Novel Predictive Model Evaluates Risk for Psoriatic Arthritis in Patients With Plaque Psoriasis

Researchers developed a novel prediction model to evaluate the risk for psoriatic arthritis in plaque psoriasis, using available patient characteristics and clinical manifestations.

A novel predictive nomogram was shown to evaluate the risk for psoriatic arthritis (PsA) in patients with plaque psoriasis, with good efficiency, according to results of an analysis published in Frontiers in Immunology.

The researchers sought to establish an effective, simple predictive model to determine risk for PsA among patients with plaque psoriasis, using characteristics and clinical manifestations available at the time of a patient’s visit. The prediction model was developed to assist in the education and personalized treatment of patients with high-risk PsA, as well as improve the overall quality of life of patients with psoriasis.

The retrospective study was conducted among patients with psoriasis or PsA who were enrolled from the Department of Dermatology at Xiangya Hospital of Central South University in Changsha, China, between January 2017 and January 2020. Demographic characteristics, skin lesions, and nail clinical manifestations were collected from all participants.

A total of 746 patients with plaque psoriasis and 109 patients with PsA were included in the study. In addition, 584 patients with plaque psoriasis and 105 patients with PsA visiting Xiangya Hospital of Central South University were enrolled in the study as external validation cohort 1, and 53 patients with plaque psoriasis and 37 patients with PsA visiting Dalian Dermatosis Hospital in Delian, China, as external validation cohort 2.

Age at symptom onset, duration of having plaque psoriasis, nail involvement, onychorrhexis, erythematous lunula, oil drop, and subungual hyperkeratosis were all shown to be good predictors for performance of the nomogram (P <.05). The predictive model demonstrated good calibration and discrimination (C-index, 0.759; 95% CI, 0.707-0.811), which was determined to be 0.741 through bootstrapping validation. The C-index was found to be 0.844 and 0.845 via external validation cohort 1 and external validation cohort 2, respectively, thus indicating good discrimination power of the prediction model.

The area under the curve (AUC) for the prediction nomogram was 0.7578092, with a sensitivity of 69.7% and a specificity of 72.1%. The AUC for the probability of PsA was 0.844, with a sensitivity of 81.0% and a specificity of 78.3%, in external validation cohort 1; the AUC was 0.845, with a sensitivity of 83.3% and a specificity of 77.4%, in external validation cohort 2. The decision curve demonstrated good effect of the PsA nomogram in guiding clinical practice.

The researchers concluded, “The assessment of the risk [for] PsA in plaque psoriasis patients can help physicians guide patients’ lifestyles and make an individualized treatment plan.”


Liu P, Kuang Y, Ye L, et al. Predicting the risk of psoriatic arthritis in plaque psoriasis patients: development and assessment of a new predictive nomogram. Front Immunol. Published online January 20, 2022. doi:10.3389/fimmu.2021.740968   

This article originally appeared on Rheumatology Advisor