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Updated: Nov 1, 2025

Dynamic Adhesion Assay for the Functional Analysis of Anti-adhesion Therapies in Inflammatory Bowel Disease
Published on: September 20, 2018
Flares as dynamic predictive factor of response to adalimumab in hidradenitis suppurativa: real-life data
Raffaele D Caposiena Caro1, Andrea Chiricozzi2, Andrea Sechi3
1Unit of Dermatology, Department of Systems Medicine, Tor Vergata University, Rome, Italy - dcaposiena@hotmail.com.
Background:
Hidradenitis suppurativa (HS) is characterized by periodic worsening of both clinical manifestations and symptoms. The aim of this study was to investigate the role of flare outbreak as a possible predictive factor of response to adalimumab.
Methods:
One hundred fifteen HS patients in treatment with adalimumab, with moderate-severe HS, ≥3 abscesses and inflammatory-nodules (ANs) from 5 Italian centers were included in this retrospective analysis. The information about gender, ages at onset/baseline, therapeutic delay, family history, body mass index, smoking, comorbidities, phenotypes, body areas, severity indexes at baseline was collected. Baseline characteristics, total number and timeline of flares were analyzed by regression and survival analysis with Hidradenitis Suppurativa Clinical Response (HiSCR).
Results:
During the observational period, 80.9% of patients developed flares, detecting 252 flares. Univariate model identified five factors associated with the absence of response: age (P=0.020), comorbidities (P=0.030), genital-perineal involvement (P=0.004), no response at week 12 (P=0.027), and flares outbreak (P=0.010). Joint analysis of recurrent and terminal events showed a positive correlation between flare recurrence and no response (P<0.001). Among the identified variables associated with poor response to the therapy: occurrence of a flare before week 12 was the one with the highest risk of no response (P<0.001).
Conclusions:
The analysis of a "dynamic" variable, as flares evaluation together with an appropriate clinical baseline assessment can be a useful approach to predict the middle-long-term response to adalimumab.
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