Massimiliano Copetti1, Hetal Shah2,3, Andrea Fontana1, Maria Giovanna Scarale4, Claudia Menzaghi4, Salvatore De Cosmo5, Monia Garofolo6, Maria Rosaria Sorrentino7, Olga Lamacchia7, Giuseppe Penno6, Alessandro Doria2,3, Vincenzo Trischitta4,8. 1. Unit of Biostatistics, Fondazione IRCCS "Casa Sollievo della Sofferenza", San Giovanni Rotondo, Italy. 2. Research Division, Joslin Diabetes Center, Boston, Massachusetts. 3. Department of Medicine, Harvard Medical School, Boston, Massachusetts. 4. Research Unit of Diabetes and Endocrine Diseases, Fondazione IRCCS "Casa Sollievo della Sofferenza", San Giovanni Rotondo, Italy. 5. Department of Clinical Sciences, Fondazione IRCCS "Casa Sollievo Della Sofferenza", San Giovanni Rotondo, Italy. 6. Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy. 7. Unit of Endocrinology and Diabetology, Department of Medical and Surgical Sciences, University of Foggia, Foggia, Italy. 8. Department of Experimental Medicine, "Sapienza" University, Rome, Italy.
Abstract
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.
RCT Entities:
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 diabetiCpatiEnts), 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:Whitepatients 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 whitepatients with type 2 diabetes from a real-life setting.
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