最小绝对值收缩与选择算子（Lasso）回归是一种统计技术，可用于研究临床变量在预测结果中的影响。本研究旨在系统评述Lasso回归在胃肠病学中开发预测模型的应用，并提供一种进行Lasso回归的方法。根据《系统评价与荟萃分析的优选报告项目》（PRISMA）指南，我们在PubMed、Embase和Cochrane CENTRAL数据库中进行了综合检索（关键词：Lasso回归；胃肠道/疾病）。根据预定义的选择标准筛选符合条件的研究，并使用标准化表格提取数据。共纳入16项研究，涵盖了多种胃肠病学相关的结果。样本量范围从134到8861个受试者不等。其中11项研究报道了与肝脏疾病相关的预测模型，而5项研究则聚焦于非肝脏病因模型。Lasso回归用于变量选择、风险预测和模型开发，采用了不同的验证方法和性能评估指标。模型性能评估指标包括受试者工作特征曲线下面积（AUROC）、C指数和校准图。在胃肠病学中，Lasso回归已被应用于炎症性肠病、肝脏疾病和食管癌等多种疾病。它对于具有多个预测因子的复杂情景非常有价值。然而，它的有效性取决于高质量和完整的数据。虽然它能够识别重要变量，但不提供因果解释。因此，在考虑研究设计和数据质量时，需要谨慎解读。© 2023年印度胃肠病学学会。

Least absolute shrinkage and selection operator (Lasso) regression is a statistical technique that can be used to study the effects of clinical variables in outcome prediction. In this study, we aimed at systematically reviewing the application of Lasso regression in gastroenterology for developing predictive models and providing a method of performing Lasso regression. A comprehensive search strategy was conducted in PubMed, Embase and Cochrane CENTRAL databases (Keywords: lasso regression; gastrointestinal tract/diseases) following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Studies were screened for eligibility based on pre-defined selection criteria and the data was extracted using a standardized form. Total 16 studies were included, comprising a diverse range of gastroenterological disease-related outcomes. Sample sizes ranged from 134 to 8861 subjects. Eleven studies reported liver disease-related prediction models, while five focused on non-hepatic etiology models. Lasso regression was applied for variable selection, risk prediction and model development, with various validation methods and performance metrics used. Model performance metrics included Area Under the Receiver Operating Characteristics (AUROC), C-index and calibration plots. In gastroenterology, Lasso regression has been used in various diseases such as inflammatory bowel disease, liver disease and esophageal cancer. It is valuable for complex scenarios with many predictors. However, its effectiveness depends on high-quality and complete data. While it identifies important variables, it doesn't provide causal interpretations. Therefore, cautious interpretation is necessary considering the study design and data quality.© 2023. Indian Society of Gastroenterology.