A multi-centre longitudinal study analysing multiple sclerosis disease-modifying therapy prescribing patterns during the COVID-19 pandemic
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic raised concern amongst clinicians that disease-modifying therapies (DMT), particularly anti-CD20 monoclonal antibodies (mAb) and fingolimod, could worsen COVID-19 in people with multiple sclerosis (pwMS). This study aimed to examine DMT prescribing trends pre- and post-pandemic onset. METHODS: A multi-centre longitudinal study with 8,771 participants from MSBase was conducted. Two time periods were defined: pre-pandemic (March 11 2018-March 10 2020) and post-pandemic onset (March 11 2020-11 March 2022). The association between time and prescribing trends was analysed using multivariable mixed-effects logistic regression. DMT initiation refers to first initiation of any DMT, whilst DMT switches indicate changing regimen within 6 months of last use. RESULTS: Post-pandemic onset, there was a significant increase in DMT initiation/switching to natalizumab and cladribine [(Natalizumab-initiation: OR 1.72, 95% CI 1.39-2.13; switching: OR 1.66, 95% CI 1.40-1.98), (Cladribine-initiation: OR 1.43, 95% CI 1.09-1.87; switching: OR 1.67, 95% CI 1.41-1.98)]. Anti-CD20mAb initiation/switching decreased in the year of the pandemic, but recovered in the second year, such that overall odds increased slightly post-pandemic (initiation: OR 1.26, 95% CI 1.06-1.49; Switching: OR 1.15, 95% CI 1.02-1.29. Initiation/switching of fingolimod, interferon-beta, and alemtuzumab significantly decreased [(Fingolimod-initiation: OR 0.55, 95% CI 0.41-0.73; switching: OR 0.49, 95% CI 0.41-0.58), (Interferon-gamma-initiation: OR 0.48, 95% CI 0.41-0.57; switching: OR 0.78, 95% CI 0.62-0.99), (Alemtuzumab-initiation: OR 0.27, 95% CI 0.15-0.48; switching: OR 0.27, 95% CI 0.17-0.44)]. CONCLUSIONS: Post-pandemic onset, clinicians preferentially prescribed natalizumab and cladribine over anti-CD20 mAbs and fingolimod, likely to preserve efficacy but reduce perceived immunosuppressive risks. This could have implications for disease progression in pwMS. Our findings highlight the significance of equitable DMT access globally, and the importance of evidence-based decision-making in global health challenges.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".