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Record W4387564463 · doi:10.1093/bjd/ljad388

Treatment of Hidradenitis Suppurativa Evaluation Study (THESEUS): a prospective cohort study

2023· article· en· W4387564463 on OpenAlexaff
John R Ingram, Janine Bates, Rebecca Cannings‐John, Fiona Collier, Judith Evans, Angela Gibbons, Ceri Harris, Laura Howells, Kerenza Hood, Rachel Howes, Paul Leighton, Muhammad Riaz, Jeremy Rodrigues, Helen Stanton, Kim S Thomas, Emma Thomas‐Jones

Bibliographic record

VenueBritish Journal of Dermatology · 2023
Typearticle
Languageen
FieldMedicine
TopicHidradenitis Suppurativa and Treatments
Canadian institutionsInstitute of Infection and Immunity
FundersUCB PharmaUniversity of OxfordNational Institute for Health and Care ResearchDepartment of Health and Social CareCancer Research UKInsmedPfizer
KeywordsHidradenitis suppurativaMedicineDermatologyProspective cohort studyCohortCohort studySurgeryDiseasePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Hidradenitis suppurativa (HS) is a chronic, painful disease affecting flexures and other skin regions, producing nodules, abscesses and skin tunnels. Laser treatment targeting hair follicles and deroofing of skin tunnels are standard HS interventions in some countries but are rarely offered in the UK. OBJECTIVES: To describe current UK HS management pathways and influencing factors to inform the design of future randomized controlled trials (RCTs). METHODS: THESEUS was a nonrandomized 12-month prospective cohort study set in 10 UK hospitals offering five interventions: oral doxycycline 200 mg daily; oral clindamycin and rifampicin both 300 mg twice daily for 10 weeks, extended for longer in some cases; laser treatment targeting hair follicles; deroofing; and conventional surgery. The primary outcome was the combination of clinician-assessed eligibility and participant hypothetical willingness to receive each intervention. The secondary outcomes were the proportion of participants selecting each intervention as their final treatment option; the proportion who switch treatments; treatment fidelity; and attrition rates. THESEUS was prospectively registered on the ISRCTN registry: ISRCTN69985145. RESULTS: The recruitment target of 150 participants was met after 18 months, in July 2021, with two pauses due to the COVID-19 pandemic. Baseline demographics reflected the HS secondary care population: average age 36 years, 81% female, 20% non-White, 64% current or ex-smokers, 86% body mass index ≥ 25, 68% with moderate disease, 19% with severe disease and 13% with mild disease. Laser was the intervention with the highest proportion (69%) of participants eligible and willing to receive treatment, then deroofing (58%), conventional surgery (54%), clindamycin and rifampicin (44%), and doxycycline (37%). Laser was ranked first choice by the greatest proportion of participants (41%). Attrition rates were 11% and 17% after 3 and 6 months, respectively. Concordance with doxycycline was 52% after 3 months due to lack of efficacy, participant choice and adverse effects. Delays with procedural interventions were common, with only 43% and 26% of participants starting laser and deroofing, respectively, after 3 months. Uptake of conventional surgery was too small to characterize the intervention. Switching treatment was uncommon and there were no serious adverse events. CONCLUSIONS: THESEUS has established laser treatment and deroofing for HS in the UK and demonstrated their popularity with patients and clinicians for future RCTs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.340
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2023
Admission routes1
Has abstractyes

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