Study protocol for a two-site clinical trial to validate a smartphone-based artificial intelligence classifier identifying cervical precancer and cancer in HPV-positive women in Cameroon

Article Article scientifique Article Study protocol for a two-site clinical trial to validate a smartphone-based artificial intelligence classifier identifying cervical precancer and cancer in HPV-positive women in Cameroon eng 2021-12-16 2021 author Baleydier Inès Orphée Aster 0000-0001-6340-6815 University of Geneva, Faculty of Medicine, Geneva, Switzerland. 839144 author Vassilakos Pierre Department of Pediatrics, Gynecology and Obstetrics, University Hospitals of Geneva, Geneva, Switzerland. 25351 author Viñals Roser Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. author Wisniak Ania Department of Pediatrics, Gynecology and Obstetrics, University Hospitals of Geneva, Geneva, Switzerland. 717179 ania Wisniak author Kenfack Bruno Department of Obstetrics Gynecology and Maternal Health, Dschang District Hospital, University of Dschang, Dschang, Cameroon. author Tsuala Fouogue Jovanny 0000-0003-0055-0902 Department of Obstetrics Gynecology and Maternal Health, Dschang District Hospital, University of Dschang, Dschang, Cameroon.,Regional Hospital of Bafoussam, Bafoussam, Cameroon. author Enownchong Enow Orock George Regional Hospital of Bafoussam, Bafoussam, Cameroon. author Lemoupa Makajio Sophie Hilda 0009-0000-1705-752X Department of Pediatrics, Gynecology and Obstetrics, University Hospitals of Geneva, Geneva, Switzerland.,Department of Obstetrics Gynecology and Maternal Health, Dschang District Hospital, University of Dschang, Dschang, Cameroon. 945528 Sophie Hilda Lemoupa Makajio author Foguem Tincho Evelyn Department of Obstetrics Gynecology and Maternal Health, Dschang District Hospital, University of Dschang, Dschang, Cameroon. author Undurraga Manuela Department of Pediatrics, Gynecology and Obstetrics, University Hospitals of Geneva, Geneva, Switzerland. 758054 Département de Pédiatrie, Gynécologie et Obstétrique (PETRI) Manuela Stefania Undurraga Malinverno author Cattin Magali Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.,EssentialTech Centre, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. author Makohliso Solomzi Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. author Schönenberger Klaus Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. author Gervaix Alain Department of Pediatrics, Gynecology and Obstetrics, University Hospitals of Geneva, Geneva, Switzerland. 31715 Département de Pédiatrie, Gynécologie et Obstétrique (PETRI) author Thiran Jean-Philippe Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. author Petignat Patrick Department of Pediatrics, Gynecology and Obstetrics, University Hospitals of Geneva, Geneva, Switzerland. 586685 Département de Pédiatrie, Gynécologie et Obstétrique (PETRI) e0260776 10.1371/journal.pone.0260776 34914727 1932-6203 PMC8675688 https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0260776 Introduction: Cervical cancer remains a major public health challenge in low- and middle-income countries (LMICs) due to financial and logistical issues. WHO recommendation for cervical cancer screening in LMICs includes HPV testing as primary screening followed by visual inspection with acetic acid (VIA) and treatment. However, VIA is a subjective procedure dependent on the healthcare provider's experience. Its accuracy can be improved by computer-aided detection techniques. Our aim is to assess the performance of a smartphone-based Automated VIA Classifier (AVC) relying on Artificial Intelligence to discriminate precancerous and cancerous lesions from normal cervical tissue. Methods: The AVC study will be nested in an ongoing cervical cancer screening program called "3T-study" (for Test, Triage and Treat), including HPV self-sampling followed by VIA triage and treatment if needed. After application of acetic acid on the cervix, precancerous and cancerous cells whiten more rapidly than non-cancerous ones and their whiteness persists stronger overtime. The AVC relies on this key feature to determine whether the cervix is suspect for precancer or cancer. In order to train and validate the AVC, 6000 women aged 30 to 49 years meeting the inclusion criteria will be recruited on a voluntary basis, with an estimated 100 CIN2+, calculated using a confidence level of 95% and an estimated sensitivity of 90% +/-7% precision on either side. Diagnostic test performance of AVC test and two current standard tests (VIA and cytology) used routinely for triage will be evaluated and compared. Histopathological examination will serve as reference standard. Participants' and providers' acceptability of the technology will also be assessed. The study protocol was registered under ClinicalTrials.gov (number <a href="http://clinicaltrials.gov/show/NCT04859530" rel="noopener noreferrer" target="_blank">NCT04859530</a>). Expected results: The study will determine whether AVC test can be an effective method for cervical cancer screening in LMICs. Acetic Acid / chemistry Adult Artificial Intelligence Cameroon / epidemiology Cervical Intraepithelial Neoplasia / diagnosis Cervical Intraepithelial Neoplasia / epidemiology Cervical Intraepithelial Neoplasia / virology Clinical Trials as Topic Early Detection of Cancer / methods Female Humans Middle Aged Papillomaviridae / genetics Papillomaviridae / isolation & purification Papillomavirus Infections / complications Papillomavirus Infections / virology Prognosis Prospective Studies Smartphone / statistics & numerical data Uterine Cervical Neoplasms / diagnosis Uterine Cervical Neoplasms / epidemiology Uterine Cervical Neoplasms / virology Dewey 618 58 Département de pédiatrie, gynécologie et obstétrique 223 false 590 Prévention du cancer du col utérin 933 PloS one 16 12 b5ca5306-9a30-42e2-93f4-912fdbc503d1 Article (Published version) Public Article-scientifique-from-unpaywall.pdf 1703282 application/pdf CC BY-4.0 e84236350d89ddc7a799b8751e61b224d310a87eb31bc41c2e8d558b4d2b4075 ed0ee95a-7778-47f5-9c83-111b49405193 Appendix Public journal.pone.0260776.s001.pdf 134938 application/pdf SPIRIT 2013 checklist 403d69e139b145e70d4d7a056c7d77a25972d398f2647f743fb2b375ac70a81d c49d6411-b40f-4655-b125-52b555b54898 Appendix Public journal.pone.0260776.s002(2).tif 229848 image/tiff SPIRIT schedule d732df74879c74af67530f9b50145bf1c5bd1426aa6c32552b21edb2ec4210e8 f383476c-0c9b-4311-9cf2-437ebe8778d9 Appendix Public journal.pone.0260776.s003.pdf 789534 application/pdf Clinical study protocol NCT03757299 6e5eee9ae7cbb8cfcf786ce90a9376396b80a6295048db74fe9b17292b39c6a2 openAccess Faculté de médecine / Section de médecine clinique / Département de pédiatrie, gynécologie et obstétrique

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Study protocol for a two-site clinical trial to validate a smartphone-based artificial intelligence classifier identifying cervical precancer and cancer in HPV-positive women in Cameroon	PloS one			2021	196	180

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Baleydier, Inès Orphée Aster