Bethel Mary Angelyn, Hyland Kristen A, Chacra Antonio R, Deedwania Prakash, Fulcher Gregory R, Holman Rury R, Jenssen Trond, Levitt Naomi S, McMurray John J V, Boutati Eleni, Thomas Laine, Sun Jie-Lena, Haffner Steven M
Diabetes Trials Unit, Oxford Centre for Diabetes, Endocrinology, and Metabolism, University of Oxford, Oxford, UK.
Wilmington VA Medical Center, Wilmington, DE, USA.
J Diabetes Complications. 2017 May;31(5):859-863. doi: 10.1016/j.jdiacomp.2017.02.012. Epub 2017 Mar 2.
Predicting incident diabetes could inform treatment strategies for diabetes prevention, but the incremental benefit of recalculating risk using updated risk factors is unknown. We used baseline and 1-year data from the Nateglinide and Valsartan in Impaired Glucose Tolerance Outcomes Research (NAVIGATOR) Trial to compare diabetes risk prediction using historical or updated clinical information.
Among non-diabetic participants reaching 1year of follow-up in NAVIGATOR, we compared the performance of the published baseline diabetes risk model with a "landmark" model incorporating risk factors updated at the 1-year time point. The C-statistic was used to compare model discrimination and reclassification analyses to demonstrate the relative accuracy of diabetes prediction.
A total of 7527 participants remained non-diabetic at 1year, and 2375 developed diabetes during a median of 4years of follow-up. The C-statistic for the landmark model was higher (0.73 [95% CI 0.72-0.74]) than for the baseline model (0.67 [95% CI 0.66-0.68]). The landmark model improved classification to modest (<20%), moderate (20%-40%), and high (>40%) 4-year risk, with a net reclassification index of 0.14 (95% CI 0.10-0.16) and an integrated discrimination index of 0.01 (95% CI 0.003-0.013).
Using historical clinical values to calculate diabetes risk reduces the accuracy of prediction. Diabetes risk calculations should be routinely updated to inform discussions about diabetes prevention at both the patient and population health levels.
预测新发糖尿病可为糖尿病预防的治疗策略提供依据，但利用更新后的风险因素重新计算风险所带来的额外益处尚不清楚。我们使用了葡萄糖耐量受损转归研究（NAVIGATOR）试验中的基线数据和1年数据，以比较使用既往或更新后的临床信息进行糖尿病风险预测的情况。
在NAVIGATOR试验中随访满1年的非糖尿病参与者中，我们将已发表的基线糖尿病风险模型的性能与纳入了1年时间点更新的风险因素的“里程碑”模型进行了比较。C统计量用于比较模型的区分度，重新分类分析用于证明糖尿病预测的相对准确性。
共有7527名参与者在1年时仍未患糖尿病，在中位4年的随访期间，有2375人患糖尿病。“里程碑”模型的C统计量（0.73 [95%CI 0.72 - 0.74]）高于基线模型（0.67 [95%CI 0.66 - 0.68]）。“里程碑”模型改善了对4年低（<20%）、中（20% - 40%）和高（>40%）风险的分类，净重新分类指数为0.14（95%CI 0.10 - 0.16），综合判别指数为0.01（95%CI 0.003 - 0.013）。
使用既往临床值计算糖尿病风险会降低预测准确性。糖尿病风险计算应定期更新，以便在患者和人群健康层面为有关糖尿病预防的讨论提供信息。
