Prior to the coronavirus disease 2019 (COVID-19) pandemic, telehealth was rarely utilized for oncologic care in metropolitan areas. Our large New York City based outpatient breast/gynecologic cancer clinic administered an 18-question survey to patients from March to June 2020, to assess the perceptions of the utility of telehealth medicine. Of the 622 patients, 215 (35%) completed the survey, and of the 215 respondents, 74 (35%) had participated in a telehealth visit. We evaluated the use of telehealth services using the validated Service User Technology Acceptability Questionnaire. Sixty-eight patients (92%) reported that telehealth services saved them time, 54 (73%) reported telehealth increased access to care, and 58 (82%) reported telehealth improved their health. Overall, 67 (92%) of patients expressed satisfaction with the use of telehealth services for oncologic care during the COVID-19 pandemic. Telehealth services should be carefully adopted as an addition to in-person clinical care of patients with cancer.

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This study evaluated the mental health and cancer treatment-related impact of the first wave of the COVID-19 pandemic on patients with breast and gynecologic cancers. An 18-question survey was administered in June 2020 at a New York City-based cancer center to assess the quality of life (QOL) and overall health (OH) during both the pandemic time period from March 1, 2020, through June 30, 2020, and the pre-pandemic period (prior to March 1, 2020). Survey questions were answered on a 5-point Likert scale and a 7-point EORTC QLQ-C30 QOL scale. Differences in mean QOL and OH scores were evaluated using a paired t-test. QOL and OH were significantly worsened by the pandemic, with significant increases in anxiety, depression, and mood swings.

Introduction: The aim of this study was to assess for clinicopathologic and socioeconomic features that predict improved survival for patients with advanced breast cancer with synchronous brain metastases at diagnosis. Methods: We utilized the National Cancer Database (NCDB) to identify all patients with brain metastases present at diagnosis, with adequate information on receptor status (ER, PR, Her2), clinical T stage of cT1-4, clinical M1, with 3,943 patients available for analysis. The association between brain metastases patterns and patient/disease variables was examined by robust Poisson regression model. Cox proportional hazards model was used to quantify the associations between overall survival (OS) and these variables. Results: In univariable analysis, OS was significantly associated with the number of sites of metastases (p < 0.0001). Patients with 2 or more additional extracranial sites of metastases had significantly worse OS (median 8.8 months, 95% confidence interval [CI] 7.8, 9.9) than patients with brain metastases only (median OS 10.6 months, 95% CI 9.4, 12.9) or brain metastases plus one other extracranial site of metastases (median OS 13.1 months, 95% CI 11.8, 14.4). Risk factors which predicted poor prognosis included triple-negative disease, high comorbidity score, poorly differentiated tumors, invasive lobular histology, multi-organ involvement of metastases, and government or lack of insurance. Factors which improve survival include younger age and Hispanic race. Discussion/Conclusion: Using a large NCDB, we identified various factors associated with prognosis for patients with brain metastases at the time of breast cancer diagnosis. Insurance status and related socioeconomic challenges provide potential areas for improvement in care for these patients. This information may help stratify patients into prognostic categories at the time of diagnosis to improve treatment plans.

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e12511 Background: The RSClin model, which incorporates the Oncotype Recurrence Score (RS) and clinicopathologic features, was recently developed to further tailor prognosis and prediction of chemotherapy benefit for patients with early-stage hormone positive (HR+) breast cancer (BC) (Sparano et al, 2020). The RSClin calculator is available online to assist treatment planning for situations where chemotherapy benefit is uncertain. Covariates include Oncotype RS, tumor grade, tumor size and patient age. The risk calculator generates a 10-year distant recurrence risk and absolute chemotherapy benefit. This tool may be especially helpful to determine treatment management for premenopausal patients with early-stage HR+ BC with intermediate risk (IR) Oncotype RS (16-25). We retrospectively applied RSClin to this patient population to determine if it would have changed treatment recommendations. Methods: We identified premenopausal women with node-negative early-stage BC with IR RS (16-25) within our large Oncotype database. Using the RSClin model, we selected >5% absolute chemotherapy benefit as a reasonable cutoff to recommend chemotherapy. We compared the treatment recommendation based on RSClin with the treatment previously recommended by breast oncologists at our large academic medical center in New York City. Results: There were 86 patients who met criteria with a median age of 46 years. Of these, 26 patients (30%) were recommended chemotherapy plus endocrine therapy (ET) and 60 (70%) were recommended ET alone. After applying the RSClin model (data available for 83/86 patients), 19 (23%) would have resulted in a change in treatment recommendation and 64 (77%) would have remained unchanged. Overall, 8 (10%) would have withheld chemotherapy when it was previously offered and 11 (13%) would have recommended chemotherapy when it was previously excluded. There were 8 (9%) secondary invasive breast events in this population, with 2 (2%) being ipsilateral, 3 (3%) being contralateral and 3 (3%) metastatic at a median follow up of 46.9 months. Conclusions: The RSClin model would have changed management of premenopausal patients with IR RS in 23% of patients. This model, although not yet prospectively validated, may help individualize therapy for patients with less definitive treatment plans. Using RSClin, we can aim to minimize recurrence rates and avoid unnecessary chemotherapy in selected patients. This model is easy to apply and will have important clinical utility moving forward.