Abstract
Purpose
Novel approaches are needed to ensure all patients with cancer have access to quality genetic education before genetic testing to enable informed treatment decisions. The purpose of this study was to test the use of an artificial intelligence (AI) intervention for the delivery of genetic education by non-genetic providers to patients with cancer undergoing active treatment.
Methods
A conversational AI-based application was developed on the HealthFAX platform to provide tailored genetic education to patients with cancer and tested at Johns Hopkins Hospital between April 2021 and Feb 2022. Patients’ responses around the adoption, use, and experience of the AI application were assessed.
Results
Out of 64 individuals who consented to the study, 51 accessed the tool. The responding participants had a mean age of 61 years (ranging from 30–90 years) with 39 individuals undergoing active treatment for breast cancer and 12 for advanced prostate cancer. All patients chose to complete the tool at home. The median time between study enrollment and AI application initiation was 1 day, and the median time to complete the application was 24 min. All participants in their survey responses felt that the tool was secure, easy to use, liked the convenience of viewing it at home, and felt it provided valuable information. Eighteen percent of participants viewed the application with a family member. Ninety-eight percent of the participants completed their genetic education prior to receiving their test results. In 16%, a pathogenic variant was identified.
Conclusions
The 51 patients who adopted the AI application were highly satisfied with its usability and convenience. Our results support the continued evaluation of this cost-effective AI application in a large-scale study.
Implications for Cancer Survivors
Tailored pre-test genetic education can be successfully delivered to patients with cancer undergoing active treatment via an AI application at their convenience.
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Data availability
The data generated and analyzed during the study are available from the corresponding author upon reasonable request.
References
Referenced with permission from the NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®) for genetic/familial high-risk assessment: colorectal V..2022. © National Comprehensive Cancer Network, Inc. 2022. All rights reserved. Accessed April 6, 2023. To view the most recent and complete version of the guideline, go online to NCCN.org.
Referenced with permission from the NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®) for genetic/familial high-risk assessment: breast, ovarian, and pancreatic V.3.2023. © National Comprehensive Cancer Network, Inc. 2023. All rights reserved. Accessed April 6, 2023. To view the most recent and complete version of the guideline, go online to NCCN.org.
Referenced with permission from the NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®) for prostate cancer early detection V.1.2023. © National Comprehensive Cancer Network, Inc. 2023. All rights reserved. Accessed January 19, 2023. To view the most recent and complete version of the guideline, go online to NCCN.org.
Riley BD, et al. Essential elements of genetic cancer risk assessment, counseling, and testing: updated recommendations of the National Society of Genetic Counselors. J Genet Couns. 2012. https://doi.org/10.1007/s10897-011-9462-x.
Penon-Portmann M, et al. Genetics workforce: distribution of genetics services and challenges to health care in California. Genet Med. 2020. https://doi.org/10.1038/s41436-019-0628-5.
Robson ME, et al. American Society of Clinical Oncology policy statement update: genetic and genomic testing for cancer susceptibility. J Clin Oncol. 2015. https://doi.org/10.1200/jco.2015.63.0996.
National Accreditation Program for Breast Centers Standards Manual. American College of Surgeons. 2018. https://www.facs.org/media/pofgxojm/napbc_standards_manual_2018.pdf. Accessed Apr 2023.
Frey MK, et al. Cascade testing for hereditary cancer syndromes: should we move toward direct relative contact? A systematic review and meta-analysis. J Clin Oncol. 2022. https://doi.org/10.1200/jco.22.00303.
Domchek SM, et al. Association of risk-reducing surgery in BRCA1 or BRCA2 mutation carriers with cancer risk and mortality. JAMA. 2010. https://doi.org/10.1001/jama.2010.1237.
Gross AL, Blot WJ, Visvanathan K. BRCA1 and BRCA2 testing in medically underserved medicare beneficiaries with breast or ovarian cancer. JAMA. 2018. https://doi.org/10.1001/jama.2018.8258.
Reid S, et al. Disparities in BRCA counseling across providers in a diverse population of young breast cancer survivors. Genet Med. 2020. https://doi.org/10.1038/s41436-020-0762-0.
Gutierrez AM, et al. Examining access to care in clinical genomic research and medicine: experiences from the CSER Consortium. J Clin Transl Sci. 2021. https://doi.org/10.1017/cts.2021.855.
Choi JJ, et al. The role of race and insurance status in access to genetic counseling and testing among high-risk breast cancer patients. Oncologist. 2022. https://doi.org/10.1093/oncolo/oyac132.
Kurian AW, et al. Gaps in incorporating germline genetic testing into treatment decision-making for early-stage breast cancer. J Clin Oncol. 2017. https://doi.org/10.1200/jco.2016.71.6480.
Villegas C, Haga SB. Access to genetic counselors in the Southern United States. J Pers Med. 2019. https://doi.org/10.3390/jpm9030033.
Reid S, et al. An overview of genetic services delivery for hereditary breast cancer. Breast Cancer Res Treat. 2022. https://doi.org/10.1007/s10549-021-06478-z.
Vadaparampil ST, et al. Pre-test genetic counseling services for hereditary breast and ovarian cancer delivered by non-genetics professionals in the state of Florida. Clin Genet. 2015. https://doi.org/10.1111/cge.12405.
Cragun D, et al. A web-based tool to automate portions of pretest genetic counseling for inherited cancer. J Natl Compr Canc Netw. 2020. https://doi.org/10.6004/jnccn.2020.7546.
Watson CH, et al. Video-assisted genetic counseling in patients with ovarian, fallopian and peritoneal carcinoma. Gynecol Oncol. 2016. https://doi.org/10.1016/j.ygyno.2016.07.094.
Schmidlen T, et al. Patient assessment of chatbots for the scalable delivery of genetic counseling. J Genet Couns. 2019. https://doi.org/10.1002/jgc4.1169.
Fitzpatrick KK, Darcy A, Vierhile M. Delivering cognitive behavior therapy to young adults with symptoms of depression and anxiety using a fully automated conversational agent (Woebot): a randomized controlled trial. JMIR Ment Health. 2017. https://doi.org/10.2196/mental.7785.
Philip P, et al. Virtual human as a new diagnostic tool, a proof of concept study in the field of major depressive disorders. Sci Rep. 2017. https://doi.org/10.1038/srep42656.
Dhinagaran DA, et al. Conversational agent for healthy lifestyle behavior change: web-based feasibility study. JMIR Form Res. 2021. https://doi.org/10.2196/27956.
Hauser-Ulrich S, et al. A smartphone-based health care chatbot to promote self-management of chronic pain (SELMA): pilot randomized controlled trial. JMIR Mhealth Uhealth. 2020. https://doi.org/10.2196/15806.
Chavez-Yenter D, et al. Patient interactions with an automated conversational agent delivering pretest genetics education: descriptive study. J Med Internet Res. 2021. https://doi.org/10.2196/29447.
Nazareth S, et al. Hereditary cancer risk using a genetic chatbot before routine care visits. Obstet Gynecol. 2021. https://doi.org/10.1097/aog.0000000000004596.
Heald B, et al. Using chatbots to screen for heritable cancer syndromes in patients undergoing routine colonoscopy. J Med Genet. 2020. https://doi.org/10.1136/jmedgenet-2020-107294.
McLellan S, Muddimer A, Peres SC. The effect of experience on system usability scale ratings. J Usability Stud. 2012;7:56–67.
Dobosh, MA. The Sage encyclopedia of communication research methods. In: Allen M, editor. SAGE Publications, Inc. 2017. p. 1702.
Funding
The clinical study was supported by funding from Maryland Cigarrette Restitution Fund and the Johns Hopkins Sidney Kimmel Comprehensive Cancer Center Support Grant (P30CA006973).
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Contributions
Development of tool: K.V., D.P., B.M., N.S., G.N., and A.K. Conception and design of clinical study: K.V., B.M., M.M., and R.T. Financial support for the clinical study: K.V. Provision of study materials or patients: K.V., M.M., B.M., C.A.K., A.J., G.K., M.C., C.J.P., R.C., M.W., L.J., J.L., D.J., M.A.C., and M.H. Collection and assembly of the data: K.V., M.M., and B.M. Data analysis and interpretation: K.V., D.P., M.M., G.K., R.T. Manuscript writing: K.V. Final approval of manuscript: all authors read and approved the final manuscript.
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This study was approved by the Institutional Review Board of Johns Hopkins University Bloomberg School of Public Health.
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Informed consent was obtained from all participants included in the study.
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Visvanathan, K., Petry, D., McCullough, M.S. et al. The ENGAGE study: evaluation of a conversational virtual agent that provides tailored pre-test genetic education to cancer patients. J Cancer Surviv (2023). https://doi.org/10.1007/s11764-023-01495-x
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DOI: https://doi.org/10.1007/s11764-023-01495-x