Table 2.
Discriminant evaluation of predictive models.
| Model | Accuracy | ROCAUC (95% CI) | P valuea | PRAUC (95% CI) | P valueb |
|---|---|---|---|---|---|
| LR model 1 | 87.42% | 0.73 (0.68, 0.74) | Ref | 0.30 (0.24, 0.32) | Ref |
| XGBoost model 1 | 83.87% | 0.64 (0.61, 0.72) | .023 | 0.26 (0.21, 0.39) | .312 |
| LR model 2 | 87.10% | 0.78 (0.73, 0.81) | .156 | 0.34 (0.27, 0.40) | .283 |
| XGBoost model 2 | 88.39% | 0.82 (0.75, 0.82) | .006 | 0.44 (0.31, 0.47) | <.001 |
Notes: features in model 1: sex, age, duration of type 2 diabetes, body mass index, systolic blood pressure, diastolic blood pressure, triglyceride, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and total cholesterol. Features in model 2: duration of type 2 diabetes, age, systolic blood pressure, total cholesterol, alanine, citrulline, glutamate, ornithine, phenylalanine, threonine, tyrosine, C18 : 1, C18 : 1OH, and C18 : 2. aDelong test for area under the curve of receiver operating characteristic curve. bDelong test for area under the curve of precision recall curve. Abbreviations: ROC: receiver operating characteristic; AUC: area under the curve; CI; confidence interval; PR: precision recall; LR: logistic regression; XGBoost: extreme gradient boosting; Ref: reference.