Efficacy and Safety of the Addition of Internal Mammary Irradiation to Standard Adjuvant Radiation in Early-Stage Breast Cancer: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Existing data on adding internal mammary nodal irradiation (IMNI) to the regional nodal fields are inconsistent. Methods: Randomized trials investigating the addition of IMNI to standard adjuvant radiation were identified. Hazard ratios (HRs) and 95% confidence intervals (CI) were extracted for overall-survival (OS), breast cancer specific-survival (BCSS), and disease-free survival (DFS) as well as distant-metastasis free survival (DMFS). The odds ratios (ORs) for regional and loco-regional recurrence, non-breast cancer mortality, secondary non-breast cancer, contralateral breast cancer, and cardiovascular morbidity and mortality were also extracted. Results: Analysis included five trials comprising 10,994 patients, predominantly with higher risk, lymph node positive disease. Compared to the control group, IMNI was associated with significant improvement in OS (HR = 0.91, p = 0.004), BCSS (HR = 0.84, p < 0.001), DFS (HR = 0.89, p= 0.01), and DMFS (HR = 0.89, p = 0.02). IMNI was also associated with reduced odds for regional (OR = 0.58, p < 0.001) and loco-regional recurrence (OR = 0.85, p = 0.04). The odds for cardiotoxicity were not statistically significantly higher (OR = 1.23, p = 0.07). There were comparable odds for cardiovascular mortality (OR = 1.00, p = 1.00), non-breast cancer mortality (OR = 1.05, p = 0.74), secondary cancer (OR = 0.95, p = 0.51), and contra-lateral breast cancer (OR = 1.07, 95% 0.77−1.51, p = 0.68). Conclusions: Compared to the control group, the addition of IMNI in high-risk patients is associated with a statistically significant improvement in survival, albeit with a magnitude of questionable clinical meaningfulness.
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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.028 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".