CONCERTO: A randomized, placebo-controlled trial of oral laquinimod in relapsing-remitting multiple sclerosis
Bibliographic record
Abstract
Background: Interventions targeting the adaptive immune response are needed in multiple sclerosis (MS). Objective: Evaluate laquinimod’s efficacy, safety, and tolerability in patients with relapsing-remitting multiple sclerosis (RRMS). Methods: CONCERTO was a randomized, double-blind, placebo-controlled, phase-3 study. RRMS patients were randomized 1:1:1 to receive once-daily oral laquinimod 0.6 or 1.2 mg or placebo for ⩽24 months ( n = 727, n = 732, and n = 740, respectively). Primary endpoint was time to 3-month confirmed disability progression (CDP). The laquinimod 1.2-mg dose arm was discontinued (1 January 2016) due to cardiovascular events at high doses. Safety was monitored throughout the study. Results: CONCERTO did not meet the primary endpoint of significant effect with laquinimod 0.6-mg versus placebo on 3-month CDP (hazard ratio: 0.94; 95% confidence interval: 0.67–1.31; p = 0.706). Secondary endpoint p values were nominal and non-inferential. Laquinimod 0.6 mg demonstrated 40% reduction in percent brain volume change from baseline to Month 15 versus placebo ( p < 0.0001). The other secondary endpoint, time to first relapse, and annualized relapse rate (an exploratory endpoint) were numerically lower (both, p = 0.0001). No unexpected safety findings were reported with laquinimod 0.6 mg. Conclusion: Laquinimod 0.6 mg demonstrated only nominally significant effects on clinical relapses and magnetic resonance imaging (MRI) outcomes and was generally well tolerated. Clinical trial registration number: ClinicalTrials.gov (NCT01707992).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| 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 | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".