Prediction models are everywhere in clinical medicine. We use them to assign a diagnosis or a prognosis, and there have been continuous efforts to develop better prediction models. It is important to understand the fundamentals of prediction modelling, thus, we herein describe nine steps to develop and validate a clinical prediction model with the intention of implementing it in clinical practice: Determine if there is a need for a new prediction model; define the purpose and intended use of the model; assess the quality and quantity of the data you wish to develop the model on; develop the model using sound statistical methods; generate risk predictions on the probability scale (0-100%); evaluate the performance of the model in terms of discrimination, calibration, and clinical utility; validate the model using bootstrapping to correct for the apparent optimism in performance; validate the model on external datasets to assess the generalisability and transportability of the model; and finally publish the model so that it can be implemented or validated by others.

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开发和验证肝病临床预测模型 - 临床医生概述

预测模型在临床医学中无处不在。我们使用它们来进行诊断或预后，并且一直在不断努力开发更好的预测模型。了解预测建模的基础知识非常重要，因此，我们在此描述了开发和验证临床预测模型的九个步骤，旨在将其应用于临床实践： 确定是否需要新的预测模型；定义模型的目的和预期用途；评估您希望开发模型的数据的质量和数量；使用合理的统计方法开发模型；生成概率范围（0-100%）的风险预测；评估模型在区分度、校准和临床实用性方面的性能；使用引导程序验证模型以纠正性能中明显的乐观情绪；在外部数据集上验证模型，以评估模型的通用性和可移植性；最后发布模型，以便其他人可以实现或验证。