Treatment strategies for triple-negative primary breast cancer in older women: a systematic review
Bibliographic record
Abstract
BACKGROUND: Although the relative proportion of triple-negative breast cancer decreases with age, its prevalence is rising with an aging population. This study examined real-world treatment practices, whether age in older women with triple-negative breast cancer affects therapy and outcomes, focusing on the potentially curable nature of early-stage triple-negative breast cancer. METHODS: A Preferred Reporting Items for Systematic Reviews and Meta-Analyses, PRISMA-compliant search using population, intervention, comparison, outcomes criteria identified literature from 2014 to 2023 across 5 databases (MEDLINE, Embase, PubMed, Web of Science, and Scopus), focusing on women aged 65 years and older with early-stage triple-negative breast cancer. RESULTS: From 7171 records, 37 studies were included. Older women with triple-negative breast cancer exhibited less aggressive features, including lower Ki67, higher androgen receptor, and higher Bcl2 expression. Breast-conserving surgery with radiation therapy (RT) was associated with improved overall survival and breast cancer-specific survival, with fewer recurrences compared with mastectomy with or without RT. Older women with triple-negative breast cancer were more likely to receive RT than systemic therapy, and the lack of RT correlated with worse outcomes. Multivariate analyses showed that systemic treatment improved 5-year overall survival and breast cancer-specific survival. Overall, outcomes did not show significant differences between women aged 70 years and older and women younger than 70 years at a median follow-up of 46 months. CONCLUSIONS: The lack of overall outcome improvements for older women with triple-negative breast cancer following treatment may not solely be due to absent targetable receptors because the intrinsic biology in older patients may be relatively favorable. Instead, treatment selection biases against active treatment due to age-related factors may contribute substantially. Treatment decisions should be biology based and guided by a multidisciplinary, holistic, and patient-centered approach that carefully considers comorbidities, functional status, social support, and patient preferences.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.004 | 0.004 |
| 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) | 0.003 | 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".