Palliative radiation therapy for locally advanced breast cancer
Bibliographic record
Abstract
PURPOSE OF REVIEW: Globally, breast cancer is the most commonly diagnosed cancer in women. Locally advanced breast cancers (LABCs) may necessitate palliative radiation therapy (RT) due to the severity of the patients' symptoms, inoperability, or other reasons precluding curative-intent treatment such as poor performance status and patient comorbidities. This review aims to discuss current evidence on palliative RT in LABC. RECENT FINDINGS: Advanced targeted RT techniques have led to improvements in local control with reduced treatment-related toxicities. Emerging short-course palliative RT prescriptions offer feasible options that avoid delay in systemic therapy. Additionally, recent studies also highlight approaches for integrating palliative RT with systemic therapies. SUMMARY: Palliative RT plays a vital role in managing symptoms and enhancing quality of life for LABC patients. However, there is currently no consensus on the optimal prescriptions for palliative RT in these patients. Standardized reporting of palliative RT studies is needed for robust comparison of efficacy and toxicity between various treatment regimens. Furthermore, future research on the optimal integration of RT with novel systemic agents is needed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".