MétaCan
Menu
Back to cohort
Record W4384463912 · doi:10.58931/cht.2022.1211

Immunotherapy in Hodgkin lymphoma

2022· article· en· W4384463912 on OpenAlexaffabout
John Kuruvilla

Bibliographic record

VenueCanadian Hematology Today · 2022
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsBrentuximab vedotinMedicinePembrolizumabNivolumabOncologyInternal medicineLymphomaClinical trialMalignancyImmunotherapyChemotherapyCancerHodgkin lymphoma

Abstract

fetched live from OpenAlex

Classical Hodgkin lymphoma (cHL) is a very curable form of cancer for the majority of patients that receive standard primary therapy. Many patients will have a second opportunity for cure at the time of first progression using approaches that incorporate high dose chemotherapy and autologous stem cell transplant (ASCT). In the non-curative setting, a group of patients (including patients with advanced age and comorbidities precluding standard therapy approaches and those with lymphoma that persists despite these treatments) will be treated with palliative intent. While these patients have had limited options in the past, novel therapies have rapidly become the standard of care in this setting. Antibodies targeting CD30 (the antibody drug conjugate brentuximab vedotin [BV]) and the immune checkpoint through PD1 (nivolumab and pembrolizumab) have now become standard approved treatments for patients beyond second-line treatment. The biology of PD1 appears particularly relevant in cHL, providing a strong clinical rationale for evaluating these agents in this malignancy. Clinicians in Canada now have several choices when making treatment decisions in patients with relapsed or refractory cHL (RR-cHL). Prospective trials are now determining the role of anti-PD1 antibodies in the curative setting.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.011
GPT teacher head0.244
Teacher spread0.233 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Hematology TodaySame topicLymphoma Diagnosis and TreatmentFrench-language works237,207