Predicting incident heart failure among patients with type 2 diabetes mellitus: The DM-CURE risk score

Abstract

Aim: Early identification and prediction of incident heart failure (HF) is important because of severe morbidity and mortality. This study aimed to predict onset of HF among patients with diabetes.

Methods: A time-varying Cox model was derived from ACCORD clinical trial to predict the risk of incident HF, defined by hospitalization for HF (HHF). External validation was performed on patient-level data from the Harmony Outcome trial and Chronic Renal Insufficiency Cohort (CRIC) study. The model was transformed into an integer-based scoring algorithm for 10-year risk evaluation. A stepwise algorithm identified and selected predictors from demographic characteristics, physical examination, laboratory results, medical history, medication and health care utilization, to develop a risk prediction model. The main outcome was incident HF, defined by HHF. The C statistic and Brier score were used to assess model performance.

Results: In total, 9649 patients with diabetes free of HF were used, with median follow-up of 4 years and 299 incident hospitalization of HF events. The model identified several predictors for the 10-year HF incidence risk score 'DM-CURE': socio-Demographic [education, age at type 2 diabetes (T2DM) diagnosis], Metabolic (glycated haemoglobin, systolic blood pressure, body mass index, high-density lipoproteins), diabetes-related Complications (myocardial infarction, revascularization, cardiovascular medications, neuropathy, hypertension duration, albuminuria, urine albumin-to-creatinine ratio, End Stage Kidney Disease), and health care Utilization (all-cause hospitalization, emergency room visits) for Risk Evaluation. Among them, the strongest impact factors for future HF were age at T2DM diagnosis, health care utilization and cardiovascular disease-related variables. The model showed good discrimination (C statistic: 0.838, 95% CI: 0.821-0.855) and calibration (Brier score: 0.006, 95% CI: 0.006-0.007) in the ACCORD data and good performance in the validation data (Harmony: C statistic: 0.881, 95% CI: 0.863-0.899; CRIC: C statistic: 0.813, 95% CI: 0.794-0.833). The 10-year risk of incident HF increased in a graded fashion, from ≤1% in quintile 1 (score ≤14), 1%-5% in quintile 2 (score 15-23), 5%-10% in quintile 3 (score 24-27), 10%-20% in quintile 4 (score 28-33) and ≥20% in quintile 5 (score >33).

Conclusions: The DM-CURE model and score were useful for population risk stratification of incident HHF among patients with T2DM and can be easily applied in clinical practice.

Keywords: cardiovascular; diabetes complications; disease; heart failure; type 2 diabetes.

FIGURE 1

The receiver operating characteristic curve for the DM-CURE (socio-Demographic variables, Metabolic, diabetes-related Complication factors, and health care Utilization for Risk Evaluation) model for predicting incident HF in the external validation data set (A) Harmony Outcome trial and (B) Chronic Renal Insufficiency Cohort (CRIC) study