Spss statistics ver 19

The significance of differences in demographic characteristics and composition of trunk muscles among age groups was tested by one-way analysis of variance, with post hoc testing performed with the Bonferroni method for continuous variables and with chi-square tests for categorical data. The Jonckheere-Terpstra trend test was used to identify trends in the relationship among age, trunk muscle area, and density. The analysis of covariance adjusted for age was performed to examine the trunk muscle area and density among patients who survived more than 3 months versus those who survived less than 3 months.
Survival was estimated with the Kaplan-Meier method, and survival estimates were compared with the log-rank test. Data were censored on September 30, 2019. Patients who were lost to follow-up were censored at the date of last contact/follow-up. Patients who were alive on September 30, 2019 were censored for overall survival analysis. Overall survival was calculated from the date of diagnosis of spinal metastasis to the date of death. IBM SPSS Statistics ver. 19.0 (IBM Corp., Armonk, NY, USA) was used for all statistical analyses; p<0.05 was considered statistically significant.

All statistical analyses were performed using SPSS software (IBM SPSS Statistics ver. 19.0; IBM, Inc., Amonk, NY, USA). We compared the frequencies of pleural plaque and lung fibrosis in the different demographic characteristics using chi-square test. Linear-by-linear association was used to test whether there was a linear association in advanced age and duration of exposure with the prevalence of pleural plaque and lung fibrosis. In all statistical analyses, values of P<0.05 were considered statistically significant.

Values are expressed as mean±standard devaiton or estimated mean±standard error. All SDS values are expressed relative to CA. Comparisons of the results were assessed by using the Student t-test or Mann-Whitney test, according to data distribution. The chi-square test was also used. For longitudinal comparisons, repeated-measures analysis of variance was performed. Analysis of covariance was used to determine the covariate-adjusted differences across the weight groups. Stepwise multiple linear regression analyses were performed to evaluate the factors that affect change in BMI-SDS during the GnRHa treatment. Statistical analyses were performed by using IBM SPSS Statistics ver. 19.0 (IBM Co., Armonk, NY, USA), and a P-value of <0.05 was considered statistically significant.