Department of Neurosurgery, Heinrich-Heine University Medical Center, Düsseldorf, Germany.
Department of Public Health, Erasmus MC, Rotterdam, The Netherlands.
Neurosurgery. 2019 Sep 1;85(3):302-311. doi: 10.1093/neuros/nyz282.
Clinical prediction models in neurosurgery are increasingly reported. These models aim to provide an evidence-based approach to the estimation of the probability of a neurosurgical outcome by combining 2 or more prognostic variables. Model development and model reporting are often suboptimal. A basic understanding of the methodology of clinical prediction modeling is needed when interpreting these models. We address basic statistical background, 7 modeling steps, and requirements of these models such that they may fulfill their potential for major impact for our daily clinical practice and for future scientific work.
神经外科学中越来越多地报告了临床预测模型。这些模型旨在通过结合 2 个或更多预后变量，为估计神经外科结局的概率提供一种基于证据的方法。模型的开发和报告往往并不理想。在解释这些模型时，需要对临床预测建模的方法学有基本的了解。我们解决了基本的统计背景、7 个建模步骤和这些模型的要求，以便它们能够为我们的日常临床实践和未来的科学工作带来重大影响。
