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Spss statistics 22 statistical software

Manufactured by IBM

SPSS Statistics 22 is a statistical software package developed by IBM. It provides a comprehensive set of tools for data analysis, including data management, visualization, and advanced statistical modeling. The software is designed to help users analyze and interpret data from various sources, enabling them to make informed decisions. SPSS Statistics 22 supports a wide range of data types and offers a user-friendly interface for conducting statistical analyses.

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Lab products found in correlation

2 protocols using spss statistics 22 statistical software

1

Efficacy of Cetuximab-based Therapy in Wild-type RAS mCRC

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Patients with wild-type RAS WT (KRAS exons 2, 3, and 4 and NRAS exons 2, 3, 4) unresectable mCRC who were treated with cetuximab-based chemotherapy as the first-line therapy between January 2013 and December 2018 at the Zhejiang Cancer Hospital (Hangzhou, China) were retrospectively investigated. Chemotherapy regimens were not restricted. The study was approved by the Ethics Committee and Institutional Review Board of Zhejiang Cancer Hospital and was conducted in compliance with the Helsinki Declaration. The main objective of the study should be progression-free survival (PFS), and the secondary endpoints were overall survival (OS), objective response rate (ORR), and disease control rate (DCR).
The follow-up period was defined as the time from diagnosis to the last observation or death. Progression-free survival was defined as the time between the date of the time from randomization until patient’s tumor progression and death. The log-rank test was used to estimate and compare survival. IBM SPSS Statistics 22 statistical software was used to statistically analyze the data.
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2

Functional Status Comparison in SMA

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Four functional status groups were predefined for comparison analyses:19 nonsitters with Type 2 SMA, sitters with Type 2 SMA, nonambulant patients with Type 3 SMA, and ambulant patients with Type 3 SMA. To determine whether outcome measures could differentiate between patients in different groups, proportions were compared using the Chi‐square test, and quantitative variables were compared using the Kruskal–Wallis one‐way analysis of variance; post hoc analyses based on the Dunn‐Bonferroni method were performed for significant results. The Wilcoxon signed‐rank test was used to assess changes over time. The relationships between variables were examined using Spearman's correlation coefficients. Standardized response means (SRM) were calculated for all assessments. All analyses were performed using SPSS Statistics 22 Statistical software (IBM Corp, Armonk, NY). The limit of statistical significance was set to 0.05.
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