Autologous haematopoietic stem cell transplantation for rheumatic diseases: best practice recommendations from the EBMT Practice Harmonization and Guidelines Committee
Bibliographic record
Abstract
Immune-mediated rheumatologic and musculoskeletal diseases (RMDs) comprise a heterogeneous group of systemic conditions that affect the connective tissues of the musculoskeletal system and internal organs. Immune-mediated RMDs are driven by chronic autoimmune responses and typically require continuous or repeated administration of immunosuppressive or biologic disease-modifying drugs. Although generally effective, these therapies can cause both short- and long-term side effects and may fail to control the disease with risk of irreversible tissue damage. For such patients, haematopoietic stem cell transplantation (HSCT) has been successfully employed over the past 30 years, but this procedure requires caution due to significant side effects. To address these aspects, updated recommendations for the use of HSCT in RMDs have been developed in collaboration with an international expert panel from the European Society for Blood and Marrow Transplantation (EBMT). The panel reviewed all available evidence regarding HSCT application since 2004. Based on this review, EBMT expert-based consensus recommendations were formulated to guide best practices and ensure high-quality patient care. These recommendations include detailed indications, contraindications, and cautionary notes specific to each RMD, along with comprehensive protocols for diagnostic work-up. They are intended to support clinicians, scientists, patients, and caregivers in the field of RMDs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".