Wang Yu, Shi Yao, Wang Li, Rong Wenli, Du Yunhong, Duan Yuliang, Peng Lili
School of Nursing, Hunan University of Chinese Medicine, No. 300, Bachelor Road, Hanpu Science and Education Park, Yuelu District, Changsha, Hunan Province, 410208, China.
Department of Anesthesia, The First Affiliated Hospital of Naval Medical University, No. 168, Changhai Road, Yangpu District, Shanghai, 200433, China.
World J Surg Oncol. 2025 Mar 1;23(1):72. doi: 10.1186/s12957-025-03726-0.
Currently, various risk prediction models for surgical site infection (SSI) in patients with gastrointestinal tumors have been developed, but comprehensive comparisons regarding the model construction process, performance, and data sample bias are lacking. This study conducts a systematic review of relevant research to evaluate the risk bias and clinical applicability of these models.
The Web of Science, PubMed, Cochrane Library, Embase, CINAHL, CBM, CNKI, Wanfang, and VIP databases were searched for studies related to SSI prediction models in gastrointestinal cancer patients published up to August 19, 2024. Two researchers independently screened the literature, extracted the data, and evaluated the quality. A meta-analysis was conducted on the common predictive factors included in the model, using odds ratio (OR) values and 95% confidence interval (CI) as effect statistics. The Q test and heterogeneity index I were used to assess heterogeneity. All the statistical analyses were performed via Stata 16.0 software. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist was submitted as a supplement.
A total of 28 articles were included, and 39 models were constructed. The area under the receiver operating characteristic curve (AUC) for the models ranged from 0.660 to 0.950, indicating good predictive performance. Eight studies conducted internal validation, eight studies conducted external validation, and two studies used a combination of internal and external validation for model evaluation. The overall risk of bias in the literature was high, but the applicability was good. The results of the meta-analysis revealed that factors such as underlying diseases, surgical factors, demographic factors, and laboratory-related indicators are the main predictors of surgical site infections in patients with gastrointestinal tumors.
Currently, risk prediction models for surgical site infections in patients with gastrointestinal cancer remain in the developmental phase, and there is a high risk of bias in the areas of study subjects, outcomes, and analysis. Researchers need to enhance research methodologies, conduct large-scale prospective studies, and refer to the reporting standards of the bias risk assessment tool for predictive models to construct predictive models with low bias risk and high applicability.
目前，已经开发了多种用于预测胃肠道肿瘤患者手术部位感染（SSI）的风险预测模型，但在模型构建过程、性能和数据样本偏差方面缺乏全面比较。本研究对相关研究进行系统评价，以评估这些模型的风险偏差和临床适用性。
检索Web of Science、PubMed、Cochrane图书馆、Embase、CINAHL、CBM、CNKI、万方和维普数据库，查找截至2024年8月19日发表的与胃肠道癌患者SSI预测模型相关的研究。两名研究人员独立筛选文献、提取数据并评估质量。对模型中包含的常见预测因素进行荟萃分析，使用比值比（OR）值和95%置信区间（CI）作为效应统计量。采用Q检验和异质性指数I评估异质性。所有统计分析均通过Stata 16.0软件进行。提交系统评价和荟萃分析的首选报告项目（PRISMA）清单作为补充材料。
共纳入28篇文章，构建了39个模型。模型的受试者工作特征曲线下面积（AUC）范围为0.660至0.950，表明具有良好的预测性能。八项研究进行了内部验证，八项研究进行了外部验证，两项研究使用内部和外部验证相结合的方式进行模型评估。文献中的总体偏倚风险较高，但适用性良好。荟萃分析结果显示，基础疾病、手术因素、人口统计学因素和实验室相关指标等因素是胃肠道肿瘤患者手术部位感染的主要预测因素。
目前，胃肠道癌患者手术部位感染的风险预测模型仍处于发展阶段，在研究对象、结局和分析等方面存在较高的偏倚风险。研究人员需要加强研究方法，开展大规模前瞻性研究，并参考预测模型偏倚风险评估工具的报告标准，构建偏倚风险低、适用性高的预测模型。
