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Идёт набор NCT04859530

Automated Cervical Cancer Screening Using a Smartphone-based Artificial Intelligence Classifier

Без фазы С лечением Cervical Cancer HPV

Ориентир для пациента и семьи

Простыми словами

Автоматическая сводка по структурированным данным реестра. Она помогает сориентироваться, но не заменяет официальный протокол или оценку врача.

Что изучают
В протоколе указаны: AVC test.
Кому может быть актуально
Состояния в реестре: Cervical Cancer, HPV. Базовые параметры: 30 лет — 49 лет · Женщины.
Что важно проверить
Возраст, диагноз и пол — только базовые ориентиры. Предыдущее лечение, анализы и другие обязательные условия указаны ниже в критериях участия.
Где проводится
Cameroon
Следующий шаг
Сохраните исследование, покажите его лечащему врачу и уточните актуальный статус у исследовательского центра. Расходы, документы и поездка →
Официальное название

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

Обзор

Cervical cancer remains a major public health challenge in low- and middle-income countries (LMICs) due to financial and logistical issues. The World Health Organization (WHO) recommendation for cervical cancer screening in LMICs includes Human Papillomavirus (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. Therefore, an objective approach based on quantitative diagnostic algorithms is desirable to improve performance of VIA. With this objective and in a collaboration between the Gynecology and Obstetrics Department of the Geneva University Hospital (HUG) and the Swiss Institute of Technology (EPFL), our group started the development of an automated smartphone-based image classification device called AVC (for Automatic VIA Classifier). Two-minute videos of the cervix are recorded during VIA and classified using an artificial neural network (ANN) and image processing techniques to differentiate precancer and cancer from non-neoplastic cervical tissue. The result is displayed on the smartphone screen with a delimitation map of the lesions when appropriate. The key feature used for classification is the dynamic of cervical acetowhitening during the 120 second following the application of acetic acid. Precancerous and cancerous cells whiten more rapidly than non-cancerous ones and their whiteness persists stronger overtime. Our aim is to assess the diagnostic performance of the AVC and to compare it with the performance of current triage tests (VIA and cytology). Histopathological examination will serve as reference standard. Participants' and providers' acceptability will also be considered as part of the study. The study will be nested in an ongoing cervical cancer screening program called "3T-approach" (for Test, Triage and Treat) which includes HPV self-sampling for women aged 30 to 49 years, followed by VIA triage and treatment if needed. The AVC will be evaluated in this context. The study's risk category is A according to swiss ethical guidelines. This decision is based on the fact that the planned measures for sampling biological material or collecting personal data entail only minimal risks and burdens.

Вмешательства

  • Диагностический тест AVC test
    The AVC test will be performed during VIA by local midwives: 120 second videos focused on the cervix will be taken right after the application of acetic acid on the cervix. The recording smartphone will be fixed on a tripod situated 15cm away from the cervix.

Первичные конечные точки

  • Estimate accuracy of the AVC test [Срок оценки: 2 years]
Вторичные конечные точки (4)
  • Compare accuracy of the AVC test and VIA to detect cervical precancer and cancer [Срок оценки: 2 years]
  • Compare accuracy of the AVC test and cytology to detect cervical precancer and cancer [Срок оценки: 2 years]
  • Estimate feasibility of the AVC test [Срок оценки: 2 years]
  • Estimate acceptability of the AVC test [Срок оценки: 2 years]

Критерии участия

Критерии включения

  • Free and informed consent to take part in the study on a voluntary basis

Критерии исключения

  • No initiation of sexual intercourse
  • Pregnancy at the screening consultation
  • Any condition altering the cervix visualization at the screening consultation (e.g. heavy vaginal bleeding)
  • History of anogenital cancer or known anogenital cancer at the screening consultation
  • Previous hysterectomy
  • Not sufficiently healthy to participate in the study

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Да

Дизайн исследования

Распределение
Не применимо
Модель
Одна группа
Маскирование
Открытое
Основная цель
Профилактика

Центры проведения

Cameroon · 1 центр
  • Dschang District Hospital — Dschang

Публикации

  • Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018 Nov;68(6):394-424. doi: 10.3322/caac.21492. Epub 2018 Sep 12. PMID 30207593
  • Bruni L, Diaz M, Barrionuevo-Rosas L, Herrero R, Bray F, Bosch FX, de Sanjose S, Castellsague X. Global estimates of human papillomavirus vaccination coverage by region and income level: a pooled analysis. Lancet Glob Health. 2016 Jul;4(7):e453-63. doi: 10.1016/S2214-109X(16)30099-7. PMID 27340003
  • Baleydier I, Vassilakos P, Vinals R, Wisniak A, Kenfack B, Tsuala Fouogue J, Enownchong Enow Orock G, Lemoupa Makajio S, Foguem Tincho E, Undurraga M, Cattin M, Makohliso S, Schonenberger K, Gervaix A, Thiran JP, Petignat P. 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 PMID 34914727

Идентификаторы

NCT: NCT04859530 · 2017-01110b

Первоисточники (государственные реестры)

Открыть это исследование на ClinicalTrials.gov ↗