OCRELIZUMAB IN PRIMARY PROGRESSIVE MS: THE ORATORIO STUDY
Bibliographic record
Abstract
Introduction B cells are implicated in MS pathophysiology, including primary progressive MS (PPMS). Ocrelizumab (OCR) is a humanised monoclonal antibody that selectively targets CD20+ B cells. OCR was evaluated in PPMS in a Phase III, randomised, double-blind, placebo-controlled study (ORATORIO; NCT01194570). Methods Eligible PPMS patients were randomised 2:1 to receive OCR 600 mg or placebo every 24 weeks for ≥120 weeks, until a pre-specified number of 12-week confirmed disability progression (CDP) events occurred. The primary endpoint was time-to-onset of 12-week CDP. Secondary endpoints included: time-to-onset of ≥24-week CDP; changes in timed 25-foot walk (T25-FW), total T2 lesion volume at 120 weeks and total brain volume between 24 and 120 weeks; and safety. Results Compared with placebo, OCR significantly reduced: risk of 12- (24%; p=0.0321) and 24-week CDP (25%; p=0.0365); T25FW progression rate (29% [OCR: +39%; placebo: +55%; p=0.0404]); T2 lesion volume (OCR: –3.4%; placebo: +7.4%; p<0.0001); and brain volume loss rate (17.5% [OCR: –0.9%; placebo: –1.1%; p=0.0206]). Adverse events (AEs) and serious AEs were balanced between groups. Conclusions OCR is the first investigational therapy to meet key efficacy outcomes with a favourable safety profile in a Phase III PPMS study. Sponsored by F. Hoffmann-La Roche Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".