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.
Keywords: Aneurysmal subarachnoid hemorrhage; Clinical prediction; Model development; Neurosurgery; Outcome; Risk assessment.
Copyright © 2019 by the Congress of Neurological Surgeons.