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Outcome Measures for the Evaluation of Treatment Response in Hidradenitis Suppurativa for Clinical Practice

2023· article· en· W4387077952 on OpenAlex
Nicole Mastacouris, Rachel Tannenbaum, Andrew Strunk, Jonathan Koptyev, Pim Aarts, Raed Alhusayen, Falk G. Bechara, Farida Benhadou, Vincenzo Bettoli, Alain Brassard, Debra Brown, Siew Eng Choon, Patricia Coutts, Dimitri Luz Felipe da Silva, Steven Daveluy, Robert P. Dellavalle, V. del Mármol, Lennart Emtestam, Kurt Gebauer, Ralph George, Evangelos J. Giamarellos‐Bourboulis, Noah Goldfarb, Iltefat Hamzavi, Paul G. Hazen, Barbara Horváth, Jennifer L. Hsiao, John R Ingram, Gregor B. E. Jemec, Joslyn S. Kirby, Michelle A. Lowes, Angelo Valerio Marzano, Łukasz Matusiak, Haley B. Naik, Martin M. Okun, Hazel H. Oon, Lauren A.V. Orenstein, So Yeon Paek, J.C. Pascual, Pablo Fernández‐Peñas, Barry I. Resnik, Christopher J. Sayed, Linnea Thorlacius, Hessel H. van der Zee, Kelsey R. van Straalen, Amit Garg

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJAMA Dermatology · 2023
Typearticle
Languageen
FieldMedicine
TopicHidradenitis Suppurativa and Treatments
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
FundersSchool of Medicine, University of North Carolina at Chapel HillFeinstein Institutes for Medical ResearchBaylor University Medical CenterSchool of Medicine, Emory UniversityCilagLEO FondetBaylor UniversityPennsylvania State UniversityUniversity of SydneyU.S. Department of Veterans AffairsNorthwell HealthIncyteEmory UniversityNovartis PharmaLeonard M. Miller School of MedicineUniversity of PennsylvaniaGaldermaUniversity of MiamiCelgenePfizer
KeywordsMedicineDelphi methodHidradenitis suppurativaPatient-reported outcomeDelphiClinical PracticeClinical trialMEDLINEFamily medicineQuality of life (healthcare)NursingDiseasePathology

Abstract

fetched live from OpenAlex

Importance: Although several clinician- and patient-reported outcome measures have been developed for trials in hidradenitis suppurativa (HS), there is currently no consensus on which measures are best suited for use in clinical practice. Identifying validated and feasible measures applicable to the practice setting has the potential to optimize treatment strategies and generate generalizable evidence that may inform treatment guidelines. Objective: To establish consensus on a core set of clinician- and patient-reported outcome measures recommended for use in clinical practice and to establish the appropriate interval within which these measures should be applied. Evidence Review: Clinician- and patient-reported HS measures and studies describing their psychometric properties were identified through literature reviews. Identified measures comprised an item reduction survey and subsequent electronic Delphi (e-Delphi) consensus rounds. In each consensus round, a summary of outcome measure components and scoring methods was provided to participants. Experts were provided with feasibility characteristics of clinician measures to aid selection. Consensus was achieved if at least 67% of respondents agreed with use of a measure in clinical practice. Findings: Among HS experts, response rates for item reduction, e-Delphi round 1, and e-Delphi round 2 surveys were 76.4% (42 of 55), 90.5% (38 of 42), and 92.9% (39 of 42), respectively; among patient research partners (PRPs), response rates were 70.8% (17 of 24), 100% (17 of 17), and 82.4% (14 of 17), respectively. The majority of experts across rounds were practicing dermatologists with 18 to 19 years of clinical experience. In the final e-Delphi round, most PRPs were female (12 [85.7%] vs 2 males [11.8%]) and aged 30 to 49 years. In the final e-Delphi round, HS experts and PRPs agreed with the use of the HS Investigator Global Assessment (28 [71.8%]) and HS Quality of Life score (13 [92.9%]), respectively. The most expert-preferred assessment interval in which to apply these measures was 3 months (27 [69.2%]). Conclusions and Relevance: An international group of HS experts and PRPs achieved consensus on a core set of HS measures suitable for use in clinical practice. Consistent use of these measures may lead to more accurate assessments of HS disease activity and life outcomes, facilitating shared treatment decision-making in the practice setting.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.318
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.282
GPT teacher head0.513
Teacher spread0.230 · 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