Wearing-Off Effect Reports in People With Multiple Sclerosis Receiving Ocrelizumab
Bibliographic record
Abstract
Background: A wearing-off effect has been reported in people with multiple sclerosis (MS) receiving ocrelizumab and other monoclonal antibodies. We sought to describe the real-world occurrence of wearing-off effect among people with MS in Canada treated with ocrelizumab. Methods: Canadian self-reports coded to the Medical Dictionary for Regulatory Activities preferred term therapeutic response shortened (which included reports using the terms wearing-off, crap gap, wore off, or end-of-cycle phenomenon) between November 5, 2008, and March 15, 2023, were identified from the Roche Global Safety Database. Cases were then linked to patient-level data from the Canadian Roche Patient Support Program (COMPASS). Only people with MS who had received 3 or more doses of ocrelizumab were included. Results: A total of 10,055 people with MS in Canada received 3 or more doses of ocrelizumab within COMPASS. Therapeutic response shortened was reported 140 times among 138 unique cases (1.3%) over an average of 7.4 infusions. Discontinuation of ocrelizumab was generally uncommon. In the overall COMPASS population, 11.4% (1143 of 10,055) discontinued ocrelizumab. Among those who reported therapeutic response shortened, 15.9% (22 of 138) discontinued while the majority (116 of 138; 84.1%) continued ocrelizumab treatment. Of individuals reporting the adverse event of interest, those with relapsing-remitting MS more frequently remained on therapy (98 of 112; 87.5%) compared with those with primary progressive MS (18 of 26; 69.2%). Conclusions: A wearing-off effect was infrequently reported and was not treatment limiting among people with MS in the real-world COMPASS patient support program.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".