon's signed-rank test with multiple comparison procedure. Statistical analysis was performed using SPSS statistical software for Windows Version 24 (SPSS for Windows, Version 24; SPSS, IL, U.S.A.). A value of p < 0.05 was considered statistically significant.

SPSS statistical software for Windows, version 24.0 (IBM Corp., Armonk, NY, USA) was used for all statistical analyses. Normality tests were performed via the Shapiro–Wilcoxon test in SPSS. We conducted independent Student’s t-tests to compare two variables and repeated-measures ANOVA for comparing three variables. The p-values of the multiple tests were adjusted with the Bonferroni method. A comparative analysis of qualitative variables was performed using the chi-squared test. The long-term reproducibility was determined using the intraclass correlation coefficient (ICC), coefficient of variation (CV), and test–retest standard deviation (TRTSD). The TRTSD was calculated as follows: axial lengths were measured three times over 2 years and averaged, and the standard deviation of the mean value of each measured value was defined as the TRTSD. The ICC was calculated by dividing the within-subject variance by the total variance, and the CV was calculated by dividing the TRTSD by the mean of the total measured values, then multiplying by 100. A value of p < 0.05 was considered statistically significant.
For correlation analysis, keratometry, axial length, and anterior chamber depth (ACD) were measured using partial interferometry, and lens thickness was measured using ultrasound.

All data are expressed as the means ± the standard deviation (SD). Statistical analyses were performed using SPSS statistical software for Windows (version 24.0; SPSS Inc.). For significances in glycan data, the HILIC-UPLC data were logit transformed and then used MANOVA and Tukey test. For Western blot densitometry, proliferation and migration assays, parametric T test was used. For RT-qPCR, a 2-way ANOVA was used with a post-hoc T test. p values were adjusted for multiple testing using the Benjamini–Hochberg method. The criterion for significance was set at *p value ≤ 0.05 or **p value ≤ 0.005.

Data were analyzed with Statistical Product and Service Solutions (SPSS) statistical software for Windows, version 24.0 (SPSS Inc., Chicago, IL, United States) and GraphPad Prism (version 7.0; GraphPad Software, La Jolla, CA). One-sample Kolmogorov–Smirnov testing was used to detect whether variables were normally distributed. Continuous variables with skewed distribution were presented as median (25%–75% interquartile range); categorical variables were presented as frequencies or percentages. Categorical variables were compared with Pearson’s chi-squared (χ²) test or Fisher’s exact test. Continuous variables were compared with Mann–Whitney U-test. The correlation between two parameters was analyzed by Spearman’s rank coefficient of correlation. Cumulative probabilities of remission were assessed according to the Kaplan–Meier survival analysis method and the log-rank (Mantel–Cox) test. Univariable and multivariable Cox regression analyses were used to screen for risk factors affecting prognosis. Based on univariate Cox regression analysis and clinical judgements, variables at baseline that might influence the remission with p < 0.05 in the univariable analyses were selected into the multivariable Cox regression analysis. Statistical significance was defined as a two-sided p < 0.05.

The time of CAR-T cell transfusion was used as the origin in all the time-to-event analyses. Analysis of CIR used relapse as the event. For analysis of EFS, no response, relapse or death, whichever occurred first, was regarded as the event. In survival analyses, death was the event. Subjects without an event were censored at the date they were last known to be alive. Two subjects receiving a second allotransplant were censored at the time of second transplant. The primary study endpoints were safety and efficacy. Secondary endpoints were covariates associated with safety and efficacy. Data were analyzed as of September 30, 2019 with a median follow-up of survivors of 17 months (range, 6–47 months).
The chi-square statistic or Fisher exact test was used for comparisons between categorical variables, and the Mann–Whitney U test was used for continuous variables. The Kaplan–Meier method was used to calculate the probability of EFS and survival. P values were two-sided, and P < 0.05 was considered significant. SPSS statistical software for Windows, version 24.0 (SPSS, Chicago, IL, USA) was used for statistical analyses.