Wang Jiao, Chen Jianrong, Liu Ying, Xu Jixiong
Department of Endocrinology and Metabolism, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Jiangxi Clinical Research Center for Endocrine and Metabolic Disease, Nanchang, China.
JMIR Med Inform. 2025 Jan 28;13:e64992. doi: 10.2196/64992.
Many tools have been developed to predict the risk of diabetes in a population without diabetes; however, these tools have shortcomings that include the omission of race, inclusion of variables that are not readily available to patients, and low sensitivity or specificity.
We aimed to develop and validate an easy, systematic index for predicting diabetes risk in the Asian population.
We collected the data from the NAGALA (NAfld [nonalcoholic fatty liver disease] in the Gifu Area, Longitudinal Analysis) database. The least absolute shrinkage and selection operator model was used to select potentially relevant features. Multiple Cox proportional hazard analysis was used to develop a model based on the training set.
The final study population of 15464 participants had a mean age of 42 (range 18-79) years; 54.5% (8430) were men. The mean follow-up duration was 6.05 (SD 3.78) years. A total of 373 (2.41%) participants showed progression to diabetes during the follow-up period. Then, we established a novel parameter (the FHTHWA index), to evaluate the incidence of diabetes in a population without diabetes, comprising 6 parameters based on the training set. After multivariable adjustment, individuals in tertile 3 had a significantly higher rate of diabetes compared with those in tertile 1 (hazard ratio 32.141, 95% CI 11.545-89.476). Time receiver operating characteristic curve analyses showed that the FHTHWA index had high accuracy, with the area under the curve value being around 0.9 during the more than 12 years of follow-up.
This research successfully developed a diabetes risk assessment index tailored for the Japanese population by utilizing an extensive dataset and a wide range of indices. By categorizing the diabetes risk levels among Japanese individuals, this study offers a novel predictive tool for identifying potential patients, while also delivering valuable insights into diabetes prevention strategies for the healthy Japanese populace.
已经开发了许多工具来预测非糖尿病人群患糖尿病的风险；然而，这些工具存在缺陷，包括忽略种族、纳入患者不易获得的变量以及低敏感性或特异性。
我们旨在开发并验证一种简单、系统的指数，用于预测亚洲人群的糖尿病风险。
我们从NAGALA（岐阜地区非酒精性脂肪性肝病纵向分析）数据库收集数据。使用最小绝对收缩和选择算子模型来选择潜在相关特征。基于训练集，采用多重Cox比例风险分析来建立模型。
最终的15464名研究参与者的平均年龄为42岁（范围18 - 79岁）；54.5%（8430名）为男性。平均随访时间为6.05年（标准差3.78）。在随访期间，共有373名（2.41%）参与者发展为糖尿病。然后，我们基于训练集建立了一个新的参数（FHTHWA指数），用于评估非糖尿病人群中糖尿病的发病率，该指数包含6个参数。多变量调整后，与第一三分位数的个体相比，第三三分位数的个体患糖尿病的比率显著更高（风险比32.141，95%置信区间11.545 - 89.476）。时间接受者操作特征曲线分析表明，FHTHWA指数具有较高的准确性，在超过12年的随访期间，曲线下面积值约为0.9。
本研究通过利用广泛的数据集和众多指标，成功开发了一种针对日本人群的糖尿病风险评估指数。通过对日本个体的糖尿病风险水平进行分类，本研究提供了一种用于识别潜在患者的新型预测工具，同时也为健康的日本民众提供了有关糖尿病预防策略的宝贵见解。
