Hypofractionated Versus Conventional Fractionated Radiotherapy for Patients with Triple Negative Breast Cancer: A Single Institution Randomized Trial
Bibliographic record
Abstract
Introduction: Delivering hypofractionated radiotherapy schedules for patients with breast cancer is a growing interest. The current study aimed to determine whether hypofractionated radiotherapy is as effective and safe as conventional fractionated radiotherapy for patients with triple negative breast cancer, irrespective of lymph node status or surgical type. Methods: The current study is a randomized, open-label trial. A total of 148 female participants with non-metastatic triple negative breast cancer (TNBC) were recruited from January 2019 to December 2023. Eligible participants were randomly assigned (1:1) for hypofractionated schedule or conventional radiotherapy schedule. The trial included all nonmetastatic TNBC eligible to adjuvant radiotherapy due to positively involved lymph nodes or high-risk features of the primary tumor. The 3- year Loco-regional recurrence free survival (RFS) was the primary end point. Results: At a median follow-up of 24 months, seven (5.3%) patients had developed locoregional recurrence, all of them in hypofractionated radiotherapy (RT) arm. The 3-year Loco-regional RFS rate was significantly higher in conventional RT arm compared to the hypofractionated RT arm (p <0.001). The 3-year distant metastases free survival was not significantly differed in the two groups (p =0.121). The 3-year overall survival was 90.4%, with no significant difference between the groups (p= 0.091). Conclusion: The effectiveness of hypofractionated radiotherapy for disease control of triple-negative disease, irrespective of lymph node status or type of surgical interference remains questionable.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".