Blastic Plasmacytoid Dendritic Cell Neoplasm (BPDCN):Multi-Center Collaboration and Global Registry Program
Bibliographic record
Abstract
Background BPDCN is a rare, aggressive hematologic malignancy derived from the precursors of plasmacytoid dendritic cells (pDC), typically presenting with primary cutaneous dissemination and involvement of bone marrow (BM) as well as extramedullary sites including central nervous system (CNS). In 2008, it was recognized by WHO as a distinct entity and is now recognized under Myeloid/Histiocytic/Dendritic neoplasms in the 2022 5th edition update of WHO Classification. Since the recognition of this unique entity, recent efforts have been put forward for greater understanding and international collaboration, however usually focused on North America and Europe(Pemmaraju at al and Pagano et al), with this current effort representing the largest known international efforts including more parts of the world, including Asia, Middle East and Africa. Objective Due to its historical rarity and heterogeneous presentation of disease, as well as differences in availability of therapies across geo-locations, at present there is no worldwide consensus on the management of BPDCN. The outcomes remain poor, and the optimal therapy of disease remains to be determined. Launched on July 1st, 2022, the aim of our global registry is through a multi-center international collaboration to build a large database of patients with BPDCN in order to generate data-driven diagnostic and treatment recommendations. Materials and Methods The registry collects retrospective and prospective data on clinical presentation, diagnostics, treatment regimens and outcomes of patients diagnosed with BPDCN after January 1st, 2010. The data is collected globally through eCRF and Excel form. The Registry is included in ClinicalTrials.gov database (NCT05430971). Results Through July 15 th, 2023, 15 centers from 11 countries (Armenia, Canada, Cyprus, Egypt, Georgia, India, Italy, Taiwan, Turkey, UK and USA) have joined the registry and another 13 centers from USA, UK, Egypt, Iraq, Canada, Netherlands, Tajikistan, Czech Republic, Guatemala, Brazil, Serbia, Germany are onboarding. 27 retrospective and 2 prospective pts are currently included in the registry. 76 % of pts are male, in keeping with historical expectation BPDCN. Median age at diagnosis was 62 years (4-97). In 90 % of patients the tumor cells were triple positive with CD4+, CD56+, CD123+ immunophenotype. 53.6% of patients presented with cutaneous manifestation. 21% of pts received the initial treatment with AML-based regimens, 66% with ALL-based and 7% with lymphoma-based regimens. 21% of pts underwent alloSCT. 35% of pts were diagnosed after 2018, only 1 patient has received tagraxofusp, a CD123-directed therapy that received FDA approval for previously untreated or relapsed/refractory BPDCN in 2018(Pemmaraju N et al NEJM 2019). 69 % of patients achieved complete response (CR), from which 90 % were treated with ALL-based regimens. 52% of patients experienced relapse. Conclusion Current analysis of a 29-patient worldwide cohort of BPDCN demonstrates a high degree of heterogeneity in treatment regimens based on a multitude of considerations including geographic, socio-economic, drug availability, and varied clinical preferences. The outcome of ALL-based treatment was superior as compared to AML-based, but relapse rate remained high. Further global collaboration is needed to collect additional data and to identify the best diagnostic and therapeutic approaches for this challenging disease.
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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 | 0.001 |
| 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".