Literature DB >> 33544084

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

Ann Sato1, Eri Haneda1, Nobuyasu Suganuma2, Hiroto Narimatsu1,3,4.   

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. ©Ann Sato, Eri Haneda, Nobuyasu Suganuma, Hiroto Narimatsu. Originally published in JMIR Formative Research (http://formative.jmir.org), 05.02.2021.

Entities:  

Keywords:  IBM Watson; artificial intelligence; augmented intelligence; cancer; chatbot; familial cancer; feasibility; genetics; hereditary cancer; preliminary screening; screening

Year:  2021        PMID: 33544084      PMCID: PMC7895643          DOI: 10.2196/25184

Source DB:  PubMed          Journal:  JMIR Form Res        ISSN: 2561-326X


  9 in total

Review 1.  Genetic predisposition to breast cancer: past, present, and future.

Authors:  Clare Turnbull; Nazneen Rahman
Journal:  Annu Rev Genomics Hum Genet       Date:  2008       Impact factor: 8.929

2.  National Estimates of Genetic Testing in Women With a History of Breast or Ovarian Cancer.

Authors:  Christopher P Childers; Kimberly K Childers; Melinda Maggard-Gibbons; James Macinko
Journal:  J Clin Oncol       Date:  2017-08-18       Impact factor: 44.544

3.  A smartphone Chatbot application to optimize monitoring of older patients with cancer.

Authors:  Antoine Piau; Rachel Crissey; Delphine Brechemier; Laurent Balardy; Fati Nourhashemi
Journal:  Int J Med Inform       Date:  2019-05-14       Impact factor: 4.046

4.  Proceedings of the international consensus conference on breast cancer risk, genetics, & risk management, April, 2007.

Authors:  Gordon F Schwartz; Kevin S Hughes; Henry T Lynch; Carol J Fabian; Ian S Fentiman; Mark E Robson; Susan M Domchek; Lynn C Hartmann; Roland Holland; David J Winchester
Journal:  Cancer       Date:  2008-11-15       Impact factor: 6.860

5.  Frequency of Germline Mutations in 25 Cancer Susceptibility Genes in a Sequential Series of Patients With Breast Cancer.

Authors:  Nadine Tung; Nancy U Lin; John Kidd; Brian A Allen; Nanda Singh; Richard J Wenstrup; Anne-Renee Hartman; Eric P Winer; Judy E Garber
Journal:  J Clin Oncol       Date:  2016-03-14       Impact factor: 44.544

6.  When Chatbots Meet Patients: One-Year Prospective Study of Conversations Between Patients With Breast Cancer and a Chatbot.

Authors:  Benjamin Chaix; Jean-Emmanuel Bibault; Arthur Pienkowski; Guillaume Delamon; Arthur Guillemassé; Pierre Nectoux; Benoît Brouard
Journal:  JMIR Cancer       Date:  2019-05-02

7.  Risks of Breast, Ovarian, and Contralateral Breast Cancer for BRCA1 and BRCA2 Mutation Carriers.

Authors:  Karoline B Kuchenbaecker; John L Hopper; Daniel R Barnes; Kelly-Anne Phillips; Thea M Mooij; Marie-José Roos-Blom; Sarah Jervis; Flora E van Leeuwen; Roger L Milne; Nadine Andrieu; David E Goldgar; Mary Beth Terry; Matti A Rookus; Douglas F Easton; Antonis C Antoniou; Lesley McGuffog; D Gareth Evans; Daniel Barrowdale; Debra Frost; Julian Adlard; Kai-Ren Ong; Louise Izatt; Marc Tischkowitz; Ros Eeles; Rosemarie Davidson; Shirley Hodgson; Steve Ellis; Catherine Nogues; Christine Lasset; Dominique Stoppa-Lyonnet; Jean-Pierre Fricker; Laurence Faivre; Pascaline Berthet; Maartje J Hooning; Lizet E van der Kolk; Carolien M Kets; Muriel A Adank; Esther M John; Wendy K Chung; Irene L Andrulis; Melissa Southey; Mary B Daly; Saundra S Buys; Ana Osorio; Christoph Engel; Karin Kast; Rita K Schmutzler; Trinidad Caldes; Anna Jakubowska; Jacques Simard; Michael L Friedlander; Sue-Anne McLachlan; Eva Machackova; Lenka Foretova; Yen Y Tan; Christian F Singer; Edith Olah; Anne-Marie Gerdes; Brita Arver; Håkan Olsson
Journal:  JAMA       Date:  2017-06-20       Impact factor: 56.272

8.  Germline pathogenic variants of 11 breast cancer genes in 7,051 Japanese patients and 11,241 controls.

Authors:  Yukihide Momozawa; Yusuke Iwasaki; Michael T Parsons; Yoichiro Kamatani; Atsushi Takahashi; Chieko Tamura; Toyomasa Katagiri; Teruhiko Yoshida; Seigo Nakamura; Kokichi Sugano; Yoshio Miki; Makoto Hirata; Koichi Matsuda; Amanda B Spurdle; Michiaki Kubo
Journal:  Nat Commun       Date:  2018-10-04       Impact factor: 14.919

9.  Use of the Chatbot "Vivibot" to Deliver Positive Psychology Skills and Promote Well-Being Among Young People After Cancer Treatment: Randomized Controlled Feasibility Trial.

Authors:  Stephanie Greer; Danielle Ramo; Yin-Juei Chang; Michael Fu; Judith Moskowitz; Jana Haritatos
Journal:  JMIR Mhealth Uhealth       Date:  2019-10-31       Impact factor: 4.773

  9 in total
  1 in total

Review 1.  Efficacy of Clinical Guidelines in Identifying All Japanese Patients with Hereditary Breast and Ovarian Cancer.

Authors:  Eri Haneda; Ann Sato; Nobuyasu Suganuma; Yoshiko Sebata; Saki Okamoto; Soji Toda; Kaori Kohagura; Yuka Matsubara; Yuko Sugawara; Takashi Yamanaka; Toshinari Yamashita; Satoru Shimizu; Hiroto Narimatsu
Journal:  Int J Environ Res Public Health       Date:  2022-05-19       Impact factor: 4.614

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.