To Lump or Split When Assessing Psoriatic Arthritis — Not Mutually Exclusive?
Bibliographic record
Abstract
Arguably, the most important advances in modern clinical care have arisen not through the development of new drugs but instead through a recognition that the Gestalt approach to disease assessment is simply not adequate when it comes to selecting and assessing response to therapy. Accurate and regular assessment with an appropriate measurement instrument gives the clinician and patient reliable information to track disease trajectory and make treatment decisions. Achieving consensus on a single disease-specific instrument has considerable advantages, facilitating adoption of international treatment guidelines, and interpretation of data from trials, cohorts, and registries to make translation into routine care seamless1. In the context of rheumatoid arthritis (RA), the 28-joint count Disease Activity Score (DAS28) has been widely adopted as the most frequently used generally continuous measure of activity. The DAS28 has established cutpoints for high, moderate, and low disease activity and remission. The term near remission is increasingly preferred because it better differentiates those with some residual disease from those in true remission. Clinicians are used to the measure and what the numbers mean clinically, and this has allowed a smooth translation of research findings into clinical practice, including the implementation of treat to target and adoption of clinical guidelines. It has been harder to achieve this consensus in the field of psoriatic arthritis (PsA), with no current agreement on the most appropriate instrument to adopt. Why is this the case, and what are the key barriers2? The greatest challenge in the adoption of a composite measure for routine care in PsA has been philosophical: should we incorporate multiple domains of disease into a single measure to identify the totality of disease, or should we focus on 1 domain at a time for accurate assessment and to avoid diluting responsiveness? PsA may manifest in a variety … Address correspondence to W. Tillett, Royal National Hospital for Rheumatic Diseases, Upper Borough Walls, Bath BA1 1RL, UK. E-mail: w.tillett{at}nhs.net
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.083 | 0.201 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.008 | 0.020 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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 source (direct Gemma or distilled Codex), 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".