Publications by authors named "Julia E McGuinness"

Purpose: Medication nonadherence is common among patients with breast cancer (BC) and increases BC mortality and complications from comorbidities. There is growing interest in mobile health interventions such as smartphone applications (apps) to promote adherence.

Methods: Use of Medisafe, a medication reminder and tracking app, was tested over 12 weeks among patients on BC treatment and at least one oral medication.

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Deep learning-based mammographic evaluations could noninvasively assess response to breast cancer chemoprevention. We evaluated change in a convolutional neural network-based breast cancer risk model applied to mammograms among women enrolled in SWOG S0812, which randomly assigned 208 premenopausal high-risk women to receive oral vitamin D3 20 000 IU weekly or placebo for 12 months. We applied the convolutional neural network model to mammograms collected at baseline (n = 109), 12 months (n = 97), and 24 months (n = 67) and compared changes in convolutional neural network-based risk score between treatment groups.

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Unlabelled: Breast cancer chemoprevention with selective estrogen receptor modulators (SERM) or aromatase inhibitors (AI) remains underutilized among high-risk women. A potential barrier to chemoprevention is competing comorbidities such as atherosclerotic cardiovascular disease (ASCVD), due to concern for additional medication side effects. We conducted a retrospective cohort study among women with atypical hyperplasia (AH) or lobular carcinoma in situ (LCIS), an important target population for chemoprevention.

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Cyclin-dependent kinase 4 and 6 inhibitors (CDK4/6i) are key therapeutic agents in the management of metastatic hormone-receptor-positive breast cancer. However, the emergence of drug resistance limits their long-term efficacy. Here, we show that breast cancer cells develop CDK4/6i resistance via a sequential two-step process of E2F activation.

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A cross-sectional survey was conducted among high-risk, racially/ethnically diverse adults at the point in time when New York City (NYC) became the COVID-19 pandemic's global epicenter. The study objective was to assess the threat and coping appraisals (cognitive factors known to correspond with people's willingness to adopt behaviorally focused interventions) and levels of distress, anxiety, and intolerance for uncertainty (emotional factors). Survey respondents were recruited in April 2020 using an online survey with unpaid recruitment on the GetHealthyHeights.

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Article Synopsis
  • Deep learning techniques, particularly convolutional neural networks (CNNs), may enhance breast cancer risk prediction when combined with clinical factors from the Breast Cancer Surveillance Consortium (BCSC) model.
  • A study of 23,467 women aged 35-74 analyzed mammograms and clinical data to assess whether adding CNN evaluations improved risk predictions over traditional methods.
  • Although the hybrid model didn't show a significant overall improvement, it performed better in predicting breast cancer risk for non-Hispanic Blacks and Hispanics, suggesting its potential benefits for diverse populations with further validation.
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Introduction: In 2009, the U.S. Preventive Services Task Force updated recommended mammography screening frequency from annual to biennial for average-risk women aged 50-74 years.

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Background: Chemoprevention with anti-estrogens, such as tamoxifen, raloxifene or aromatase inhibitors, have been shown to reduce breast cancer risk in randomized controlled trials; however, uptake among women at high-risk for developing breast cancer remains low. The aim of this study is to identify provider-related barriers to shared decision-making (SDM) for chemoprevention in the primary care setting.

Methods: Primary care providers (PCPs) and high-risk women eligible for chemoprevention were enrolled in a pilot study and a randomized clinical trial of web-based decision support tools to increase chemoprevention uptake.

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Importance: To promote the identification of women carrying BRCA1/2 variants, the US Preventive Services Task Force recommends that primary care clinicians screen asymptomatic women for an increased risk of carrying a BRCA1/2 variant risk.

Objective: To examine the effects of patient and clinician decision support about BRCA1/2 genetic testing compared with standard education alone.

Design, Setting, And Participants: This clustered randomized clinical trial was conducted at an academic medical center including 67 clinicians (unit of randomization) and 187 patients.

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Unlabelled: Significant underutilization of breast cancer chemoprevention remains, despite guidelines stating that physicians should recommend chemoprevention with antiestrogen therapy to high-risk women. We randomized women, ages 35 to 75 years, who met high-risk criteria for breast cancer, without a personal history of breast cancer or prior chemoprevention use, to standard educational materials alone or combined with a web-based decision aid. All healthcare providers, including primary care providers and breast specialists, were given access to a web-based decision support tool.

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Article Synopsis
  • A fully automated convolutional neural network (CNN) was developed to predict breast cancer relapse in women with operable hormone receptor-positive breast cancer using mammogram data.
  • The study analyzed data from 848 women treated at Columbia University Medical Center, finding a significant difference in CNN risk scores between patients who relapsed and those who remained in remission.
  • The results suggest that a short-term increase in CNN score is linked to a higher risk of relapse, indicating the model could be useful in future studies for breast cancer management.
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Unlabelled: We evaluated strategies to identify and recruit a racially/ethnically diverse cohort of women at high-risk for breast cancer to a randomized controlled trial (RCT). We enrolled 300 high-risk women and 50 healthcare providers to a RCT of standard educational materials alone or in combination with web-based decision support tools. We implemented five strategies to identify high-risk women: (i) recruitment among patients previously enrolled in a study evaluating breast cancer risk; (ii) automated breast cancer risk calculation using information extracted from the electronic health record (EHR); (iii) identification of women with atypical hyperplasia or lobular carcinoma in situ (LCIS) using International Classification of Diseases (ICD)-9/10 diagnostic codes; (iv) clinical encounters with enrolled healthcare providers; (v) recruitment flyers/online resources.

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In March 2020, days after New York shut down to mitigate the spread of COVID-19, we developed a cross-sectional, participant-administered electronic survey to explore how New Yorkers were impacted by and were responding to the ongoing crisis. A critical component of the survey was to assess how credible and trustworthy respondents found various information sources. To advertise and distribute the survey, we embedded an invitation to participate using a popup on the GetHealthyHeights.

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Women at high risk for breast cancer may benefit from enhanced screening and risk-reduction strategies. However, limited time during clinical encounters is one barrier to routine breast cancer risk assessment. We evaluated if electronic health record (EHR) data downloaded using Fast Healthcare Interoperability Resources (FHIR) is sufficient for breast cancer risk calculation in our decision support tools, RealRisks and BNAV.

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Introduction: Diagnosis of LM is limited by low sensitivity of cerebrospinal fluid (CSF) cytopathology. Detecting tumor cells in CSF (CSF-TCs) might be more sensitive. We evaluated if CNSide (CNSide), a novel assay for tumor cell detection in CSF, can detect CSF-TCs better than conventional CSF cytology.

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Purpose: Increasing usage of multigene panel testing has identified more patients with pathogenic or likely pathogenic (P or LP) variants in low-moderate penetrance genes or variants of uncertain significance (VUS). Our study evaluates the association between genetic test results and contralateral prophylactic mastectomy (CPM) among patients with breast cancer.

Methods: We conducted a retrospective cohort study among women diagnosed with unilateral stage 0-III breast cancer between 2013 and 2020 who underwent genetic testing.

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Purpose: Diffuse optical tomography breast imaging system (DOTBIS) non-invasively measures tissue concentration of hemoglobin, which is a potential biomarker of short-term response to neoadjuvant chemotherapy. We evaluated whether DOTBIS-derived measurements are modifiable with targeted therapies, including AKT inhibition and endocrine therapy.

Methods: We conducted a proof of principle study in seven postmenopausal women with stage I-III breast cancer who were enrolled in pre-surgical studies of the AKT inhibitor MK-2206 (n = 4) or the aromatase inhibitors exemestane (n = 2) and letrozole (n = 1).

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While checkpoint inhibitors have been approved in patients with newly metastatic PDL1-positive triple negative breast cancer, similar clinical benefit with immunotherapy alone or in combination with chemotherapy has not been observed in patients with hormone receptor-positive, HER2- negative breast cancer in the metastatic setting. However, in the ISPY2 trial, an increase in pathologic response has been observed with the addition of immunotherapy (± PARP inhibition) to chemotherapy compared to chemotherapy alone in patients with high-risk hormone receptor-positive, HER2- breast cancer. We review strategies to enhance the immunotherapeutic activity in this subtype of breast cancer, including combinations of checkpoint inhibition with chemotherapy, endocrine therapy, PARP inhibitors, HDAC inhibitors, CDK4/6 inhibitors, and radiotherapy.

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Introduction: Metastatic triple-negative breast cancers (mTNBC) are characterized by aggressive behavior and worse clinical outcomes than other breast cancer subtypes, as well as poor response to cytotoxic chemotherapies. The use of antibody-drug conjugates (ADCs) has been investigated as a potential treatment strategy, particularly in heavily pretreated disease.

Areas Covered: This article reviews the preclinical and clinical data supporting the use of the ADCs sacituzumab govitecan (SG), ladiratuzumab vedotin (LV), and trastuzumab deruxtecan (T-DXd) in mTNBC, and highlights ongoing clinical trials and future clinical applications.

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Genetic counseling is under-utilized in women who meet family history criteria for BRCA1 and BRCA2 (BRCA1/2) testing, particularly among racial/ethnic minorities. We evaluated the uptake of BRCA1/2 genetic testing among women presenting for screening mammography in a predominantly Hispanic, low-income population of Washington Heights in New York City. We administered the Six-Point Scale (SPS) to women presenting for screening mammography at Columbia University Irving Medical Center (CUIMC) in the Washington Heights neighborhood of New York, NY.

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Purpose: A barrier 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, accounting for age, race/ethnicity, first-degree family history of breast cancer, benign breast disease, and mammographic density, using data collected from the electronic health records (EHRs) and self-reports.

Patients And Methods: Among women undergoing screening mammography, we enrolled those age 35 to 74 years without a prior history of breast cancer.

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Genetic testing is a method to assess hereditary cancer risk. However, it is under-utilized and various methods of family history intake have been evaluated in previous studies. The six-point-scale (SPS) is a validated family history screener that is used to determine eligibility for BRCA genetic counseling.

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Screening mammography is recommended by U.S. medical organizations for breast cancer screening in average risk women because of its demonstrated reductions in breast cancer mortality.

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