ADAMTS5 Is a Biomarker for Prediction of Response to Infliximab in Patients with Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: To identify a biomarker for prediction of the response to infliximab (IFX) in patients with rheumatoid arthritis (RA), we focused on a disintegrin and metalloproteinase with thrombospondin motifs 5 (ADAMTS5) that seems to play a key role in aggrecan degradation in cartilage. METHODS: Seventy-three randomly selected patients with active RA were treated with IFX. Peripheral blood samples were collected at baseline and ADAMTS5 messenger RNA (mRNA) was quantified using real-time polymerase chain reaction. RESULTS: Baseline ADAMTS5 mRNA levels in the good responder group were significantly lower (1.84 +/- 1.56; p = 0.0408) than those in the moderate and nonresponder groups (2.54 +/- 1.70) at 38 weeks of treatment with IFX. The 28-joint count Disease Activity Score (DAS28) at 38 weeks of treatment was significantly lower in the low ADAMTS5 group (2.30 +/- 1.28; p = 0.0038) than in the high ADAMTS5 group (3.90 +/- 1.61). The percentage reduction of the DAS28 was significantly higher in the low ADAMTS5 group (52.5% +/- 28.8%; p = 0.0156) than in the high ADAMTS5 group (29.4% +/- 27.2%). Further, the Delta Health Assessment Questionnaire (DeltaHAQ) score, an estimate of the improvement in the HAQ score, at 38 weeks of treatment was significantly higher in the low ADAMTS5 group (1.18 +/- 0.60; p = 0.0102) than in the high ADAMTS5 group (0.21 +/- 0.78). The positive predictive value of a low baseline ADAMTS5 level for predicting good response and remission (DAS28 < 2.6 at 38 weeks) was 90.0% and 70.0%, respectively. CONCLUSION: The baseline ADAMTS5 mRNA level is a candidate biomarker for prediction of the response to IFX in patients with RA.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".