Moderately hypofractionated post-operative radiation therapy for breast cancer: Preferences amongst radiation oncologists from countries in Latin America and the Caribbean
Bibliographic record
Abstract
Abstract Purpose The safety and effectiveness of moderately hypofractionated post-operative radiation therapy for breast cancer were demonstrated by several trials. This study aimed to evaluate the current patterns of practice and to assess possible aspects that affect the decision-making process regarding the use of fractionation in breast cancer patients in Latin America and the Caribbean (LAC). Methods Radiation oncologists from LAC were invited to contribute to this this study. A 38-question survey was used to evaluate their opinions. Results A total of 173 radiation oncologists from 13 countries answered the questionnaire. The majority of respondents (84.9%) preferred moderately hypofractionated post-operative radiation therapy as their first choice in cases of whole breast irradiation. For whole breast plus regional nodal irradiation, post-mastectomy (chest wall and regional nodal irradiation) without reconstruction, and post-mastectomy (chest wall and regional node irradiation) with reconstruction hypofractionated post-operative radiation therapy was preferred by 72.2% 71.1%, and 53.7% of respondents, respectively. Breast cancer stage, and flap-based breast reconstruction were the factors associated with absolute contraindications for the use of hypofractionated schedules. Conclusion Even though moderately hypofractionated post-operative radiation therapy for breast cancer is considered a new standard to the vast majority of the patients, its unrestricted application in clinical practice across LAC still faces reluctance.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".