Ignite Creation Date:
2024-05-06 @ 7:32 PM
Last Modification Date:
2024-10-26 @ 3:08 PM
Study NCT ID:
NCT06042543
Status:
RECRUITING
Last Update Posted:
2024-03-08
First Post:
2023-09-06
Brief Title:
Novel One Stop Affordable Point of Care and AI Supported System of Screening Triage and Treatment Selection for Cervical Cancer in LMICs
Sponsor:
International Agency for Research on Cancer
Organization:
International Agency for Research on Cancer
Study Overview
Official Title:
A Novel One Stop Affordable Point of Care and Artificial Intelligence Supported System of Screening Triage and Treatment Selection for Cervical Cancer and Precancer in the Low-to-middle Income Countries
Status:
RECRUITING
Status Verified Date:
2024-08
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
EASTER
Brief Summary:
Artificial intelligence AI is fast gaining reputation as a highly promising solution for cervical cancer screening AI-based detection of cervical neoplasias is named automated visual exam AVE by the National Cancer Institute USA The investigators propose to develop and evaluate the performance characteristics of a novel AI system to both screen and triage women as well as help in treatment decision making AI will analyse infrared spectroscopic signals derived from urine samples of unscreened women for the presence of high-risk human papillomavirus hr-HPV Our preliminary study has shown that spectroscopy can detect hr-HPV in urine For screen-positive women the AI will interpret a set of cervical images captured with a high-quality devoted camera to detect high grade cervical precancers and cancers and to determine the type of transformation zone TZ helps in treatment decision The prototype device for image capture and the AI algorithms are already developed by us The technologies will be further improved in part 1 initial 2 years and validated in part 2 subsequent 3 years During Part 1 the investigators will analyse urine samples collected from 1100 women at multiple screening clinics in Zimbabwe for the presence of hr-HPV using spectroscopy and use the signals generated to improve the AI algorithm In this part the investigators will also assess the concordance between hr-HPV detection in urine samples using spectroscopy and cervical human papillomavirus HPV detection using a validated HPV test The cervical image recognition device and the AI algorithm will be further improved during part 1 by collecting more images from hr-HPV positive and negative women AI will also be trained to interpret the cervical images to determine the TZ type In part 2 total 2100 women will be screened in Zimbabwe with AI-supported spectroscopic analysis of urine to detect hr-HPV and a validated HPV test to evaluate and compare their sensitivity and specificity to detect histology-proved high grade cervical precancers and cancers The sensitivity and specificity of AI-supported detection of cervical neoplasias on cervical images will be evaluated to triage the HPV positive women The accuracy of AI to determine TZ type will be compared with expert opinion During the field validation part part 2 the investigators will also conduct a cost analysis and compare cost of our approach to current standard Zimbabwean practice The International Agency for Research on Cancer- World Health Organization WHO IARC-WHO has partnered with The Neo Sense Vector Company NSV Delaware USA industry The Engineering Department Lancaster University Lancaster UK and The University of Zimbabwe College of Health Sciences Harare Zimbabwe to implement this study focusing on innovation that will greatly contribute to the global elimination of cervical cancer a WHO priority
Detailed Description:
Cervical cancer is a major public health challenge killing over 300000 women annually at the most productive period of their lives and disproportionately affecting women in low- and middle-income countries LMICs Even in developed countries like the USA the disparity between low- and high-income populations is striking A cervical cancer death dramatically alters family and societal dynamics In sub-Saharan Africa SSA for every 100 women who die from cervical cancer 14 to 30 children die as an indirect consequence Indeed cervical cancer mortality is a real impediment to achieving WHOs Sustainable Development Goal of reducing premature mortality from non- communicable diseases NCD by a third before 2030 WHO have also recently adopted a resolution to eliminate cervical cancer globally Whilst HPV vaccination will undoubtedly support this ambition for the next generation of girls this vision also demands an effective screening and treatment programme Yet current LMIC screening investigation and treatment regimes especially are deeply flawed and not widely adopted
The EASTER project aims to further develop and validate two new technologies for cervical cancer screening and diagnosis i screening for human papillomavirus HPV in urine with spectroscopy and ii diagnosis with artificial intelligence-assisted technology from the Neo Sense Vector Company NSV a private company The project will recruit 3200 women and screen them for HPV
The project will be implemented in two parts Part 1 Technology improvement to achieve two key improvements
Improve the performance of spectroscopy and AI to detect high-risk human papillomavirus hr-HPV in urine samples
Improve the performance of the n-Gyn device and Artificial intelligence AI to capture the cervical images and interpret them
Part 2 In the second part of the study the investigators will test the functionality and effectiveness of the AI algorithms and devices developed through Part 1 in the same setting in Zimbabwe The developed system of AI interpretation of urine samples will be evaluated as a screening test to detect cervical intraepithelial neoplasia grade 2 or worse CIN2 lesions and compared to a validated HPV detection test The AI diagnostic accuracy of n-Gyn system to detect CIN2 lesions based on captured cervical images will be evaluated as a triage test for HPV positive women in the detection of histopathologically confirmed CIN 2 lesions
Settings procedures and analysis
The EASTER project Part 1 and Part 2 will be implemented in two screening polyclinics Epworth and Mbare in Harare where women are routinely screened with an average of 15 of women living with HIV WLHIV participants Women aged 25-49 who agree to participate and sign the corresponding Institutional Review Board IRB approved consent forms will be requested to provide two self-collected samples 1 a first void urine sample and 2 a self-collected vaginal sample Recruitment specimens will be tested for HPV with Ampfire Women HPV positive in either sample will be referred to colposcopy for disease ascertainment
The colposcopist will examine the cervical images on the n-Gyn screen and independent of AI will document the visibility and location of the squamocolumnar junction SCJ type of transformation zone TZ Swede score most appropriate site for taking biopsy if any abnormalities are present and suitability for treatment by ablation Sequential images of the transformation zone will be obtained before and after cleaning with normal saline and then after applying 5 acetic acid for one minute Appropriate magnifications will be used to enable delineation of the SCJ and to identify the worst area of suspected abnormality A final image will be captured after the application of Lugols iodine After the images have been collected the clinician will take at least one punch biopsy from the most abnormal site determined by himher If no lesion is visible biopsies will be obtained from the 6 and 12 oclock positions closest to the SCJ All histopathology slides will be examined by pathologists at Lancet Laboratories in Harare The patient will be managed based according to the local management protocol
Women will be managed according to clinical coloscopy diagnosis women without visible lesion will exit the study at this point Women with visible lesions will be treated with thermal ablation if eligible or large loop excision of the transformation zone LLETZ if needed and exit the study Women diagnosed with cancer will be referred to the regular system for appropriate management and exit the study
Data management and study supervision will be the responsibility of the International Agency for Research on Cancer IARC and the local Principal Investigators who are experienced HPV researchers
The outcome of primary interest for the statical evaluation will be histologically confirmed cervical intraepithelial neoplasia grade 2 or worse CIN2 including CIN2 lesions positive for p16 For Part I our analyses will focus on the agreement between hr-HPV detection by spectroscopic analysis of urine and by Ampfire HPV which will be tested using the Cohens kappa statistic Spectroscopy will be deemed as good as HPV testing in defining screen results if a kappa of 07 80 agreement is achieved For Part 2 standard formulations will be used to calculate the test performance characteristics sensitivityspecificity For the comparison of the performance characteristics of the screening tests if ẟ is the hypothesized relative sensitivity or specificity the equivalence of the two tests will be inferred if the true relative risk to be within the interval ẟ to 1ẟ The test of proportions will be used to assess if the performance characteristics of the triage tests are not different from the hypothesized value
The EASTER project aims to further develop and validate two new technologies for cervical cancer screening and diagnosis i screening for human papillomavirus HPV in urine with spectroscopy and ii diagnosis with artificial intelligence-assisted technology from the Neo Sense Vector Company NSV a private company The project will recruit 3200 women and screen them for HPV
The project will be implemented in two parts Part 1 Technology improvement to achieve two key improvements
Improve the performance of spectroscopy and AI to detect high-risk human papillomavirus hr-HPV in urine samples
Improve the performance of the n-Gyn device and Artificial intelligence AI to capture the cervical images and interpret them
Part 2 In the second part of the study the investigators will test the functionality and effectiveness of the AI algorithms and devices developed through Part 1 in the same setting in Zimbabwe The developed system of AI interpretation of urine samples will be evaluated as a screening test to detect cervical intraepithelial neoplasia grade 2 or worse CIN2 lesions and compared to a validated HPV detection test The AI diagnostic accuracy of n-Gyn system to detect CIN2 lesions based on captured cervical images will be evaluated as a triage test for HPV positive women in the detection of histopathologically confirmed CIN 2 lesions
Settings procedures and analysis
The EASTER project Part 1 and Part 2 will be implemented in two screening polyclinics Epworth and Mbare in Harare where women are routinely screened with an average of 15 of women living with HIV WLHIV participants Women aged 25-49 who agree to participate and sign the corresponding Institutional Review Board IRB approved consent forms will be requested to provide two self-collected samples 1 a first void urine sample and 2 a self-collected vaginal sample Recruitment specimens will be tested for HPV with Ampfire Women HPV positive in either sample will be referred to colposcopy for disease ascertainment
The colposcopist will examine the cervical images on the n-Gyn screen and independent of AI will document the visibility and location of the squamocolumnar junction SCJ type of transformation zone TZ Swede score most appropriate site for taking biopsy if any abnormalities are present and suitability for treatment by ablation Sequential images of the transformation zone will be obtained before and after cleaning with normal saline and then after applying 5 acetic acid for one minute Appropriate magnifications will be used to enable delineation of the SCJ and to identify the worst area of suspected abnormality A final image will be captured after the application of Lugols iodine After the images have been collected the clinician will take at least one punch biopsy from the most abnormal site determined by himher If no lesion is visible biopsies will be obtained from the 6 and 12 oclock positions closest to the SCJ All histopathology slides will be examined by pathologists at Lancet Laboratories in Harare The patient will be managed based according to the local management protocol
Women will be managed according to clinical coloscopy diagnosis women without visible lesion will exit the study at this point Women with visible lesions will be treated with thermal ablation if eligible or large loop excision of the transformation zone LLETZ if needed and exit the study Women diagnosed with cancer will be referred to the regular system for appropriate management and exit the study
Data management and study supervision will be the responsibility of the International Agency for Research on Cancer IARC and the local Principal Investigators who are experienced HPV researchers
The outcome of primary interest for the statical evaluation will be histologically confirmed cervical intraepithelial neoplasia grade 2 or worse CIN2 including CIN2 lesions positive for p16 For Part I our analyses will focus on the agreement between hr-HPV detection by spectroscopic analysis of urine and by Ampfire HPV which will be tested using the Cohens kappa statistic Spectroscopy will be deemed as good as HPV testing in defining screen results if a kappa of 07 80 agreement is achieved For Part 2 standard formulations will be used to calculate the test performance characteristics sensitivityspecificity For the comparison of the performance characteristics of the screening tests if ẟ is the hypothesized relative sensitivity or specificity the equivalence of the two tests will be inferred if the true relative risk to be within the interval ẟ to 1ẟ The test of proportions will be used to assess if the performance characteristics of the triage tests are not different from the hypothesized value
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None
Secondary IDs
| Secondary ID | Type | Domain | Link |
|---|---|---|---|
| R37CA275824 | NIH | None | httpsreporternihgovquickSearchR37CA275824 |