Abstract PS1-50: Locoregional therapy in de novo metastatic breast cancer: Systemic review and meta-analysis
Bibliographic record
Abstract
Abstract Background: De novo metastatic breast cancer represents around 6% of breast cancer diagnoses. Retrospective data suggest that locoregional therapy (LRT) for the primary breast cancer in metastatic disease may improve outcomes. Randomized control trials (RCTs) have evaluated the role of LRT in this setting with inconsistent results. Methods: We searched PubMed to identify RCTs that compared LRT and standard systemic therapy to standard therapy alone in de novo metastatic breast cancer. The search was supplemented by a review of abstracts from key conferences. Hazard ratios (HRs) and their associated 95% confidence intervals (CIs) were computed and pooled in a meta-analysis using generic inverse variance. Overall survival (OS) data were extracted for the intention to treat (ITT) population and for pre-specified subgroups defined by tumor subtype and by site of metastases. Subgroup analysis evaluated the effect of systemic treatment prior randomization to LRT. Results: Analyses included 4 trials comprising 970 patients. LRT included standard surgery to the primary breast tumor in all studies, and adjuvant radiation per standard of care was mandatory in 3 studies. Systemic treatment prior randomization showed similar results (HR=0.92 and HR=1.06 for upfront LRT and LRT following systemic treatment, respectively, p for the subgroup difference=0.72). LRT was not associated with improved OS in the ITT population (HR 0.97, 95% CI 0.72-1.29, p=0.81). LRT was not associated with improved OS in any tumor subtypes, including hormone receptor positive (HR for OS= 0.96, 95% CI 0.65-1.43, p=0.85), triple negative (HR 1.4, 95% CI 0.50-3.91, p=0.52) and human epidermal growth factor receptor 2 (HER2) positive disease (HR 0.93, 95% CI 0.68-1.28, p=0.67). Additionally, LRT did not improve OS in bone only disease (HR 0.97, 95% CI 0.58-1.62, p=0.92) and in visceral disease (HR=1.02, 95% CI 0.77-1.35, p=0.90). Conclusions: LRT in de novo metastatic breast cancer is not associated with improved OS. Results are consistent among different breast cancer subgroups. Citation Format: Daniel Jack Reinhorn, Raz Mutai, Rinat Yerushalmi, Assaf Moore, Eitan Amir, Hadar Goldvaser. Locoregional therapy in de novo metastatic breast cancer: Systemic review and meta-analysis [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS1-50.
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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 | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.034 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".