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Record W2551609581 · doi:10.1097/mph.0000000000000703

Nivolumab in the Treatment of Refractory Pediatric Hodgkin Lymphoma

2016· article· en· W2551609581 on OpenAlexaff
Alexandra E. Foran, Helen Nadel, Anna F. Lee, Kerry J. Savage, Rebecca Deyell

Bibliographic record

VenueJournal of Pediatric Hematology/Oncology · 2016
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsChild and Family Research InstituteUniversity of British ColumbiaBC Children's HospitalBC Cancer Agency
FundersBristol-Myers Squibb
KeywordsMedicineNivolumabRenal cell carcinomaOncologyLymphomaAdverse effectInternal medicineCancerRefractory (planetary science)Progressive diseaseDiseaseImmunotherapy

Abstract

fetched live from OpenAlex

The programmed death-1 (PD-1) pathway of immune evasion is exploited by many malignancies to limit host T-cell-mediated immune responses. Nivolumab is a PD-1-blocking monoclonal antibody that disrupts this pathway and is FDA approved for the treatment of metastatic melanoma, renal cell carcinoma, and squamous non-small cell lung cancer. In this case report, we describe the first published pediatric experience of nivolumab in refractory classic Hodgkin lymphoma. In this patient with primary refractory disease and high disease burden, cytokine release syndrome requiring inotropic support developed following the first infusion of nivolumab. The patient subsequently demonstrated a dramatic clinical response with resolution of fevers, transfusion independence, improvement in functional status, and very good partial response on PET/CT following a single dose. Nivolumab was continued with corticosteroid and antihistamine premedication without further adverse events and clinical benefit was sustained at 11 months after therapy initiation, despite evidence of slow radiographic disease progression.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.038
GPT teacher head0.358
Teacher spread0.320 · 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 designNon-randomized trial
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

Citations44
Published2016
Admission routes1
Has abstractyes

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