拉索回归在胃肠病学中的应用和影响:系统性审查
Hassam Ali1, Maria Shahzad2, Shiza Sarfraz2
1Department of Gastroenterology and Hepatology, East Carolina University, Greenville, NC, USA.
最小绝对收缩和选择操作员 (Lasso) 回归有助于胃肠病学,通过开发IBD和肝脏疾病等疾病的预测模型. 这一系统性审查强调了其在复杂患者数据的变量选择中的有用性.
科学领域:
- 医学中的统计建模.
- 临床预测模型的临床预测模型.
- 胃肠病学研究的研究.
背景情况:
- 最小绝对收缩和选择操作员 (Lasso) 回归是一种使用临床变量预测结果的统计方法.
- 它在胃肠病学中的应用,用于预测模型的开发,需要进行系统的审查.
研究的目的:
- 系统地审查胃肠病学中的拉索回归应用,以开发预测模型.
- 为在这个领域执行拉索回归提供指导.
主要方法:
- 在PubMed,Embase和Cochrane CENTRAL中进行全面的文献搜索,遵循PRISMA指南.
- 包括标准和数据提取使用标准化表格.
- 对16项关于胃肠道疾病的研究进行分析.
主要成果:
- 拉索回归在16项研究中用于变量选择,风险预测和各种胃肠道疾病 (例如,炎症性肠道疾病,肝脏疾病,食道癌症) 的模型开发.
- 11项研究专注于肝病预测,5项研究专注于非肝病,样本大小从134个到8861.
- 使用诸如接收器操作特征下的面积 (AUROC),C指数和校准图表等指标来评估性能.
结论:
- 拉索回归对于具有众多预测因子的复杂胃肠道学预测场景非常有价值.
- 高质量的数据对于有效的拉索回归应用至关重要.
- 虽然确定了重要的变量,但拉索回归不提供因果解释,因此需要根据研究设计和数据质量进行谨慎的解释.
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