Haematopoietic cell transplantation for blastic plasmacytoid dendritic cell neoplasm: a North American multicentre collaborative study
Bibliographic record
Abstract
Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is incurable with conventional therapies. Limited retrospective data have shown durable remissions after haematopoietic cell transplantation (HCT) [allogeneic (allo) or autologous (auto)]. We conducted a multicentre retrospective study in BPDCN patients treated with allo-HCT and auto-HCT at 8 centres in the United States and Canada. Primary endpoint was overall survival (OS). The population consisted of 45 consecutive patients who received an allo-HCT (n = 37) or an auto-HCT (n = 8) regardless of age, pre-transplant therapies, or remission status at transplantation. Allo-HCT recipients were younger (50 (14-74) vs. 67 (45-72) years, P = 0·01) and had 1-year and 3-year OS of 68% [95% confidence interval (CI) = 49-81%] and 58% (95% CI = 38-75%), respectively. Allo-HCT in first complete remission (CR1) yielded superior 3-year OS (versus not in CR1) [74% (95% CI = 48-89%) vs. 0, P < 0·0001]. Allo-HCT outcomes were not impacted by regimen intensity [3-year OS for myeloablative conditioning = 61% (95% CI = 28-83%) vs. reduced-intensity conditioning = 55% (95% CI = 28-76%)]. One-year OS for auto-HCT recipients was 11% (95% CI = 8-50%). These results demonstrate efficacy of allo-HCT in BPDCN, especially in patients in CR1. Pertaining to auto-HCT, our results suggest lack of efficacy against BPDCN, but this observation is limited by the small sample size. Larger prospective studies are needed to better define the role of HCT in BPDCN.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".