Damage and Progression on Radiographs in Individual Joints: Data from Pivotal Randomized Controlled Trials
Bibliographic record
Abstract
OBJECTIVE: Radiographic progression is usually assessed by Sharp-based methods (van der Heijde-modified Sharp score and the Genant-modified Sharp score). The aim of this study was to evaluate, in a range of randomized controlled trials (RCT), the presence of erosions and joint space narrowing (JSN) in all individual joints, as well as progression in these joints, and to determine if any redundancy exists due to infrequently involved joints. METHODS: Four databases of rheumatoid arthritis RCT that were all scored according to van der Heijde's modification of the Sharp score were included in a descriptive analysis. RESULTS: Irrespective of different readers, different patient populations, and different disease durations per trial, similar patterns emerged. Both erosions and JSN occurred in all sites. Erosions occurred most frequently in the feet, preferentially in 5th metatarsophalangeal joint (MTP-5). JSN occurred most frequently in the wrist. Change from baseline in erosions and JSN followed the pattern of involvement at baseline, so that MTP-5, and to a lesser extent MTP-3 and MTP-4, preferentially showed progression in erosive damage. Joints in the wrist showed highest tendency to worsen over time with respect to JSN. CONCLUSION: These data indicate that both erosions and JSN must be assessed for damage, and that a more abbreviated joint count cannot be used for radiographic scoring.
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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 | 0.040 | 0.098 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.009 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".