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Record W2416665505 · doi:10.1097/mph.0000000000000594

Aggressive Metastatic Inflammatory Myofibroblastic Tumor After Allogeneic Stem Cell Transplant With Fatal Pulmonary Toxicity From Crizotinib

2016· article· en· W2416665505 on OpenAlexaff
Hwazen A. Shash, Camelia Stefanovici, Susan Phillips, Geoff D.E. Cuvelier

Bibliographic record

VenueJournal of Pediatric Hematology/Oncology · 2016
Typearticle
Languageen
FieldMedicine
TopicIgG4-Related and Inflammatory Diseases
Canadian institutionsUniversity of ManitobaCancerCare Manitoba
Fundersnot available
KeywordsCrizotinibMedicineAnaplastic lymphoma kinaseMalignancyAnaplastic large-cell lymphomaLymphomaPathologyPulmonary toxicityLungStem cellInternal medicineLung cancer

Abstract

fetched live from OpenAlex

Inflammatory myofibroblastic tumors (IMTs) are rare tumors with an intermediate spectrum of biological behavior. IMTs are uncommon secondary malignancies after hematopoietic stem cell transplant. The presence of anaplastic lymphoma kinase rearrangements in 50% of IMTs has led to therapeutic trials with crizotinib, although limited experience remains with crizotinib use in children. We describe the first reported case of a highly aggressive and metastatic IMT (secondary malignancy) in an 8-year-old girl following umbilical cord blood transplant. Although tumor response was demonstrated with anaplastic lymphoma kinase inhibition, she later developed fatal pulmonary toxicity from diffuse alveolar damage, a feature felt most likely to be due to crizotinib.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.242
Teacher spread0.232 · 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 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

Citations15
Published2016
Admission routes1
Has abstractyes

Explore more

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