Related Experiment Videos
On the prediction and prevention of myocardial infarctions: models based on retrospective and doubly censored
1Owen Graduate School of Management, Vanderbilt University, Nashville, TN 37203, USA. bruce.cooil@owen.vanderbilt.edu
Insights
An age-sex based calcium score percentile (CS%) is a strong predictor of myocardial infarction (MI). This score, along with smoking, helps assess cardiovascular disease risk, enabling earlier detection and intervention for coronary heart disease.
Area of Science:
- Cardiology
- Medical Imaging
- Preventive Medicine
Background:
- Coronary heart disease (CHD) poses a significant public health burden.
- Early detection of pre-clinical CHD is crucial for reducing its impact.
- Coronary artery calcification, identified via electron beam tomography (EBT) calcium scoring, reflects atherosclerotic plaque development.
Purpose of the Study:
- To evaluate the predictive value of an age-sex based calcium score percentile (CS%) for myocardial infarction (MI).
- To examine the relationship between CS% and traditional cardiovascular risk factors.
- To develop models for predicting MI risk using CS% and other risk factors.
Main Methods:
- Analysis of two patient groups: retrospective (MI survivors) and prospective (asymptomatic subjects followed for MI).
- Utilized logistic regression models to compare groups and develop an MI mortality model.
- Employed joint and event-time regression models incorporating CS%, smoking, and traditional risk factors.
Main Results:
- CS% emerged as a significant predictor of MI, independent of traditional risk factors.
- The interaction between CS% and smoking was a key predictor in both joint and event-time models.
- Models demonstrated subadditive effects between smoking and CS%, providing insights into combined risk.
Conclusions:
- Elevated CS% levels are associated with increased MI risk.
- CS% is an invaluable tool for early CHD detection and risk stratification.
- Integrating CS% into risk assessment models enhances prediction accuracy for cardiovascular events.
Abstract:
Early detection of coronary heart disease (CHD) in its pre-clinical stages may offer a way to reduce the impact of this endemic disease on society. Coronary calcification accompanies the development of an atherosclerotic plaque, the pathological substrate of CHD, and its identification is currently possible by means of electron beam tomography (EBT). This is a non-invasive imaging test that quantifies the extent of coronary artery plaque calcification by means of a calcium score. In this study, we show that an age-sex based calcium score percentile (CS%) provides an invaluable predictor for myocardial infarction (MI), and examine how CS% is related to traditional risk factors. We study two separate groups of patients: 172 patients who underwent EBT screening after surviving an MI (retrospective group); and 676 asymptomatic subjects who were screened and followed for several years for the occurrence of an MI (prospective group). We use CS% with traditional risk factors in logistic regression models to: (1) compare patients in the retrospective and prospective groups, and (2) develop a mortality model for MIs that occurred in the prospective group. These logistic regressions are used to develop a joint model for the relative log-odds of an MI, which is non-linear in the covariates of the mortality model. We also use baseline covariates in the prospective group to fit an event-time regression model and estimate probabilities for 2 and 3 year exposure periods. The event-time regression provides independent estimates of the relative odds that are associated with risk factors. CS%, smoking, and their interaction were preeminent as predictors in the joint model for the relative odds of an MI and in the event-time regression, although the effects of smoking and CS% were generally subadditive. These models provide important information on the risks associated with elevated CS% levels.
