对于银屑病患者来说，缓解后停用生物制剂在日常实践中已变得更加常见。我们的目的是确定预测因素并构建生物制剂退出后复发时间的预测模型。这项为期 12 年的多中心观察性队列研究在2011 年 2 月至 2024 年 2 月期间，我们对六个皮肤科中心进行了研究。我们确定了中度至重度银屑病患者的生物治疗次数，并且仅包括临床缓解（银屑病面积和严重性指数评分减少 50% [PASI 50]）的治疗次数达到了与基线相比），并且患者退出了生物治疗，并且状态得到良好控制（PASI < 10 且 PASI 与基线相比改善≥ 50%）。主要结局是复发时间，定义为从最后一次生物制剂给药到复发的时间。使用扩展的多变量Cox比例风险分析（Prentice-Williams-Peterson Gap time模型）来预测复发并生成预测模型。本研究筛选了1613次生物治疗，并入组了991次治疗。随着先前退出生物治疗的次数增加，复发时间显着缩短 (p < 0.001)。同样，随着先前使用的生物制剂数量的增加，复发时间显着缩短 (p < 0.001)。随着先前退出生物制剂次数的增加，生物治疗期间的最大 PASI 改善下降，而退出生物治疗时的 PASI 评分则平行增加。白细胞介素 (IL)-23 抑制剂 (IL-23i) 停药后复发时间最长，其次是 IL-12/23i、IL-17 抑制剂 (IL-17i) 和肿瘤坏死因子-α 抑制剂。调整后，多变量 Cox 回归确定了以下停药后复发的重要预测因子：生物制剂的作用机制（IL-17i 与 IL-12/23i 的风险比 [HR]，1.59；IL-23i 与 IL-12 的 HR） /23i, 0.60)、之前退出生物治疗的次数（HR 1.23；95% 置信区间 [CI] 1.13-1.33）、达到 PASI 50 的时间（HR 1.01；95% CI 1.00-1.02）、最大 PASI 改善生物制剂（HR 0.98；95% CI 0.98-0.99）和治疗结束时的 PASI（HR 1.03；95% CI 1.01-1.05）。该模型具有良好的预测和判别能力。这些结果有可能帮助医生和患者做出个体化的治疗决策；关于停用生物制剂后特定时间点银屑病复发风险的信息对于考虑停止生物制剂或按需生物制剂治疗的患者特别有价值。然而，应仔细权衡重复停用生物制剂的益处和风险，因为治疗效果和缓解持续时间会随着停用次数的增加而下降。© 2024。作者获得 Springer Nature Switzerland AG 的独家许可。

For patients with psoriasis, discontinuation of biologics following remission has become more common in daily practice.We aimed to identify predictors and construct a predictive model for time to relapse following withdrawal from biologics.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.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.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.© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.