Treatment Patterns, Clinical Outcomes and Quality of Life in BRCA1/2-Associated Breast Cancer Patients: A Retrospective Analysis
Bibliographic record
Abstract
Background: Breast cancer (BC) patients with germline BRCA1/2 pathogenic variants (PVs) often face unique challenges compared to non-carriers. However, the impact of PVs on treatment patterns, clinical outcomes, and quality of life (QoL) remains insufficiently explored. This study aims to assess these factors in these individuals. Methods: A retrospective analysis was conducted using data from the Medical University of Vienna Center for Familial Breast and Ovarian Cancer between 2011 and 2021. Among 1285 individuals identified, 338 were included (120 BRCA1 PVs, 47 BRCA2 PVs, and 171 non-carriers). Clinical data including treatment patterns and outcomes were collected; QoL was assessed in BRCA1/2 PV carriers using the SF-12 questionnaire. Results: Among 338 BC patients, BRCA1 PV carriers were significantly younger at disease onset and more likely to present with triple-negative BC, with higher Ki-67 (>10%) than BRCA2 or non-carriers. Platinum-based chemotherapy was more frequently administered to BRCA PV carriers for neoadjuvant treatment (OR 7.7, p < 0.001), and therapeutic bilateral mastectomy was more common in BRCA1 carriers (44.7%) compared to BRCA2 (37.8%, p = 0.114) and non-carriers (25.2%, p = 0.003). Epirubicin was the primary agent for adjuvant chemotherapy across all groups compared to other chemotherapeutic agents. QoL assessments revealed significant physical health challenges, particularly among those who underwent neoadjuvant chemotherapy and surgery, while mental health scores remained relatively high. Conclusions: This study highlights the distinct treatment patterns and tumor characteristics associated with BRCA1/2 carriers, including the impact of treatments on quality of life. Nevertheless, our findings ought to be interpreted with caution due to the small sample size. Larger prospective studies with more complete treatment data, including PARP inhibitor use, and further research on supportive care strategies are needed for this high-risk population.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".