CONTEXT: We previously developed and validated an inexpensive and parsimonious prediction model of 2-year all-cause mortality in real-life patients with type 2 diabetes. OBJECTIVE: This model, now named ENFORCE (EstimatioN oF mORtality risk in type 2 diabetiC patiEnts), was investigated in terms of (i) prediction performance at 6 years, a more clinically useful time-horizon; (ii) further validation in an independent sample; and (iii) performance comparison in a real-life vs a clinical trial setting. DESIGN: Observational prospective randomized clinical trial. SETTING: White patients with type 2 diabetes. PATIENTS: Gargano Mortality Study (GMS; n = 1019), Foggia Mortality Study (FMS; n = 1045), and Pisa Mortality Study (PMS; n = 972) as real-life samples and the standard glycemic arm of the ACCORD (Action to Control Cardiovascular Risk in Diabetes) clinical trial (n = 3150). MAIN OUTCOME MEASURE: The endpoint was all-cause mortality. Prediction accuracy and calibration were estimated to assess the model's performances. RESULTS: ENFORCE yielded 6-year mortality C-statistics of 0.79, 0.78, and 0.75 in GMS, FMS, and PMS, respectively (P heterogeneity = 0.71). Pooling the three cohorts showed a 6-year mortality C-statistic of 0.80. In the ACCORD trial, ENFORCE achieved a C-statistic of 0.68, a value significantly lower than that obtained in the pooled real-life samples (P < 0.0001). This difference resembles that observed with other models comparing real-life vs clinical trial settings, thus suggesting it is a true, replicable phenomenon. CONCLUSIONS: The time horizon of ENFORCE has been extended to 6 years and validated in three independent samples. ENFORCE is a free and user-friendly risk calculator of all-cause mortality in white patients with type 2 diabetes from a real-life setting.
|Number of pages||9|
|Journal||The Journal of clinical endocrinology and metabolism|
|Publication status||Published - Oct 1 2019|
ASJC Scopus subject areas
- Endocrinology, Diabetes and Metabolism
- Clinical Biochemistry
- Biochemistry, medical