Dataset Information

Preliminary Screening for Hereditary Breast and Ovarian Cancer Using a Chatbot Augmented Intelligence Genetic Counselor: Development and Feasibility Study.

ABSTRACT:

Background

Breast cancer is the most common form of cancer in Japan; genetic background and hereditary breast and ovarian cancer (HBOC) are implicated. The key to HBOC diagnosis involves screening to identify high-risk individuals. However, genetic medicine is still developing; thus, many patients who may potentially benefit from genetic medicine have not yet been identified.

Objective

This study's objective is to develop a chatbot system that uses augmented intelligence for HBOC screening to determine whether patients meet the National Comprehensive Cancer Network (NCCN) BRCA1/2 testing criteria.

Methods

The system was evaluated by a doctor specializing in genetic medicine and certified genetic counselors. We prepared 3 scenarios and created a conversation with the chatbot to reflect each one. Then we evaluated chatbot feasibility, the required time, the medical accuracy of conversations and family history, and the final result.

Results

The times required for the conversation were 7 minutes for scenario 1, 15 minutes for scenario 2, and 16 minutes for scenario 3. Scenarios 1 and 2 met the BRCA1/2 testing criteria, but scenario 3 did not, and this result was consistent with the findings of 3 experts who retrospectively reviewed conversations with the chatbot according to the 3 scenarios. A family history comparison ascertained by the chatbot with the actual scenarios revealed that each result was consistent with each scenario. From a genetic medicine perspective, no errors were noted by the 3 experts.

Conclusions

This study demonstrated that chatbot systems could be applied to preliminary genetic medicine screening for HBOC.

SUBMITTER: Sato A

PROVIDER: S-EPMC7895643 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Preliminary Screening for Hereditary Breast and Ovarian Cancer Using a Chatbot Augmented Intelligence Genetic Counselor: Development and Feasibility Study.

Sato Ann A Haneda Eri E Suganuma Nobuyasu N Narimatsu Hiroto H

JMIR formative research 20210205 2

<h4>Background</h4>Breast cancer is the most common form of cancer in Japan; genetic background and hereditary breast and ovarian cancer (HBOC) are implicated. The key to HBOC diagnosis involves screening to identify high-risk individuals. However, genetic medicine is still developing; thus, many patients who may potentially benefit from genetic medicine have not yet been identified.<h4>Objective</h4>This study's objective is to develop a chatbot system that uses augmented intelligence for HBOC ...[more]

PMID: 33544084

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Project description:BackgroundGenetic testing has become an integrated part of health care for patients with breast or ovarian cancer, and the increasing demand for genetic testing is accompanied by an increasing need for easy access to reliable genetic information for patients. Therefore, we developed a chatbot app (Rosa) that is able to perform humanlike digital conversations about genetic BRCA testing.ObjectiveBefore implementing this new information service in daily clinical practice, we wanted to explore 2 aspects of chatbot use: the perceived utility and trust in chatbot technology among healthy patients at risk of hereditary cancer and how interaction with a chatbot regarding sensitive information about hereditary cancer influences patients.MethodsOverall, 175 healthy individuals at risk of hereditary breast and ovarian cancer were invited to test the chatbot, Rosa, before and after genetic counseling. To secure a varied sample, participants were recruited from all cancer genetic clinics in Norway, and the selection was based on age, gender, and risk of having a BRCA pathogenic variant. Among the 34.9% (61/175) of participants who consented for individual interview, a selected subgroup (16/61, 26%) shared their experience through in-depth interviews via video. The semistructured interviews covered the following topics: usability, perceived usefulness, trust in the information received via the chatbot, how Rosa influenced the user, and thoughts about future use of digital tools in health care. The transcripts were analyzed using the stepwise-deductive inductive approach.ResultsThe overall finding was that the chatbot was very welcomed by the participants. They appreciated the 24/7 availability wherever they were and the possibility to use it to prepare for genetic counseling and to repeat and ask questions about what had been said afterward. As Rosa was created by health care professionals, they also valued the information they received as being medically correct. Rosa was referred to as being better than Google because it provided specific and reliable answers to their questions. The findings were summed up in 3 concepts: "Anytime, anywhere"; "In addition, not instead"; and "Trustworthy and true." All participants (16/16) denied increased worry after reading about genetic testing and hereditary breast and ovarian cancer in Rosa.ConclusionsOur results indicate that a genetic information chatbot has the potential to contribute to easy access to uniform information for patients at risk of hereditary breast and ovarian cancer, regardless of geographical location. The 24/7 availability of quality-assured information, tailored to the specific situation, had a reassuring effect on our participants. It was consistent across concepts that Rosa was a tool for preparation and repetition; however, none of the participants (0/16) supported that Rosa could replace genetic counseling if hereditary cancer was confirmed. This indicates that a chatbot can be a well-suited digital companion to genetic counseling.

Project description:BackgroundBreast, colorectal, ovarian, and endometrial cancers constitute approximately 30% of newly diagnosed cancer cases in Switzerland, affecting more than 12,000 individuals annually. Hundreds of these patients are likely to carry germline pathogenic variants associated with hereditary breast ovarian cancer (HBOC) or Lynch syndrome (LS). Genetic services (counseling and testing) for hereditary susceptibility to cancer can prevent many cancer diagnoses and deaths through early identification and risk management.ObjectiveCascade screening is the systematic identification and testing of relatives of a known mutation carrier. It determines whether asymptomatic relatives also carry the known variant, needing management options to reduce future harmful outcomes. Specific aims of the CASCADE study are to (1) survey index cases with HBOC or LS from clinic-based genetic testing records and determine their current cancer status and surveillance practices, needs for coordination of medical care, psychosocial needs, patient-provider and patient-family communication, quality of life, and willingness to serve as advocates for cancer genetic services to blood relatives, (2) survey first- and second-degree relatives and first-cousins identified from pedigrees or family history records of HBOC and LS index cases and determine their current cancer and mutation status, cancer surveillance practices, needs for coordination of medical care, barriers and facilitators to using cancer genetic services, psychosocial needs, patient-provider and patient-family communication, quality of life, and willingness to participate in a study designed to increase use of cancer genetic services, and (3) explore the influence of patient-provider communication about genetic cancer risk on patient-family communication and the acceptability of a family-based communication, coping, and decision support intervention with focus group(s) of mutation carriers and relatives.MethodsCASCADE is a longitudinal study using surveys (online or paper/pencil) and focus groups, designed to elicit factors that enhance cascade genetic testing for HBOC and LS in Switzerland. Repeated observations are the optimal way for assessing these outcomes. Focus groups will examine barriers in patient-provider and patient-family communication, and the acceptability of a family-based communication, coping, and decision-support intervention. The survey will be developed in English, translated into three languages (German, French, and Italian), and back-translated into English, except for scales with validated versions in these languages.ResultsDescriptive analyses will include calculating means, standard deviations, frequencies, and percentages of variables and participant descriptors. Bivariate analyses (Pearson correlations, chi-square test for differences in proportions, and t test for differences in means) will assess associations between demographics and clinical characteristics. Regression analyses will incorporate generalized estimating equations for pairing index cases with their relatives and explore whether predictors are in direct, mediating, or moderating relationship to an outcome. Focus group data will be transcribed verbatim and analyzed for common themes.ConclusionsRobust evidence from basic science and descriptive population-based studies in Switzerland support the necessity of cascade screening for genetic predisposition to HBOC and LS. CASCADE is designed to address translation of this knowledge into public health interventions.Trial registrationClinicalTrials.gov NCT03124212; https://clinicaltrials.gov/ct2/show/NCT03124212 (Archived by WebCite at http://www.webcitation.org/6tKZnNDBt).

Project description:ImportanceGenomic screening for hereditary breast and ovarian cancer (HBOC) in unselected women offers an opportunity to prevent cancer morbidity and mortality, but the potential clinical impact and cost-effectiveness of such screening have not been well studied.ObjectiveTo estimate the lifetime incremental incidence of HBOC and the quality-adjusted life-years (QALYs), costs, and cost-effectiveness of HBOC genomic screening in an unselected population vs family history-based testing.Design, setting, and participantsIn this study conducted from October 27, 2017, to May 3, 2020, a decision analytic Markov model was developed that included health states for precancer, for risk-reducing mastectomy (RRM) and risk-reducing salpingo-oophorectomy (RRSO), for earlier- and later-stage HBOC, after cancer, and for death. A complimentary cascade testing module was also developed to estimate outcomes in first-degree relatives. Age-specific RRM and RRSO uptake probabilities were estimated from the Geisinger MyCode Community Health Initiative and published sources. Parameters including RRM and RRSO effectiveness, variant-specific cancer risk, costs, and utilities were derived from published sources. Sensitivity and scenario analyses were conducted to evaluate model assumptions and uncertainty.Main outcomes and measuresLifetime cancer incidence, QALYs, life-years, and direct medical costs for genomic screening in an unselected population vs family history-based testing only were calculated. The incremental cost-effectiveness ratio (ICER) was calculated as the difference in cost between strategies divided by the difference in QALYs between strategies. Earlier-stage and later-stage cancer cases prevented and total cancer cases prevented were also calculated.ResultsThe model found that population screening of 30-year-old women was associated with 75 (95% credible range [CR], 60-90) fewer overall cancer cases and 288 QALYs (95% CR, 212-373 QALYs) gained per 100 000 women screened, at an incremental cost of $25 million (95% CR, $21 millon to $30 million) vs family history-based testing; the ICER was $87 700 (78% probability of being cost-effective at a threshold of $100 000 per QALY). In contrast, population screening of 45-year-old women was associated with 24 (95% CR, 18-29) fewer cancer cases and 97 QALYs (95% CR, 66-130 QALYs) gained per 100 000 women screened, at an incremental cost of $26 million (95% CR, $22 million to $30 million); the ICER was $268 200 (0% probability of being cost-effective at a threshold of $100 000 per QALY). A scenario analysis without cascade testing increased the ICER to $92 600 for 30-year-old women and $354 500 for 45-year-old women. A scenario analysis assuming a 5% absolute decrease in mammography screening in women without a variant was associated with the potential for net harm (-90 QALYs per 100 000 women screened; 95% CR, -180 to 10 QALYs).Conclusions and relevanceThe results of this study suggest that population HBOC screening may be cost-effective among younger women but not among older women. Cascade testing of first-degree relatives added a modest improvement in clinical and economic value. The potential for harm conferred by inappropriate reduction in mammography among noncarriers should be quantified.

Project description:BACKGROUND:Development of psychosocial group interventions for ovarian cancer survivors has been limited. Drawing from elements of cognitive-behavioral stress management (CBSM), mindfulness-based stress reduction (MBSR), and acceptance and commitment therapy (ACT), we developed and conducted preliminary testing of an Internet-based group intervention tailored specifically to meet the needs of ovarian cancer survivors. The Internet-based platform facilitated home delivery of the psychosocial intervention to a group of cancer survivors for whom attending face-to-face programs could be difficult given their physical limitations and the small number of ovarian cancer survivors at any one treatment site. OBJECTIVE:The aim of this study was to develop, optimize, and assess the usability, acceptability, feasibility, and preliminary intended effects of an Internet-based group stress management intervention for ovarian cancer survivors delivered via a tablet or laptop. METHODS:In total, 9 ovarian cancer survivors provided feedback during usability testing. Subsequently, 19 survivors participated in 5 waves of field testing of the 10-week group intervention led by 2 psychologists. The group met weekly for 2 hours via an Internet-based videoconference platform. Structured interviews and weekly evaluations were used to elicit feedback on the website and intervention content. Before and after the intervention, measures of mood, quality of life (QOL), perceived stress, sleep, and social support were administered. Paired t tests were used to examine changes in psychosocial measures over time. RESULTS:Usability results indicated that participants (n=9) performed basic tablet functions quickly with no errors and performed website functions easily with a low frequency of errors. In the field trial (n=19), across 5 groups, the 10-week intervention was well attended. Perceived stress (P=.03) and ovarian cancer-specific QOL (P=.01) both improved significantly during the course of the intervention. Trends toward decreased distress (P=.18) and greater physical (P=.05) and functional well-being (P=.06) were also observed. Qualitative interviews revealed that the most common obstacles participants experienced were technical issues and the time commitment for practicing the techniques taught in the program. Participants reported that the intervention helped them to overcome a sense of isolation and that they appreciated the ability to participate at home. CONCLUSIONS:An Internet-based group intervention tailored specifically for ovarian cancer survivors is highly usable and acceptable with moderate levels of feasibility. Preliminary psychosocial outcomes indicate decreases in perceived stress and improvements in ovarian cancer-specific QOL following the intervention. A randomized clinical trial is needed to demonstrate the efficacy of this promising intervention for ovarian cancer survivors.

Project description:ImportanceConsumers are increasingly using artificial intelligence (AI) chatbots as a source of information. However, the quality of the cancer information generated by these chatbots has not yet been evaluated using validated instruments.ObjectiveTo characterize the quality of information and presence of misinformation about skin, lung, breast, colorectal, and prostate cancers generated by 4 AI chatbots.Design, setting, and participantsThis cross-sectional study assessed AI chatbots' text responses to the 5 most commonly searched queries related to the 5 most common cancers using validated instruments. Search data were extracted from the publicly available Google Trends platform and identical prompts were used to generate responses from 4 AI chatbots: ChatGPT version 3.5 (OpenAI), Perplexity (Perplexity.AI), Chatsonic (Writesonic), and Bing AI (Microsoft).ExposuresGoogle Trends' top 5 search queries related to skin, lung, breast, colorectal, and prostate cancer from January 1, 2021, to January 1, 2023, were input into 4 AI chatbots.Main outcomes and measuresThe primary outcomes were the quality of consumer health information based on the validated DISCERN instrument (scores from 1 [low] to 5 [high] for quality of information) and the understandability and actionability of this information based on the understandability and actionability domains of the Patient Education Materials Assessment Tool (PEMAT) (scores of 0%-100%, with higher scores indicating a higher level of understandability and actionability). Secondary outcomes included misinformation scored using a 5-item Likert scale (scores from 1 [no misinformation] to 5 [high misinformation]) and readability assessed using the Flesch-Kincaid Grade Level readability score.ResultsThe analysis included 100 responses from 4 chatbots about the 5 most common search queries for skin, lung, breast, colorectal, and prostate cancer. The quality of text responses generated by the 4 AI chatbots was good (median [range] DISCERN score, 5 [2-5]) and no misinformation was identified. Understandability was moderate (median [range] PEMAT Understandability score, 66.7% [33.3%-90.1%]), and actionability was poor (median [range] PEMAT Actionability score, 20.0% [0%-40.0%]). The responses were written at the college level based on the Flesch-Kincaid Grade Level score.Conclusions and relevanceFindings of this cross-sectional study suggest that AI chatbots generally produce accurate information for the top cancer-related search queries, but the responses are not readily actionable and are written at a college reading level. These limitations suggest that AI chatbots should be used supplementarily and not as a primary source for medical information.

Dataset Information

Preliminary Screening for Hereditary Breast and Ovarian Cancer Using a Chatbot Augmented Intelligence Genetic Counselor: Development and Feasibility Study.

Background

Objective

Methods

Results

Conclusions

Publications

Preliminary Screening for Hereditary Breast and Ovarian Cancer Using a Chatbot Augmented Intelligence Genetic Counselor: Development and Feasibility Study.

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