Abstract PO3-16-11: Attrition rates from first- to third-line therapy in HER2+ metastatic breast cancer in Europe
Bibliographic record
Abstract
Abstract Background: Patients (pts) with human epidermal growth factor receptor 2 (HER2)-positive (HER2+) metastatic breast cancer (mBC) who experience progression with adjuvant first-line (1L) therapy (trastuzumab, pertuzumab, and a taxane) typically require treatment escalation. Trastuzumab emtansine was standard of care in the second-line (2L) setting until the recent approval (Jul 2022 in the EU) of trastuzumab deruxtecan in ≥2L settings. Receiving optimal targeted therapy in the earliest indicated setting is important to maximize the likelihood of durable clinical benefit. As new therapies become available, understanding subsequent lines of therapy may help guide treatment decision making and inform the optimal treatment paradigm for pts with HER2+ mBC. This study characterizes contemporary attrition rates in pts with HER2+ mBC receiving routine care in Europe. Methods: In this ongoing, multicenter, observational study, electronic medical record (EMR) data were collected from female pts ≥18 years old diagnosed with HER2+ mBC between Jan 1, 2017, and Jun 30, 2021, in the UK, France, Germany, Italy, and Spain. Structured EMR data and manually abstracted unstructured data from oncology centers were curated. Pts were followed for ≥12 months from mBC diagnosis. Data analysis is ongoing. The primary endpoint was attrition rate (percentage of pts who completed a line of therapy [LOT] but did not receive the subsequent LOT after 1L and 2L therapy). Documented reasons for attrition included death or move to end-of-life palliative care, end of study period, loss to follow up, or discontinuation due to toxicity. Reasons were categorized as ‘other’ if they did not meet these criteria, or if death or move to end-of-life palliative care occurred >30 days after treatment discontinuation. This abstract reports interim data from the UK, France, and Germany. Results: This interim analysis included data from 335 pts across five sites in three countries: two sites in the UK, one in France, and two in Germany (Table). Overall, 307 (91.6%) pts started 1L therapy and 172 (51.3%) pts started 2L therapy; overall attrition rates were 28.9% (70/242; 95% CI 23.3, 35.1) after 1L therapy and 33.1% (42/127; 95% CI 25.0, 42.0) after 2L therapy. The proportion of pts starting 1L and 2L therapy and attrition rates for each country are shown in the Table. Overall reasons for attrition were death (1L, n=28 [40.0%]; 2L, n=12 [28.6%]), move to end-of-life palliative care (1L, n=14 [20.0%]; 2L, n=5 [11.9%]), toxicity (1L, n=2 [2.9%]; 2L, n=1 [2.4%]), loss to follow up (1L, n=6 [8.6%]; 2L, n=4 [9.5%]), end of study period (1L, n=1 [1.4%]; 2L, n=4 [9.5%]), and other (1L, n=19 [27.1%]; 2L, n=16 [38.1%]). Further breakdown of results by country and hormone receptor (HR) status is shown in the Table. Conclusions: These data from routine clinical practice in the UK, France, and Germany indicate that a substantial proportion of pts with HER2+ mBC who completed 1L or 2L therapy did not receive a subsequent LOT (2L or 3L, respectively) for reasons other than death or move to end-of-life palliative care. Future analyses will focus on pooled and country-level treatment rates and real-world effectiveness. XX XX Citation Format: Peter Hall, Sue Cheeseman, Paul Cottu, Markus Krebs, Christian Scholz, Mahéva Vallet, Nicolas Niklas, Catherine Hogg, Markus Lucerna, Simon M Collin, Amanda Logue, Gráinne Long. Attrition rates from first- to third-line therapy in HER2+ metastatic breast cancer in Europe [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-16-11.
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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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.002 | 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".