MétaCan
Menu
Back to cohort
Record W2606626129 · doi:10.3899/jrheum.161473

Treating Psoriasis and Psoriatic Arthritis: Position Paper on Applying the Treat-to-target Concept to Canadian Daily Practice

2017· article· en· W2606626129 on OpenAlexaffvenueabout
Dafna D. Gladman, Yves Poulin, Karen E. Adams, Marc Bourcier, Snezana Barac, Kirk Barber, Vinod Chandran, Jan Dutz, Cathy Flanagan, Melinda Gooderham, Wayne Gulliver, Vincent Ho, Chih-ho Hong, Jacob Karsh, Majed Khraishi, Charles Lynde, Kim Papp, Proton Rahman, Sherry Rohekar, Cheryl F. Rosen, Anthony S. Russell, Ronald Vender, Jensen Yeung, Olga Ziouzina, Michel Zummer

Bibliographic record

VenueThe Journal of Rheumatology · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPsoriasis: Treatment and Pathogenesis
Canadian institutionsUniversité de SherbrookeWestern University
Fundersnot available
KeywordsPsoriatic arthritisMedicinePsoriasisObservational studyTask forceClinical PracticeTask (project management)Physical therapyPosition paperAlternative medicineDermatologyInternal medicinePathologyManagement

Abstract

fetched live from OpenAlex

OBJECTIVE: To develop preliminary treat-to-target (T2T) recommendations for psoriasis and psoriatic arthritis (PsA) for Canadian daily practice. METHODS: A task force composed of expert Canadian dermatologists and rheumatologists performed a needs assessment among Canadian clinicians treating these diseases as well as an extensive literature search on the outcome measures used in clinical trials and practice. RESULTS: Based on results from the needs assessment and literature search, the task force established 5 overarching principles and developed 8 preliminary T2T recommendations. CONCLUSION: The proposed recommendations should improve management of psoriasis and PsA in Canadian daily practice. However, these recommendations must be further validated in a real-world observational study to ensure that their use leads to better longterm outcomes.

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)0.048
metaresearch head score (Gemma)0.082
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.159
Threshold uncertainty score0.462

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0480.082
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.003
Science and technology studies0.0070.006
Scholarly communication0.0080.004
Open science0.0050.005
Research integrity0.0080.013
Insufficient payload (model declined to judge)0.0060.002

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 head0.012
GPT teacher head0.251
Teacher spread0.239 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations24
Published2017
Admission routes3
Has abstractyes

Explore more

Same venueThe Journal of RheumatologySame topicPsoriasis: Treatment and PathogenesisFrench-language works237,207