Abstract PD14-08: Effectiveness of aromatase inhibitors versus tamoxifen in lobular compared to ductal carcinoma: Individual patient data meta-analysis of 9328 women with central histopathology, and 7654 women with e-Cadherin status
Bibliographic record
Abstract
Abstract Background: In post-menopausal women with hormone receptor (HR) positive early breast cancer, aromatase inhibitors (AIs) are more effective than tamoxifen as endocrine therapy. However, some trial reports indicate greater benefit from AIs in lobular than ductal cancers. Invasive lobular cancer can be identified using conventional microscopy and/or immunohistochemistry for e-Cadherin status. We performed an individual patient data meta-analysis to explore possible differential treatment benefits for AI vs tamoxifen in women with lobular vs ductal hormone receptor positive breast cancer. Methods: Individual patient data were collected from three randomised controlled trials (BIG 01-98, TEAM and ATAC) of AI vs tamoxifen for postmenopausal women with estrogen receptor positive breast cancer, as well as results of central pathology review and e-Cadherin expression. Central pathology and e-Cadherin data were available on 9328 and 7654 women. Local pathology data was available for TEAM, BIG 01-98. Data were analysed using the same methodology as the previous EBCTCG meta-analysis of AI vs tamoxifen: results of different methods of diagnosing ductal vs lobular cancer were cross tabulated, and outcomes analysed using log-rank methods, yielding event rate ratios (RR) and confidence intervals. Interactions were evaluated using standard tests for heterogeneity; the primary outcomes were time to any invasive breast cancer recurrence, and time to distant recurrence. Results: Rates of lobular cancer were higher when assessed by central pathology (BIG 01-98 16%; ATAC 16%; TEAM 12%) than e-Cadherin (15% vs 14% vs 9%). Methods agreed in over 80% of cases classified as ductal using either pathology or e-Cadherin, while the agreement rate for lobular cancers was only about 50%. A similar pattern was seen comparing local pathology with either central pathology or e-Cadherin. Consequently, analyses were stratified by pathology and e-Cadherin both separately and together. Consistent with the previous meta-analysis there was a significant reduction in recurrence for AI compared to tamoxifen (RR 0.73 (0.61-0.87) p=0.0004). Exploration of interaction found no evidence of heterogeneity of treatment effect on recurrence by pathology (ductal HR 0.76 (0.64-0.89); lobular HR 0.76 (0.50-1.15) interaction p>0.99; nor by e-Cadherin status (interaction p=0.9). No significant interactions were seen on other endpoints. Conclusion: Analyses of three large trials of adjuvant AI vs tamoxifen found discordance in identifying patients with lobular carcinoma by local or central pathology or e-Cadherin status, indicating variability in the consistency of diagnosis. The trials included showed a benefit for AI over tamoxifen in line with the previous meta-analysis, but with no evidence of differential efficacy in lobular compared to ductal carcinomas, however measured. These data cannot rule out smaller quantitative interactions or differences in site of recurrence: however, in contrast to earlier reports, this meta-analysis of the totality of the data does not identify ductal/lobular cancer as a predictive marker for differential endocrine treatment benefit. Citation Format: Robert K Hills, Steffi Oesterreich, Otto Metzger, David Dabbs, Hongchao Pan, Jeremy Braybrooke, Richard Gray, Richard Peto, Rosie Bradley, Ewan Straiton, Richard Berry, Daniel Rea, David Cameron, Jack Cuzick, Meredith Regan, Mitch Dowsett, Ivana Sestak, Jonas Bergh, Sandra M Swain, John Bartlett, Early Breast Cancer Trialists' Collaborative Group. Effectiveness of aromatase inhibitors versus tamoxifen in lobular compared to ductal carcinoma: Individual patient data meta-analysis of 9328 women with central histopathology, and 7654 women with e-Cadherin status [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD14-08.
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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 | 0.023 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.054 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".