Spss software package

A linear-by-linear association test was performed to compare the status of stromal p16 expression between histological types and to determine whether stromal p16 expression was significantly different according to degree of malignancy. Statistical analyses were performed using the SPSS Software Package (version 18.0; IBM SPSS, Chicago, IL, USA). Statistical significance was set at P < 0.05.

Data were presented as mean ± SEM. We used the Student’s t-test to examine the difference in mean between the two groups. Non-abnormal distribution data were analyzed using a nonparametric test. The Kaplan–Meier method was used to compare the survival times of different CRG expression levels. Univariate Cox regression analysis was used to analyze the prognostic value of a single gene; for factors with a p-value < 0.05, we performed multivariate Cox regression to analyze the independent risk factors that affect GC patients. p-value <0.05 was considered to be statistically different. * represents p < 0.05 and ** represents p < 0.01. Statistical analysis was performed using the SPSS software package (version 24.0, IBM SPSS) and GraphPad Prism (version 8.0, GraphPad Software).

Fracture types were classified according to the Neer system. A postoperative assessment of reduction quality was made according to the method of Schnetzke—based on the three parameters head-shaft displacement (HSD), NSA and greater tuberosity (GT) cranialization (Table 1) [26 (link)]. Using the scoring of these parameters, cases were assigned as being with either (1) anatomical reduction if all parameters were anatomical, (2) acceptable reduction or (3) malreduction if any of the parameters were classed as malreduced. Outcomes in terms of functional scores and ROM were compared at each follow-up. Furthermore, the functional scores were investigated across categorical age groups below 60, 60–80 or over 80 years, and also with consideration of the age as a covariate.
Statistical analysis was performed using SPSS software package (v.27, IBM SPSS, NY, USA). Normality of data distribution was screened and proved with the Shapiro-Wilk test. One-Way Analysis of Variance (ANOVA), General Linear Model, Independent- and Paired-Samples t-tests, and Chi-Square tests were applied to detect significant differences in outcomes among treatment groups, Neer fracture types, age groups, at follow-ups, and considering the patient characteristics. Level of significance was set to 0.05 for all statistical tests.