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Record W4323044156 · doi:10.1016/j.oooo.2023.01.013

World Workshop on Oral Medicine VIII: Development of a core outcome set for oral lichen planus: a consensus study

2023· review· en· W4323044156 on OpenAlexaff
Rosa María López‐Pintor, Márcio Diniz Freitas, Shilpa Shree Kuduva Ramesh, J. Amadeo Valdéz, Caroline Bissonnette, Hongxia Dan, Michael T. Brennan, Nancy W. Burkhart, Martin S. Greenberg, Arwa M. Farag, Catherine Hong, Thomas P. Sollecito, Jane Setterfield, Sook‐Bin Woo, Richeal Ní Ríordáin, Jairo Robledo‐Sierra, Jennifer M. Taylor

Bibliographic record

VenueOral Surgery Oral Medicine Oral Pathology and Oral Radiology · 2023
Typereview
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsUniversité de Montréal
FundersChurch and DwightColgate-Palmolive Company
KeywordsOral lichen planusDelphi methodOutcome (game theory)MedicineMedical physicsClinical trialOral medicineSet (abstract data type)DelphiPathologyComputer scienceDentistryArtificial intelligence

Abstract

fetched live from OpenAlex

ObjectiveA core outcome set (COS) is the minimum agreed-on data set required to be measured in interventional trials. To date, there is no COS for oral lichen planus (OLP). This study describes the final consensus project that brought together the results of the previous stages of the project to develop the COS for OLP.Study DesignThe consensus process followed the Core Outcome Measures in Effectiveness Trials guidelines and involved the agreement of relevant stakeholders, including patients with OLP. Delphi-style clicker sessions were conducted at the World Workshop on Oral Medicine VIII and the 2022 American Academy of Oral Medicine Annual Conference. Attendees were asked to rate the importance of 15 outcome domains previously identified from a systematic review of interventional studies of OLP and a qualitative study of OLP patients. In a subsequent step, a group of OLP patients rated the domains. A further round of interactive consensus led to the final COS.ResultsThe consensus processes led to a COS of 11 outcome domains to be measured in future trials on OLP.ConclusionThe COS developed by consensus will help reduce the heterogeneity of outcomes measured in interventional trials. This will allow future pooling of outcomes and data for meta-analyses. This project showed the effectiveness of a methodology that could be used for future COS development. A core outcome set (COS) is the minimum agreed-on data set required to be measured in interventional trials. To date, there is no COS for oral lichen planus (OLP). This study describes the final consensus project that brought together the results of the previous stages of the project to develop the COS for OLP. The consensus process followed the Core Outcome Measures in Effectiveness Trials guidelines and involved the agreement of relevant stakeholders, including patients with OLP. Delphi-style clicker sessions were conducted at the World Workshop on Oral Medicine VIII and the 2022 American Academy of Oral Medicine Annual Conference. Attendees were asked to rate the importance of 15 outcome domains previously identified from a systematic review of interventional studies of OLP and a qualitative study of OLP patients. In a subsequent step, a group of OLP patients rated the domains. A further round of interactive consensus led to the final COS. The consensus processes led to a COS of 11 outcome domains to be measured in future trials on OLP. The COS developed by consensus will help reduce the heterogeneity of outcomes measured in interventional trials. This will allow future pooling of outcomes and data for meta-analyses. This project showed the effectiveness of a methodology that could be used for future COS development.

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 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)0.023
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.842
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0230.012
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0110.001
Bibliometrics0.0030.003
Science and technology studies0.0010.007
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0020.003
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 head0.617
GPT teacher head0.560
Teacher spread0.057 · 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
GenreReview

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

Citations11
Published2023
Admission routes1
Has abstractyes

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