Hematopoietic Stem Cell Transplantation for Multiple Sclerosis: Collaboration of the CIBMTR and EBMT to Facilitate International Clinical Studies
Bibliographic record
Abstract
Clinical investigation of autologous hematopoietic stem cell transplantation (HSCT) as therapy for multiple sclerosis (MS) has been ongoing for over a decade. While several phase II studies have been finalized or are in progress, no definitive prospective randomized studies comparing HSCT versus alternative therapies for MS have been completed. In this conference report of North American and European experts who are involved in the care of MS patients, including neurologists and HSCT physicians, and representatives of the Center for International Blood and Marrow Transplant Research (CIBMTR) and European Group for Blood and Marrow Transplantation (EBMT), we (1) critically review progress to date in HSCT for MS; (2) describe current registry based projects including long-term follow-up studies in HSCT for MS and harmonization of the MS disease-specific research forms that will be used in future by both databases; (3) discuss challenges in study design for a prospective randomized clinical trial of HSCT versus alternative therapy for MS such as feasibility, and the importance of multidisciplinary clinical teams, need for a large sample size and duration of observation required for outcomes assessment; and (4) address future directions in HSCT therapy for MS. To undertake a definitive multicenter clinical trial in autologous HSCT for MS, it will be important to begin well in advance to assemble the team, evaluate proposals for study design, and consider options for the infrastructure and logistical support that will be needed. International collaboration, including partnership with the CIBMTR and EBMT, may be desirable and may in fact be critical for successful completion of a definitive comparative study.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".