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Development and Validation of a Nomogram for Predicting Long-Term Net Adverse Clinical Events in High Bleeding Risk
Junyan Zhang1, Zhongxiu Chen1, Ran Liu2
1Department of Cardiology, West China Hospital of Sichuan University, 610041 Chengdu, Sichuan, China.
Insights
A new nomogram predicts 1-year net adverse clinical events (NACEs) in high bleeding risk patients undergoing percutaneous coronary intervention (PCI-HBR). Key predictors include chronic kidney disease and multivessel disease, showing strong predictive ability.
Area of Science:
- Cardiology
- Interventional Cardiology
- Clinical Prediction Modeling
Background:
- Percutaneous coronary intervention (PCI) in high bleeding risk (HBR) patients requires accurate prognostic tools.
- Existing criteria (ARC-HBR) define HBR, but prognostic predictors need further exploration.
- An effective prediction model is crucial for managing PCI-HBR patients.
Purpose of the Study:
- To develop and validate a prognostic prediction model for 1-year net adverse clinical events (NACEs) in PCI-HBR patients.
- To construct a nomogram based on identified risk factors.
- To assess the model's predictive ability, calibration, and clinical utility.
Main Methods:
- Prospective enrollment of 1512 PCI-HBR patients (May 2022-April 2024).
- Cohort split into training (70%) and internal validation (30%) sets.
- LASSO and multivariable Cox regression used for variable selection and model development; nomogram construction.
- NACEs defined as death, myocardial infarction, ischemic stroke, or BARC grade 3-5 bleeding.
Main Results:
- Five significant risk factors identified: chronic kidney disease, left main stem lesion, multivessel disease, triglycerides (TG), and creatine kinase-myocardial band (CK-MB).
- A prognostic nomogram was constructed using these factors.
- The nomogram demonstrated strong predictive ability for 1-year NACE-free survival (AUC = 0.728) with favorable accuracy and discrimination in internal validation.
Conclusions:
- A validated nomogram can predict 1-year NACE outcomes in PCI-HBR patients.
- The model shows strong predictive capability and clinical utility.
- Further validation in diverse populations is recommended to enhance accuracy.
Background:
Patients with a high risk of bleeding undergoing percutaneous coronary intervention (PCI-HBR) were provided consensus-based criteria by the Academic Research Consortium for High Bleeding Risk (ARC-HBR). However, the prognostic predictors in this group of patients have yet to be fully explored. Thus, an effective prognostic prediction model for PCI-HBR patients is required.
Methods:
We prospectively enrolled PCI-HBR patients from May 2022 to April 2024 at West China Hospital of Sichuan University. The cohort was randomly divided into training and internal validation sets in a ratio of 7:3. The least absolute shrinkage and selection operator (LASSO) regression algorithm was employed to select variables in the training set. Subsequently, a prediction model for 1-year net adverse clinical events (NACEs)-free survival was developed using a multivariable Cox regression model, and a nomogram was constructed. The outcome of the NACEs is defined as a composite endpoint that includes death, myocardial infarction, ischemic stroke, and Bleeding Academic Research Consortium (BARC) grade 3-5 major bleeding. Validation was conducted exclusively using the internal validation cohort, assessing the discrimination, calibration, and clinical utility of the nomogram.
Results:
This study included 1512 patients with PCI-HBR, including 1058 in the derivation cohort and 454 in the validation cohort. We revealed five risk factors after LASSO regression, Cox regression, and clinical significance screening. These were then utilized to construct a prognostic prediction nomogram, including chronic kidney disease, left main stem lesion, multivessel disease, triglycerides (TG), and creatine kinase-myocardial band (CK-MB). The nomogram exhibited strong predictive ability (the area under the curve (AUC) to predict 1-year NACE-free survival was 0.728), displaying favorable levels of accuracy, discrimination, and clinical usefulness in the internal validation cohort.
Conclusions:
This study presents a nomogram to predict 1-year NACE outcomes in PCI-HBR patients. Internal validation showed strong predictive capability and clinical utility. Future research should validate the nomogram in diverse populations and explore new predictors for improved accuracy.
Clinical Trial Registration:
The data for this study were obtained from the PPP-PCI registry, NCT05369442 (https://clinicaltrials.gov/study/NCT05369442).
