Alejandro Vanegas
Columbia University
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Featured researches published by Alejandro Vanegas.
Cancer Prevention Research | 2017
Meghna S. Trivedi; Austin M. Coe; Alejandro Vanegas; Rita Kukafka; Katherine D. Crew
Women with atypical hyperplasia and lobular or ductal carcinoma in situ (LCIS/DCIS) are at increased risk of developing invasive breast cancer. Chemoprevention with selective estrogen receptor modulators or aromatase inhibitors can reduce breast cancer risk; however, uptake is estimated to be less than 15% in these populations. We sought to determine which factors are associated with chemoprevention uptake in a population of women with atypical hyperplasia, LCIS, and DCIS. Women diagnosed with atypical hyperplasia/LCIS/DCIS between 2007 and 2015 without a history of invasive breast cancer were identified (N = 1,719). A subset of women (n = 73) completed questionnaires on breast cancer and chemoprevention knowledge, risk perception, and behavioral intentions. Descriptive statistics were generated and univariate and multivariable log-binomial regression were used to estimate the association between sociodemographic and clinical factors and chemoprevention uptake. In our sample, 29.3% had atypical hyperplasia, 23.3% had LCIS, and 47.4% had DCIS; 29.4% used chemoprevention. Compared with women with atypical hyperplasia, LCIS [RR, 1.43; 95% confidence interval (CI), 1.16–1.76] and DCIS (RR, 1.54; 95% CI, 1.28–1.86) were significantly associated with chemoprevention uptake, as was medical oncology referral (RR, 5.79; 95% CI, 4.80–6.98). Younger women were less likely to take chemoprevention (RR, 0.61; 95% CI, 0.42–0.87), and there was a trend toward increased uptake in Hispanic compared with non-Hispanic white women. The survey data revealed a strong interest in learning about chemoprevention, but there were misperceptions in personal breast cancer risk and side effects of chemoprevention. Improving communication about breast cancer risk and chemoprevention may allow clinicians to facilitate informed decision-making about preventative therapy. Cancer Prev Res; 10(8); 434–41. ©2017 AACR.
Cancer Epidemiology and Prevention Biomarkers | 2018
Julia E. McGuinness; William Ueng; Meghna S. Trivedi; Hae Seung Yi; Raven David; Alejandro Vanegas; Jennifer Vargas; Rossy Sandoval; Rita Kukafka; Katherine D. Crew
Background: Potential harms of screening mammography include false positive results, such as recall breast imaging or biopsies. Methods: We recruited women undergoing screening mammography at Columbia University Medical Center in New York, New York. They completed a questionnaire on breast cancer risk factors and permitted access to their medical records. Breast cancer risk status was determined using the Gail model and a family history screener. High risk was defined as a 5-year invasive breast cancer risk of ≥1.67% or eligible for BRCA genetic testing. False positive results were defined as recall breast imaging (BIRADS score of 0, 3, 4, or 5) and/or biopsies that did not yield breast cancer. Results: From November 2014 to October 2015, 2,361 women were enrolled and 2,019 were evaluable, of whom 76% were Hispanic and 10% non-Hispanic white. Fewer Hispanic women met high-risk criteria for breast cancer than non-Hispanic whites (18.0% vs. 68.1%), but Hispanics more frequently engaged in annual screening (71.9% vs. 60.8%). Higher breast density (heterogeneously/extremely dense vs. mostly fat/scattered fibroglandular densities) and more frequent screening (annual vs. biennial) were significantly associated with false positive results [odds ratio (OR), 1.64; 95% confidence interval (CI), 1.32–2.04 and OR, 2.18; 95% CI, 1.70–2.80, respectively]. Conclusions: We observed that women who screened more frequently or had higher breast density were at greater risk for false positive results. In addition, Hispanic women were screening more frequently despite having a lower risk of breast cancer compared with whites. Impact: Our results highlight the need for risk-stratified screening to potentially minimize the harms of screening mammography. Cancer Epidemiol Biomarkers Prev; 27(4); 446–53. ©2018 AACR.
BMC Health Services Research | 2018
Thomas B. Silverman; Alejandro Vanegas; Awilda Marte; Jennie Mata; Margaret Sin; Juan Carlos Rodriguez Ramirez; Wei-Yann Tsai; Katherine D. Crew; Rita Kukafka
BackgroundBRCA1 and BRCA2 mutations confer a substantial breast risk of developing breast cancer to those who carry them. For this reason, the United States Preventative Services Task Force (USPSTF) has recommended that all women be screened in the primary care setting for a family history indicative of a mutation, and women with strong family histories of breast or ovarian cancer be referred to genetic counseling. However, few high-risk women are being routinely screened and fewer are referred to genetic counseling. To address this need we have developed two decision support tools that are integrated into clinical care.MethodThis study is a cluster randomized controlled trial of high-risk patients and their health care providers. Patient-provider dyads will be randomized to receive either standard education that is supplemented with the patient-facing decision aid, RealRisks, and the provider-facing Breast Cancer Risk Navigation Toolbox (BNAV) or standard education alone. We will assess these tools’ effectiveness in promoting genetic counseling uptake and informed and shared decision making about genetic testing.DiscussionIf found to be effective, these tools can help integrate genomic risk assessment into primary care and, ultimately, help expand access to risk-appropriate breast cancer prevention options to a broader population of high-risk women.Trial registrationThis trial is retrospectively registered with ClinicalTrials.gov Identifier: NCT03470402: 20 March 2018.
Journal of Clinical Oncology | 2017
Xinyi Li; Julia E. McGuinness; Alejandro Vanegas; Hilary Colbeth; Jennifer Vargas; Rossy Sandoval; Rita Kukafka; Katherine D. Crew
e13044Background: One of the barriers to chemoprevention uptake among high-risk women is the lack of routine breast cancer risk assessment in the primary care setting. We calculated breast cancer risk using the Breast Cancer Surveillance Consortium (BCSC) model, which accounts for age, race/ethnicity, first-degree family history of breast cancer, benign breast disease, and mammographic density, using data collected from the electronic health record (EHR) compared to self-report. Methods: Among women undergoing screening mammography, we collected breast cancer risk information from the EHR and a self-administered survey. Eligibility criteria for calculating 5-year invasive breast cancer risk using the BCSC model included age 35-74, no prior history of breast cancer, mastectomy, or breast augmentation. We extracted data on demographics, structured first-degree family history, breast radiology and pathology reports from the EHR. We assessed agreement in breast cancer risk information between the EHR and self...
Cancer Research | 2016
William Ueng; Julia E. McGuinness; Katherine Infante; Meghna S. Trivedi; Hae Seung Yi; Raven David; Alejandro Vanegas; Jennifer Vargas; Rossy Sandoval; Rita Kukafka; Katherine D. Crew
Objective - High rates of screening mammography have been reported among Hispanic women in the U.S. However, a potential harm of screening is a false positive result with recall breast imaging or biopsy. Our objective was to identify factors associated with false positive results on screening mammography among a predominantly Hispanic population in New York City. Methods - We enrolled women receiving mammography at Columbia University Medical Center in New York, NY. They completed a questionnaire on breast cancer risk factors and gave consent to access their medical records for breast imaging and biopsy reports for the past 15 years. Breast cancer risk was assessed using the Gail model and eligibility for BRCA genetic testing was determined using a family history screener. High breast density was defined qualitatively as heterogeneously or extremely dense. Recall breast imaging was based upon a BIRADS score of 0, 3, 4, 5, or 6 on the screening mammogram. False positive breast biopsies were any biopsies that did not yield breast cancer. Results - From November 2014 to May 2015, 1325 women were enrolled: median age 58 years (range, 29-89); white/black/Hispanic/other (%): 10/10/76/4; 25% met high-risk criteria for breast cancer; 31% had high breast density; 71% were undergoing annual mammography; 53% had at least one recall breast imaging and 6% had at least one false positive breast biopsy. In multivariable analysis, high breast cancer risk, high breast density, and more frequent screening mammograms were associated with recall breast imaging and biopsy. Conclusions - Based upon our results, a potential strategy to reduce the false positive rates on screening mammography is to target women at high risk for breast cancer or with high breast density for screening with breast tomosynthesis, which has less false positives than digital mammography. Additionally, we may adopt less frequent breast cancer screening in average risk women to further reduce the harms of screening. Citation Format: William Ueng, Julia McGuinness, Katherine Infante, Meghna S. Trivedi, Hae Seung Yi, Raven David, Alejandro Vanegas, Jennifer Vargas, Rossy Sandoval, Rita Kukafka, Katherine D. Crew. Factors associated with false positive results on screening mammography in a population of predominantly Hispanic women. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1790.
Cancer Research | 2018
Trivedi; H Colbeth; Hae Seung Yi; Alejandro Vanegas; R Starck; Wk Chung; Ps Appelbaum; Rita Kukafka; I Schechter; Katherine D. Crew
Cancer Research | 2018
Alejandro Vanegas; Jennifer Vargas; Rita Kukafka; Katherine D. Crew
Journal of Clinical Oncology | 2017
Julia E. McGuinness; Meghna S. Trivedi; Alejandro Vanegas; Hilary Colbeth; Rossy Sandoval; Rita Kukafka; Katherine D. Crew
Journal of Clinical Oncology | 2017
Jersen Telfort; Meghna S. Trivedi; Hae Seung Yi; Hilary Colbeth; Alejandro Vanegas; Jennifer Vargas; Rossy Sandoval; Jeffrey Wood; Jill Dimond; Joseph Finkelstein; Rita Kukafka; Katherine D. Crew
Cancer Research | 2017
Am Coe; Trivedi; Alejandro Vanegas; Rita Kukafka; Katherine D. Crew