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Abstract GS4-02: Regional lymph node irradiation in early stage breast cancer: An EBCTCG meta-analysis of 13,000 women in 14 trials

2019· article· en· W2944119619 on OpenAlexaff
David Dodwell, Carolyn Taylor, Paul McGale, Charlotte E. Coles, Frances Duane, Richard Gray, Thorsten Kühn, Christophe Hennequin, S. Oliveros, Xiang Wang, Jens Overgaard, Philip Poortmans, Timothy J. Whelan

Bibliographic record

VenueCancer Research · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsJuravinski Cancer Centre
Fundersnot available
KeywordsMedicineBreast cancerInterquartile rangeLymph nodeRadiation therapyCancerAxillaNODALStage (stratigraphy)Internal medicineNuclear medicineOncologySurgery

Abstract

fetched live from OpenAlex

Abstract Background There is uncertainty as to which lymph node regions should be irradiated following breast cancer surgery. Systematic review of radiation dosimetry indicates that in randomised trials of nodal radiation therapy (RT) versus not, radiation delivery was qualitatively better in modern trials compared to older trials. Methods We undertook an individual patient data meta–analysis of randomised trials assessing the benefits and risks of RT to different lymph node regions including the axilla, supraclavicular fossa (SCF) and internal mammary chain (IMC). Eligible studies started before 2009, and included a randomisation, or pseudo–randomisation (by left–versus–right sided tumours), in which the only difference between treatment groups was the use, or extent, of nodal irradiation. Surgery/RT to the breast was the same in both arms. Analyses used standard log–rank methods, and were stratified by study, age, nodal status and year of follow–up. – Studies were categorised according to estimated mean heart dose in the nodal RT arm and whether regimens were likely to have delivered ≥85% of prescribed dose to target nodal regions. Results Information was available on 13,132 women in 14 comparisons of nodal RT versus not. There were 3260 recurrences, 2545 deaths from breast cancer and 4147 deaths overall. Eight trials starting 1961–1978, with median follow–up 9.2 (interquartile [IQR] range 3.4–17.5) years, had estimated >8 Gy mean heart dose and likely nodal dose <85% in the nodal RT arm. In these older trials, including 2178 women, nodal RT had no effect on breast cancer recurrence [Rate ratio (RR)=0.98, 95% CI 0.85–1.13, p=0.83] or breast cancer mortality (RR=1.05, 0.91–1.21, p=0.54), but increased non–breast cancer mortality (RR=1.44, 1.20–1.73, p<0.0001), leading to a net increase in any death (RR=1.18, 1.06–1.32, p=0.004). Six studies starting 1989–2003, with a mean follow–up 9.1 [IQR 7.0–11.0] years, had likely nodal dose ≥85%, and estimated mean heart dose <8 Gy in the nodal RT arm. In these more recent studies, including 10,954 women, nodal RT reduced breast cancer recurrence (RR=0.86, 95% CI 0.79–0.94, p=0.0006), breast cancer mortality (RR=0.81, 0.74–0.90, p<0.0001) and overall mortality (RR=0.86, 0.80–0.93, p=0.0002). No excess of non–breast cancer mortality was apparent (RR=0.96, 0.79–1.18, p=0.71). Recurrence rate ratios did not vary significantly according to nodal region(s) irradiated (axilla/SCF/IMC), or the use of adjuvant chemotherapy. Conclusions RT to regional lymph nodes in older (1961–78) studies increased the overall risk of death, probably explained by radiation exposure of the lungs and heart. Nodal RT in more recent (1989–2003) studies reduced breast cancer recurrence, breast cancer mortality and overall mortality without increasing non–breast cancer mortality. The proportional benefits from today's RT may be larger. Absolute benefits for individual women will depend on their absolute recurrence and breast cancer mortality risks. Citation Format: Dodwell D, Taylor C, McGale P, Coles C, Duane F, Gray R, Kühn T, Hennequin C, Oliveros S, Wang Y, Overgaard J, Poortmans P, Whelan T. Regional lymph node irradiation in early stage breast cancer: An EBCTCG meta-analysis of 13,000 women in 14 trials [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr GS4-02.

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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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.114
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.145
GPT teacher head0.425
Teacher spread0.280 · 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.

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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Citations50
Published2019
Admission routes1
Has abstractyes

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