Early Aggressive Therapy for Patients with Juvenile Idiopathic Arthritis: Are We There Yet?
Bibliographic record
Abstract
This is an extremely exciting time in the field of pediatric rheumatology. Advances in understanding the pathogenesis of juvenile idiopathic arthritis (JIA) have led to novel treatments with resultant marked improvements in patient outcomes, as is eloquently summarized in a review by Lovell and colleagues1. Critical to the study of these new therapies has been the development of standardized outcome measures. These are not only relevant to research studies but also assist in making treatment decisions in clinical practice. The definition of improvement by the American College of Rheumatology (ACR) core set response criteria2 and more recently, criteria of inactive disease and remission, both on and off medication, have been developed and adopted by the ACR3 (Table 1). Application of these standardized outcome measures has greatly facilitated the reporting and generalizing of study results, as well as allowed comparison of results between trials. View this table: Table 1. ACR definitions of clinical inactive disease and clinical remission for JIA. From: Wallace, et al . Arthritis Care Res 2011;63:929–363; with permission. Earlier studies, in the “prebiologics era,” used differing measures for reporting remission and classifying patients; and the length of followup varied. As a result, it was extremely difficult to compare results between studies. A Canadian multicenter retrospective cohort study reported that 10 years following diagnosis of juvenile rheumatoid arthritis4, the probability of remission (defined as 2 years without taking medication) was 37% in patients with systemic disease, 47% in oligoarthritis, 23% in rheumatoid factor (RF)-negative polyarthritis, and 6% in RF-positive polyarthritis5. This is in contrast to a multicenter retrospective cohort study (Italy and the United States) in which, after a median of 7.7 years post-JIA diagnosis (similar categories considered as above), 40% of patients were in remission (defined as 6 months without taking medication). However, … Address reprint requests to Dr. Laxer; E-mail: ronald.laxer{at}sickkids.ca
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.010 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".