Centre for Prognosis Research, Arthritis Research UK Primary Care Centre, Research Institute for Primary Care & Health Sciences, Keele University, Keele, Staffordshire, UK.
Centre for Prognosis Research, Arthritis Research UK Primary Care Centre, Research Institute for Primary Care & Health Sciences, Keele University, Keele, Staffordshire, UK.
J Clin Epidemiol. 2018 Oct;102:38-49. doi: 10.1016/j.jclinepi.2018.05.008. Epub 2018 May 18.
Measurement error in predictor variables may threaten the validity of clinical prediction models. We sought to evaluate the possible extent of the problem. A secondary objective was to examine whether predictors are measured at the intended moment of model use.
A systematic search of Medline was used to identify a sample of articles reporting the development of a clinical prediction model published in 2015. After screening according to a predefined inclusion criteria, information on predictors, strategies to control for measurement error, and intended moment of model use were extracted. Susceptibility to measurement error for each predictor was classified into low and high risks.
Thirty-three studies were reviewed, including 151 different predictors in the final prediction models. Fifty-one (33.7%) predictors were categorized as high risk of error; however, this was not accounted for in the model development. Only 8 (24.2%) studies explicitly stated the intended moment of model use and when the predictors were measured.
Reporting of measurement error and intended moment of model use is poor in prediction model studies. There is a need to identify circumstances where ignoring measurement error in prediction models is consequential and whether accounting for the error will improve the predictions.
预测变量中的测量误差可能会威胁临床预测模型的有效性。我们旨在评估该问题的可能程度。次要目的是检查预测因子是否在模型使用的预期时刻进行测量。
系统地检索 Medline，以确定 2015 年发表的报告临床预测模型开发的文章样本。根据预先确定的纳入标准进行筛选后，提取了有关预测因子，控制测量误差的策略以及模型使用的预期时刻的信息。将每个预测因子的测量误差易感性分为低风险和高风险。
共审查了 33 项研究，最终预测模型中包含了 151 个不同的预测因子。其中 51 个（33.7％）预测因子被归类为高误差风险；但是，在模型开发中并未考虑到这一点。只有 8 项（24.2％）研究明确说明了模型使用的预期时刻以及何时测量了预测因子。
预测模型研究中对测量误差和模型使用的预期时刻的报告很差。需要确定在哪些情况下忽略预测模型中的测量误差会产生后果，以及是否可以通过考虑误差来提高预测效果。
