Iwakami Naotsugu, Nagai Toshiyuki, Furukawa Toshiaki A, Nishimura Kunihiro, Anzai Toshihisa
Department of Cardiovascular Medicine, National Cerebral and Cardiovascular Center Suita Japan.
Department of Research Promotion and Management, National Cerebral and Cardiovascular Center Suita Japan.
Circ Rep. 2019 Dec 5;2(1):10-16. doi: 10.1253/circrep.CR-19-0111.
Prediction models are combinations of predictors to assess the risks of specific endpoints such as the presence or prognosis of a disease. Many novel predictors have been developed, modelling techniques have been evolving, and prediction models are currently abundant in the medical literature, especially in cardiovascular medicine, but evidence is still lacking regarding how to use them. Recent methodological advances in systematic reviews and meta-analysis have enabled systematic evaluation of prediction model studies and quantitative analysis to identify determinants of model performance. Knowing what is critical to model performance, under what circumstances model performance remains adequate, and when a model might require further adjustment and improvement will facilitate effective utilization of prediction models and will enhance diagnostic and prognostic accuracy in clinical practice. In this review article, we provide a current methodological overview of the attempts to implement evidence-based utilization of prognostic prediction models for all potential model users, including patients and their families, health-care providers, administrators, researchers, guideline developers and policy makers.
预测模型是预测因素的组合，用于评估特定终点事件的风险，如疾病的存在或预后。许多新型预测因素已被开发出来，建模技术也在不断发展，目前医学文献中充斥着预测模型，尤其是在心血管医学领域，但在如何使用这些模型方面仍缺乏证据。系统评价和荟萃分析方面的最新方法进展使得对预测模型研究进行系统评价和定量分析成为可能，以确定模型性能的决定因素。了解对模型性能至关重要的因素、模型性能在何种情况下仍足够以及模型何时可能需要进一步调整和改进，将有助于有效利用预测模型，并提高临床实践中的诊断和预后准确性。在这篇综述文章中，我们为所有潜在的模型使用者，包括患者及其家属、医疗保健提供者、管理人员、研究人员、指南制定者和政策制定者，提供了当前关于实施基于证据的预后预测模型应用的方法概述。
