Network geometry of evidence from randomised controlled trials addressing donor selection and source of haematopoietic progenitor cells used in allogeneic transplantation: a systematic scoping review
Bibliographic record
Abstract
BACKGROUND AND METHODS: A scoping review of randomised controlled trials (RCTs) addressing source of cells and choice of donor for allogeneic haematopoietic cell transplantation (HCT) was performed to create a network of best evidence that allows us to identify new potential indirect comparisons for the strategic development of future studies that connect to the existing evidence network. RESULTS: A total of 19 eligible RCTs (2589 total patients) were identified. Nine studies (1566 patients) compared clinical outcomes following the use of peripheral blood progenitor cells (PBPCs) with bone marrow (BM) from matched related donors (eight studies) or matched unrelated donors (one study). The remaining studies compared BM or PBPCs with various methods of BM stimulation or manipulation (six studies), compared different methods of surface molecule-based selection and/or depletion of grafts (two studies) or compared the optimal number of units for paediatric cord blood transplantation (two studies). No published RCTs compared different types of donors. The geometry of the evidence network was analysed to identify opportunities for potential novel indirect comparisons and to identify opportunities to expand the network. Few indirect comparisons are currently feasible due to small sample size and heterogeneity in patient diagnoses and demographics between treatment nodes in the network. CONCLUSION: More RCTs that enrol greater numbers of similar patients are needed to leverage the current evidence network concerning donor choice and source of cells used in allogeneic 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 | 0.111 | 0.466 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.015 | 0.012 |
| Bibliometrics | 0.040 | 0.033 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".