Skin Toxicity in Early Breast Cancer Patients Treated with Field-In-Field Breast Intensity-Modulated Radiotherapy versus Helical Inverse Breast Intensity-Modulated Radiotherapy: Results of a Phase III Randomised Controlled Trial
Bibliographic record
Abstract
AIMS: Skin toxicity is a common adverse effect of breast radiotherapy. We investigated whether inverse-planned intensity-modulated radiotherapy (IMRT) would reduce the incidence of skin toxicity compared with forward field-in-field breast IMRT (FiF-IMRT) in early stage breast cancer. MATERIALS AND METHODS: This phase III randomised controlled trial compared whole-breast irradiation with either FiF-IMRT or helical tomotherapy IMRT (HT-IMRT), with skin toxicity as the primary end point. Patients received 50 Gy in 25 fractions and were assessed to compare skin toxicity between treatment arms. RESULTS: In total, 177 patients were available for assessment and the median follow-up was 73.1 months. Inverse IMRT achieved more homogeneous coverage than FiF-IMRT; erythema and moist desquamation were higher with FiF-IMRT compared with HT-IMRT (61% versus 34%; P < 0.001; 33% versus 11%; P < 0.001, respectively). Multivariate analysis showed large breast volume, FiF-IMRT and chemotherapy were independent factors associated with worse acute toxicity. There was no difference between treatment arms in the incidence of late toxicities. The 5-year recurrence-free survival was 96.3% for both FiF-IMRT and HT-IMRT and the 5-year overall survival was 96.3% for FiF-IMRT and 97.4% for HT-IMRT. CONCLUSIONS: Our study showed significant reduction in acute skin toxicity using HT-IMRT compared with FiF-IMRT, without significant reduction in late skin toxicities. On the basis of these findings, inverse-planned IMRT could be used in routine practice for whole-breast irradiation with careful plan optimisation to achieve the required dose constraints for organs at risk.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".