1486: Derivation and Internal Validation of a Disease-specific Cardiovascular Risk Prediction Model for Patients with Psoriatic Arthritis and Psoriasis

Keith Colaco¹, Ker-Ai Lee², Vinod Chandran³, Paula Harvey⁴, Richard Cook², Vincent Piguet⁴, Dafna Gladman⁵ and Lihi Eder⁶, ¹University of Toronto, Toronto, ON, Canada, ²University of Waterloo, Waterloo, ON, Canada, ³Departments of Medicine and Laboratory Medicine and Pathobiology, University of Toronto/ Schroeder Arthritis Institute, Krembil Research Institute, University Health Network, Toronto, ON, Canada, ⁴Women's College Hospital, Toronto, ON, Canada, ⁵Toronto Western Hospital, Schroeder Arthritis Institute, Toronto, ON, Canada, ⁶Women’s College Research Institute, Department of Medicine, University of Toronto, Toronto, ON, Canada

Background/Purpose: Cardiovascular risk in patients with psoriatic disease (PsD) may be underestimated by conventional scoring systems. We derived and internally validated a 5-year disease-specific cardiovascular risk prediction model for patients with PsD.

Methods: Participants from a longitudinal PsD cohort without a prior history of cardiovascular events who were followed from 1992 to 2020 were analyzed. Data on cardiovascular risk factors, and PsD-related features that included measures of musculoskeletal and skin inflammation, patient-reported outcomes and medications were obtained from the cohort's database. The study outcome included a composite cardiovascular event including any of the following: angina, myocardial infarction, congestive heart failure, transient ischemic attack, stroke, revascularization procedures and cardiovascular death. Using time-varying covariates, we fit models to predict cardiovascular events within a 5-year time period. A base prediction model including traditional cardiovascular risk factors was first assessed, followed by an expanded model that included the base model and PsD-related features. Model performance was assessed using measures of discrimination and calibration, and sensitivity and specificity.

Results: A total of 1,336 patients (92% with psoriatic arthritis) were analyzed (mean age 48 ± 12.9 years, 46.8% female) (Table 1). During a mean follow-up of 6.8 years, 85 (6.4%) patients developed incident cardiovascular events. Discriminative ability of the base model (with traditional cardiovascular risk factors alone) was excellent, with an AUC of 85.5 (95% CI 81.9-89.1) (Figure 1). An expanded model that included traditional cardiovascular risk factors and the number of damaged joints did not improve risk discrimination compared to the base model (AUC 85.5, 95% CI 82.0-89.1). All models were well calibrated and appeared to be an accurate estimate of the observed number of cardiovascular events (Figure 2). Sensitivity and specificity of the 10% cut-off point for cardiovascular risk was 49% and 92%, respectively. When considering the total number of cardiovascular events, depending on the model, up to 53% of events occurred in patients who were classified as 'intermediate risk' (< 10%).

Conclusion: A prediction model that includes traditional cardiovascular risk factors alone is accurate in predicting cardiovascular risk in patients with PsD, showing excellent discrimination and calibration in this patient population.
Table 1 - Baseline characteristics of the study population.

Figure 1. Receiver operating characteristic (ROC)-curve for the different risk prediction models. Comparison of base model (traditional CV risk factors) and expanded model (traditional CV risk factors plus other disease-related factors) for prediction of cardiovascular events.

Figure 2 - Observed (grey) versus predicted (white) probability of CV events in deciles of predicted risk, for the base (A), expanded (B), and sensitivity analysis (C) risk prediction models.
Disclosures: K. Colaco, None; K. Lee, None; V. Chandran, AbbVie, AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Janssen, Novartis, Amgen, Pfizer Inc, UCB; P. Harvey, None; R. Cook, None; V. Piguet, None; D. Gladman, AbbVie, Amgen, Eli Lilly, Janssen, Gilead, Novartis, Pfizer, Bristol-Myers Squibb(BMS), Galapagos, UCB Pharma, Celgene; L. Eder, AbbVie, Lilly, Novartis, UCB, Pfizer.