Development and validation of the CANHEART population-based laboratory prediction models for atherosclerotic cardiovascular disease

Background — Prediction of atherosclerotic cardiovascular disease (ASCVD) in primary prevention assessments exclusively with laboratory results may facilitate automated risk reporting and improve uptake of preventive therapies.

Objective —To develop and validate sex-specific prediction models for ASCVD using age and routine laboratory tests and compare their performance with that of the pooled cohort equations (PCEs).

Design — Derivation and validation of the CANHEART (Cardiovascular Health in Ambulatory Care Research Team) Lab Models.

Setting — Population-based cohort study in Ontario, Canada.

Participants — A derivation and internal validation cohort of adults aged 40 to 75 years without cardiovascular disease from April 2009 to December 2015; an external validation cohort of primary care patients from January 2010 to December 2014.

Measurements — Age and laboratory predictors measured in the outpatient setting included serum total cholesterol, high-density lipoprotein cholesterol, triglycerides, hemoglobin, mean corpuscular volume, platelets, leukocytes, estimated glomerular filtration rate, and glucose. The ASCVD outcomes were defined as myocardial infarction, stroke, and death from ischemic heart or cerebrovascular disease within 5 years.

Results — Sex-specific models were developed and internally validated in 2 160 497 women and 1 833 147 men. They were well calibrated, with relative differences less than 1% between mean predicted and observed risk for both sexes. The c-statistic was 0.77 in women and 0.71 in men. External validation in 31 697 primary care patients showed a relative difference less than 14% and an absolute difference less than 0.3 percentage points in mean predicted and observed risks for both sexes. The c-statistics for the laboratory models were 0.72 for both sexes and were not statistically significantly different from those for the PCEs in women (change in c-statistic, −0.01 [95% CI, −0.03 to 0.01]) or men (change in c-statistic, −0.01 [CI, −0.04 to 0.02]).

Limitation — Medication use was not available at the population level.

Conclusion — The CANHEART Lab Models predict ASCVD with similar accuracy to more complex models, such as the PCEs.