Suppr超能文献

采用倾向评分匹配法评估糖尿病对胃癌预后的影响。

Evaluating the effect of diabetes on the prognosis of gastric cancer using a propensity score matching method.

作者信息

Sheng Lili, Peng Hui, Pan Yang, Wang Chengci, Zhu Yiping

机构信息

Department of Oncology, the First Affiliated Hospital of Wannan Medical College, Wuhu, China.

Wannan Medical College, Wuhu, China.

出版信息

J Gastrointest Oncol. 2020 Oct;11(5):999-1008. doi: 10.21037/jgo-20-375.

Abstract

BACKGROUND

Gastric cancer (GC) is one of the malignant tumors with high incidence in China. At present, the relationship between type 2 diabetes (T2DM) and the therapeutic effect of various malignant tumors has attracted more and more attention. This study aimed to investigate whether T2DM is a prognostic factor for patients with GC.

METHODS

Patients who had GC and who were admitted to our hospital from November 2008 to December 2015 were included in the study. Among these patients, 84 patients GC complicated with T2DM (GC + T2DM) were enrolled in the observation group, and 215 patients with normal blood glucose were enrolled in the control group. Patients' general information was collected by referring to their electronic and paper medical records, and their living status was followed up by conducting a telephone survey, referring to their hospitalization record, and performing an outpatient review. A propensity score matching method was used to select a 1:1 matched control for each patient with GC and diabetes. An overall survival curve was established using the Kaplan-Meier method. The survival rate was compared via a log-rank test. A Cox proportional hazards regression model was used to the analyse single and multiple factors affecting patient outcomes.

RESULTS

Before matching was conducted, the differences in gender, stage, treatment, and comorbidity were found to be statistically significant (P>0.05). After matching was completed, the clinical data and pathological differences between the two groups were not statistically significant (P<0.05). A histogram matching the pre- and post-propensity scores showed that the matching was successful. The results of the Cox regression model revealed that grouping, pathological type, and treatment were the independent risk factors of the survival of patients with GC. Survival analysis found that the 3-year, 5-year, and overall survival rates of the observation group were significantly lower than those of the control group (P<0.05).

CONCLUSIONS

T2DM plays an important role in the development of GC, and is a prognostic factor among patients with GC.

摘要

背景

胃癌(GC)是中国高发的恶性肿瘤之一。目前,2型糖尿病(T2DM)与各种恶性肿瘤治疗效果之间的关系越来越受到关注。本研究旨在探讨T2DM是否为GC患者的预后因素。

方法

纳入2008年11月至2015年12月在我院住院的GC患者。其中,84例GC合并T2DM患者(GC+T2DM)纳入观察组,215例血糖正常患者纳入对照组。通过查阅电子和纸质病历收集患者的一般信息,并通过电话调查、查阅住院记录和门诊复查对患者的生存状况进行随访。采用倾向评分匹配法为每例GC合并糖尿病患者选择1:1匹配的对照。采用Kaplan-Meier法绘制总生存曲线。通过对数秩检验比较生存率。采用Cox比例风险回归模型分析影响患者预后的单因素和多因素。

结果

匹配前,两组在性别、分期、治疗及合并症方面差异有统计学意义(P>0.05)。匹配完成后,两组临床资料及病理差异无统计学意义(P<0.05)。倾向评分匹配前后的直方图显示匹配成功。Cox回归模型结果显示,分组、病理类型和治疗是GC患者生存的独立危险因素。生存分析发现,观察组的3年、5年生存率及总生存率均显著低于对照组(P<0.05)。

结论

T2DM在GC发生发展中起重要作用,是GC患者的预后因素。

相似文献

6
Impact of diabetes on prognosis of gastric cancer patients performed with gastrectomy.
Chin J Cancer Res. 2020 Oct 31;32(5):631-644. doi: 10.21147/j.issn.1000-9604.2020.05.08.

本文引用的文献

1
Review: Diabetes, Obesity, and Cancer-Pathophysiology and Clinical Implications.
Endocr Rev. 2020 Feb 1;41(1). doi: 10.1210/endrev/bnz014.
3
The intricate relationship between diabetes, obesity and pancreatic cancer.
Biochim Biophys Acta Rev Cancer. 2020 Jan;1873(1):188326. doi: 10.1016/j.bbcan.2019.188326. Epub 2019 Nov 9.
6
Diabetes Increases Risk of Gastric Cancer After Eradication: A Territory-Wide Study With Propensity Score Analysis.
Diabetes Care. 2019 Sep;42(9):1769-1775. doi: 10.2337/dc19-0437. Epub 2019 Jul 11.
7
Cancer risk among patients with type 2 diabetes: A real-world study in Shanghai, China.
J Diabetes. 2019 Nov;11(11):878-883. doi: 10.1111/1753-0407.12926. Epub 2019 May 8.
9
Diabetes mellitus and the risk of gastric cancer: a meta-analysis of cohort studies.
Oncotarget. 2017 Jul 4;8(27):44881-44892. doi: 10.18632/oncotarget.16487.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验