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Enregistrement W4414137478 · doi:10.1002/jvc2.70172

Treating to Target in Hidradenitis Suppurativa: Canadian Perspectives

2025· article· en· W4414137478 sur OpenAlexaffabout
Wayne Gulliver, Irina Turchin, Tracey Brown‐Maher, Marni Wiseman, Lauren Lam, Jessica Asgarpour, Raed Alhusayen

Notice bibliographique

RevueJEADV Clinical Practice · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueHidradenitis Suppurativa and Treatments
Établissements canadiensWomen's College HospitalUniversity of ManitobaNewfoundland and Labrador Centre for Applied Health ResearchMemorial University of NewfoundlandProbity Medical ResearchUniversity of TorontoDalhousie UniversityPetroleum Research Newfoundland and LabradorSunnybrook HospitalSt. John’s Health Sciences Centre
Organismes subventionnairesnon disponible
Mots-clésHidradenitis suppurativaPsoriasisQuality of life (healthcare)DiseaseTimelineClinical PracticeDisease managementHealthcare system

Résumé

récupéré en direct d'OpenAlex

Recently published European and North American guidelines made important contributions to the management of hidradenitis suppurativa (HS) [1, 2]. While treat-to-target (TTT) for HS has been discussed in the literature, no evidence-based parameters or outcomes have been published to date [3]. While acknowledging it as a distinctly different disease, lessons learned from psoriasis can be applied, where Canadian dermatologists pioneered the TTT approach, recommending the ideal treatment targets of psoriasis area and severity index (PASI) 100, body surface area, (BSA) 0, physician global assessment (PGA) 0, with a holistic evidence-based approach [4]. Meanwhile, with recent therapeutic advances in HS, progress has been made in defining HS disease activity and outcome measures, and thus we feel it is time for a TTT approach to be applied in HS. In addition, many dermatologist colleagues do not feel confident in identifying when to escalate treatment, and given the importance of timely interventions, a TTT approach could provide some valuable guidance. To effectively manage HS, a TTT approach must combine targets related to medical and surgical therapies, focusing on reducing inflammation, preventing disease progression and scarring, and improving quality of life [3]. Therefore, we, a group of Canadian dermatologists, propose a holistic, evidence-based TTT approach with specific timelines and outcomes to facilitate management and improve outcomes in HS. We propose the treatment targets of a minimum Hidradenitis Suppurativa Clinical Response (HiSCR) 25 at Week 12, HiSCR 50 at Weeks 24–48, and International Hidradenitis Suppurativa Severity Score System (IHS4)-55 at Weeks 24–48 (see Table 1). The target of HiSCR 25 at Week 12 is a minimal target based on data from the PIONEER studies showing that continuing weekly adalimumab past Week 12 after at least partial treatment success leads to better outcomes than dose reduction or treatment interruption [1]. It is important to initiate early and appropriate treatment including the use of rescue therapies in the interim, however based on clinical experience, some patients with severe disease may require 6–12 months of treatment to see optimal results, and treatment discontinuation would not be beneficial for these patients. To this end, identifying predictors of early response is an area of interest for future research to help guide earlier decision making. IHS4-55 at Week 24–48 IHS 90–100 after Week 48 At least 4-point reduction from baseline at Week 24–48 DLQI 0–1 after Week 48 At least 30% reduction from baseline at Week 24–48 Pain NRS 0–1 after Week 48 Furthermore, with the introduction of the new targeted and biologic therapies, treatment targets of HiSCR and IHS 90–100 can be achieved beyond 48 weeks. Specifically, these proposed treatment targets were determined based on review of recently published guidelines and data from trials for approved biologic therapies (adalimumab, secukinumab) and new and emerging therapies (bimekizumab, lutikizumab, povorcitinib, sonelokimab and upadacitinib) (see Table 2). As seen in the table, clinical response measures have evolved in trials with newer agents investigating more stringent treatment targets. Looking beyond HS disease activity scores, a clinically meaningful reduction in DLQI of 4 points from baseline and at least 30% pain reduction from baseline should be achieved within 24–48 weeks of treatment. Targets should be maintained over time and improve to include no additional tunnels and no new draining tunnels (DT), DLQI 0–1 and pain NRS 0–1 after 48 weeks (Table 1). In practice, once targets are established, close monitoring is required to assess treatment response, such that if target is not achieved, treatment adjustments are made (dose, medication switch or addition, or additional surgical management) [3]. To optimize the management of HS, it is important to combine medical and surgical interventions. With respect to TTT, we suggest all surgical interventions (deroofing, surgical excision, management of scars) be completed within 12–24 months of treatment initiation. A holistic evidence-based approach is recommended, including wound care and management of comorbidities (e.g., diabetes, hypertension, obesity, inflammatory bowel disease [IBD] and anxiety/depression) through multidisciplinary collaboration. In conclusion, we feel a TTT management approach is feasible in HS. Applying a holistic approach with evidence-based outcomes and timelines will enhance our management of this life-altering progressive disease. As seen with new and emergent therapies, complete disease control with achievement of IHS4 100, HiSCR 100 and accompanying improvement in quality of life (DLQI 0 or 1) may be achieved for many of our patients. All authors contributed to the development and review of the contents of this letter to the editor. Medical writing support provided by Jordanna Bermack, PhD. Wayne Gulliver: Grants/research support: AbbVie, Amgen, Eli Lilly, Novartis, Pfizer. Honoraria for Ad Boards/Invited Talks/Consultation: AbbVie, Actelion, Amgen, Arylide, Bausch Health, Boehringer, Celgene, Cipher, Eli Lilly, Galderma, Janssen, LEO Pharma, Merck, Novartis, PeerVoice, Pfizer, Sanofi-Genzyme, Tribute, UCB, Sun Pharma, Valeant. Other: Clinical trials (study fees): AbbVie, Asana Biosciences, Astellas, Boerhinger-Ingleheim, Celgene, Corrona/National Psoriasis Foundation, Devonian, Eli Lilly, Galapagos, Galderma, Janssen, LEO Pharma, Novartis, Pfizer, Regeneron, Sun Pharma, UCB. Irina Turchin: Received honoraria and/or grants as a consultant, speaker, or investigator from AbbVie, Amgen, Apogee Therapeutics, Arcutis, Aristea, Bausch Health, Bristol Myers Squibb, Boehringer Ingelheim, Eli Lilly and Company, Galderma, Horizon Therapeutics, Inmagene Bio, Incyte, Janssen, Kiniksa, LEO Pharma, Mallinckrodt, MoonLake Immunotherapeutics, Novartis, Pfizer, Sanofi, Sun Pharma, Takeda, UCB and Ventyx Biosciences. Tracey Brown-Maher: Received honoraria and/or educational grants as consultant, speaker from Abbvie, Actelion, Amgen, Atlantic Canada Team of Dermatology (ACTD), Bausch, Boehringer Ingelheim, Bristol Myers Squibb, Celgene, Eli Lilly, Galderma, Incyte, Innomar Strategies, JAMP, Janssen, LEO Pharma, Novartis, Pfizer, Sanofi, Sun Pharma, UCB. Clinical Trials PI: AbbVie, Alumis, Amgen, Apollo therapeutics, Bausch, BioJAMP, Bristol Myers Squibb, Celgene, Celldex Therapeutics, Corrona LLC, Dermavant Sciences, Devonian Health Group, Eli Lilly, Incyte, Insmed Inc, Janssen, LEO Pharma, Novartis, Sanofi, UCB. Marni Wiseman: Received honoraria and/or grants as a consultant from AbbVie, Amgen, Arcutis, Bausch Health, Bristol Myers Squibb, Celgene, Celltrion, Eli Lilly, Galderma, Incyte, Janssen, LEO Pharma A/S, L'Oreal, Novartis, Pfizer, Sanofi, Sun Pharma, UCB. Clinical trials PI:Acelyrin, AbbVie (previously Abbott), Akros, Alumis, Apogee, Amgen, Arcutis, Asana BioSciences, AstraZeneca, Bausch Health, Bristol Myers Squibb, Celgene, Concert Pharma, Dermavant, Dermira, Dice, Eli Lilly, Evelo, Galderma, Glenmark, Incyte, Janssen, LEO Pharma A/S, Merck Frosst Canada, Moonlake, Novartis, Pfizer, Principia, PRCL Research, Sun Pharma, Regeneron, Takeda, Timber, UCB. Lauren Lam: AbbVie, Amgen, Arcutis, Beiersdorf, Bioderma, Boehringer-Ingheim, Bristol-Meyers-Squibb, Celltrion, Eli-Lily, Galderma, Janssen, JAMP Pharma, Incyte, Kenvue, LEO Pharma, L'Oreal, Novartis, Pfizer, Sanofi, Sun Pharma, UCB. Jessica Asgarpour: Abbvie, Amgen, Arcutis, Aveeno, Bausch, Beiersdorf, Bioderma, Biojamp, BMS, Boehringer, Celltrion, Eli Lilly, Fresenius Kabi, Galderma, ICPDHM, Incyte, Janssen, J&J, Leo, La roche posay, L'Oreal, Medplan, Neutrogena, Novartis, Pfizer, Polaris, RBC consultants, Sanofi, Sunpharma, UCB. Raed Alhusayen: has received personal fees from Abbvie, Bausch health, Boehringer Ingelheim, Fresenius kabi, Janssen, Novartis, Pfizer, Sandoz, and UCB; investigator fees from Abbvie, Bausch health, Incyte, and Janssen. Not applicable. The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,018
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,877
Score d'incertitude au seuil0,990

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,018
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,033
Tête enseignante GPT0,449
Écart entre enseignants0,415 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2025
Routes d'admission2
Résumé présentoui

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