Journal Article

Development and validation of a risk prediction nomogram for in-stent restenosis in patients undergoing percutaneous coronary intervention

He, Wenbo, Lei, Jiyong, Wang, Xiaoying, Qiu, Qinfang, Luo, Da, Xu, Changwu, Hu, Yingying

2021

Overview

Background This study aimed to develop and validate a nomogram to predict probability of in-stent restenosis (ISR) in patients undergoing percutaneous coronary intervention (PCI). Methods Patients undergoing PCI with drug-eluting stents between July 2009 and August 2011 were retrieved from a cohort study in a high-volume PCI center, and further randomly assigned to training and validation sets. The least absolute shrinkage and selection operator (LASSO) regression model was used to screen out significant features for construction of nomogram. Multivariable logistic regression analysis was applied to build a nomogram-based predicting model incorporating the variables selected in the LASSO regression model. The area under the curve (AUC) of the receiver operating characteristics (ROC), calibration plot and decision curve analysis (DCA) were performed to estimate the discrimination, calibration and utility of the nomogram model respectively. Results A total of 463 patients with DES implantation were enrolled and randomized in the development and validation sets. The predication nomogram was constructed with five risk factors including prior PCI, hyperglycemia, stents in left anterior descending artery (LAD), stent type, and absence of clopidogrel, which proved reliable for quantifying risks of ISR for patients with stent implantation. The AUC of development and validation set were 0.706 and 0.662, respectively, indicating that the prediction model displayed moderate discrimination capacity to predict restenosis. The high quality of calibration plots in both datasets demonstrated strong concordance performance of the nomogram model. Moreover, DCA showed that the nomogram was clinically useful when intervention was decided at the possibility threshold of 9%, indicating good utility for clinical decision-making. Conclusions The individualized prediction nomogram incorporating 5 commonly clinical and angiographic characteristics for patients undergoing PCI can be conveniently used to facilitate early identification and improved screening of patients at higher risk of ISR.

• Publisher: BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
• Subject: Accuracy / Aged / Angiology / Angioplasty / Blood Transfusion Medicine / Calibration / Cardiac Surgery / Cardiology / Cardiovascular disease / Care and treatment / Clinical Decision-Making / Clopidogrel / Complications and side effects / Coronary Angiography / Coronary Artery Disease - diagnostic imaging / Coronary Artery Disease - therapy / Coronary heart disease / Coronary restenosis / Coronary Restenosis - diagnostic imaging / Coronary Restenosis - etiology / Decision making / Decision Support Techniques / Drug delivery / Evaluation / Female / Health aspects / Humans / Hyperglycemia / Implants / In-stent restenosis / Internal Medicine / Laboratories / Male / Medicine / Medicine & Public Health / Middle Aged / Nomogram / Nomograms / Nomography (Mathematics) / Patients / Percutaneous coronary intervention / Percutaneous Coronary Intervention - adverse effects / Percutaneous Coronary Intervention - instrumentation / Prediction models / Predictive Value of Tests / Predictors / Probability / Prognosis / Registries / Regression analysis / Reproducibility of Results / Restenosis / Risk Assessment / Risk Factors / Statistical analysis / Stents / Time Factors / Transluminal angioplasty / Treatment Outcome