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建立和验证胃肠道癌症患者肌少症风险预测模型:基于系统评价和荟萃分析的方法。

Establishment and validation of a risk prediction model for sarcopenia in gastrointestinal cancer patients: A systematic review and meta-analysis-based approach.

机构信息

School of Nursing, Wenzhou Medical University, Wenzhou 315035, China; Cixi Biomedical Research Institute, Wenzhou Medical University, Cixi 315300, China.

The First Clinical College, Wenzhou Medical University, Wenzhou 325000, China.

出版信息

Clin Nutr. 2024 Nov;43(11):91-98. doi: 10.1016/j.clnu.2024.08.014. Epub 2024 Aug 26.

Abstract

OBJECTIVE

The study aimed to develop a model to predict the risk of sarcopenia in gastrointestinal cancer patients. The goal was to identify these patients early and classify them into different risk categories based on their likelihood of developing sarcopenia.

METHODS

This study evaluated risk factors for sarcopenia in patients with gastrointestinal cancers through a systematic review and meta-analysis. The natural logarithm of the combined risk estimate for each factor was used as a coefficient to assign scores within the model for risk prediction. Data from 270 patients with gastrointestinal cancers, collected between October 2023 and April 2024, was used to assess the predictive performance of the scoring model.

RESULTS

The analysis included 17 studies that included 9405 patients with gastrointestinal cancers, out of which 4361 had sarcopenia. The model identified several significant predictors of sarcopenia, including age (OR = 2.45), sex (OR = 1.15), combined diabetes (OR = 2.02), neutrophil-to-lymphocyte ratio (NLR) category (OR = 1.61), TNM stage (OR = 1.61), and weight change (OR = 1.60). Model validation was performed using an external cohort through logistic regression, resulting in an area under the curve (AUC) of 0.773. This model attained a sensitivity of 0.714 and a specificity of 0.688 and ultimately selected 16.5 as the ideal critical risk score. Furthermore, an AUC of 0.770 was obtained from Bayesian model validation; the optimal critical risk score was determined to be 19.0, which corresponds to a sensitivity of 0.658 and a specificity of 0.847.

CONCLUSIONS

The model of risk prediction developed through systematic review and meta-analysis demonstrates substantial for sarcopenia in patients with gastrointestinal cancers. Its clinical usability facilitates the screening of patients at high risk for sarcopenia.

摘要

目的

本研究旨在建立一个预测胃肠道癌症患者发生肌肉减少症风险的模型。目标是早期识别这些患者,并根据其发生肌肉减少症的可能性将其分为不同的风险类别。

方法

本研究通过系统评价和荟萃分析评估了胃肠道癌症患者发生肌肉减少症的危险因素。采用模型中每个因素的综合风险估计值的自然对数作为系数,为风险预测分配模型内的分数。使用 2023 年 10 月至 2024 年 4 月期间收集的 270 名胃肠道癌症患者的数据来评估评分模型的预测性能。

结果

该分析纳入了 17 项研究,共纳入了 9405 名胃肠道癌症患者,其中 4361 名患有肌肉减少症。该模型确定了几个肌肉减少症的显著预测因子,包括年龄(OR=2.45)、性别(OR=1.15)、合并糖尿病(OR=2.02)、中性粒细胞与淋巴细胞比值(NLR)类别(OR=1.61)、TNM 分期(OR=1.61)和体重变化(OR=1.60)。通过逻辑回归对外部队列进行模型验证,得到曲线下面积(AUC)为 0.773。该模型的敏感性为 0.714,特异性为 0.688,最终选择 16.5 作为理想的临界风险评分。此外,贝叶斯模型验证得到 AUC 为 0.770,最佳临界风险评分确定为 19.0,其敏感性为 0.658,特异性为 0.847。

结论

通过系统评价和荟萃分析建立的风险预测模型对胃肠道癌症患者发生肌肉减少症具有显著预测能力。其临床可用性便于筛选发生肌肉减少症风险高的患者。

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