Hypofractionated radiotherapy in early breast cancer: Clinical, dosimetric and radio-genomic issues
Bibliographic record
Abstract
Curative radiotherapy is enhanced by partitioning the total dose into daily dose increments, called fractions. Most human cancer types respond to total dose rather than to the size of daily fractions [1]. This is an important point of difference in comparison with the responses of normal tissues responsible for the most important late adverse effects, which are sensitive to fraction size as well as total dose. This difference underpins the historical use of 'small' fractions, classically ≤2.0 Gy, to deliver the highest possible tolerated total dose, thereby, ensuring the highest rate of tumour control. The α/β ratio is an empirical descriptor of fraction size sensitivity, early reacting normal tissues and most cancer types being insensitive (α/β ratio 7–20 Gy) relative to the late reacting (dose limiting) normal tissues with low α/β ratios in the range 0.5–6 Gy [2]. This difference in fractionation sensitivity between cancers and late reacting normal tissues has been challenged in the last 20 years by randomised clinical trials offering high level evidence that breast cancer is an exception in showing comparable sensitivity to fraction size as the normal tissues of the breast and ribcage. The evidence base includes four randomised trials from Canada and the UK [3–7]. The results suggest that there is no disadvantage to hypofractionation in terms of safety and efficacy, and benefits to patients and health services in terms of convenience and cost.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".