NDLI: Development and validation of a model to predict cardiovascular death, nonfatal myocardial infarction, or nonfatal stroke in patients with type 2 diabetes mellitus and established atherosclerotic cardiovascular disease

Content Provider	Springer Nature : BioMed Central
Author	Stevens, Susanna R. Segar, Matthew W. Pandey, Ambarish Lokhnygina, Yuliya Green, Jennifer B. McGuire, Darren K. Standl, Eberhard Peterson, Eric D. Holman, Rury R.
Abstract	Background Among individuals with atherosclerotic cardiovascular disease (ASCVD), type 2 diabetes mellitus (T2DM) is common and confers increased risk for morbidity and mortality. Differentiating risk is key to optimize efficiency of treatment selection. Our objective was to develop and validate a model to predict risk of major adverse cardiovascular events (MACE) comprising the first event of cardiovascular death, myocardial infarction (MI), or stroke for individuals with both T2DM and ASCVD. Methods Using data from the Trial Evaluating Cardiovascular Outcomes with Sitagliptin (TECOS), we used Cox proportional hazards models to predict MACE among participants with T2DM and ASCVD. All baseline covariates collected in the trial were considered for inclusion, although some were excluded immediately because of large missingness or collinearity. A full model was developed using stepwise selection in each of 25 imputed datasets, and comprised candidate variables selected in 20 of the 25 datasets. A parsimonious model with a maximum of 10 degrees of freedom was created using Cox models with least absolute shrinkage and selection operator (LASSO), where the adjusted R-square was used as criterion for selection. The model was then externally validated among a cohort of participants with similar criteria in the ACCORD (Action to Control Cardiovascular Risk in Diabetes) trial. Discrimination of both models was assessed using Harrell’s C-index and model calibration by the Greenwood-Nam-D’Agostino statistic based on 4-year event rates. Results Overall, 1491 (10.2%) of 14,671 participants in TECOS and 130 (9.3%) in the ACCORD validation cohort (n = 1404) had MACE over 3 years’ median follow-up. The final model included 9 characteristics (prior stroke, age, chronic kidney disease, prior MI, sex, heart failure, insulin use, atrial fibrillation, and microvascular complications). The model had moderate discrimination in both the internal and external validation samples (C-index = 0.65 and 0.61, respectively). The model was well calibrated across the risk spectrum—from a cumulative MACE rate of 6% at 4 years in the lowest risk quintile to 26% in the highest risk quintile. Conclusion Among patients with T2DM and prevalent ASCVD, this 9-factor risk model can quantify the risk of future ASCVD complications and inform decision making for treatments and intensity.
Related Links	https://cardiab.biomedcentral.com/counter/pdf/10.1186/s12933-022-01603-8.pdf
Ending Page	11
Page Count	11
Starting Page	1
File Format	HTM / HTML
ISSN	14752840
DOI	10.1186/s12933-022-01603-8
Journal	Cardiovascular Diabetology
Issue Number	1
Volume Number	21
Language	English
Publisher	BioMed Central
Publisher Date	2022-08-27
Access Restriction	Open
Subject Keyword	Diabetes Angiology Cardiology Atherosclerotic cardiovascular disease Type 2 diabetes mellitus Major adverse cardiovascular events Risk modeling
Content Type	Text
Resource Type	Article
Subject	Cardiology and Cardiovascular Medicine Internal Medicine Endocrinology, Diabetes and Metabolism
Journal Impact Factor	8.5/2023
5-Year Journal Impact Factor	8.9/2023

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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