Personalized survivorship care: Routine breast cancer risk assessment in the gynecologic oncology clinic.

INTRODUCTION: Gynecologic and breast cancers share several risk factors. Breast cancer risk assessment tools can identify those at elevated risk and allow for enhanced breast surveillance and chemoprevention, however such tools are underutilized. We aim to evaluate the use of routine breast cancer risk assessment in a gynecologic oncology clinic. METHODS: A patient-facing web-based tool was used to collect personal and family history and run four validated breast cancer risk assessment models (Tyrer-Cuzick (TC), Gail, BRCAPRO, and Claus) in a gynecologic oncology clinic. We evaluated completion of the tools and identification of patients at elevated risk for breast cancer using the four validated models. RESULTS: A total of 99 patients were included in this analysis. The BRCAPRO model had the highest completion rate (84.8%), followed by the TC model (74.7%), Gail model (74.7%), and the Claus model (52.1%). The TC model identified 21.6% of patients completing the model as having ≥20% lifetime risk of breast cancer, compared to 6.8% by the Gail model, and 0% for both the BRCAPRO and Claus models. The Gail model identified 52.5% of patients as having ≥1.67% 5-year risk of breast cancer. Among patients identified as high-risk for breast cancer and eligible for screening, 9/9 (100%) were referred to a high-risk breast clinic. CONCLUSION: Among patients that completed the TC breast cancer risk assessment in a gynecologic oncology clinic, approximately 1 in 5 were identified to be at significantly elevated lifetime risk for breast cancer. The gynecologic oncologist's office might offer a convenient and feasible setting to incorporate this risk assessment into routine patient care, as gynecologic oncologists often have long-term patient relationships and participate in survivorship care.

Chatbot Artificial Intelligence for Genetic Cancer Risk Assessment and Counseling: A Systematic Review and Meta-Analysis.

PURPOSE: Most individuals with a hereditary cancer syndrome are unaware of their genetic status to underutilization of hereditary cancer risk assessment. Chatbots, or programs that use artificial intelligence to simulate conversation, have emerged as a promising tool in health care and, more recently, as a potential tool for genetic cancer risk assessment and counseling. Here, we evaluated the existing literature on the use of chatbots in genetic cancer risk assessment and counseling. METHODS: A systematic review was conducted using key electronic databases to identify studies which use chatbots for genetic cancer risk assessment and counseling. Eligible studies were further subjected to meta-analysis. RESULTS: Seven studies met inclusion criteria, evaluating five distinct chatbots. Three studies evaluated a chatbot that could perform genetic cancer risk assessment, one study evaluated a chatbot that offered patient counseling, and three studies included both functions. The pooled estimated completion rate for the genetic cancer risk assessment was 36.7% (95% CI, 14.8 to 65.9). Two studies included comprehensive patient characteristics, and none involved a comparison group. Chatbots varied as to the involvement of a health care provider in the process of risk assessment and counseling. CONCLUSION: Chatbots have been used to streamline genetic cancer risk assessment and counseling and hold promise for reducing barriers to genetic services. Data regarding user and nonuser characteristics are lacking, as are data regarding comparative effectiveness to usual care. Future research may consider the impact of chatbots on equitable access to genetic services.

Achieving universal genetic assessment for women with ovarian cancer: Are we there yet? A systematic review and meta-analysis.

PURPOSE: Several professional organizations recommend universal genetic assessment for people with ovarian cancer as identifying pathogenic variants can affect treatment, prognosis, and all-cause mortality for patients and relatives. We sought to evaluate the literature on genetic assessment for women with ovarian cancer and determine if any interventions or patient characteristics drive utilization of services. METHODS: We searched key electronic databases to identify trials that evaluated genetic assessment for people with ovarian cancer. Trials with the primary aim to evaluate utilization of genetic assessment with or without interventions were included. Eligible trials were subjected to meta-analysis and the moderating influence of health interventions on rates of genetic assessment were examined. RESULTS: A total of 35 studies were included (19 report on utilization of genetic services without an intervention, 7 with an intervention, and 9 with both scenarios). Without an intervention, pooled estimates for referral to genetic counseling and completion of genetic testing were 39% [CI 27-53%] and 30% [CI 19-44%]. Clinician-facilitated interventions included: mainstreaming of genetic services (99% [CI 86-100%]), telemedicine (75% [CI 43-93%]), clinic-embedded genetic counselor (76% [CI 32-95%]), reflex tumor somatic genetic assessment (64% [CI 17-94%]), universal testing (57% [28-82%]), and referral forms (26% [CI 10-53%]). Random-effects pooled proportions demonstrated that Black vs. White race was associated with a lower rate of genetic testing (26%[CI 17-38%] vs. 40% [CI 25-57%]) as was being un-insured vs. insured (23% [CI 18-28%] vs. 38% [CI 26-53%]). CONCLUSIONS: Reported rates of genetic testing for people with ovarian cancer remain well below the goal of universal testing. Interventions such as mainstreaming can improve testing uptake. Strategies aimed at improving utilization of genetic services should consider existing disparities in race and insurance status.