Limited effects of non-steroidal anti-inflammatory drugs (NSAIDs) on imaging outcomes in osteoarthritis: observational data from the osteoarthritis initiative (OAI)
Bibliographic record
Abstract
BACKGROUND: Non-steroidal anti-inflammatory drugs (NSAIDs) are commonly prescribed for pain relief in osteoarthritis (OA), and their anti-inflammatory effects may play a role in shaping the disease course. The aim of this investigation was to examine the relationship between new use of prescription NSAIDs and changes in imaging biomarkers of synovitis in the knee, and to evaluate the association of NSAID use with structural cartilage damage over a period of four years. METHODS: Applying a new user design to identify treatment effects in observational data, we selected participants from the Osteoarthritis Initiative (OAI) who were prescribed regular, oral NSAID medication between baseline and 48 months follow-up and who had available 3T MRIs of the right knee with whole-organ magnetic resonance imaging score (WORMS) readings as well as semi-quantitative assessments of synovitis for both timepoints. These individuals were frequency-matched with non-NSAID users matching for age, gender, body mass index (BMI), baseline Kellgren & Lawrence (KL) grade, Western Ontario and McMaster Universities Osteoarthritis (WOMAC) scores, and for the presence of an inflammatory imaging phenotype at baseline. Ordinal regression analyses and marginal estimated means were used to determine the effect of NSAID use on structural imaging outcomes, controlling for age, gender, BMI, and non-prescription NSAID use. RESULTS: In this longitudinal analysis over 48 months, 142 individuals met prespecified criteria for new NSAID exposure, and 707 matched controls were identified. Regression analyses did not show a significant association between new NSAID use and changes in effusion-synovitis, Hoffa's synovitis, or synovial proliferation scores over 4 years. However, NSAID users showed a significantly slower progression of cartilage lesions as measured by WORMS grading; this effect was marginally more pronounced in participants with an inflammatory imaging phenotype (beta - 0.92; p = 0.043) than in the population overall (beta - 0.48; p = 0.020). CONCLUSION: New NSAID use was not associated with MRI-detected synovitis over 4 years but had a modest association with reduced structural cartilage damage progression. This effect was more pronounced in individuals with an inflammatory imaging phenotype.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".