Key result
Adding FPG and HbA1c to clinical risk models improves 3-year type 2 diabetes prediction to ~0.88 AUC.
Cohort (n=37,416)
Yes
Answers are grounded in this paper and cite their sources.
OBJECTIVE: Risk models and scores have been developed to predict incidence of type 2 diabetes in Western populations, but their performance may differ when applied to non-Western populations. We developed and validated a risk score for predicting 3-year incidence of type 2 diabetes in a Japanese population. METHODS: Participants were 37,416 men and women, aged 30 or older, who received periodic health checkup in 2008-2009 in eight companies. Diabetes was defined as fasting plasma glucose (FPG) ≥ 126 mg/dl, random plasma glucose ≥ 200 mg/dl, glycated hemoglobin (HbA1c) ≥ 6.5%, or receiving medical treatment for diabetes. Risk scores on non-invasive and invasive models including FPG and HbA1c were developed using logistic regression in a derivation cohort and validated in the remaining cohort. RESULTS: The area under the curve (AUC) for the non-invasive model including age, sex, body mass index, waist circumference, hypertension, and smoking status was 0.717 (95% CI, 0.703-0.731). In the invasive model in which both FPG and HbA1c were added to the non-invasive model, AUC was increased to 0.893 (95% CI, 0.883-0.902). When the risk scores were applied to the validation cohort, AUCs (95% CI) for the non-invasive and invasive model were 0.734 (0.715-0.753) and 0.882 (0.868-0.895), respectively. Participants with a non-invasive score of ≥ 15 and invasive score of ≥ 19 were projected to have >20% and >50% risk, respectively, of developing type 2 diabetes within 3 years. CONCLUSIONS: The simple risk score of the non-invasive model might be useful for predicting incident type 2 diabetes, and its predictive performance may be markedly improved by incorporating FPG and HbA1c.
No takes yet. Share an insight, caveat, or question.
Nanri et al. (2015) conducted a cohort in Type 2 diabetes (n=37,416). Invasive risk score model (including fasting plasma glucose and HbA1c) vs. Non-invasive risk score model (age, sex, BMI, waist circumference, hypertension, smoking) was evaluated on 3-year incidence of type 2 diabetes (AUC 0.882, 95% CI 0.868-0.895). Adding FPG and HbA1c to a non-invasive clinical risk model improved 3-year type 2 diabetes prediction, yielding validation AUCs of 0.882 (95% CI 0.868-0.895) vs 0.734 (95% CI 0.715-0.753).
Synapse has enriched 10 related papers. Consider them for comparative context: