Blastic plasmacytoid dendritic cell neoplasm: challenges and future prospects
Bibliographic record
Abstract
Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare CD4+ CD56+ myeloid malignancy that is challenging to diagnose and treat. BPDCN typically presents with nonspecific cutaneous lesions with or without extra-cutaneous manifestations before progressing to leukemia. Currently, there is no standard of care for the treatment of BPDCN and various approaches have been used including acute myeloid leukemia, acute lymphoblastic leukemia, and lymphoma-based regimens with or without stem cell transplantation. Despite these treatment approaches, the prognosis of BPDCN remains poor and there is a lack of prospective data upon which to base treatment decisions. Recent work examining the mutational landscape and gene expression profiles of BPDCN has identified a number of potential therapeutic targets. One such target is CD123, the α subunit of the human interleukin-3 receptor, which is the subject of intervention studies using the novel agent SL-401. Other investigational therapies include UCART123, T-cell immunotherapy, and venetoclax. Prospective trials are needed to determine the best treatment for this uncommon and aggressive neoplasm.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".