China Journal of Leprosy and Skin Diseases ›› 2026, Vol. 42 ›› Issue (10): 696-704.doi: 10.12144/zgmfskin202610696

• Original Articles • Previous Articles     Next Articles

Development and validation of active surveillance trigger tools for adverse drug events in psoriasis

ZHUO Yuqian1, PENG Shangjie1, ZHANG Jinxin2, LI Wei1, LIANG Jingyao1, ZHONG Jinbao1, WANG Meng1, LI Man1, ZHANG Sanquan1, ZHU Huilan1, ZHANG Xibao1, ZHANG Yuyan1   

  1. 1 Institute of Dermatology Guangzhou Medical University, Guangzhou Dermatology Hospital, Guangzhou 510095, China; 2 School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
  • Online:2026-10-15 Published:2026-10-09

Abstract: Objective: To develop a trigger tools set for active surveillance of adverse drug events (ADEs) in patients with psoriasis and to evaluate its triggering performance, with the aim of strengthening medication safety in this population. Methods: The 46 initial trigger items were formed through a review of psoriasis-related guidelines, consensus, drug instructions, Global Trigger Tool white papers and literature. The items were rated and refined through two rounds of Delphi consultation. Software SPSS 25.0 was used to analyze the data. The final trigger items were determined based on the arithmetic mean (Mj ≥ the 15.87th percentile), the full-mark rate (Kj ≥ the 15.87th percentile), and the coefficient of variation (CV ≤ the 84.13th percentile) for each item. A single-center retrospective analysis was then conducted to validate the triggers. Trigger activation was assessed through automated identification of structured fields followed by manual review, and ADEs detected by the active surveillance approach were compared with those reported through the hospital's voluntary reporting system. Results: The recovery rates of questionnaires were both 100%, the authority coefficient(Cr) was>0.7, CV was<0.3, and the Kendall(W) coefficient was 0.344. Finally 48 trigger items were formulated, categorized into four dimensions: laboratory indices(16 items), clinical symptoms(22 items), concomitant medications(7 items) and intervention measures(3 items). Based on 20 335 outpatient and inpatient encounter records of patients with psoriasis in 2025, the triggers generated 2038 signals. The positive predictive value (PPV), negative predictive value (NPV), sensitivity, specificity, and overall accuracy were 45.04%, 99.72%, 93.16%, 95.70%, and 95.61%, respectively. Active surveillance identified 760 ADE cases, yielding a detection rate of 3.74%. Conclusion: By integrating the GTT and Delphi method, this study established an active surveillance trigger tools for ADEs in psoriasis patients, which is designed to facilitate precise surveillance and early warning of medication-related risks.

Key words: psoriasis, adverse drug event, trigger tools, Delphi method, active surveillance