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Stratification of coronary artery disease patients for revascularization procedure based on estimating adverse
Sebastian Pölsterl1, Maneesh Singh2, Amin Katouzian3
1Computer Aided Medical Procedures, Technische Universität München, Boltzmannstr. 3, 85748, Garching b. München, Germany. sebastian.poelsterl@tum.de.
Insights
This study developed a personalized treatment strategy for coronary atherosclerosis, reducing adverse events by up to 31.2% and saving costs. The subgroup-specific model improved risk prediction for percutaneous coronary intervention (PCI) versus traditional methods.
Area of Science:
- Cardiovascular Medicine
- Medical Informatics
- Health Economics
Background:
- Percutaneous coronary intervention (PCI) is a common treatment for coronary atherosclerosis but has a higher revascularization rate than coronary artery bypass grafting surgery.
- PCI is cost-effective only for a subset of patients, necessitating risk estimation for personalized treatment strategies.
- Current treatment strategies for coronary atherosclerosis do not fully account for patient-specific risk factors.
Purpose of the Study:
- To develop patient-subgroup-specific classifiers for predicting adverse events associated with different treatment options for coronary atherosclerosis.
- To create a personalized treatment strategy that optimizes effectiveness, safety, and cost.
- To compare the proposed subgroup-specific model with conventional classification and current clinical practice.
Main Methods:
- Modeled clinical knowledge to identify patient-subgroup-specific classifiers for risk prediction.
- Constructed hierarchical models for subgroup-specific feature interpretation and aggregation.
- Implemented a two-stage test with optimized predictive values, analyzing 2,377 patients undergoing PCI.
Main Results:
- The proposed method reduced adverse events by 25.0% at 36 months and 31.2% at 12 months compared to current practice.
- Estimated cost savings per patient were $693 at 12 months and $794 at 36 months.
- The subgroup-specific model improved prediction accuracy, increasing the area under the ROC curve from 0.57 to 0.61 for restenosis and 0.76 to 0.85 for hazardous events.
Conclusions:
- The study demonstrated the efficacy of personalized treatment strategies for coronary atherosclerosis.
- Bare-metal stents and coronary artery bypass grafting surgery were shown to be effective for specific patient subsets.
- This approach has the potential to significantly impact treatment costs for coronary atherosclerosis.
Background:
Percutaneous coronary intervention (PCI) is the most commonly performed treatment for coronary atherosclerosis. It is associated with a higher incidence of repeat revascularization procedures compared to coronary artery bypass grafting surgery. Recent results indicate that PCI is only cost-effective for a subset of patients. Estimating risks of treatment options would be an effort toward personalized treatment strategy for coronary atherosclerosis.
Methods:
In this paper, we propose to model clinical knowledge about the treatment of coronary atherosclerosis to identify patient-subgroup-specific classifiers to predict the risk of adverse events of different treatment options. We constructed one model for each patient subgroup to account for subgroup-specific interpretation and availability of features and hierarchically aggregated these models to cover the entire data. In addition, we deviated from the current clinical workflow only for patients with high probability of benefiting from an alternative treatment, as suggested by this model. Consequently, we devised a two-stage test with optimized negative and positive predictive values as the main indicators of performance. Our analysis was based on 2,377 patients that underwent PCI. Performance was compared with a conventional classification model and the existing clinical practice by estimating effectiveness, safety, and costs for different endpoints (6 month angiographic restenosis, 12 and 36 month hazardous events).
Results:
Compared to the current clinical practice, the proposed method achieved an estimated reduction in adverse effects by 25.0% (95% CI, 17.8 to 30.2) for hazardous events at 36 months and 31.2% (95% CI, 25.4 to 39.0) for hazardous events at 12 months. Estimated total savings per patient amounted to $693 and $794 at 12 and 36 months, respectively. The proposed subgroup-specific method outperformed conventional population wide regression: The median area under the receiver operating characteristic curve increased from 0.57 to 0.61 for prediction of angiographic restenosis and from 0.76 to 0.85 for prediction of hazardous events.
Conclusions:
The results of this study demonstrated the efficacy of deployment of bare-metal stents and coronary artery bypass grafting surgery for subsets of patients. This is one effort towards development of personalized treatment strategies for patients with coronary atherosclerosis that could significantly impact associated treatment costs.
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