Spss for windows version 17

The association of age (young and elderly) with clinicopathologic parameters was analyzed by the chi-squared (χ2) test. Continuous variables were analyzed using the Student's t-test. Survival curves were generated using Kaplan–Meier estimates; differences between the curves were analyzed by log-rank test. Multivariable Cox regression models were built for analysis of risk factors for survival outcomes. All statistical analyses were performed using the statistical software package SPSS for Windows, version 17 (SPSS Inc., Chicago, IL, USA). Results were considered statistically significant when a two-tailed test of a p value of less than 0.05 was achieved.

Data analysis was performed using SPSS for Windows, version 17 (SPSS, USA). Continuous variables were compared using Student’s t-tests. The criterion for statistical significance used was P < 0.05.

Age, sex, ethnicity, extension of primary tumor invasion, lymph nodes status, histological grade, survival time, and CSS were extracted from the SEER database. All cases were restaged according to the criteria described in the AJCC Cancer Staging Manual (7th edition, 2010). Within the SEER database, marital status of the patient is recorded at the time of diagnosis. Marital status is coded as married, divorced, widowed, separated, and never married. Individuals in the separated and divorced group were clustered together as the divorced/separated group in this study.
Patient baseline characteristics were compared with the χ² test, as appropriate. The rate of CRC death was compared between groups using the Kaplan–Meier method. Multivariable Cox regression models were built for analysis of risk factors for survival outcomes. The primary endpoint of this study was CSS, which was calculated from the date of diagnosis to the date of cancer specific death. Deaths attributed to CRC were treated as events and deaths from other causes were treated as censored observations. All of statistical analyses were performed using the statistical software package SPSS for Windows, version 17 (SPSS Inc, Chicago, IL, USA). Statistical significance was set at two-sided P < 0.05.

The χ2 test was adopted to analyze individuals’ basic characteristics appropriately. Cox proportional hazards models were used to calculate the overall survival of CRC patients with the hazard ratio (HR) and corresponding 95% confidence interval (95% CI). The confounding factors including gender, age, education (in quartiles), household income (in quartiles), and race/ethnicity were adjusted. Survival plots were generated using the Kaplan-Meier method. A 2-sided p value 0.05 was considered to be statistically significant. All analyses were performed using the statistical software package SPSS for Windows, version 17 (SPSS Inc., Chicago, IL, USA).

Categorical variables were summarized using frequency (%). A comparison of the categorical variables between LNs count subgroups was conducted using Pearson's χ2 test. Continuous variables were compared using the Mann-Whitney U test. Survival curves were generated using the Kaplan-Meier method; differences between the curves were analyzed by the log-rank test. Multivariable Cox proportional hazards regression models were used to assess potential risk factors for CSS. Cox stepwise regression analysis was also performed to determine predictive factors for gastric cancer prognosis, with a significance level of 0.05 for entering and 0.10 for removing the respective explanatory variables. Nomograms for possible prognostic factors associated with CSS and OS were established by R software, and the model performance for predicting outcome was evaluated by Harrell's concordance index (c-index), which is a measure of discrimination.
All statistical analyses were performed using the statistical software package SPSS for Windows, version 17 (SPSS Inc., Chicago, IL, USA). The results were considered statistically significant when a two-tailed test provided a P-value of less than 0.05.

The end point of the study was in-hospital mortality. Unless otherwise specified, data are presented as means, standard deviation, or percentages. Continuous variables were compared using the unpaired t-test and Wilcoxon rank-sum test, and categorical variables were compared using the chi-squared test. The univariable and multivariable logistic regression analysis were performed to determine the characteristics that were independently associated with in-hospital mortality. The effective sample size is too small the stepwise bootstrap-adjusted analysis including all variables was used to identify best-fitting variables for the final multivariable Cox- regression model [33 (link),34 (link),35 (link)]. Clinical, microbiological, and echocardiographic variables found to be significantly associated with mortality in a univariate analysis (p < 0.1) were included in the multivariable logistic regression analysis and bootstrap -adjusted analysis. The statistical analyses were performed using a statistical software program (SPSS for Windows, version 17; SPSS Inc., Chicago, IL, USA). Two-sided values of p < 0.05 were considered statistically significant. The study (104-6096B) was approved by the Institutional Review Committee on Human Research at Kaohsiung Chang Gung Memorial Hospital.