Clinical utility gains from incorporating comorbidity and geographic location information into risk estimation equations for atherosclerotic cardiovascular disease.
Clinical utility gains from incorporating comorbidity and geographic location information into risk estimation equations for atherosclerotic cardiovascular disease.
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DOI：
10.1093/jamia/ocad017
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发表时间：
2023-04-19
影响因子：
6.4
通讯作者：
Shah, Nigam H.
中科院分区：
文献类型：
--
作者：
Xu, Yizhe;Foryciarz, Agata;Steinberg, Ethan;Shah, Nigam H.
关键词：
文献中有超过 363 个美国心脏病学会和美国心脏协会 (ACC/AHA) 汇集队列方程 (PCE) 的定制风险模型，但它们在临床实用性方面的收益很少得到评估。我们为患有特定合并症和地理位置的患者建立新的风险模型，并评估性能改进是否转化为临床效用的收益。我们使用 ACC/AHA PCE 变量重新训练基线 PCE，并对其进行修改以纳入地理位置和 2 种合并症的受试者级信息。我们应用固定效应、随机效应和极限梯度增强（XGB）模型来处理位置引起的相关性和异质性。使用来自 Optum© Clinformatics® 数据集市的 2 464 522 条索赔记录对模型进行训练，并在保留集中进行验证 (N = 1 056 224)。我们评估模型的整体表现以及根据是否存在慢性肾病 (CKD) 或类风湿性关节炎 (RA) 以及地理位置定义的亚组的表现。我们使用净收益评估模型的预期效用，并使用多种区分和校准指标评估模型的统计特性。与基线 PCE 相比，修订后的固定效应和 XGB 模型在总体和所有合并症亚组中产生了更好的区分度。 XGB 改进了对 CKD 或 RA 亚组的校准。然而，净收益的增长可以忽略不计，特别是在低汇率的情况下。修订风险计算器并纳入额外信息或应用灵活模型的常用方法可能会提高统计性能；然而，这种改进并不一定转化为更高的临床效用。因此，我们建议未来开展工作来量化使用风险计算器来指导临床决策的后果。
There are over 363 customized risk models of the American College of Cardiology and the American Heart Association (ACC/AHA) pooled cohort equations (PCE) in the literature, but their gains in clinical utility are rarely evaluated. We build new risk models for patients with specific comorbidities and geographic locations and evaluate whether performance improvements translate to gains in clinical utility. We retrain a baseline PCE using the ACC/AHA PCE variables and revise it to incorporate subject-level information of geographic location and 2 comorbidity conditions. We apply fixed effects, random effects, and extreme gradient boosting (XGB) models to handle the correlation and heterogeneity induced by locations. Models are trained using 2 464 522 claims records from Optum©’s Clinformatics® Data Mart and validated in the hold-out set (N = 1 056 224). We evaluate models’ performance overall and across subgroups defined by the presence or absence of chronic kidney disease (CKD) or rheumatoid arthritis (RA) and geographic locations. We evaluate models’ expected utility using net benefit and models’ statistical properties using several discrimination and calibration metrics. The revised fixed effects and XGB models yielded improved discrimination, compared to baseline PCE, overall and in all comorbidity subgroups. XGB improved calibration for the subgroups with CKD or RA. However, the gains in net benefit are negligible, especially under low exchange rates. Common approaches to revising risk calculators incorporating extra information or applying flexible models may enhance statistical performance; however, such improvement does not necessarily translate to higher clinical utility. Thus, we recommend future works to quantify the consequences of using risk calculators to guide clinical decisions.
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影响因子：
1
作者：
Pepe MS;Fan J;Feng Z;Gerds T;Hilden J
通讯作者：
Hilden J
影响因子：
13.8
作者：
Khera R;Pandey A;Ayers CR;Carnethon MR;Greenland P;Ndumele CE;Nambi V;Seliger SL;Chaves PHM;Safford MM;Cushman M;Xanthakis V;Vasan RS;Mentz RJ;Correa A;Lloyd-Jones DM;Berry JD;de Lemos JA;Neeland IJ
通讯作者：
Neeland IJ
影响因子：
2
作者：
Pencina, MJ;D'Agostino, RB
通讯作者：
D'Agostino, RB
影响因子：
39.2
作者：
Cook, Nancy R.;Ridker, Paul M.
通讯作者：
Ridker, Paul M.
影响因子：
39.3
作者：
Soran, Handrean;Schofield, Jonathan D.;Durrington, Paul N.
通讯作者：
Durrington, Paul N.