A Clinically Accessible Nomogram for Identifying Likely Psoriatic Arthritis Among Patients with Psoriasis: A Multicenter Cross-Sectional Study.

Background/Objectives: Psoriatic arthritis (PsA) affects up to 30% of psoriasis patients but remains underdiagnosed due to heterogeneous early manifestations. Existing tools rely on advanced imaging or biomarkers, limiting feasibility. This study aimed to develop a simple nomogram, using routinely available clinical features to identify patients with likely PsA. Methods: This multicenter cross-sectional study enrolled adult psoriasis patients from two tertiary hospitals (training: n = 884; validation: n = 690). PsA was diagnosed using the Classification Criteria for Psoriatic Arthritis (CASPAR) by rheumatologists and dermatologists who were blinded to each other's assessments. Thirteen candidate predictors, including demographics, disease history, and lesion characteristics, were prespecified. Independent predictors were selected using least absolute shrinkage and selection operator (LASSO) regression, followed by multivariable logistic regression. Internal validation used 1000 bootstrap resamples, followed by temporal-geographic validation. Performance was assessed using area under the curve (AUC), calibration plots, the Hosmer-Lemeshow test, decision curve analysis (DCA), and clinical impact curves (CIC). Sensitivity analyses included E-value analysis for unmeasured confounding and alternative model specifications. Results: Five independent predictors were identified: uveitis (odds ratio (OR): 5.23, 95% confidence interval (CI): 1.94-14.10), inverse lesions (OR: 1.65, 95% CI: 1.09-2.48), scalp lesions (OR: 2.97, 95% CI: 1.45-6.10), nail lesions (OR: 5.98, 95% CI: 3.69-9.68), and arthralgia (OR: 20.23, 95% CI: 13.14-31.13). The nomogram showed good discrimination (AUC: 0.885 training, 0.874 validation), with good calibration and clinical utility confirmed by DCA and CIC. Conclusions: This nomogram, integrating five clinically accessible predictors, offers a practical tool to identify psoriasis patients with likely PsA, supporting timely referral in tertiary dermatology outpatient settings.