Autologous haematopoietic stem cell transplantation as a first-line disease-modifying therapy in patients with ‘aggressive’ multiple sclerosis
Bibliographic record
Abstract
Background: Autologous haematopoietic stem cell transplantation (AHSCT) is an effective treatment for patients with multiple sclerosis (MS) who have highly active disease, despite the use of standard disease-modifying therapies (DMTs). However, the optimal time for offering AHSCT to patients with ‘aggressive’ MS is yet to be established. Objectives: The objective was to explore the safety and efficacy of AHSCT as a first-line DMT in patients with ‘aggressive’ MS. Methods: All patients with ‘aggressive’ MS who received AHSCT as a first-line DMT in five European and North American centres were retrospectively evaluated. Results: Twenty patients were identified. The median interval between diagnosis and AHSCT was 5 (1–20) months. All had multiple poor prognostic markers with a median pre-transplant Expanded Disability Status Scale (EDSS) score of 5.0 (1.5–9.5). After a median follow-up of 30 (12–118) months, the median EDSS score improved to 2.0 (0–6.5, p < 0.0001). No patient had further relapses. Three had residual magnetic resonance imaging (MRI) disease activities in the first 6 months post-transplant, but no further new or enhancing lesions were observed in subsequent scans. Conclusion: AHSCT is safe and effective as a first-line DMT in inducing rapid and sustained remission in patients with ‘aggressive’ MS.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".