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Late Effects in the Era of Modern Therapy for Hodgkin Lymphoma

2011· review· en· W2103610103 on OpenAlexaff
David Hodgson

Bibliographic record

VenueHematology · 2011
Typereview
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineRadiation therapyToxicityOncologyInternal medicineCumulative incidenceClinical trialIncidence (geometry)DiseaseSurgeryCohort

Abstract

fetched live from OpenAlex

Extended-field and subtotal nodal radiation therapy (RT), developed in the 1960s, was the first reliably curative treatment for early-stage Hodgkin lymphoma (HL). However, the large volume of normal tissue irradiated resulted in significant delayed toxicity, including cardiac disease and second cancers (SCs). The 30-year cumulative incidence of heart disease among adult survivors receiving 40-45 Gy of extended-field or mantle RT is approximately 30%; the incidence of SCs is similar. Improving disease control while reducing the toxicity of treatment has been a major objective of HL trials for more than 2 decades. Contemporary involved-field RT (IFRT) reduces irradiated volumes and produces significant reductions in normal tissue dose compared with historic treatments. Recent data indicate that, compared with mantle RT, IFRT reduces the relative risk of breast cancer among young females receiving mediastinal RT by approximately 60% and also reduces cardiac dose. The recent transition to involved-node RT allows further reductions in normal tissue dose. Response-adapted therapy is being evaluated in clinical trials as a means of identifying those patients most likely to benefit from treatment reduction or intensification, enhanced screening will facilitate early intervention to reduce the clinical burden of late effects, and there is increasing interest in elucidating the genetic correlates of treatment toxicity.

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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.053
GPT teacher head0.343
Teacher spread0.290 · 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

Citations109
Published2011
Admission routes1
Has abstractyes

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