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Record W2896013468 · doi:10.1093/annonc/mdy270.241

Toxicity and clinical outcomes of partial breast irradiation (PBI) compared to whole breast irradiation (WBI) for early stage breast cancer: A systematic review and meta-analysis

2018· review· en· W2896013468 on OpenAlexaff
Hadar Goldvaser, Anthony Fyles, Daniel Shepshelovich, Eitan Amir, Yasmin Korzets

Bibliographic record

VenueAnnals of Oncology · 2018
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineBreast cancerOdds ratioBrachytherapySubgroup analysisOncologyInternal medicineRadiation therapyConfidence intervalCancerSurgery

Abstract

fetched live from OpenAlex

Background: There is uncertainty about efficacy and toxicity differences between adjuvant PBI and WBI in women with early-stage breast cancer treated with breast conservation. Methods: We identified randomized trials that compared PBI to WBI in early-stage invasive breast cancer using PubMed. Odds ratios (ORs), 95% confidence intervals (CI) and absolute risks were computed for pre-specified efficacy and toxicity outcomes including cosmetics. Subgroup analysis evaluated the effect of PBI modality (external beam radiation treatment [EBRT], intraoperative radiation treatment [IORT] or brachytherapy) on efficacy. Meta-regression analysis explored the influence of median follow-up as well as patients and tumor characteristics on results. Results: Eight trials comprising 10298 patients were included. Efficacy results, weighted absolute differences and subgroup analysis are shown in the table. PBI was associated with increased odds of local recurrence compared to WBI. However, PBI was associated with reduced odds of death without breast cancer recurrence and improved overall survival (OS). Subgroup analysis showed the effect on local recurrence was influenced by modality of radiation; odds of local recurrence were increased with IORT and brachytherapy, but not with EBRT. Nodal involvement was associated with higher local recurrence risk while larger tumors were associated with lesser improvement in death without breast cancer recurrence and OS. PBI was associated with higher odds of fat necrosis (p = 0.002). Worse cosmetic outcome with PBI approached significance (p = 0.06). Conclusions: Compared to WBI, PBI is associated with higher odds for local recurrence and toxicity, but less death without breast cancer recurrence and improved OS. The balance between benefit and risk of PBI appears optimal for women with smaller ER positive tumors and without nodal involvement.Table: 246POR, 95% CIP value all/subgroup differenceWeighted absolute difference5-year local recurrenceAll2.28 (1.66-3.15)<0.0011.47%EBRT IORT Brachytherapy0.64 (0.25-1.62) 3.1 (2.12-4.51) 1.44 (0.63-3.29)0.0045-year regional recurrenceAll1.49 (0.88-2.53)0.140.3%EBRT IORT Brachytherapy1.96 (0.20-18.92) 1.45 (0.80-2.63) 1.56 (0.39-6.27)0.975-year contralateral breast cancerAll0.94 (0.59-1.47)0.77-0.1%EBRT IORT Brachytherapy0.85 (0.44-1.63) 1.54 (0.65-3.66) 0.64 (0.25-1.62)0.375-year death without breast cancer recurrenceAll0.55 (0.41-0.73)<0.001-1.6%EBRT IORT Brachytherapy0.71 (0.42-1.20) 0.45 (0.29-0.69) 0.57 (0.29-1.13)0.415-year overall survivalAll0.76 (0.61-0.95)0.02-1.1%EBRT IORT Brachytherapy0.79 (0.51-1.22) 0.78 (0.59-1.04) 0.61 (0.32-1.14)0.75 Open table in a new tab Legal entity responsible for the study: Hadar Goldvaser. Funding: Has not received any funding. Disclosure: All authors have declared no conflicts of interest.

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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)0.009
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.022
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0150.031
Bibliometrics0.0040.004
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.002
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 head0.184
GPT teacher head0.475
Teacher spread0.290 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations1
Published2018
Admission routes1
Has abstractyes

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