Do women younger than 40 treated in the hormone-therapy era benefit from a radiotherapy boost as a part of adjuvant breast radiotherapy?
Bibliographic record
Abstract
72 Background: The EORTC 22881 trial showed a 10% reduction in local relapse with a radiotherapy boost (RTB) after breast conserving therapy (BCT) among women ≤40 years old. However no premenopausal patients received hormone therapy (HT) in this study. A policy change in December 1998 recommended the use of HT after chemotherapy for premenopausal ER positive women. A second policy change in December 2001 recommended an RTB after BCT for women ≤40 years old. The purpose of our study was to describe: 1)how the use of HT and RTB after BCT changed after practice guidelines were implemented in a population-based cancer care program; and 2) how local relapse rates (LRR) changed after these policy changes. Methods: A provincial database was used to analyse all women ≤ 40 years old referred for consideration of radiotherapy with margin negative stage 1 and 2 (≤3 nodes positive) breast cancer, treated with lumpectomy and whole breast radiotherapy. Cases were grouped into three eras according to policy transition with 3 month gaps: 1) Jan 1996-Sep 1998, 2) Jan 1999-Sep 2001, 3) Jan 2002 to Sep 2004. Changes in the use of HT and RTB over these eras were assessed. Eight year LR-free survival was calculated using the Kaplan-Meier method and the three eras compared using log rank tests. Multivariable analysis (MVA) was performed including era, size of tumour, nodal status (0 vs 1-3), grade, lymphovascular space invasion (LVI), and use of chemotherapy. Results: There were 130 eligible patients from Era 1, 145 patients from Era 2, and 140 patients from Era 3. ER status did not differ across eras. HT was used for ER positive patients in 13% of Era 1, 68% of Era 2, and 83% of Era 3 cases (p<0.001). RTB was used in 40% of Era 1, 28% of Era 2, and 77% of Era 3 patients (p<0.001). LRR at 8 years were 87.3% Era 1, 94.8 % Era 2, and 94.5% Era 3 (p=0.03). Era (used as surrogate for transitions in the use of HT and RTB) remained significant on MVA (0=0.008). Conclusions: Patterns of use of HT and RTB changed after policy changes. The benefit of adding a boost in women ≤40 years old shown by the EORTC was not observed after the introduction of routine HT at a population level.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".