Systemic Sclerosis as an Indication for Autologous Hematopoietic Cell Transplantation: Position Statement from the American Society for Blood and Marrow Transplantation
Bibliographic record
Abstract
Systemic sclerosis is a progressive inflammatory disease that is frequently fatal and has limited treatment options. High-dose chemotherapy with autologous hematopoietic cell transplantation (AHCT) has been evaluated as treatment for this disease in observational studies, multicenter randomized controlled clinical trials, and meta-analyses. On behalf of the American Society for Blood and Marrow Transplantation (ASBMT), a panel of experts in transplantation and rheumatology was convened to review available evidence and make a recommendation on AHCT as an indication for systemic sclerosis. Three randomized trials have compared the efficacy of AHCT with cyclophosphamide only, and all demonstrated benefit for the AHCT arm for their primary endpoint (improvement in the American Scleroderma Stem Cell versus Immune Suppression Trial, event-free survival in Autologous Stem Cell Transplantation International Scleroderma trial, and change in global rank composite score in Scleroderma: Cyclophosphamide or Transplantation trial). AHCT recipients also had better overall survival and a lower rate of disease progression. These findings have been confirmed in subsequent meta-analyses. Based on this high-quality evidence, the ASBMT recommends systemic sclerosis should be considered as a "standard of care" indication for AHCT. Close collaboration between rheumatologists and transplant clinicians is critical for optimizing patient selection and patient outcomes. Transplant centers in the United States are strongly encouraged to report patient and outcomes data to the Center for International Blood and Marrow Transplant Research on their patients receiving AHCT for this indication.
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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 | 0.037 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.024 | 0.025 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".