Association of biomarkers with pre–radiographically defined and radiographically defined knee osteoarthritis in a population‐based study
Bibliographic record
Abstract
OBJECTIVE: To evaluate 10 biomarkers in magnetic resonance imaging (MRI)-determined, pre-radiographically defined osteoarthritis (pre-ROA) and radiographically defined OA (ROA) in a population-based cohort of subjects with symptomatic knee pain. METHODS: Two hundred one white subjects with knee pain, ages 40-79 years, were classified into OA subgroups according to MRI-based cartilage (MRC) scores (range 0-4) and Kellgren/Lawrence (K/L) grades of radiographic severity (range 0-4): no OA (MRC score 0, K/L grade<2), pre-ROA (MRC score>or=1, K/L grade<2), or ROA (MRC score>or=1, K/L grade>or=2). Urine and serum samples were assessed for levels of the following biomarkers: urinary biomarkers C-telopeptide of type II collagen (uCTX-II), type II and types I and II collagen cleavage neoepitopes (uC2C and uC1,2C, respectively), and N-telopeptide of type I collagen, and serum biomarkers sC1,2C, sC2C, C-propeptide of type II procollagen (sCPII), chondroitin sulfate 846 epitope, cartilage oligomeric matrix protein, and hyaluronic acid. Multicategory logistic regression was performed to evaluate the association of OA subgroup with individual biomarker levels and biomarker ratios, adjusted for age, sex, and body mass index. RESULTS: The risk of ROA versus no OA increased with increasing levels of uCTX-II (odds ratio [OR] 3.12, 95% confidence interval [95% CI] 1.35-7.21), uC2C (OR 2.13, 95% CI 1.04-4.37), and uC1,2C (OR 2.07, 95% CI 1.06-4.04), and was reduced in association with high levels of sCPII (OR 0.53, 95% CI 0.30-0.94). The risk of pre-ROA versus no OA increased with increasing levels of uC2C (OR 2.06, 95% CI 1.05-4.01) and uC1,2C (OR 2.06, 95% CI 1.12-3.77). The ratios of type II collagen degradation markers to collagen synthesis markers were better than individual biomarkers at differentiating the OA subgroups, e.g., the ratio of [uCTX-II][uC1,2C] to sCPII was associated with a risk of ROA versus no OA of 3.47 (95% CI 1.34-9.03) and a risk of pre-ROA versus no OA of 2.56 (95% CI 1.03-6.40). CONCLUSION: Different cartilage degradation markers are associated with pre-ROA than are associated with ROA, indicating that their use as diagnostic markers depends on the stage of OA. Biomarker ratios contrasting cartilage degradation with cartilage synthesis are better able to differentiate OA stages compared with levels of the individual markers.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 | 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".