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Record W4417529893 · doi:10.1007/s12672-025-02433-2

Blastic plasmacytoid dendritic cell neoplasm (BPDCN): international, multi-center collaboration and global registry program

2025· article· en· W4417529893 on OpenAlexaff
Astghik Voskanyan, Maria Badikyan, Marina Konopleva, Alvaro J. Alencar, Arusyak Ivanyan, Carolyn Owen, Consolato Sergi, Ching‐Tien Peng, Dickran Kazandjian, Justin Taylor, Funda Tekkeşin, Hasanein H. Ghali, Karen Bedirian, Maria Paola Martelli, Enrico Attardi, Maria Teresa Voso, Mariam Abramashvili, Mazin Faisal Al‐Jadiry, Michalis Michael, Min‐Yu Su, Nare Martirosyan, Nerses Ghahramanyan, Nino Totogashvili, Pavel P Kotoucek, Rejin Kebudi, Robin Ohannessian, Ruzanna Papyan, Shushan Hovsepyan, Salma Elashwah, Sameer Bakhshi, Samvel Bardakhchyan, Samvel Danelyan, Shaimaa El‐Ashwah, M. Tezer Kutluk, Deniz Tuğcu, Ahmad Alhuraiji, Vassilios Lazaris, Gevorg Tamamyan, Naveen Pemmaraju

Bibliographic record

VenueDiscover Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicCutaneous lymphoproliferative disorders research
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of OttawaUniversity of Calgary
FundersNational Institutes of HealthNational Cancer InstituteAptitude HealthAstellas PharmaBeiGeneGenentechMEI PharmaEli Lilly and CompanyAstraZenecaAmerican Society of Clinical OncologyCelgeneIncyteF. Hoffmann-La RocheAstellas Pharma USAmgenGilead SciencesU.S. Department of Defense
KeywordsComprehensionMEDLINEReal world dataClinical trial

Abstract

fetched live from OpenAlex

BACKGROUND: Blastic Plasmacytoid Dendritic Cell Neoplasm (BPDCN) is a rare and aggressive hematologic malignancy originating from plasmacytoid dendritic cell precursors. BPDCN shares common diagnostic and clinical features with other hematologic malignancies and various dermatological disorders. Differential diagnosis and treatment are challenging and require awareness by the dermatologist, hemato-oncologist, pathologist for detailed diagnostic and therapeutic workup. The outcomes remain poor, and the optimal treatment for the disease is yet to be established, emphasizing the need for a more comprehensive and globally inclusive approach. METHODS: In response to these challenges, we initiated an international, multi-center collaboration and established a global registry program for BPDCN patients. The registry collected both retrospective and prospective data on demographics, clinical presentations, diagnostic criteria, treatment regimens, and outcomes for cases diagnosed after Jan 2010. Data for this report was obtained from 36 patients across 16 centers in 12 countries, with ongoing contributions from additional centers. RESULTS: Preliminary analysis revealed a male predominance (78%), with a median age at diagnosis of 63 years, involving all age groups. The immunophenotype (CD123 + , CD4 + , CD56 +) was consistently observed in a majority of patients (88.8%), validating its diagnostic utility and paramount significance in the BPDCN diagnosis. Treatment responses varied based on initial regimens, with ALL-like approaches demonstrating more favorable outcomes compared to AML-like strategies, which were given to younger patients. Notably, relapse rates remained high. CONCLUSION: The BPDCN International Registry Program provides a valuable tool in consolidating global data and fostering collaboration among researchers and clinicians. This collaborative effort involving multiple countries on several continents not only aims to advance our comprehension of BPDCN but also lays the groundwork for standardized treatment protocols for improving outcomes for BPDCN patients worldwide.

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 imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.007
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.015
GPT teacher head0.387
Teacher spread0.373 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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