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Record W2077349663 · doi:10.1002/pbc.24258

Impact of low‐dose involved‐field radiation therapy on pediatric patients with lymphocyte‐predominant Hodgkin lymphoma treated with chemotherapy: A report from the Children's Oncology Group

2012· article· en· W2077349663 on OpenAlexaff
Burton Appel, Lu Chen, Allen Buxton, Suzanne L. Wolden, David Hodgson, James B. Nachman

Bibliographic record

VenuePediatric Blood & Cancer · 2012
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer Centre
FundersNational Cancer InstituteNational Institutes of Health
KeywordsMedicineChemotherapyRadiation therapyLymphomaHodgkin lymphomaInternal medicineBlood cancerOncologyCancer

Abstract

fetched live from OpenAlex

BACKGROUND: Treatment of pediatric lymphocyte-predominant Hodgkin lymphoma (LPHL) is controversial but has typically consisted of both chemotherapy and radiation. Radiation therapy is associated with potential late effects in children and adolescents. We examined the impact of radiation therapy on long-term outcome of patients with LPHL treated on CCG-5942, a large pediatric cooperative group study of Hodgkin lymphoma (HL). PROCEDURE: Eighty-two patients with LPHL were registered on CCG-5942. Fifty-two patients (63%) received chemotherapy alone; 29 patients (35%) received chemotherapy followed by involved-field radiation therapy (IFRT). RESULTS: The median follow-up of the LPHL patients is 7.7 years; 63 patients (77%) have >5 years of follow-up. The 5-year event-free survival (EFS) and overall survival (OS) were 97% and 100%. Two relapses occurred, both in patients who did not receive IFRT. There were no significant differences in EFS or OS between patients who received or did not receive IFRT. CONCLUSIONS: This subset analysis demonstrates the chemosensitivity of pediatric LPHL. Patients who had a complete response to chemotherapy had an excellent EFS and OS without the addition of radiotherapy.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.008
GPT teacher head0.261
Teacher spread0.253 · 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.

Study designObservational
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

Citations30
Published2012
Admission routes1
Has abstractyes

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