Construction and validation of a prediction model for risks in diabetes
Objective To use the Jinchang cohort population to build a database for constructing a risk predic-tion model for diabetes and to validate it.Methods A total of 31 463 patients from baseline and a three-phase follow-up from 2014 to 2019 were selected as the study subjects.According to the ratio of 7∶3,they were randomly divided into a training set and validation set,with 22 025 in the former and 9 438 were in the latter.The data in the training set screened predictors through univariate and multivariate Cox proportional hazards models,and a nomogram prediction model based on the Cox model was established.The area under the receiver operating characteristic curve was used to evaluate the model discrimination.The accuracy of the model was evaluated by plotting a calibration curve.The clinical application of the model was evaluated by decision curve analysis.At the same time,the differentiation,accuracy and clinical application value of the prediction model were internally verified.Results Gender,age,body mass index,alcohol consumption,hyper-tension,triglyceride,high density lipoprotein cholesterol,gamma-glutamyl transpeptidase,family history of diabetes,cholecystitis and gallbladder removal were used as predictors to construct the risk prediction model for diabetes.The area under the receiver operating characteristic curve of the model in the training set and the validation set were 0.783,0.825,0.842,and 0.782,0.805,0.807 in the 3-year,5-year and 7-year models,respectively.The results showed that the model had a good discrimination.The calibration curves were all close to the diagonal,indicating that the accuracy of the model was high.In the decision curve analysis,the model curve indicated a higher level of net benefit and the predictive model being with better clinical utility.Conclusion The nomogram prediction model constructed in this study has good predictive ability and clinical practicability.It can provide a convenient and cost-effective method for screening patients with undiagnosed diabetes or high-risk groups in China.
万方数据
维普
