Carolyn Menendez

Positions:

Assistant Professor of Surgery

Surgical Oncology
School of Medicine

Member of the Duke Cancer Institute

Duke Cancer Institute
School of Medicine

Education:

B.S. 1994

University of California - Irvine

M.D. 1998

Eastern Virginia Medical School

General Surgery Internship, Surgery

Eastern Virginia Medical School

General Surgery Residency, Surgery

University of California San Francisco at Fresno, School of Medicine

Publications:

Mortality in Older Patients with Breast Cancer Undergoing Breast Surgery: How Low is "Low Risk"?

BACKGROUND: Breast surgery carries a low risk of postoperative mortality. For older patients with multiple comorbidities, even low-risk procedures can confer some increased perioperative risk. We sought to identify factors associated with postoperative mortality in breast cancer patients ≥70 years to create a nomogram for predicting risk of death within 90 days. METHODS: Patients diagnosed with nonmetastatic invasive breast cancer (2010-2016) were selected from the National Cancer Database. Unadjusted OS was estimated using the Kaplan-Meier method. Multivariate logistic regression was used to estimate the association of age and surgery with 90-day mortality and to build a predictive nomogram. RESULTS: Among surgical patients ≥70 years, unadjusted 90-day mortality increased with increasing age (70-74 = 0.4% vs. ≥85 = 1.6%), comorbidity score (0 = 0.5% vs. ≥3 = 2.7%), and disease stage (I = 0.4% vs. III = 2.7%; all p < 0.001). After adjustment, death within 90 days of surgery was associated with higher age (≥85 vs. 70-74: odds ratio [OR] 3.16, 95% confidence interval [CI] 2.74-3.65), comorbidity score (≥3 vs. 0: OR 4.79, 95% CI 3.89-5.89), and disease stage (III vs. I: OR 4.30, 95% CI 3.69-5.00). Based on these findings, seven variables (age, gender, comorbidity score, facility type, facility location, clinical stage, and surgery type) were selected to build a nomogram; estimates of risk of death within 90 days ranged from <1 to >30%. CONCLUSIONS: Breast operations remain relatively low-risk procedures for older patients with breast cancer, but select factors can be used to estimate the risk of postoperative mortality to guide surgical decision-making among older women.
MLA Citation
Dillon, Jacquelyn, et al. “Mortality in Older Patients with Breast Cancer Undergoing Breast Surgery: How Low is "Low Risk"?Ann Surg Oncol, vol. 28, no. 10, 2021, pp. 5758–67. Pubmed, doi:10.1245/s10434-021-10502-3.
URI
https://scholars.duke.edu/individual/pub1483069
PMID
34309779
Source
pubmed
Published In
Annals of Surgical Oncology
Volume
28
Published Date
Start Page
5758
End Page
5767
DOI
10.1245/s10434-021-10502-3

Hereditary Cancer Counseling and Germline Genetic Testing

Screening for inherited predisposition to cancer and germline genetic testing are part of the standard of care for breast cancer management, with implications for immediate and survivorship management. The advent of multigene next-generation sequencing panels has increased the complexity of testing while also making it less expensive. The dynamic nature of genetic knowledge and testing technology necessitates ongoing assessment for new or updated genetics evaluation throughout survivorship to maximize the reduction of cancer morbidity and mortality.
MLA Citation
Menendez, Carolyn, et al. “Hereditary Cancer Counseling and Germline Genetic Testing.” Common Issues in Breast Cancer Survivors A Practical Guide to Evaluation and Management, edited by G. G. Kimmick et al., Springer, 2021, pp. 305–18. Manual, doi:10.1007/978-3-030-75377-1_20.
URI
https://scholars.duke.edu/individual/pub1501503
Source
manual
Published Date
Start Page
305
End Page
318
DOI
10.1007/978-3-030-75377-1_20

ASO Visual Abstract: Mortality in Older Patients with Breast Cancer Undergoing Breast Surgery-How Low is "Low Risk"?

MLA Citation
Dillon, Jacquelyn, et al. “ASO Visual Abstract: Mortality in Older Patients with Breast Cancer Undergoing Breast Surgery-How Low is "Low Risk"?Ann Surg Oncol, Aug. 2021. Pubmed, doi:10.1245/s10434-021-10612-y.
URI
https://scholars.duke.edu/individual/pub1494138
PMID
34432191
Source
pubmed
Published In
Annals of Surgical Oncology
Published Date
DOI
10.1245/s10434-021-10612-y

Disparities in Genetic Testing for Heritable Solid-Tumor Malignancies

Authors
Dillon, J; Ademuyiwa, FO; Barrett, M; Moss, HA; Wignall, E; Menendez, C; Hughes, KS; Plichta, JK
MLA Citation
Dillon, J., et al. “Disparities in Genetic Testing for Heritable Solid-Tumor Malignancies.” Surgical Oncology Clinics of North America, Jan. 2021. Scopus, doi:10.1016/j.soc.2021.08.004.
URI
https://scholars.duke.edu/individual/pub1499629
Source
scopus
Published In
Surgical Oncology Clinics of North America
Published Date
DOI
10.1016/j.soc.2021.08.004

Implementation of a Molecular Tumor Registry to Support the Adoption of Precision Oncology Within an Academic Medical Center: The Duke University Experience.

Comprehensive genomic profiling to inform targeted therapy selection is a central part of oncology care. However, the volume and complexity of alterations uncovered through genomic profiling make it difficult for oncologists to choose the most appropriate therapy for their patients. Here, we present a solution to this problem, The Molecular Registry of Tumors (MRT) and our Molecular Tumor Board (MTB). PATIENTS AND METHODS: MRT is an internally developed system that aggregates and normalizes genomic profiling results from multiple sources. MRT serves as the foundation for our MTB, a team that reviews genomic results for all Duke University Health System cancer patients, provides notifications for targeted therapies, matches patients to biomarker-driven trials, and monitors the molecular landscape of tumors at our institution. RESULTS: Among 215 patients reviewed by our MTB over a 6-month period, we identified 176 alterations associated with therapeutic sensitivity, 15 resistance alterations, and 51 alterations with potential germline implications. Of reviewed patients, 17% were subsequently treated with a targeted therapy. For 12 molecular therapies approved during the course of this work, we identified between two and 71 patients who could qualify for treatment based on retrospective MRT data. An analysis of 14 biomarker-driven clinical trials found that MRT successfully identified 42% of patients who ultimately enrolled. Finally, an analysis of 4,130 comprehensive genomic profiles from 3,771 patients revealed that the frequency of clinically significant therapeutic alterations varied from approximately 20% to 70% depending on the tumor type and sequencing test used. CONCLUSION: With robust informatics tools, such as MRT, and the right MTB structure, a precision cancer medicine program can be developed, which provides great benefit to providers and patients with cancer.
Authors
Green, MF; Bell, JL; Hubbard, CB; McCall, SJ; McKinney, MS; Riedel, JE; Menendez, CS; Abbruzzese, JL; Strickler, JH; Datto, MB
MLA Citation
URI
https://scholars.duke.edu/individual/pub1497103
PMID
34568718
Source
pubmed
Published In
Jco Precision Oncology
Volume
5
Published Date
DOI
10.1200/PO.21.00030