Derivation and Internal Validation of a Disease-Specific Cardiovascular Risk Prediction Model for Patients With Psoriatic Arthritis and Psoriasis.

Autor: Colaco, Keith, Ker-Ai Lee, Akhtari, Shadi, Winer, Raz, Chandran, Vinod, Harvey, Paula, Cook, Richard J., Piguet, Vincent, Gladman, Dafna D., Eder, Lihi
Předmět:
MYOCARDIAL infarction risk factors
CARDIOVASCULAR disease prevention
HEART failure risk factors
CARDIOVASCULAR disease related mortality
CARDIOVASCULAR diseases risk factors
PSORIATIC arthritis
PSORIASIS
CONFIDENCE intervals
RESEARCH methodology
MAJOR adverse cardiovascular events
MULTIPLE regression analysis
NONSTEROIDAL anti-inflammatory agents
REGRESSION analysis
ACQUISITION of data
ANGINA pectoris
RISK assessment
SEVERITY of illness index
ANTIRHEUMATIC agents
THEORY
RESEARCH funding
DESCRIPTIVE statistics
QUESTIONNAIRES
MEDICAL records
MYOCARDIAL revascularization
BLOOD sedimentation
HEALTH behavior
PREDICTION models
SENSITIVITY & specificity (Statistics)
RECEIVER operating characteristic curves
DATA analysis software
LONGITUDINAL method
BEHAVIOR modification
DISEASE risk factors
DISEASE complications
Zdroj: Arthritis & Rheumatology; Feb2024, Vol. 76 Issue 2, p238-246, 9p
Abstrakt: Objective. To address suboptimal cardiovascular risk prediction in patients with psoriatic disease (PsD), we developed and internally validated a five-year disease-specific cardiovascular risk prediction model. Methods. We analyzed data from a prospective cohort of participants with PsD without a history of cardiovascular events. Traditional cardiovascular risk factors and PsD-related measures of disease activity were considered as potential predictors. The study outcome included nonfatal and fatal cardiovascular events. A base prediction model included 10 traditional cardiovascular risk factors. Eight PsD-related factors were assessed by adding them to the base model to create expanded models, which were controlled for PsD therapies. Variable selection was performed using Least Absolute Shrinkage and Selection Operator (LASSO) penalized regression with 10-fold cross-validation. Model performance was assessed using measures of discrimination and calibration and measures of sensitivity and specificity. Results. Between 1992 and 2020, 85 of 1,336 participants developed cardiovascular events. Discrimination of the base model (with traditional cardiovascular risk factors alone) was excellent, with an area under the receiver operator characteristic curve (AUC) of 85.5 (95% confidence interval [CI] 81.9–89.1). Optimal models did not select any of the tested disease-specific factors. In a sensitivity analysis, which excluded lipid lowering and antihypertensive treatments, the number of damaged joints was selected in the expanded model. However, this model did not improve risk discrimination compared to the base model (AUC 85.5, 95% CI 82.0–89.1). Conclusion. Traditional cardiovascular risk factors alone are effective in predicting cardiovascular risk in patients with PsD. A risk score based on these factors performed well, indicating excellent discrimination and calibration. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index
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