Prevalence, outcomes, and predictive factors: a systematic literature review to inform the development of EULAR Points to Consider for the definition of Difficult-to-Manage and Treatment-Refractory psoriatic arthritis
Bibliographic record
Abstract
Objectives To perform a systematic literature review (SLR) to inform the EULAR Task Force "Points to Consider for the definitions of Difficult-to-Manage (D2M) and Treatment-Refractory (TR) psoriatic arthritis (PsA)". Methods The SLR addressed 3 separate questions concerning the following: (1) prevalence, (2) outcomes, and (3) predictors of D2M/TR PsA. A search was conducted in MEDLINE (Ovid), Cochrane Database of Systematic Reviews, CENTRAL, EMBASE, and Epistemonikos from inception to March 3, 2024, as well as EULAR/ACR abstracts for 2023/24 and 2022/23, respectively. This systematic review adhered to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and was registered on PROSPERO. Data are summarised descriptively. Meta-analysis was not possible due to significant heterogeneity and/or lack of high-quality evidence. Risk of bias (RoB) was assessed using the Newcastle-Ottawa Scale. Results Overall, 70, 4, and 25 articles/abstracts were included for questions 1, 2, and 3, respectively. For question 1, 30/70 records had low/moderate RoB, with the prevalence of D2T PsA ranging from 5% to 80% depending on both the timepoint at which prevalence was measured and the definition of D2M/TR PsA applied, which varied significantly between studies. For question 2, all records had a high RoB; therefore, no conclusions could be drawn. For question 3, all records had a moderate RoB, and 84 categories of potential predictors were identified, with large differences in strength and direction of association between studies. Conclusions Despite significant heterogeneity in the published literature regarding the scope, definition, long-term outcomes, and predictors of D2M/TR PsA, certain patterns emerged that helped shape the final EULAR Task Force recommendations.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".