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Record W2954357071 · doi:10.1111/bjd.18309

Defining lesional, perilesional and unaffected skin in hidradenitis suppurativa: proposed recommendations for clinical trials and translational research studies

2019· letter· en· W2954357071 on OpenAlexaff
John W. Frew, Kristina Navrazhina, Angel S. Byrd, Amit Garg, John R Ingram, Joslyn S. Kirby, Michelle A. Lowes, Haley B. Naik, Vincent Piguet, Errol P. Prens

Bibliographic record

VenueBritish Journal of Dermatology · 2019
Typeletter
Languageen
FieldMedicine
TopicHidradenitis Suppurativa and Treatments
Canadian institutionsWomen's College HospitalUniversity of Toronto
FundersNational Institute of Arthritis and Musculoskeletal and Skin Diseases
KeywordsHidradenitis suppurativaMedicineDermatologyClinical trialTranslational researchSurgeryPathologyDisease

Abstract

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Dear Editor, Hidradenitis suppurativa (HS) is a chronic, recurring inflammatory skin condition for which the pathogenesis is not completely elucidated.1 With the increase in HS‐related research comes the need to enhance the reproducibility, quality and accuracy of scientific methods. Unlike in other inflammatory dermatoses such as psoriasis or atopic dermatitis, HS lesions are morphologically diverse and include nodules, abscesses, tunnels and fibrosis in various permutations and combinations admixed in the same anatomical region.1 This makes general definitions such as ‘lesional’ and ‘nonlesional’ insufficient for HS‐related investigations. A definition for nonlesional skin is lacking. Accurate assessment of the pathophysiological changes in HS lesions (and the response to therapeutics) requires standardized definitions of lesional, perilesional and unaffected skin biopsies. This is especially pertinent given the well‐characterized compartmentalization of cytokines in HS,2 indicating that serum inflammatory markers may not accurately reflect the inflammatory milieu of lesional HS tissue.2 An additional complicating factor is the unique inflammatory environment of healthy axillae, groin and submammary folds, with an increased interleukin‐17 and innate immune signature.3 This makes it crucial to ensure that unaffected skin samples are taken from a site that ensures an accurate comparison. For control specimens, or samples from healthy volunteers, the use of surgical discard from abdominoplasty is problematic given the unique immunological milieu of apocrine‐rich (axillary, inguinal, submammary) skin.3 The use of region‐matched control tissue is vital to avoid overestimation of the relative change of T helper 17 cells and other innate immune markers. Region matching should occur for intertriginous sites as well as less common sites (e.g. neck, postauricular, limbs). Ideally, healthy control skin should only be used after a careful patient history is taken, and it should also be matched for other criteria such as age, sex, smoking status and ethnicity. Examination of the existing literature4 pertaining to inflammatory mediators in HS identified two high‐quality studies with a priori definitions of biopsy sites.5,6 Lesional skin was defined as the edge of an inflammatory lesion, perilesional as normal‐appearing skin 2 cm away from the inflammatory lesion, and unaffected skin as normal‐appearing skin ≥ 10 cm distant. An important caveat is that the reference lesion in these studies requires a priori definition. For the majority of published studies this was an inflammatory nodule. Biopsies for tunnels may require deeper full‐dermal tissue sampling. It is known that histologically fibrotic tissue attenuates the levels of inflammatory mediators compared with nonfibrotic tissue, and the invasive proliferative gelatinous mass of HS tunnels has a specific cytokine signature distinct from that of lesional tissue.7 Therefore, classifying the reference lesion (nodule, tunnel, hypertrophic scar) is crucial for comparison across studies. The presence of dermal tunnels may introduce unintended pathology, which can be difficult to appreciate clinically (even after careful palpation), and hence ultrasound is a useful noninvasive assessment tool to identify dermal tunnels and deep abscesses in order to avoid inadvertent biopsy of a lesion in place of a control sample. In the context of clinical trials, assessment of lesional tissue is often an exploratory end point8 given the lack of biomarkers in HS. While the data are not considered a primary or secondary end point, they do contribute to the existing knowledge of pathophysiology of disease. Therefore, based upon the existing literature (and the authors’ combined experience) we propose the following recommendations: (i) samples should be obtained from three sites: lesional, perilesional and unaffected skin; (ii) the definitions of lesional, perilesional and unaffected skin are as presented in Figure 1; (iii) the anatomical region of the lesion should be recorded; (iv) the lesion morphology should be classified (e.g. inflammatory nodule, abscess, tunnel etc.) and (v) unaffected skin of patients with HS and control samples (taken from healthy volunteers) should be region matched to lesional and perilesional samples (i.e. within the same anatomical region). Biopsy definition recommendations for hidradenitis suppurativa. In the absence of clear standards for HS tissue sampling, these expert recommendations seek to begin this process. Consensus among stakeholders is needed on a valid and reliable approach to tissue sampling, so that these strategies can be implemented in future studies. The next step is to create a coherent consensus and this work is underway. Funding sources: none. Conflicts of interest: A.S.B. is a subinvestigator for Eli Lilly. A.G. has served as an advisor for AbbVie, Amgen, Asana Biosciences, Pfizer, Janssen and UCB, and has received honoraria. J.R.I. is a consultant to UCB Pharma and Novartis and has received travel expenses from AbbVie. M.A.L. has received fees for participating in advisory boards for AbbVie and Janssen, and consulting fees from Incyte, BSN, XBiotech and Almirall. V.P. reports receiving educational grants in his role as Department Division Director, Dermatology, University of Toronto (on behalf of the Division of Dermatology Residency Program) from AbbVie, Celgene, Janssen, Naos, Lilly, Sanofi and Valeant; and nonfinancial support from La Roche‐Posay, outside the submitted work. V.P. has also participated in advisory boards for AbbVie, Celgene, Janssen and Novartis. None of these associations has conflict with the present study. The remaining authors declare no potential conflicts of interest.

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)0.174
metaresearch head score (Gemma)0.271
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.826
Threshold uncertainty score0.919

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1740.271
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0080.005
Bibliometrics0.0040.004
Science and technology studies0.0040.015
Scholarly communication0.0130.019
Open science0.0080.007
Research integrity0.0720.049
Insufficient payload (model declined to judge)0.0070.010

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 head0.359
GPT teacher head0.539
Teacher spread0.180 · 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.

Study designTheoretical or conceptual
DomainMethods
GenreMethods

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".

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Citations40
Published2019
Admission routes1
Has abstractyes

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