A Multicenter Randomized Trial of Breast Intensity-Modulated Radiation Therapy to Reduce Acute Radiation Dermatitis
Bibliographic record
Abstract
PURPOSE: Dermatitis is a frequent adverse effect of adjuvant breast radiotherapy. It is more likely in full-breasted women and when the radiation is distributed nonhomogeneously in the breast. Breast intensity-modulated radiation therapy (IMRT) is a technique that ensures a more homogeneous dose distribution. PATIENTS AND METHODS: A multicenter, double-blind, randomized clinical trial was performed to test if breast IMRT would reduce the rate of acute skin reaction (notably moist desquamation), decrease pain, and improve quality of life compared with standard radiotherapy using wedges. Patients were assessed each week during and up to 6 weeks after radiotherapy. RESULTS: A total of 358 patients were randomly assigned between July 2003 and March 2005 in two Canadian centers, and 331 were included in the analysis. Breast IMRT significantly improved the dose distribution compared with standard radiation. This translated into a lower proportion of patients experiencing moist desquamation during or up to 6 weeks after their radiation treatment; 31.2% with IMRT compared with 47.8% with standard treatment (P = .002). A multivariate analysis found the use of breast IMRT (P = .003) and smaller breast size (P < .001) were significantly associated with a decreased risk of moist desquamation. The use of IMRT did not correlate with pain and quality of life, but the presence of moist desquamation did significantly correlate with pain (P = .002) and a reduced quality of life (P = .003). CONCLUSION: Breast IMRT significantly reduced the occurrence of moist desquamation compared with a standard wedged technique. Moist desquamation was correlated with increased pain and reduction in the quality of life.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".