Does Locoregional Radiation Therapy Improve Survival in Breast Cancer? A Meta-Analysis
Bibliographic record
Abstract
PURPOSE: Recent randomized trials in women with node-positive breast cancer who received systemic treatment report that locoregional radiation therapy improves survival. Previous trials failed to detect a difference in survival that results from its use. A systematic review of randomized trials that examine the effectiveness of locoregional radiation therapy in patients treated by definitive surgery and adjuvant systemic therapy was conducted. METHODS: Randomized trials published between 1967 and 1999 were identified through MEDLINE database, CancerLit database, and reference lists of relevant articles. Relevant data was abstracted. The results of randomized trials were pooled using meta-analyses to estimate the effect of treatment on any recurrence, locoregional recurrence, and mortality. RESULTS: Eighteen trials that involved a total of 6,367 patients were identified. Most trials included both pre- and postmenopausal women with node-positive breast cancer treated with modified radical mastectomy. The type of systemic therapy received, sites irradiated, techniques used, and doses of radiation delivered varied between trials. Data on toxicity were infrequently reported. Radiation was shown to reduce the risk of any recurrence (odds ratio, 0.69; 95% confidence interval [CI], 0.58 to 0.83), local recurrence (odds ratio, 0.25; 95% CI, 0.19 to 0.34), and mortality (odds ratio, 0.83; 95% CI, 0.74 to 0.94). CONCLUSION: Locoregional radiation after surgery in patients treated with systemic therapy reduced mortality. Several questions remain on how these results should be translated into current-day clinical practice.
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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 | 0.020 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.053 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".