预测肾移植后患者和移植物生存的模型的比较性能:一项系统综述

IF 3.6 2区 医学 Q2 IMMUNOLOGY
Joris van de Klundert , Francisco Perez-Galarce , Marcelo Olivares , Liset Pengel , Annelies de Weerd
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引用次数: 0

摘要

cox比例风险模型长期以来一直是肾移植后生存预测的首选模型。近年来,人们提出了各种新颖的模型类型。我们研究了不同模型类型的预测性能,包括机器学习模型和传统模型类型。方法对PROBAST和CHARMS进行系统评价,并考虑扩展到TRIPOD+AI和PROBAST+AI,进行数据收集和偏倚风险评估。该综述只包括了报道不同类型模型预测性能的出版物。比较分析测试了模型类型之间的性能差异。结果纳入文献37篇,比较研究134篇。许多研究的设计仍有改进的余地,大多数研究存在较高的偏倚风险。收集的数据对22对模型类型的性能差异进行了测试,其中10对模型类型产生了显著差异。支持向量机和逻辑回归从未被发现优于其他模型类型。然而,其他比较提供了不确定的比较性能结果,并且没有任何一种模型类型的性能始终优于替代方案。结论:对现有证据和比较性能证据的严格审查发现,Cox比例风险模型在肾移植生存预测性能方面没有显著差异。许多研究的设计意味着高偏倚风险,需要更多和更好的设计研究来重新利用最佳表现的模型。这可以解决模型偏差、报告问题,并增加比较性能分析的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The comparative performance of models predicting patient and graft survival after kidney transplantation: A systematic review

Background

Cox proportional hazard models have long been the model of choice for survival prediction after kidney transplantation. In recent years, a variety of novel model types have been proposed. We investigate the prediction performance across different model types, including machine learning models and traditional model types.

Methods

A systematic review was conducted following PROBAST and CHARMS, also considering extensions to TRIPOD+AI and PROBAST+AI, for data collection and risk of bias assessment. The review only included publications that reported on prediction performance for models of different types. A comparative analysis tested performance differences between the model types.

Results

The review included 37 publications which presented 134 comparative studies. The designs of many studies left room for improvement and most studies had high risk of bias. The collected data admitted testing of performance differences for 22 pairs of model types, ten of which yielded significant differences. Support Vector Machines and Logistic Regression were never found to outperform other model types. Other comparisons, however, provide inconclusive comparative performance results and none of the model types performed consistently and significantly better than alternatives.

Conclusions

Rigorous review of current evidence and comparative performance evidence finds no significant kidney transplant survival prediction performance differences that Cox Proportional Hazard models are being outperformed. The design of many of the studies implies high risk of bias and more and better designed studies which reutilize best performing models are needed. This enables to resolve model biases, reporting issues, and to increase the power of comparative performance analysis.
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来源期刊
Transplantation Reviews
Transplantation Reviews IMMUNOLOGY-TRANSPLANTATION
CiteScore
7.50
自引率
2.50%
发文量
40
审稿时长
29 days
期刊介绍: Transplantation Reviews contains state-of-the-art review articles on both clinical and experimental transplantation. The journal features invited articles by authorities in immunology, transplantation medicine and surgery.
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