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Efficacy of clinical breast examination in chest-irradiated female survivors of childhood Hodgkin lymphoma (HL).

2021· article· en· W3167096582 on OpenAlexaff
F. Lennie Wong, Janie M. Lee, Wendy M. Leisenring, Joseph Philip Neglia, Rebecca M. Howell, Susan A. Smith, Kevin C. Oeffinger, Chaya S. Moskowitz, Tara O. Henderson, Ann C. Mertens, Paul C. Nathan, Yutaka Yasui, Wendy Landier, Gregory T. Armstrong, Leslie L. Robison, Smita Bhatia

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsHospital for Sick Children
FundersNational Institutes of HealthAmerican Cancer Society
KeywordsMedicineBreast cancerCohortPopulationRadiation therapyIncidence (geometry)PediatricsCancerInternal medicine

Abstract

fetched live from OpenAlex

10028 Background: Female survivors of childhood HL treated with ≥10 Gy of chest radiation are at high risk for breast cancer (BC). The Children’s Oncology Group (COG) guidelines recommend CBE annually starting at puberty and then semiannually from age 25, plus lifetime annual mammography (MAM) and breast Magnetic Resonance Imaging (MRI) starting 8y after chest radiation or age 25, whichever is later. While imaging-based screening recommendations are largely consistent with US guidelines for women at high BC risk, only the COG guidelines recommend CBE. The benefits of lifetime CBE starting from puberty for life in chest-irradiated HL survivors is unknown. Methods: Life-years (LYs) and lifetime BC mortality risk were estimated from a simulated cohort of 5-million HL survivors using the data from 5y female survivors of HL in the Childhood Cancer Survivor Study (CCSS) treated with ≥10 Gy of chest radiation. The simulated cohort underwent annual MAM+MRI from age 25 for life, with and without annual CBE from age 11 (presumed age of puberty) to age 24 and with and without semiannual CBE from age 25 for life with 100% adherence. BC included in-situ and invasive BC. Treatment-related BC incidence and non-BC mortality risks were estimated from the CCSS data. Risks at age <25 were extrapolated from the CCSS estimates while risks beyond age 50 were extrapolated additionally using the US population rates. CBE sensitivity (17.8%, in-situ and invasive BC) and specificity (98%) and MAM+MRI sensitivity (84.2-86.0%, in-situ; 96.7-97.1%, invasive) and specificity (75.3%) were obtained from the medical literature. Results: The CCSS cohort included 1057 female HL survivors. BC (all invasive) developed in three patients at age <25 (ages: 23, 24, 24). In the simulated cohort receiving no screening, lifetime BC risk was 40.8% and BC mortality was 17.5%. HL survivors around age 50 were at a 7.4-fold higher risk of developing BC and a 5.2-fold higher risk of non-BC mortality when compared with the general population. Compared to no annual CBE for ages 11-24y, undergoing annual CBE did not increase gains in LYs or reduce lifetime BC mortality relative to no screening (Table). Among those who survived to age ≥25, undergoing semiannual CBE from age 25 for life compared to no semiannual CBE also resulted in little gain in LYs or reduction in lifetime BC mortality relative to no screening. Conclusions: Lifetime CBE starting at puberty in conjunction with MAM+MRI appears to add little survival benefits compared with no CBE, suggesting that COG guidelines may be revised without adverse effect on long-term outcomes for chest-irradiated female survivors of childhood HL.[Table: see text]

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)0.002
metaresearch head score (Gemma)0.007
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 score0.002
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.060
GPT teacher head0.414
Teacher spread0.354 · 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
Published2021
Admission routes1
Has abstractyes

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