Predicting the Time to Relapse Following Withdrawal from Different Biologics in Patients with Psoriasis who Responded to Therapy: A 12-Year Multicenter Cohort Study

Abstract

Background

For patients with psoriasis, discontinuation of biologics following remission has become more common in daily practice.

Objective

We aimed to identify predictors and construct a predictive model for time to relapse following withdrawal from biologics.

Methods

This 12-year, multicenter, observational cohort study was performed in six dermatology centers between February 2011 and February 2024. We identified biological treatment episodes in patients with moderate-to-severe psoriasis and included only treatment episodes in which a clinical response (≥ 50% reduction in Psoriasis Area and Severity Index score [PASI 50] from baseline) was achieved and the patient withdrew from biological therapy with a well-controlled status (PASI < 10 and ≥ 50% improvement in PASI from baseline). The primary outcome was time to relapse, which was defined as the period from the last biologic administration to relapse. An extended multivariate Cox proportional hazards analysis (Prentice–Williams–Peterson Gap time model) was used to predict relapse and generate a predictive model.

Results

This study screened 1613 biological treatment episodes, and 991 treatment episodes were enrolled. The time to relapse decreased significantly as the number of previous withdrawals from biological treatment increased (p < 0.001). Similarly, the time to relapse decreased significantly as the number of previous biologics used increased (p < 0.001). The maximum PASI improvement during biological treatment decreased and the PASI score at withdrawal of biological treatment increased in parallel as the number of prior withdrawals from biologics increased. The time to relapse following withdrawal was longest for interleukin (IL)-23 inhibitors (IL-23i), followed by the IL-12/23i, IL-17 inhibitors (IL-17i), and tumor necrosis factor-α inhibitors. After adjustment, multivariate Cox regression identified the following significant predictors of relapse following withdrawal: the mechanisms of action of biologics (hazard ratio [HR] for IL-17i vs IL-12/23i, 1.59; HR for IL-23i vs IL-12/23i, 0.60), number of previous withdrawals from biological treatment (HR 1.23; 95% confidence interval [CI] 1.13‒1.33), time to achieve PASI 50 (HR 1.01; 95% CI 1.00‒1.02), maximum PASI improvement on biologics (HR 0.98; 95% CI 0.98‒0.99), and PASI at the end of therapy (HR 1.03; 95% CI 1.01‒1.05). The model had good predictive and discriminative ability.

Conclusions

These results have the potential to help physicians and patients make individualized treatment decisions; information on the risk of relapse of psoriasis at specific timepoints following the withdrawal of biologics is particularly valuable for patients considering discontinuation of biologics or as-needed biologic therapy. However, the benefit and risk of repeated withdrawals of biologics should be carefully weighed, as the treatment efficacy and duration of remission decline as the number of withdrawals increases.