Identifying Top Predictors of Change in Noncalcified Coronary Burden in Psoriasis by Machine Learning Over 1-Year. Issue 2 (April 2021)

• Record Type: Journal Article
• Authors: Munger, Eric; Dey, Amit K.; Rodante, Justin; Playford, Martin P.; Sorokin, Alexander V.; Tian, Xin; Wu, Colin O.; Hasan, Ahmed; Chen, Marcus Y.; Gelfand, Joel M.; Jafri, Mohsin Saleet; Mehta, Nehal N.
• Is Part Of: Journal of psoriasis and psoriatic arthritis. Volume 6:Issue 2(2021)
• Page Start: 113
• Page End: 117
• Publication Date: 2021-04
• Subjects: machine learning -- coronary artery disease -- inflammation -- psoriasis; Psoriasis -- Periodicals; Psoriasis -- Treatment -- Periodicals; Psoriatic arthritis -- Periodicals; Psoriatic arthritis -- Treatment -- Periodicals; Electronic journals; 616.722
• DOI: 10.1177/24755303211000757
• Languages: English
• ISSNs: 2475-5303

Abstract

Background: Psoriasis is associated with accelerated non-calcified coronary burden (NCB) by coronary computed tomography angiography (CCTA). Machine learning (ML) algorithms have been shown to effectively identify cardiometabolic variables with NCB in cross-sectional analysis. Objective: To use ML methods to characterize important predictors of change in NCB by CCTA in psoriasis over 1-year of observation. Methods: The analysis included 182 consecutive patients with 80 available variables from the Psoriasis Atherosclerosis Cardiometabolic Initiative, a prospective, observational cohort study at baseline and 1-year using the random forest regression algorithm. NCB was assessed at baseline and 1-year from CCTA. Results: Using ML, we identified variables of high importance in the context of predicting changes in NCB. For the cohort that improved NCB (n = 102), top baseline variables were cholesterol (total and HDL), white blood cell count, psoriasis area severity index score, and diastolic blood pressure. Top predictors of 1-year change were change in visceral adiposity, white blood cell count, total cholesterol, c-reactive protein, and absolute lymphocyte count. For the cohort that worsened NCB (n = 80), the top baseline variables were HDL cholesterol related including apolipoprotein A1, basophil count, and psoriasis area severity index score, and top predictors of 1-year change were change in apoA, apoB, and systolic blood pressure. Conclusion: ML methods ranked predictors of progression and regression of NCB in psoriasis over 1 year providing strong evidence to focus on treating LDL, blood pressure, and obesity; as well as the importance of controlling cutaneous disease in psoriasis.