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Second malignant neoplasm risk after mediastinal radiotherapy for pediatric Hodgkin lymphoma on Children’s Oncology Group AHOD1331.

2025· article· en· W4410803025 on OpenAlexaff
Sarah A. Milgrom, Harald Paganetti, Hitesh Dama, Lindsay A. Renfro, Yue Wu, Isaac Meyer, Susan K. Parsons, Angela Punnett, Anne-Marie Charpentier, Andrea Lo, Raymond B. Mailhot Vega, Frank G. Keller, Kara M. Kelly, Bradford S. Hoppe, Sharon M. Castellino, David Hodgson

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsPrincess Margaret Cancer CentreBC Cancer AgencyCentre Hospitalier de l’Université de MontréalUniversity Health NetworkSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsMedicineRadiation therapyPediatric oncologyHodgkin lymphomaLymphomaOncologyInternal medicineCancer

Abstract

fetched live from OpenAlex

10019 Background: The reported incidence of second malignant neoplasms (SMN) in long-term survivors of Hodgkin lymphoma (HL) is derived from patients treated with outdated radiation therapy (RT) techniques. We modeled the risk of SMN in pediatric patients with high-risk classic HL treated with modern mediastinal RT. Methods: In patients who received mediastinal RT on the Children’s Oncology Group study AHOD1331, we modeled the lifetime attributable risk (LAR) at 70 years of age of thyroid, lung, and breast carcinoma. This value indicates the absolute increased risk of SMN at 70 years of age due to RT, above the baseline population risk (mean baseline rates at 70 years of age are 0.7%, 3.3%, and 8.9% for thyroid, lung, and breast carcinoma, respectively, https://seer.cancer.gov/data/ ). Results: In 296 patients who received protocol-directed mediastinal RT, median age at diagnosis was 15.1 years, 55% were female, and 98% had large mediastinal adenopathy. Following 5 cycles of chemotherapy, patients received RT targeting the mediastinum based on criteria of this study; in addition, some patients received RT to other supradiaphragmatic sites that contained slowly responding lesions, including the axilla (n = 3, 1%), lung (n = 7, 2.4%), upper neck (n = 4, 1.3%), and lower neck (n = 8, 2.7%). The RT modality was proton therapy in 25.3%, photon intensity modulated RT (IMRT) in 45.6%, and photon 3-dimensional conformal RT (3D-CRT) in 27.7%. The RT prescription dose was 21 Gy in 83% and 30 Gy in 16% who had a partial metabolic response at the completion of chemotherapy. The mean (range) doses to the thyroid, lungs, and breasts were 12.8 Gy (0-30.3), 8.0 Gy (0.1-15.2), and 4.2 Gy (0.2-14.5), respectively. For the complete cohort, the mean LAR at 70 years of age of thyroid carcinoma was 0.063% and of lung carcinoma was 5.34%. For females, the mean LAR at 70 years of age of breast carcinoma was 2.92%. The Table summarizes the LAR for each SMN, stratified by RT modality. Conclusions: In patients treated with mediastinal RT on a recent multi-institutional study of pediatric HL, the predicted long-term risk of SMN is substantially lower than in historical cohorts. Clinicians should consider the toxicity associated with a current RT approach when selecting therapies and counseling patients. Clinical trial information: NCT02166463 , this is a post hoc modeling study that includes patients enrolled on this study. Mean [range] lifetime attributable risk (%) at an attained age of 70 years for thyroid, lung, and breast carcinoma. Thyroid Lung Breast (females) 3D-CRT 0.046 [0.002-0.332]N=81 5.07 [0.12-10.82]N=82 1.82 [0.67-5.98]N=46 IMRT 0.064 [0.001-0.386]N=135 6.24 [2.22-11.79]N=135 4.36 [0.66-8.43]N=76 Proton 0.086 [0-1.160]N=74 4.15 [0.94-7.77]N=75 1.45 [0.17-7.23]N=40

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.031
GPT teacher head0.453
Teacher spread0.422 · 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 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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