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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

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...

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Autores principales: Baleydier, Inès, Vassilakos, Pierre, Viñals, Roser, Wisniak, Ania, Kenfack, Bruno, Tsuala Fouogue, Jovanny, Enownchong Enow Orock, George, Lemoupa Makajio, Sophie, Foguem Tincho, Evelyn, Undurraga, Manuela, Cattin, Magali, Makohliso, Solomzi, Schönenberger, Klaus, Gervaix, Alain, Thiran, Jean-Philippe, Petignat, Patrick
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8675688/
https://www.ncbi.nlm.nih.gov/pubmed/34914727
http://dx.doi.org/10.1371/journal.pone.0260776
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author Baleydier, Inès
Vassilakos, Pierre
Viñals, Roser
Wisniak, Ania
Kenfack, Bruno
Tsuala Fouogue, Jovanny
Enownchong Enow Orock, George
Lemoupa Makajio, Sophie
Foguem Tincho, Evelyn
Undurraga, Manuela
Cattin, Magali
Makohliso, Solomzi
Schönenberger, Klaus
Gervaix, Alain
Thiran, Jean-Philippe
Petignat, Patrick
author_facet Baleydier, Inès
Vassilakos, Pierre
Viñals, Roser
Wisniak, Ania
Kenfack, Bruno
Tsuala Fouogue, Jovanny
Enownchong Enow Orock, George
Lemoupa Makajio, Sophie
Foguem Tincho, Evelyn
Undurraga, Manuela
Cattin, Magali
Makohliso, Solomzi
Schönenberger, Klaus
Gervaix, Alain
Thiran, Jean-Philippe
Petignat, Patrick
author_sort Baleydier, Inès
collection PubMed
description 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 NCT04859530). EXPECTED RESULTS: The study will determine whether AVC test can be an effective method for cervical cancer screening in LMICs.
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spelling pubmed-86756882021-12-17 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 Baleydier, Inès Vassilakos, Pierre Viñals, Roser Wisniak, Ania Kenfack, Bruno Tsuala Fouogue, Jovanny Enownchong Enow Orock, George Lemoupa Makajio, Sophie Foguem Tincho, Evelyn Undurraga, Manuela Cattin, Magali Makohliso, Solomzi Schönenberger, Klaus Gervaix, Alain Thiran, Jean-Philippe Petignat, Patrick PLoS One Study Protocol 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 NCT04859530). EXPECTED RESULTS: The study will determine whether AVC test can be an effective method for cervical cancer screening in LMICs. Public Library of Science 2021-12-16 /pmc/articles/PMC8675688/ /pubmed/34914727 http://dx.doi.org/10.1371/journal.pone.0260776 Text en © 2021 Baleydier et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Study Protocol
Baleydier, Inès
Vassilakos, Pierre
Viñals, Roser
Wisniak, Ania
Kenfack, Bruno
Tsuala Fouogue, Jovanny
Enownchong Enow Orock, George
Lemoupa Makajio, Sophie
Foguem Tincho, Evelyn
Undurraga, Manuela
Cattin, Magali
Makohliso, Solomzi
Schönenberger, Klaus
Gervaix, Alain
Thiran, Jean-Philippe
Petignat, Patrick
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
title 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_short 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
title_sort 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
topic Study Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8675688/
https://www.ncbi.nlm.nih.gov/pubmed/34914727
http://dx.doi.org/10.1371/journal.pone.0260776
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