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Record W3127741312 · doi:10.1111/bjd.19874

Priority research questions in atopic dermatitis: an International Eczema Council eDelphi consensus

2021· letter· en· W3127741312 on OpenAlexaff
Katrina Abuabara, Stuart G. Nicholls, Sinéad Langan, Emma Guttman‐Yassky, Nick J. Reynolds, Amy S. Paller, Sara Brown

Bibliographic record

VenueBritish Journal of Dermatology · 2021
Typeletter
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsOttawa Hospital
FundersUniversity of California, San FranciscoMedical Research CouncilNational Institute for Health and Care ResearchWellcome Trust
KeywordsAtopic dermatitisDermatologyConsensus conferenceMedicineMEDLINEFamily medicinePolitical scienceInternal medicineLaw

Abstract

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Dear Editor, Recent advances in understanding the complex pathogenesis of atopic dermatitis (AD, also known as eczema or atopic eczema), coupled with the development of new treatments, have led to increased interest from multiple stakeholders. There is a need to prioritize areas for research to inform a coordinated approach to advancing science and patient care. We sought to fill a gap in the literature, specifically from the perspective of clinicians involved in AD patient care and research. Our objective was to identify and reach consensus on a set of research questions to be prioritized for future work in AD. We conducted a three-round electronic Delphi (eDelphi) process with members of the International Eczema Council (IEC).1, 2 The IEC is a global nonprofit organization that aims to promote the optimal management of AD through research, education and patient/family care. In the first round, participants provided online consent and submitted up to three research questions they believed were the highest priority in AD. These could include areas of uncertainty (i.e. questions that are not adequately answered by existing evidence) and/or unmet needs (i.e. areas where there is not currently ongoing or adequate research). Participants were asked to align each question to one of the following five domains: (i) epidemiology, including phenotype, disease course, disease/psychological burden and comorbidities; (ii) pathophysiology and molecular mechanisms, including genomics and immunology; (iii) translational research, including stratified/personalized/precision and systems medicine (including models); (iv) therapeutics, including nonpharmacological interventions such as psychological support and educational programmes; and (v) other. These domains were based on a pilot exercise to determine research priorities, carried out with IEC members in 2015, and previous systematic reviews in dermatology.3 Data were collected using REDCap software, and free-text responses were reviewed independently by two researchers.4 Duplicate and overlapping submissions were aggregated through discussion with the investigator team. Round 1 was completed by 68 of 82 invited participants (83%). Respondents were from 22 countries; 96% were physicians and 90% were based at teaching hospitals. Among those caring for patients with AD, 45% cared primarily for adults, 22% primarily for children and 33% for both. After consolidation, 62 of 197 priority research questions were put forward to round 2. In the second and third rounds, participants were asked to score each of the submitted questions on a scale from one to nine using the COMET Initiative Delphi Manager software.5 Consensus was predefined as > 70% of participants scoring the importance of an item as seven to nine (critically important) and < 15% of participants scoring it as one to three (not important). Questions that did not meet these criteria after round 2 were dropped, and in round 3, participants were shown the groups’ scores and asked to re-score each of the remaining questions. After the final round, eight research questions achieved consensus and are listed in Table 1. These spanned all domains and focused on: prediction of disease course; identification of disease subtypes; evaluation of safe, effective and disease-modifying therapies; comparative effectiveness of treatments; biomarker assessment; and mechanisms and treatment of disease flares. The consensus that identification of subtypes remains a priority area for further research is consistent with recent work in the UK, in which the need to identify subtypes of patients with differing treatment responses was identified as a clear priority.6 Our objective was to fill a gap in the literature on research priorities from the academic clinician/researcher perspective, given that prior efforts have examined patient, translational and economic research priorities.6-8 The research questions identified reveal a different perspective from some patient-led priority-setting exercises, in which the need for research into practical issues, such as use of topical steroids and emollients and food allergy testing, were highlighted.8 Strengths of our work include high response rates and the clear consensus that emerged. Limitations relate to its generalizability and the extent to which the priority research questions reflect all stakeholder priorities for AD research. Respondents were directly involved in patient care and reported expertise in various types of AD research but were predominantly from university teaching hospitals. Geographically, they worked in six continents with differing socioeconomic contexts, but North America and Europe were overrepresented. This eDelphi exercise was completed in February 2020 and thus does not reflect changing priorities as a result of the global COVID-19 pandemic. The research questions prioritized indicate the need for multidisciplinary research including epidemiology, clinical trials and molecular medicine to address the outstanding challenges in understanding this complex disease and optimizing patient care. We thank Margaret Jung and Lynn Colegrove from the IEC for organizing telephone conferences and collating responses from IEC associates and councillors, and Morgan Ye, Vivian Lam and Natalie Tomasewski at UCSF for logistical and analytical support. Katrina Abuabara: Conceptualization (equal); Data curation (equal); Formal analysis (equal); Investigation (equal); Methodology (equal); Project administration (equal); Supervision (lead); Writing-original draft (lead); Writing-review & editing (equal). Stuart Nicholls: Conceptualization (supporting); Data curation (supporting); Investigation (supporting); Methodology (supporting); Project administration (supporting); Writing-review & editing (supporting). Sinead Langan: Conceptualization (supporting); Data curation (supporting); Formal analysis (supporting); Investigation (supporting); Methodology (supporting); Project administration (supporting); Writing-review & editing (supporting). Emma Guttman-Yassky: Conceptualization (supporting); Data curation (supporting); Formal analysis (supporting); Investigation (supporting); Methodology (supporting); Project administration (supporting); Writing-review & editing (supporting). Nick Reynolds: Conceptualization (supporting); Data curation (supporting); Investigation (supporting); Methodology (supporting); Project administration (supporting); Writing-review & editing (supporting). Amy Paller: Conceptualization (supporting); Data curation (supporting); Formal analysis (supporting); Investigation (supporting); Methodology (supporting); Project administration (supporting); Writing-review & editing (supporting). Sara Brown: Conceptualization (equal); Data curation (equal); Formal analysis (equal); Investigation (equal); Methodology (equal); Project administration (equal); Writing-original draft (supporting); Writing-review & editing (supporting). Affiliations for the members of the International Eczema Council Priority Research Group may be found in Appendix S2 in the Supporting Information. Tove Agner, Valeria Aoki, Martine Bagot, Sebastien Barbarot, Lisa Beck, Thomas Bieber, Robert Bissonnette, Andrew Blauvelt, Patrick M. Brunner, David E. Cohen, Michael J. Cork, Anna De Benedetto, Mette Deleuran, Sandipan Dhar, Ncoza Dlova, Aaron M. Drucker, Lawrence Eichenfield, James T. Elder, Kilian Eyerich, Carsten Flohr, Carlo Gelmetti, Giampiero Girolomoni, Melinda J. Gooderham, Emma Guttman, Jon M. Hanifin, DirkJan Hijnen, Emmilia Hodak, Alan D Irvine, Kenji Kabashima, Norito Katoh, Kyu Han Kim, Heidi Kong, Cheng Che E Lan, Kwang Hoon Lee, Yael Anne Leshem, Danielle Marcoux, Uffe Nygaard, Chang Ook Park, Carle Paul, Marieke Seyger, Elaine Siegfried, Jonathan Silverberg, Eric Simpson, Jean Francois Stalder, Sonja Stander, Martin Steinhoff, John Su, Jacek Szepietowski, Roberto Takaoka, Jacob P. Thyssen, Christian Vestergaard, Miriam Weinstein, Yik Weng Yew. Appendix S1 Funding and Conflicts of interest statements. Appendix S2 Affiliations for the International Eczema Council Priority Research Group. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

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How this classification was reachedexpand

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)0.006
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.730
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.000
Open science0.0020.000
Research integrity0.0020.008
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 head0.232
GPT teacher head0.462
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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreCommentary

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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Citations4
Published2021
Admission routes1
Has abstractyes

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