Abstract P4-06-10: Is Anthracycline Chemotherapy Essential in the Treatment of Women with Breast Cancer? – A Real World Comparison in the Neoadjuvant Setting
Bibliographic record
Abstract
Abstract Background: Breast cancer is the second most commonly diagnosed cancer in North American women. The administration of neoadjuvant chemotherapy (NAC) is the mainstay of treatment for individuals with high risk disease in an effort to reduce the extent of surgery, evaluate the role of additional adjuvant therapies (based on pathologic response to NAC), and improve disease-free and overall survival (OS). Anthracyclines have been shown to increase response rates leading to a greater likelihood of pathologic complete response compared to non-anthracycline regimens. However, for some individuals anthracyclines are omitted from the NAC regimen due to toxicities including greater immunosuppression, cardiac toxicity and risk of acute leukemia. We established a population-based cohort of individuals treated with NAC for breast cancer. We report the outcomes of women selected for treatment with non-anthracycline NAC compared to those treated with anthracyclines. Methods: This is a retrospective population-based cohort study using linked health administrative data held at the Institute for Clinical Evaluative Sciences (ICES) in Ontario, Canada. We identified adult women diagnosed with stage I-III breast cancer (ICD-10 C50^) between 2012 and 2020 who received NAC. Administration of at least 50% of the planned chemotherapy regimen was required. We excluded patients with bilateral breast cancer, previous malignancy and male sex. NAC regimens were classified as anthracycline and non-anthracycline-containing regimens. To address confounding between those receiving anthracycline and other regimens, we built a propensity score model including patient and disease characteristics. The association with OS was calculated using Cox proportional hazards models, and breast cancer-specific survival (BCSS) was calculated using cause-specific Cox proportional hazards models. Models were adjusted for the propensity score, radiation treatment as a time-varying covariate, age, socioeconomic status, breast cancer stage and receptor sub-type, as well as Charlson comorbidity index. Results: A total of 4,180 women were identified with a median follow up of 62 months (IQR 44 – 85). Of these, 279 (6.7%) were treated with non-anthracycline regimens compared to 3,901 treated with anthracycline. Patients who received non-anthracyclines were older (median 62 years vs. 50 years; p < 0.001), and less likely to have stage III disease (33.0% vs. 48.7%; p < 0.001), and harbor triple-negative breast cancer (TNBC) (14.0% vs. 24.4%; p < 0.001). They were more likely to have no recorded comorbidities (89.2% vs. 96.5%; p < 0.001), undergo mastectomy (82.1% vs. 71.9%; p < 0.001), and sentinel lymph node biopsy (44.4% vs. 32.3%; p < 0.001). After propensity score and multivariable adjustment, women selected for treatment with non-anthracycline regimens had similar OS (HR 0.85, 95% CI 0.60-1.21) and BCSS (cause-specific HR 0.76, 95% CI 0.46-1.25) compared to those treated with anthracyclines. When stratified by stage, women treated with non-anthracycline regimens did not have significantly higher incidences of breast cancer death or death from any cause (stages I, II, and III Gray’s Test p-value all > 0.1). The mean OS was 7.2 years for women who received non-anthracycline regimens (95% CI 7.0 – 7.4) compared to 7.9 years for those who received anthracycline (95% CI 7.9 – 8.0) (log-rank p = 0.100). Conclusions: Women with stage I-III breast cancer treated with non-anthracycline NAC regimens are a highly selected population. These patients were older and healthier, with earlier stage disease and more favorable subtype (i.e. non-TNBC) when compared to those treated with anthracycline NAC. Our results demonstrate that women were well selected to omit anthracyclines and did not have worse survival outcomes. Further research is needed to better understand in whom anthracycline can be safely omitted. Citation Format: Danilo Giffoni M. M. Mata, Matthew Castelo, Rinku Sutradhar, Lena Nguyen, Neil Faught, Danielle Rodin, Ezra Hahn, Omolara Fatiregun, Cindy Fong, Sabina Trebinjac, Andrea Eisen, Lawrence Paszat, Katarzyna Jerzak, Eileen Rakovitch. Is Anthracycline Chemotherapy Essential in the Treatment of Women with Breast Cancer? – A Real World Comparison in the Neoadjuvant Setting [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P4-06-10.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".