Prediction Model for Osteopenia in Patients With Psoriasis

Overview

This study aims to develop a clinical prediction model for osteopenia in patients with psoriasis. By retrospectively analyzing demographic, laboratory, and lifestyle variables, the investigators will identify risk factors associated with decreased bone mineral density (BMD) in this population. The study will facilitate the identification of high-risk individuals and provide evidence for early screening and intervention strategies.

Psoriasis is a chronic inflammatory skin disease associated with various systemic comorbidities, including an increased risk of bone loss. Recent studies suggest that patients with psoriasis have a significantly higher incidence of osteopenia and osteoporosis than the general population, potentially due to systemic inflammation and shared risk factors. All enrolled patients will undergo dual-energy X-ray absorptiometry (DEXA) scans to assess bone mineral density (BMD). Based on the results, patients will be categorized into normal BMD and osteopenia groups. Demographic data (age, sex, height, weight, BMI), clinical variables (disease duration, CRP, ESR, blood glucose, blood lipids, blood pressure), and lifestyle factors (smoking, alcohol use) will be collected and analyzed. Univariate and multivariate logistic regression analyses will be performed to identify independent risk factors. A prediction model will be constructed and evaluated using ROC curve analysis to assess sensitivity, specificity, and accuracy. The objective of this study is to develop a validated tool to assist clinicians in identifying patients with psoriasis at high risk for osteopenia, thereby enabling early screening and preventive management to reduce future fracture risk.

Conditions

Eligibility

Locations (1)

Outcomes