Geographic and temporal validity of prediction models: different approaches were useful to examine model performance
Geographic and temporal validity of prediction models: different approaches were useful to examine model performance
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DOI：
10.1016/j.jclinepi.2016.05.007
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发表时间：
2016-11-01
影响因子：
7.2
通讯作者：
Steyerberg, Ewout W.
中科院分区：
文献类型：
--
作者：
Austin, Peter C.;van Klaveren, David;Steyerberg, Ewout W.
目的：临床预测模型的验证传统上是指评估模型在新患者中的性能。我们研究了不同的方法，地理和时间验证的多中心数据设置从两个时间periods.Study设计和设置：我们说明了不同的分析方法验证使用的样本14,857例心力衰竭住院患者在90家医院在两个不同的时间段。Bootstrap Rescue用于评估内部效度。荟萃分析方法被用来评估地理可运输性。每个医院被用作一次验证样本，其余医院用于模型推导。使用随机效应荟萃分析方法汇总医院特异性鉴别力（c-统计量）和校准（校准截距和斜率）估计值。12统计和预测区间宽度量化地理可运输性。时间的可移植性进行了评估，从早期的模型推导和患者从后期的模型validation.Results：估计的再现性，合并医院的具体性能，和时间的可移植性平均非常相似，与C-统计量为0.75。医院之间的变化是温和的，根据I-2统计和预测区间为C-statistics.Conclusion：这项研究说明了如何预测模型的性能可以在不同的时间段与多中心数据的设置进行评估。(C)2016作者爱思唯尔公司出版
Objective: Validation of clinical prediction models traditionally refers to the assessment of model performance in new patients. We studied different approaches to geographic and temporal validation in the setting of multicenter data from two time periods.Study Design and Setting: We illustrated different analytic methods for validation using a sample of 14,857 patients hospitalized with heart failure at 90 hospitals in two distinct time periods. Bootstrap resampling was used to assess internal validity. Meta-analytic methods were used to assess geographic transportability. Each hospital was used once as a validation sample, with the remaining hospitals used for model derivation. Hospital-specific estimates of discrimination (c-statistic) and calibration (calibration intercepts and slopes) were pooled using random-effects meta-analysis methods. 12 statistics and prediction interval width quantified geographic transportability. Temporal transportability was assessed using patients from the earlier period for model derivation and patients from the later period for model validation.Results: Estimates of reproducibility, pooled hospital-specific performance, and temporal transportability were on average very similar, with c-statistics of 0.75.. Between-hospital variation was moderate according to I-2 statistics and prediction intervals for c-statistics.Conclusion: This study illustrates how performance of prediction models can be assessed in settings with multicenter data at different time periods. (C) 2016 The Authors. Published by Elsevier Inc.