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Abstract P4-11-03: The Impact of Fractionation on Local Relapse for Patients with Grade 3 Breast Cancer

2010· article· en· W2079941204 on OpenAlexaffabout
Scott Tyldesley, Ryan Woods, Caroline Speers, Alan Nichol, L. Weir, Ivo A. Olivotto

Bibliographic record

VenueCancer Research · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsLumpectomyMedicineBreast cancerMastectomyRadiation therapyPopulationInternal medicineHormonal therapyOncologyDose fractionationSurgeryCancer

Abstract

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Abstract Background: Several randomized trials have demonstrated that hypofractionated (HF) and conventionally fractionated (CF) radiotherapy (RT) provide equivalent local control following breast conserving surgery (BCS). However, an update of the Canadian trial suggested that patients with grade 3 disease had an increased risk of local relapse after HF. The risk of local relapse following HF or CF according to grade was investigated among a population-based cohort from British Columbia, Canada. Materials and methods: Female patients diagnosed between 1990 and 2000 with T1-T2N0M0 breast cancer treated with lumpectomy, axillary dissection and RT with at least 6 nodes removed and RT delivered to the breast were identified. Whole breast RT prescriptions were distributed in two groups : HF (typically 42.5 to 44 Gy in 16 fractions), and CF (45Gy to 50 Gy in 25 fractions). The 45 Gy prescription was followed by a boost to the biopsy cavity regardless of the margin status. Patients with close or positive margins received a boost (typically 7.5 to 10Gy in 3 to 4 fractions, or 10 to 20Gy in 5 to 10 fractions). Baseline demographic (age, year of diagnosis), tumour (grade, histology, size, lymphatic vascular space invasion (LVI), presence of extensive DCIS) and treatment factors (margin status, hormonal or chemotherapy use, RT fractionation group, and RT boost use) were abstracted. Cumulative rates of local relapse were estimated using a competing risk approach (distant relapses or death were competing risks) and compared across groups using Gray's test. Factors significant on univariate analysis were included with fractionation group in a multivariate (Fine and Gray) model among grade 3 patients. Results: The cohort consisted of 1,335 patients diagnosed with grade 3 breast cancers: 252 received CF and 1083 patients received HF. The fractionation groups were well balanced for most of the aforementioned factors except median age (56 years for CF vs 52 years for HF (P<0.01), and use of systemic therapy (hormones alone: 26% vs 19%; chemotherapy alone: 27%vs 33%; and chemo+hormone therapy: 8% vs 10% (p=0.04) for HF compared to CF). The 10-year cumulative incidence rate of local relapse in patients with grade 3 breast cancers was 6.9% for the HF group and 6.2 % for the CF group (p=0.99). A Fine and Gray multivariate competing risk model showed that age under 40 years (p=0.02), positive margins (p=0.05) and negative ER status (p=0.01) were associated with an increased risk of local relapse, but fractionation group was not (Hazard ratio=0.95, p=0.88). Conclusions: There was no evidence that hypofractionation was inferior to conventional fractionation for breast conserving therapy in patients with T1-T2 N0, grade 3 breast cancer in a population-based series. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P4-11-03.

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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)0.003
metaresearch head score (Gemma)0.004
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 score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.025
GPT teacher head0.383
Teacher spread0.358 · 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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Citations1
Published2010
Admission routes2
Has abstractyes

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