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Record W4413104618 · doi:10.1093/bjd/ljaf307

The Hidradenitis Suppurativa Symptom and Impact Diary: Development and psychometric evaluation of a novel set of patient-reported outcomes for hidradenitis suppurativa

2025· article· en· W4413104618 on OpenAlexaff
John R Ingram, Magdalena B. Wozniak, Anna Passera, Lorenz Uhlmann, Angela Llobet Martinez, Falk G. Bechara, Randall H. Bender, Lori McLeod, Susan Martin, Santiago G. Moreno, Jessica Marvel, Shoba Ravichandran, Alexa B. Kimball

Bibliographic record

VenueBritish Journal of Dermatology · 2025
Typearticle
Languageen
FieldMedicine
TopicHidradenitis Suppurativa and Treatments
Canadian institutionsInstitute of Infection and Immunity
FundersNovartis Pharmaceuticals UK LimitedNovartis Pharma
KeywordsHidradenitis suppurativaMedicineDermatologyInternal medicineDisease

Abstract

fetched live from OpenAlex

BACKGROUND: Hidradenitis suppurativa (HS) is associated with a substantial disease burden. Given the complex nature of HS-related symptoms, patient-reported outcome (PRO) measures are important to ensure that the patient experience is captured when evaluating the efficacy of treatments in clinical trials. OBJECTIVES: To develop the Hidradenitis Suppurativa Symptom and Impact Diary (HSSID©), a novel PRO measure for use in clinical trials to assess the symptoms and impacts of HS in adult patients, and to validate its psychometric properties. METHODS: The development phase involved patients with HS and clinicians with HS expertise and included three sequential stages: (i) concept elicitation interviews (n = 8); (ii) item development; and (iii) cognitive debriefing interviews (n = 12). The psychometric properties of the HSSID were evaluated using data from a subset of patients participating in the SUNSHINE (NCT03713619) and SUNRISE (NCT03713632) trials, and included assessments of reliability, validity and ability to detect change. Anchor-based methods to estimate meaningful change thresholds were explored. RESULTS: The HSSID comprises 11 items; 5 relate to HS symptoms (lesion-related pain, lesion-related itching, lesion drainage, odour and physical fatigue) and 6 to HS impacts (ability to walk, ability to move [other than walking], sleep disturbance, time spent with other people, negative impact on emotions and ability to complete work). Patients found the HSSID items easy to understand and reported no difficulties recalling symptoms/impacts experienced in the previous 24 h. Overall, 478 patients from SUNSHINE and SUNRISE were included in the psychometric evaluation phase. Good association with low redundancy was observed among HSSID items with moderate (> 0.30) to strong (> 0.50) inter-diary item correlations among symptoms and impact items, and across groups. Test-retest reliability estimates in stable subsets were high across SUNSHINE and SUNRISE, ranging from 0.78 to 0.96. Construct validity analysis confirmed that each HSSID item correlated with ≥ 1 targeted support variable. HSSID item scores demonstrated satisfactory responsiveness to detect change; however, anchor-based meaningful change thresholds could be established for the worst lesion-related pain item only. CONCLUSIONS: The HSSID appropriately assesses the symptoms and impacts of HS in adults. HSSID items demonstrated generally robust psychometric properties.

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)0.023
metaresearch head score (Gemma)0.035
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.035
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.345
Teacher spread0.313 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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