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Record W2899093300 · doi:10.7759/cureus.3516

Hypofractionation Radiotherapy vs. Conventional Fractionation for Breast Cancer: A Comparative Review of Toxicity

2018· review· en· W2899093300 on OpenAlexaboutno aff
Ashraf Youssef, Jason Stanford

Bibliographic record

VenueCureus · 2018
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBreast cancerToxicityBreast-conserving surgeryFractionationRadiation therapyDose fractionationOncologySurgeryInternal medicineCancerMastectomy

Abstract

fetched live from OpenAlex

The use of postoperative radiation therapy after breast-conserving surgery was longstanding standard practice. The treatment protocol used a standard fractionation of 50 Gy in 25 fractions plus a boost. Recently, the hypofractionation approach has gained support based on Canadian and English studies that claimed equal tumor control and similar toxicity to the standard protocol. We conducted a review of the literature of hypofractionation studies and compared the reported toxicity with the general literature. We placed special emphasis on breast fibrosis after hypofractionation versus standard fractionation. We found a striking difference in the breast toxicity reported by the hypofractionation literature regarding breast fibrosis as compared to standard fractionation. Breast fibrosis should be explored further via additional studies and discussed with potential breast-conserving surgery patients.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.005
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.059
GPT teacher head0.406
Teacher spread0.347 · 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 designNot applicable
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

Citations14
Published2018
Admission routes1
Has abstractyes

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