Social Determinants in Health Promotion Research Center, Hormozgan Health Institute, Hormozgan University of Medical Sciences, Bandar Abbas, Iran.
Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran.
BMC Med Inform Decis Mak. 2024 Sep 3;24(1):246. doi: 10.1186/s12911-024-02648-3.
The worldwide prevalence of type 2 diabetes mellitus in adults is experiencing a rapid increase. This study aimed to identify the factors affecting the survival of prediabetic patients using a comparison of the Cox proportional hazards model (CPH) and the Random survival forest (RSF).
This prospective cohort study was performed on 746 prediabetics in southwest Iran. The demographic, lifestyle, and clinical data of the participants were recorded. The CPH and RSF models were used to determine the patients' survival. Furthermore, the concordance index (C-index) and time-dependent receiver operating characteristic (ROC) curve were employed to compare the performance of the Cox proportional hazards (CPH) model and the random survival forest (RSF) model.
The 5-year cumulative T2DM incidence was 12.73%. Based on the results of the CPH model, NAFLD (HR = 1.74, 95% CI: 1.06, 2.85), FBS (HR = 1.008, 95% CI: 1.005, 1.012) and increased abdominal fat (HR = 1.02, 95% CI: 1.01, 1.04) were directly associated with diabetes occurrence in prediabetic patients. The RSF model suggests that factors including FBS, waist circumference, depression, NAFLD, afternoon sleep, and female gender are the most important variables that predict diabetes. The C-index indicated that the RSF model has a higher percentage of agreement than the CPH model, and in the weighted Brier Score index, the RSF model had less error than the Kaplan-Meier and CPH model.
Our findings show that the incidence of diabetes was alarmingly high in Iran. The results suggested that several demographic and clinical factors are associated with diabetes occurrence in prediabetic patients. The high-risk population needs special measures for screening and care programs.
全球成年人 2 型糖尿病的患病率正在迅速增加。本研究旨在通过比较 Cox 比例风险模型（CPH）和随机生存森林（RSF）来确定影响糖尿病前期患者生存的因素。
本前瞻性队列研究在伊朗西南部对 746 名糖尿病前期患者进行了研究。记录了参与者的人口统计学、生活方式和临床数据。使用 Cox 比例风险（CPH）模型和随机生存森林（RSF）模型来确定患者的生存情况。此外，还使用一致性指数（C 指数）和时间依赖性接受者操作特征（ROC）曲线来比较 Cox 比例风险（CPH）模型和随机生存森林（RSF）模型的性能。
5 年累积 T2DM 发生率为 12.73%。基于 CPH 模型的结果，NAFLD（HR=1.74，95%CI：1.06，2.85）、FBS（HR=1.008，95%CI：1.005，1.012）和腹部脂肪增加（HR=1.02，95%CI：1.01，1.04）与糖尿病前期患者的糖尿病发生直接相关。RSF 模型表明，FBS、腰围、抑郁、NAFLD、下午睡眠和女性等因素是预测糖尿病的最重要变量。C 指数表明，RSF 模型的一致性百分比高于 CPH 模型，在加权 Brier 评分指数中，RSF 模型的错误率低于 Kaplan-Meier 和 CPH 模型。
我们的研究结果表明，伊朗的糖尿病发病率非常高。研究结果表明，一些人口统计学和临床因素与糖尿病前期患者的糖尿病发生有关。高危人群需要采取特殊的筛查和护理计划。
