Dementia risk in the general population: large-scale external validation of prediction models in the AGES-Reykjavik study.

Dementia risk in the general population: large-scale external validation of prediction models in the AGES-Reykjavik study.
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DOI:
10.1007/s10654-021-00785-x
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发表时间:
2021-10
影响因子:
13.6
通讯作者:
Geerlings MI
Geerlings MI
中科院分区:
医学1区
文献类型:
--
作者:
Vonk JMJ;Greving JP;Gudnason V;Launer LJ;Geerlings MI

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我们旨在评估一般人群中全因痴呆或AD预测模型的外部性能,这可以帮助选择高风险个体进行临床试验和预防。我们在基于人群的AGES-Reykjavik研究中确定了36个合格的已发表预后模型中的17个用于外部验证。使用c统计量和校准图评估预测性能。所有五个c统计量> 0.75(0.76 - 0.81)的模型都包含认知测试作为预测因子,而所有c统计量较低(0.67 - 0.75)的模型都没有。所有模型的校准范围从好到差,包括系统性风险高估或特别是最高风险组的高估。过高估计风险的模型对于排除目的可能是可以接受的,但缺乏准确识别痴呆风险较高的个体的能力。更新现有模型或开发旨在识别高风险个体的新模型,以及对痴呆症预测模型进行更多的外部验证研究都是必要的。在线版本包含补充材料,可通过10.1007/s10654-021-00785-x获取。
We aimed to evaluate the external performance of prediction models for all-cause dementia or AD in the general population, which can aid selection of high-risk individuals for clinical trials and prevention. We identified 17 out of 36 eligible published prognostic models for external validation in the population-based AGES-Reykjavik Study. Predictive performance was assessed with c statistics and calibration plots. All five models with a c statistic > .75 (.76–.81) contained cognitive testing as a predictor, while all models with lower c statistics (.67–.75) did not. Calibration ranged from good to poor across all models, including systematic risk overestimation or overestimation for particularly the highest risk group. Models that overestimate risk may be acceptable for exclusion purposes, but lack the ability to accurately identify individuals at higher dementia risk. Both updating existing models or developing new models aimed at identifying high-risk individuals, as well as more external validation studies of dementia prediction models are warranted. The online version contains supplementary material available at 10.1007/s10654-021-00785-x.
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