Autologous Hematopoietic Stem Cell Transplantation for Autoimmune Disease—Is It Now Ready for Prime Time?
Bibliographic record
Abstract
Current systemic therapies are rarely curative for patients with severe life-threatening forms of autoimmune disease (AID). During the past 15 years, autologous hematopoietic stem cell transplantation (HCT) has been demonstrated to cure some patients with severe AID refractory to all other available therapies, and thus AID has become an emerging indication for cell therapy. The sustained clinical effects after autologous HCT are better explained by qualitative change in the reconstituted immune repertoire rather than transient depletion of immune cells. Since 1996, more than 1300 AID patients have been registered by the European Group for Blood and Marrow Transplantation (EBMT) and almost 500 patients by the Center for International Blood and Marrow Transplant Research (CIBMTR). Autologous HCT is most commonly performed for patients with multiple sclerosis (MS) or systemic sclerosis (SSc). Systemic lupus, Crohn's disease, type I diabetes, and juvenile idiopathic arthritis are other common indications. Allogeneic transplants are still considered too toxic for use in AID, except for cases of immune cytopenia. Although biologic therapies have been effective at controlling the manifestations of the disease, they require continuous administration, thus raising questions about their increasing costs, morbidity, and mortality related to prolonged therapy. Perhaps it is a reasonable time to ask, "Is autologous HCT for severe AID now ready for prime time?" Yet, the paucity of controlled studies, the short-term toxicities, and the upcoming availability of second-generation biologic and targeted immunotherapies argues that perhaps HCT for AID should be still limited to clinical trials. In this article, we focus on the results of autologous HCT for MS and SSc because these are the two most commonly transplanted diseases. The promising data that is emerging may establish these diseases as standard indications for HCT.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".