DataSheet_2_Development and validation of a nomogram for evaluating the incident risk of carotid atherosclerosis in patients with type 2 diabetes.csv

IntroductionThe purpose of this study was to evaluate the clinical characteristics of carotid atherosclerotic disease in patients with type 2 diabetes mellitus, investigate its risk factors, and develop and validate an easy-to-use nomogram.
Methods1049 patients diagnosed with type 2 diabetes were enrolled and randomly assigned to the training and validation cohorts. Multivariate logistic regression analysis identified independent risk factors. A method combining least absolute shrinkage and selection operator with 10-fold cross-validation was used to screen for characteristic variables associated with carotid atherosclerosis. A nomogram was used to visually display the risk prediction model. Nomogram performance was evaluated using the C index, the area under the receiver operating characteristic curve, and calibration curves. Clinical utility was assessed by decision curve analysis.
ResultsAge, nonalcoholic fatty liver disease, and OGTT3H were independent risk factors associated with carotid atherosclerosis in patients with diabetes. Age, nonalcoholic fatty liver disease, smoke, HDL-C, and LDL-C were characteristic variables used to develop the nomogram. The area under the curve for the discriminative power of the nomogram was 0.763 for the training cohort and 0.717 for the validation cohort. The calibration curves showed that the predicted probability matched the actual likelihood. The results of the decision curve analysis indicated that the nomograms were clinically useful.
DiscussionA new nomogram was developed and validated for assessing the incident risk of carotid atherosclerotic in patients with diabetes; this nomogram may act as a clinical tool to assist clinicians in making treatment recommendations.

引言 本研究旨在评估2型糖尿病患者颈动脉粥样硬化性疾病的临床特征，探究其相关危险因素，并开发并验证一款易于使用的列线图（nomogram）。
方法 本研究纳入1049例确诊2型糖尿病的患者，将其随机分配至训练队列与验证队列。采用多因素logistic回归分析筛选独立危险因素；采用结合最小绝对收缩和选择算子（least absolute shrinkage and selection operator，LASSO）与10折交叉验证的联合方法，筛选与颈动脉粥样硬化相关的特征变量。通过列线图可视化展示该风险预测模型，采用C指数、受试者工作特征曲线下面积以及校准曲线评估列线图的预测性能，并通过决策曲线分析评估其临床实用性。
结果 年龄、非酒精性脂肪性肝病以及口服葡萄糖耐量试验3小时血糖（OGTT3H）为糖尿病患者合并颈动脉粥样硬化的独立危险因素。用于构建列线图的特征变量包括年龄、非酒精性脂肪性肝病、吸烟史、高密度脂蛋白胆固醇（HDL-C）以及低密度脂蛋白胆固醇（LDL-C）。训练队列中该列线图的判别效能对应的受试者工作特征曲线下面积为0.763，验证队列中为0.717。校准曲线结果显示，模型预测概率与实际发生概率拟合度良好。决策曲线分析结果表明，该列线图具备临床实用价值。
讨论 本研究开发并验证了一款用于评估糖尿病患者颈动脉粥样硬化发病风险的新型列线图，该工具可作为临床辅助工具，帮助临床医师制定治疗决策。