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Efficacy and cost-effectiveness of breast cancer (BC) screening in female survivors of childhood Hodgkin lymphoma (HL).

2021· article· en· W3166340336 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 cancerCohortDigital mammographyPopulationMammographyQuality of life (healthcare)PediatricsGynecologyInternal medicineOncologyCancer

Abstract

fetched live from OpenAlex

6593 Background: Female childhood HL survivors treated with ≥10 Gy of chest radiation are at high risk of developing BC. The Children’s Oncology Group (COG) guidelines recommend lifetime annual mammography (MAM) and breast Magnetic Resonance Imaging (MRI) starting 8y after chest radiation or age 25, whichever is later, and clinical breast examination (CBE) annually from puberty and semiannually from age 25. Initial model results suggest that CBE adds no survival benefit in this cohort. Digital breast tomosynthesis (DBT) is increasingly replacing digital MAM in clinical practice. Here, we present the efficacy and cost-effectiveness of COG’s imaging-based screening recommendations. Methods: Life-years (LYs), quality-adjusted LYs (QALYs), BC mortality, and costs (2017 U.S.$) were estimated from simulating the lifetimes of 5-million chest-irradiated 25y old HL survivors who underwent BC screening with each of the following strategies: annual digital MAM, MRI, MAM+MRI, annual DBT or DBT+MRI from age 25 onward. Treatment-related BC risk (in-situ and invasive) and non-BC mortality were estimated from female 5y HL survivors in the Childhood Cancer Survivor Study and from U.S. population rates. Test sensitivity was 70-74% for MAM (based on prior HL studies) and 89% for DBT and MRI (based on women at high risk of de novo BC). Costs and quality of life weights were obtained from medical literature. Results: For HL survivors with no screening, lifetime BC risk was 42.7% and BC mortality was 18.1%. BC risk and non-BC mortality were, respectively, 7.4- and 5.2-fold higher at age 50 in HL survivors relative to the general population. Screening at ages 25-74 had similar LY gain and BC mortality reduction compared to lifetime screening; hence, we focused on screening for ages 25-74. For all strategies screening provided LY gain of 0.34-0.47 and reduced BC mortality by 6.7-9.8% compared with no screening; incremental cost-effectiveness ratio (ICER), or cost per QALY gained, for MAM alone was $58,726 and for DBT alone was $62,989. ICER of adding MRI to MAM ($385,285) or to DBT ($513,358) indicated lower cost-effectiveness of supplemental MRI (Table). Conclusions: Annual screening at ages 25-74y in chest-irradiated HL survivors appears beneficial. Using $100K per QALY gained as cost-effectiveness threshold, annual MAM or DBT are more cost-effective, whereas adding MRI to MAM is less cost-effective.[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)0.004
metaresearch head score (Gemma)0.011
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.418
Teacher spread0.359 · 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".

Quick stats

Citations2
Published2021
Admission routes1
Has abstractyes

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