Organ-sparing techniques and dose-volume constrains used in breast cancer radiation therapy – Results from European and Latin American surveys
Bibliographic record
Abstract
Background: Advances in local and systemic therapies have improved the outcomes of patients with breast cancer (BC), leading to a possible increased risk for postoperative radiation therapy (RT) late adverse events.The most adequate technologies and dose constraints for organs at risk (OAR) in BC RT have yet to be defined.Methods: An online survey was distributed to radiation oncologists (ROs) practicing in Europe and Latin America including the Caribbean (LAC) through personal contacts, RO and BC professional groups' networks.Demographic data and clinical practice information were collected. Results:The study included 585 responses from ROs practicing in 57 different countries.The most frequently contoured OAR by European and LAC participants were the whole heart (96.6 % and 97.7 %), the ipsilateral (84.3 % and 90.8 %), and contralateral lung (71.3 % and 77.4 %), whole lung (69.8 % and 72.9 %), and the contralateral breast (66.4 % and.83.2 %).ESTRO guidelines were preferred in Europe (33.3 %) and the RTOG contouring guideline was the most popular in LAC (62.2 %), while some participants used both recommendations (13.2 % and 19.2 %).IMRT (68.6 % and 59.1 %) and VMAT (65.6 % and 60.2 %) were the preferred modalities used in heart sparing strategies, followed by deep inspiration breath-hold (DIBH) (54.8 % and 37.4 %) and partial breast irradiation (PBI) (41.6 % and 24.6 %).Only a small percentage of all ROs reported the dose-volume constraints for OAR used in routine clinical practice.A mean heart dose (Heart-D mean ) between 4 and 5 Gy was the most frequently reported parameter (17.2 % and 39.3 %). Conclusion:The delineation approaches and sparing techniques for OAR in BC RT vary between ROs worldwide.The low response rate to the dose constraints subset of queries reflects the uncertainty surrounding this topic and supports the need for detailed consensus recommendations in the clinical practice.
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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 | 0.001 | 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".