Association of Low-Dose Colchicine With Incidence of Knee and Hip Replacements
Bibliographic record
Abstract
BACKGROUND: Osteoarthritis is a major contributor to pain and disability worldwide. Given that inflammation plays an important role in the development of osteoarthritis, anti-inflammatory drugs may slow disease progression. OBJECTIVE: To examine whether colchicine, 0.5 mg daily, reduces incident total knee replacements (TKRs) and total hip replacements (THRs). DESIGN: Exploratory analysis of the LoDoCo2 (Low-Dose Colchicine 2) randomized, controlled, double-blind trial. (Australian New Zealand Clinical Trials Registry: ACTRN12614000093684). SETTING: 43 centers in Australia and the Netherlands. PATIENTS: 5522 patients with chronic coronary artery disease. INTERVENTION: Colchicine, 0.5 mg, or placebo once daily. MEASUREMENTS: The primary outcome was time to first TKR or THR since randomization. All analyses were performed on an intention-to-treat basis. RESULTS: A total of 2762 patients received colchicine and 2760 received placebo during a median follow-up of 28.6 months. During the trial, TKR or THR was performed in 68 patients (2.5%) in the colchicine group and 97 (3.5%) in the placebo group (incidence rate, 0.90 vs. 1.30 per 100 person-years; incidence rate difference, -0.40 [95% CI, -0.74 to -0.06] per 100 person-years; hazard ratio, 0.69 [CI, 0.51 to 0.95]). In sensitivity analyses, similar results were obtained when patients with gout at baseline were excluded and when joint replacements that occurred in the first 3 and 6 months of follow-up were omitted. LIMITATION: LoDoCo2 was not designed to investigate the effect of colchicine in osteoarthritis of the knee or hip and did not collect information specifically on osteoarthritis. CONCLUSION: In this exploratory analysis of the LoDoCo2 trial, use of colchicine, 0.5 mg daily, was associated with a lower incidence of TKR and THR. Further investigation of colchicine therapy to slow disease progression in osteoarthritis is warranted. PRIMARY FUNDING SOURCE: None.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".