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Record W2108607266 · doi:10.1120/jacmp.v16i5.5386

Late radiation toxicity in Hodgkin lymphoma patients: proton therapy's potential

2015· article· en· W2108607266 on OpenAlexafffundabout
Allison Toltz, N. Shin, Ellis Mitrou, C. Laude, Carolyn Freeman, Jan Seuntjens, William Parker, David Roberge

Bibliographic record

VenueJournal of Applied Clinical Medical Physics · 2015
Typearticle
Languageen
FieldMedicine
TopicRadiation Therapy and Dosimetry
Canadian institutionsMcGill University Health CentreCentre Hospitalier de l’Université de MontréalMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaFondation de France
KeywordsMedicineTomotherapyProton therapyRadiation therapyLung cancerAbsolute risk reductionHodgkin lymphomaLymphomaInternal medicineNuclear medicineOncologyConfidence interval

Abstract

fetched live from OpenAlex

In 2010, all young patients treated for intrathoracic Hodgkin lymphoma (HL) at one of 10 radiotherapy centers in the province of Quebec received 3D conformal photon therapy. These patients may now be at risk for late effects of their treatment, notably secondary malignancies and cardiac toxicity. We hypothesized that more complex radiotherapy, including intensity-modulated proton therapy (IMPT) and possibly IMRT (in the form of helical tomotherapy (HT)), could benefit these patients. With institutional review board approval at 10 institutions, all treatment plans for patients under the age of 30 treated for HL during a six-month consecutive period of 2010 were retrieved. Twenty-six patients were identified, and after excluding patients with extrathoracic radiation or treatment of recurrence, 20 patients were replanned for HT and IMPT. Neutron dose for IMPT plans was estimated from published measurements. The relative seriality model was used to predict excess risk of cardiac mortality. A modified linear quadratic model was used to predict the excess absolute risk for induction of lung cancer and, in female patients, breast cancer. Model parameters were derived from published data. Predicted risk for cardiac mortality was similar among the three treatment techniques (absolute excess risk of cardiac mortality was not reduced for HT or IMPT (p > 0.05, p > 0.05) as compared to 3D CRT). Predicted risks were increased for HT and reduced for IMPT for secondary lung cancer (p < 0.001, p < 0.001) and breast cancers (p< 0.001, p< 0.001) as compared to 3D CRT.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.926
Threshold uncertainty score0.465

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.036
GPT teacher head0.348
Teacher spread0.312 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations18
Published2015
Admission routes3
Has abstractyes

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