None listed
Conditions
Interventions
Intervention1: Automated visual evaluation (AVE): Low-cost visual screening approachâ??automated visual evaluation (AVE) based on computer-based deep learning of cervical images collected using a mobi
HPV testing and partial typing by BD Onclarity® on vaginal sample collected by trained nurse using an Copan® FLOQ brush
Sponsors
Tata Memorial Center TMC
Eligibility
Inclusion criteria
Inclusion criteria: -Language: able to speak/understand Hindi or Punjabi. -Mental competence: apparently mentally competent. -Provision of written informed consent.
Exclusion criteria
Exclusion criteria: -Current pregnancy; -History of cervical cancer; -History of hysterectomy; -History of having undergone LEEP or cold-cone partial removal of the cervix; -Heavy menstrual bleeding (if the woman prefers not to be examined)
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| -Development and internal validation of a deep-learning based algorithm for automated visual evaluation (AVE) of cervical images captured through a mobile phone for the identification of histopathologically confirmed CIN3+/AIS for: 1) primary screening and 2) triage of HPV-positive women for colposcopy Timepoint: 12 months | — |
Secondary
| Measure | Time frame |
|---|---|
| -Sensitivity & specificity of AVE algorithm as a primary screening method and as a triage-method for HPV-positive women in the internal validation set -Prevalence & carcinogenicity of specific HPV genotypes/variants by host ancestry -Association of vaginal microbiome with cervicitis -Sensitivity & specificity of the viral methylation marker assays as a triage test for detecting precancer in vaginal specimenTimepoint: 12 months | — |
Countries
India
Contacts
Public ContactRajesh Dikshit
Center for Cancer Epidemiology (CCE), Tata Memorial Center (TMC), Mumbai
Outcome results
None listed