Allogeneic HSCT for Autoimmune Diseases: A Retrospective Study From the EBMT ADWP, IEWP, and PDWP Working Parties
Bibliographic record
Abstract
Background: This retrospective study assessed the use and long-term outcome of allogeneic hematopoietic stem cell transplantation (HSCT) in patients with severe autoimmune diseases (ADs), reported to the European Society for Blood and Marrow Transplantation (EBMT) registry. Methods: Between 1997-2014, 128 patients received allogeneic HSCT for various hematological (n=49) and non-hematological (n=79) refractory ADs. The median age was 12.7 years (0.2-62.2). Donors were syngeneic for 7, matched related for 46, unrelated for 51, haploidentical for 15 and cord blood for 9 patients. Results: The incidence of grades II-IV acute graft-versus-host disease (GvHD) was 20.8% at 100 days. Cumulative incidence of chronic GvHD was 27.8% at 5-years. Non-relapse mortality (NRM) was 12.7% at 100-days. Overall survival (OS) and Progression-Free Survival (PFS) were 70.2% and 59.4 % at 5-years respectively. By multivariate analysis, age less than 18 years, males, and more recent year of transplant were found to be significantly associated with improved PFS. Reduced conditioning intensity was associated with a lower NRM. On a subgroup of 64 patients with detailed information a complete clinical response was obtained in 67% of patients at one-year. Conclusions: This large EBMT survey suggests the potential of allogeneic HSCT to induce long-term disease control in a large proportion of refractory ADs, with acceptable toxicities and NRM, especially in younger patients.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".