Plasma MicroRNA Profiles in Patients with Early Rheumatoid Arthritis Responding to Adalimumab plus Methotrexate vs Methotrexate Alone: A Placebo-controlled Clinical Trial
Bibliographic record
Abstract
OBJECTIVE: The aim was to identify plasma (i.e., cell-free) microRNA (miRNA) predicting antitumor necrosis and/or methotrexate (MTX) treatment response in patients enrolled in an investigator-initiated, prospective, double-blinded, placebo-controlled trial (The OPERA study, NCT00660647). METHODS: We included 180 disease-modifying antirheumatic drug-naive patients with early rheumatoid arthritis (RA) randomized to adalimumab (ADA; n = 89) or placebo (n = 91) in combination with MTX. Plasma samples before and 3 months after treatment initiation were analyzed for 91 specific miRNA by quantitative reverse transcriptase-polymerase chain reaction on microfluidic dynamic arrays. A linear mixed-effects model was used to test for associations between pretreatment miRNA and changes in miRNA expression and American College of Rheumatology/European League Against Rheumatism (ACR/EULAR) Boolean (28 joints) remission at 3 and 12 months, applying false discovery rate correction for multiple testing. Using leave-one-out cross validation, we built predictive multivariate miRNA models and estimated classification performances using receiver-operating characteristics (ROC) curves. RESULTS: In the ADA group, a higher pretreatment level of miR-27a-3p was significantly associated with remission at 12 months. The level decreased in remitting patients between pretreatment and 3 months, and increased in nonremitting patients. No associations were found in the placebo group receiving only MTX. Two multivariate miRNA models were able to predict response to ADA treatment after 3 and 12 months, with 63% and 82% area under the ROC curves, respectively. CONCLUSION: We identified miR-27a-3p as a potential predictive biomarker of ACR/EULAR remission in patients with early RA treated with ADA in combination with MTX. We conclude that pretreatment plasma-miRNA profiles may be of predictive value, but the results need confirmation in independent cohorts.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".