Retrospective database analysis to assess treatment patterns, clinical outcomes, and healthcare resource utilization in metastatic or recurrent HER2-positive breast cancer in Alberta
Bibliographic record
Abstract
BACKGROUND: Population-based data from real-world sources on metastatic breast cancer (mBC) patient outcomes by HER2 status are limited, particularly in Canada. To meet this need, we examined treatment patterns, outcomes, and healthcare resource utilization in HER2-positive (HER2+) mBC in a real-world Canadian setting. PATIENTS AND METHODS: This retrospective longitudinal cohort consisted of all patients in Alberta, Canada diagnosed with de novo metastatic or recurrent HER2+ breast cancer between 2010 and 2019. Patient data were obtained from the provincial cancer registry, electronic medical records, and other administrative databases. RESULTS: 758 patients with HER2+ mBC were included, of which 461 (60.8 %) were recurrent cases. Taxane + trastuzumab + pertuzumab was the most frequent (61.7 %) first-line regimen, trastuzumab emtansine (T-DM1) was the most frequent (74.8 %) second-line regimen, and capecitabine + lapatinib was the most frequent (52.9 %) third-line regimen. Median overall survival from first-, second-, and third-line chemotherapy was 41.9 months (95 % CI: 36.9-51.2), 18.8 months (95 % CI: 15.4-24.3), and 12.9 months (95 % CI: 11.0-16.8), respectively, with no meaningful differences between de novo and recurrent patients. CONCLUSION: Uptake of guideline-recommended regimens in each line of therapy was lower in recurrent patients although survival was similar to de novo patients. These findings highlight the need for consensus on treatment regimens for de novo and recurrent HER2+ patients, effective first-and second-line management, and novel therapies to improve outcomes. MICROABSTRACT Our study evaluated real-world treatment patterns, clinical outcomes, and healthcare utilization in HER2-positive metastatic breast cancer (mBC) in Alberta, Canada. Among 758 patients, survival was similar between new diagnoses and recurrent cases, despite lower uptake of guideline-recommended therapies in recurrent patients. Our findings highlight the need for consensus on treatment strategies and novel therapies to improve mBC outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".