Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA): updated treatment recommendations for psoriatic arthritis 2021
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.
Bibliographic record
Abstract
Since the second version of the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) treatment recommendations were published in 2015, therapeutic options for psoriatic arthritis (PsA) have advanced considerably. This work reviews the literature since the previous recommendations (data published 2013-2020, including conference presentations between 2017 and 2020) and reports high-quality, evidence-based, domain-focused recommendations for medication selection in PsA developed by GRAPPA clinicians and patient research partners. The overarching principles for the management of adults with PsA were updated by consensus. Principles considering biosimilars and tapering of therapy were added, and the research agenda was revised. Literature searches covered treatments for the key domains of PsA: peripheral arthritis, axial disease, enthesitis, dactylitis, and skin and nail psoriasis; additional searches were performed for PsA-related conditions (uveitis and inflammatory bowel disease) and comorbidities. Individual subcommittees used a GRADE-informed approach, taking into account the quality of evidence for therapies, to generate recommendations for each of these domains, which were incorporated into an overall schema. Choice of therapy for an individual should ideally address all disease domains active in that patient, supporting shared decision-making. As safety issues often affect potential therapeutic choices, additional consideration was given to relevant comorbidities. These GRAPPA treatment recommendations provide up-to-date, evidence-based guidance on PsA management for clinicians and people with PsA.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it