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Record W2507286557 · doi:10.1177/1078155216665245

A rare case of blastic plasmacytoid dendritic cell neoplasm with deletion 7q.31, in the setting of heavy pre-treatment with alkylating chemotherapy

2016· article· en· W2507286557 on OpenAlexaff
Varinder Kaur, Arjun Swami, Shebli Atrash, Sara C. Shalin, Muthu Veeraputhiran, Peter D. Emanuel, Yogesh Jethava

Bibliographic record

VenueJournal of Oncology Pharmacy Practice · 2016
Typearticle
Languageen
FieldMedicine
TopicCutaneous lymphoproliferative disorders research
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsMedicineInterleukin-3 receptorPlasmacytoid dendritic cellNeoplasmBone marrowPathologyMyeloidMyeloid leukemiaLymph nodeDermisLeukemiaChemotherapyDendritic cellCancer researchImmunologyInternal medicineImmune system

Abstract

fetched live from OpenAlex

Blastic plasmacytoid dendritic cell neoplasm is rare myeloid malignancy clinically characterized by non-pruritic, violaceous and papulo-nodular skin lesions, together with bone marrow and lymph node involvement. Histologically, there is infiltration of dermis by neoplastic mono-nuclear CD4, CD56, CD123 co-expressing cells with epidermal sparing. Most commonly blastic plasmacytoid dendritic cell neoplasm presents as a de-novo condition, and treatment-related blastic plasmacytoid dendritic cell neoplasm is a rare phenomenon. Due to rarity of the disease, there is no established standard of care treatment. Both acute myeloid leukemia and acute lymphoid leukemia type induction regimens have been used for treatment of blastic plasmacytoid dendritic cell neoplasm, with initial response rate of 50%-80%. We present a rare case of therapy-associated blastic plasmacytoid dendritic cell neoplasm in a patient with remote history alkylating agent systemic therapy. A lag period of five to seven years and presence of deletion 7q.31 seen in bone marrow biopsy specimen in our patient are consistent with a likely therapy-associated etiology of his blastic plasmacytoid dendritic cell 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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.595
Threshold uncertainty score0.407

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.383
Teacher spread0.358 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations3
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Oncology Pharmacy PracticeSame topicCutaneous lymphoproliferative disorders researchFrench-language works237,207