Descriptive statistical analysis (chi-square test) was adopted to calculate the frequencies and proportion of patients presenting with localized/regional or distant metastatic TNBC according to the incorporated variables above. Univariate logistic regression analysis was used to preliminarily screen variables as potential risk factors related to distant metastasis. Subsequently, multivariate logistic regression analysis was utilized to adjust the confounding factors and verify the risk factors determined in the univariate analysis. For each variable, crude odds ratio (OR) and adjusted OR with 95% confidence interval (CI) were recorded in logistic regression analysis. The differences of breast cancer-specific survival (BCSS) and OS among each distant metastasis were analyzed by Kaplan–Meier plots with log-rank tests. All the statistical analysis were performed using SPSS statistical software, version 23.0 (SPSS, Chicago, IL, U.S.A.). A two-tailed P<0.05 was considered statistically significant.
Spss statistical software version 23
Manufactured by IBM
Sourced in United States
SPSS Statistical Software version 23.0 is a comprehensive analytical tool for data management, analysis, and reporting. It provides a wide range of statistical techniques for exploring, modeling, and understanding data. The software is designed to handle various data formats and offer a user-friendly interface for performing complex statistical analyses.
Automatically generated - may contain errors
Lab products found in correlation
Stata version 13, by StataCorp (2 mentions)
Prism analysis and graphic software version 8, by GraphPad (2 mentions)
Prism 5, by GraphPad (2 mentions)
R version 4, by R Project for Statistical Computing (2 mentions)
Prism 7, by GraphPad (2 mentions)
Prism v8, by GraphPad (1 mentions)
Version 11, by MedCalc (1 mentions)
Prism 6, by GraphPad (1 mentions)
Prism 8, by GraphPad (1 mentions)
R statistical software version 3.2.0 for windows, by R Project for Statistical Computing (1 mentions)
Sas version 9, by SAS Institute (1 mentions)
Spss modeler version 18, by IBM (1 mentions)
Epi info version 7, by IBM (1 mentions)
Version 16, by MedCalc (1 mentions)
Jmp version 11, by SAS Institute (1 mentions)
217 protocols using spss statistical software version 23
1
Factors Influencing Metastatic TNBC Prognosis
2
Comprehensive Metabolic and Lifestyle Analysis
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The mean and standard error for each of the following variables will be determined for each study group. The change from baseline to end of study will be compared between groups using repeated measures ANOVA and using nonparametric tests if necessary, for the following variables: body weight, waist circumference, BMI, blood pressure, serum levels of 25(OH)D, blood glucose, HbA1c, insulin, IGF-1, lipids, CRP, estradiol, testosterone, SHBG, specific microRNAs, dietary glycemic index, number of steps per day and quality of life. We will also test treatment differences in medication use and medication side effects. Chi-square test will be used to compare categorical variables and Student t-test or Wilcoxon test for continuous variables. The association between each variable and prognosis will be analyzed using Cox proportional hazard model and logistic regression. Finally, we will assess whether these secondary analyses are different at year 1 compared to end of study. All statistical analyses will be conducted with SPSS statistical software version 23.0 (SPSS Inc., Chicago IL, USA).
3
Comparative Analysis of GEO Data
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Data from the GEO database were analyzed using the non-parametric Wilcoxon rank-sum test. All measurements are shown as the mean ± standard deviation. A student’s t-test was used for two-sample analysis. A one-way ANOVA was used for multiple-sample analysis. All analyses were performed using SPSS statistical software version 23.0 (SPSS, Inc. Chicago, IL).
4
Comparative Analysis of Treatment Outcomes
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The distribution of patients' baseline characteristics was described. Difference of ORR and DCR between groups were compared using Fisher's exact tests and chi-square tests. Survival analysis was performed using the Kaplan–Meier method, and compared by the log rank test. Two-sided p < 0.05 was indicated statistically significant. All statistical analysis was carried out using the SPSS statistical software, version 23.0 (SPSS, Inc., Chicago, IL, USA).
5
Statistical Analysis of Experimental Data
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Data are expressed as means ± standard error of the mean (SEM). Differences of p < 0.05 between the groups were considered significant. SPSS statistical software version 23.0 was used for the statistical analysis (SPSS, Chicago, IL, USA).
6
Foot Ulcer Recurrence Risk Factors
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Data analyses were performed using the SPSS statistical software, version 23.0 (SPSS Inc., Chicago, IL, USA). For normally distributed variables, data were described as mean ± SD. One‐way ANOVA was used for multi‐group comparison and then LSD‐t test was applied for pairwise comparison. Bonferroni adjustment of α level was used to control for pairwise comparisons. For non‐normally distributed variables, data were described as median (quartiles). Kruskal‐Wallis H test was used for multi‐group comparison, and then the Mann‐Whitney U test was applied for pairwise comparison. Counting data were expressed as cases (percentage) and analysed by χ2 test. To identify the risk factors for foot ulcer recurrence, the univariate Cox regression analysis was initially used and then the factors with P < .1 in the univariate analysis were enrolled into the multivariate Cox regression analysis. Survival analysis was analysed by the Kaplan‐Meier method and the log‐rank statistic was used to compare the risk of foot ulcer recurrence between groups. Receiver operating characteristic (ROC) curve was used to determine the prognostic value of different factors in ulcer recurrence assessment and was plotted based on the logistic regression model. P‐values <.05 were considered statistically significant.
7
Multivariate Analysis of Surgical Outcomes
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Statistical analysis was performed with SPSS statistical software, version 23.0 (SPSS, Chicago, IL, USA). Factors influencing the primary and secondary endpoints of this study were first tested in univariate analysis. Continuous variables were tested with the Student’s t-test for normally distributed data and with the Mann–Whitney U test for non-normally distributed data. A chi-square test was used for dichotomised variables, and for samples with a size smaller than 5, Fisher’s exact test was used. Finally, a multivariate logistic regression analysis was performed for the primary endpoint to identify independent predictors upon identification in the univariate analysis and was corrected for the surgical approach. A p-value of <0.05 was considered statistically significant.
8
Comparative Analysis of Eyelid Ptosis Treatment
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The statistical analysis used T-test (SPSS statistical software version 23.0) for comparing the difference in age, time of onset, and follow-up time between the two treatment groups, Wilcoxon’s Sign Rank Test was used to compare the changes in the degree of upper eyelid ptosis and ophthalmoplegia, and Chi-square test for comparing the therapeutic effects on ptosis and ophthalmoplegia before and after treatment in the two groups.
9
International Survey on Hospital Characteristics
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Numbers, percentages, median and interquartile range (IQR) were used for descriptive statistics. Countries were categorised into EU and non-EU in compliance with a reference classification system [8 ]. We regrouped the transcontinental Eurasian countries, e.g. Turkey, as belonging to the Southern EU Area rather than Western Asia to be consistent with other publications [9 (link)]. We compared differences in proportions among EU and non-EU responders using Chi-square or Fisher’s exact test. Missing answers were removed from the respective analysis on a case-by-case basis. In our primary analysis, we considered all non-missing responses equivalently without taking potential nesting into account. In order to evaluate a possible overestimation of effects due to nested data, we eliminated all duplicates that we defined as respondents from the same country and from the same hospital size. We then repeated the primary analysis with the de-duplicated dataset. All analyses were performed using SPSS statistical software version 23.0 [10 ].
10
One-way ANOVA Statistical Analysis
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Results are expressed as means ± SEM usually or medians (interquartile range) for data that are not normally distributed. Data was conducted by one-way ANOVA analysis via IBM SPSS statistical software, version 23.0 (SPSS Inc., Chicago, IL, United States). Pictures are drawn and output by GraphPad Prism V.8.0 (San Diego, CA, USA). Differences considered of statistical significance were set at p < 0.05.
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