Abstract PO1-08-10: Impact of Oncologist-Led Genetic Counseling and Testing on Prophylactic Mastectomy Rates Among Multi-Ethnic Women with Operable Breast Cancer
Bibliographic record
Abstract
Abstract Introduction: Approximately 5-10% of breast cancers are attributed to an inherited pathogenic variant (PV) in breast cancer predisposition genes, such as BRCA1 and BRCA2. Identifying women with hereditary breast cancer syndromes is critical to inform risk-appropriate screening and prevention strategies. For example, contralateral prophylactic mastectomy (CPM) has been shown to reduce the risk of new breast primaries without a demonstrated survival benefit. In a prior study, we found that women with pathogenic/likely pathogenic (P/LP) variants were over four times more likely to undergo CPM compared to those with benign/likely benign (B/LB) variants. In recent years due to expanded indications for genetic testing and social distancing during the COVID-19 pandemic, oncologist-led genetic testing and telehealth genetic counseling has gradually replaced in-person genetic counseling visits. We aimed to understand how changes in the delivery of genetic counseling and testing services impacted CPM rates among multi-ethnic women with operable breast cancer in the post COVID-19 period. Methods: We conducted a retrospective cohort study among 1,080 women diagnosed with unilateral breast cancer who underwent germline genetic testing between 2013 and 2022 at Columbia University Irving Medical Center (CUIMC) in New York, NY. The pre COVID-19 period was defined as 2013-2019 and the post COVID-19 period as 2020-2022. Demographics, including age, race/ethnicity and marital status, and clinical characteristics, such as year of diagnosis, breast cancer stage, tumor hormone receptor status, family history of breast cancer, and genetic test results, were extracted from the electronic health record (EHR). We used univariable and multivariable logistic regression analyses to estimate the odds ratio (OR) and 95% confidence interval (95% CI) associated with each variable and receipt of CPM. Results: Among 1080 evaluable women, mean age at diagnosis was 51.2 years old (SD, 12.3) with 39.6% non-Hispanic White, 27.8% Hispanic, 11.4% non-Hispanic Black, 9.0% Asian, and 12.2% multi-racial/other. Within the overall study population, 12.1% of women had P/LP variants and 21.4% had variants of unknown significance (VUS) results. Non-Hispanic Whites and Blacks had the highest frequency of P/LP variants, whereas VUS results were more common among Hispanics and Asians (see Table). Twenty-three percent of women in the study population underwent CPM. In multivariable analysis, younger age at diagnosis, more advanced stage breast cancer, family history of breast cancer, Hispanic race and P/LP results on germline genetic testing were associated with increased CPM rates. Hispanic women were over 60% more likely to undergo CPM compared to non-Hispanic White women (adjusted OR=1.63, 95% CI=1.07-2.47). No significant change in CPM rates was observed in the post-COVID era compared to the pre-COVID era. Conclusion: We aimed to understand how the transition to telehealth and oncologist-led genetic testing affected CPM rates. Although we did not observe a change in CPM rates in the post-COVID era, Hispanic women had significantly more VUS results and were over 60% more likely to undergo CPM compared to non-Hispanic White women. In future studies, we hope to improve risk communication of genetic test results and the risks and benefits of CPM, particularly in vulnerable and underserved populations. Table 1 Genetic testing results and rates of contralateral prophylactic mastectomy stratified by race/ethnicity in women diagnosed with operable breast cancer and undergoing germline genetic testing from 2013-2022 at Columbia University Irving Medical Center, New York, NY Citation Format: Alissa Michel, Kelly Luo, Vicky Ro, Matthew Fine, Meghna Trivedi, Wendy Chung, Roshni Rao, Tarsha Jones, Elana Levinson, Carrie Koval-Burt, Donna Russo, Ilana Chilton, Rita Kukafka, Katherine Crew. Impact of Oncologist-Led Genetic Counseling and Testing on Prophylactic Mastectomy Rates Among Multi-Ethnic Women with Operable Breast Cancer [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 PO1-08-10.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".