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Record W4406426603 · doi:10.1136/bmjopen-2024-088267

Patient preferences for drug therapy in inflammatory arthritis: protocol for a living systematic review and evidence map to inform clinical practice guidelines

2025· article· en· W4406426603 on OpenAlexaff
Pakeezah Saadat, Nick Bansback, Marie Falahee, Mickaël Hiligsmann, Peter Tugwell, Rachelle Buchbinder, Samuel Whittle, Dawn P. Richards, Laurie Proulx, Holger J. Schünemann, Pablo Alonso‐Coello, Robby Nieuwlaat, Wojtek Wiercioch, S. W. A. Kuper, Jordi Pardo Pardo, Glen Hazlewood

Bibliographic record

VenueBMJ Open · 2025
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsAlberta Bone and Joint Health InstituteCochraneMcMaster UniversityUniversity of CalgaryImpactCanadian Arthritis Patient AllianceUniversity of OttawaResearch CanadaOttawa HospitalUniversity of British ColumbiaUniversity of Toronto
FundersMedical Research CouncilNational Health and Medical Research CouncilHospital Research Foundation
KeywordsMedicineProtocol (science)Alternative medicineClinical PracticeDrugInflammatory arthritisArthritisSystematic reviewFamily medicineMEDLINEIntensive care medicinePharmacologyPathologyInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: The pharmacological management of inflammatory arthritis often requires choices that involve trade-offs between benefits, risks and other attributes such as administration route, frequency and cost. This living systematic review aims to inform international clinical guidelines on inflammatory arthritis by creating an evidence map of patient preference studies concerning the trade-offs in pharmacological management of inflammatory arthritis. METHODS AND ANALYSIS: We will include published and peer-reviewed full-text studies in any language that quantitatively assess preferences of patients for the pharmacological management of inflammatory arthritis (rheumatoid arthritis, spondyloarthritis and juvenile idiopathic arthritis). Studies must use either stated or revealed preference methods to assess preferences and provide a quantitative assessment of relevant characteristics, such as benefits, risks, costs and process attributes. Articles will identified through Medline and EMBASE database searches from inception using search terms that combine keywords and subject headings for inflammatory arthritis and preference-based methods, and a search in the Health Preference Study and Technology Registry using keywords for the populations of interest. Two independent reviewers will perform abstract and full-text screening. Risk of bias will be assessed using the GRADE risk of bias tool. An evidence map will be generated to summarise included studies and their assessments of each trade-off. The search will be conducted every 6 months with new studies added to the inventory. ETHICS AND DISSEMINATION: Ethics approval is not required. Results from the base review will be published in a peer-reviewed journal and findings will be presented at conferences. In the living model, we will publish updates and datasets on an Open Science Framework page, with periodic updates in peer-reviewed journals.

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)0.124
metaresearch head score (Gemma)0.163
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.124
Threshold uncertainty score0.658

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1240.163
Meta-epidemiology (narrow)0.0070.006
Meta-epidemiology (broad)0.0160.022
Bibliometrics0.0190.018
Science and technology studies0.0050.007
Scholarly communication0.0110.012
Open science0.0070.010
Research integrity0.0100.010
Insufficient payload (model declined to judge)0.0880.018

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 head0.216
GPT teacher head0.550
Teacher spread0.334 · 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 designSystematic review
Domainnot available
GenreProtocol

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

Citations0
Published2025
Admission routes1
Has abstractyes

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