Validation of a Lab-free Low-cost Screening Test for Prevention of Cervical Cancer

Uterine Cervical Neoplasms

Uterine Cervical Neoplasms — a type of gynecological cancer.

Design of the HPV-automated visual evaluation (PAVE) study: Validating a novel cervical screening strategy

Background: The HPV-automated visual evaluation (PAVE) Study is an extensive, multinational initiative designed to advance cervical cancer prevention in resource-constrained regions. Cervical cancer disproportionally affects regions with limited access to preventive measures. PAVE aims to assess a novel screening-triage-treatment strategy integrating self-sampled HPV testing, deep-learning-based automated visual evaluation (AVE), and targeted therapies. Methods: Phase 1 efficacy involves screening up to 100,000 women aged 25–49 across nine countries, using self-collected vaginal samples for hierarchical HPV evaluation: HPV16, else HPV18/45, else HPV31/33/35/52/58, else HPV39/51/56/59/68 else negative. HPV-positive individuals undergo further evaluation, including pelvic exams, cervical imaging, and biopsies. AVE algorithms analyze images, assigning risk scores for precancer, validated against histologic high-grade precancer. Phase 1, however, does not integrate AVE results into patient management, contrasting them with local standard care. Phase 2 effectiveness focuses on deploying AVE software and HPV genotype data in real-time clinical decision-making, evaluating feasibility, acceptability, cost-effectiveness, and health communication of the PAVE strategy in practice. Results: Currently, sites have commenced fieldwork, and conclusive results are pending. Conclusions: The study aspires to validate a screen-triage-treat protocol utilizing innovative biomarkers to deliver an accurate, feasible, and cost-effective strategy for cervical cancer prevention in resource-limited areas. Should the study validate PAVE, its broader implementation could be recommended, potentially expanding cervical cancer prevention worldwide. Funding: The consortial sites are responsible for their own study costs. Research equipment and supplies, and the NCI-affiliated staff are funded by the National Cancer Institute Intramural Research Program including supplemental funding from the Cancer Cures Moonshot Initiative. No commercial support was obtained. Brian Befano was supported by NCI/ NIH under Grant T32CA09168.

Human papillomavirus vaccination in low- and middle-income countries: progression, barriers, and future prospective

Human papillomavirus (HPV) is a viral infection that, if does not go away, can cause health problems like genital warts and cancer. The national immunization schedules for individuals before sexual debut, significantly decreased HPV-associated mortality and it will be affordable. However, immunization programs remain vulnerable to macroeconomic factors such as inflation, fiscal policy, employment levels, and national income. This review aims to investigate the association between national income in lower-middle-income countries to explore recent advances and potential issues, as well as how to deal with challenges.

The development of “automated visual evaluation” for cervical cancer screening: The promise and challenges in adapting deep‐learning for clinical testing

AbstractThere is limited access to effective cervical cancer screening programs in many resource‐limited settings, resulting in continued high cervical cancer burden. Human papillomavirus (HPV) testing is increasingly recognized to be the preferable primary screening approach if affordable due to superior long‐term reassurance when negative and adaptability to self‐sampling. Visual inspection with acetic acid (VIA) is an inexpensive but subjective and inaccurate method widely used in resource‐limited settings, either for primary screening or for triage of HPV‐positive individuals. A deep learning (DL)‐based automated visual evaluation (AVE) of cervical images has been developed to help improve the accuracy and reproducibility of VIA as assistive technology. However, like any new clinical technology, rigorous evaluation and proof of clinical effectiveness are required before AVE is implemented widely. In the current article, we outline essential clinical and technical considerations involved in building a validated DL‐based AVE tool for broad use as a clinical test.

A demonstration of automated visual evaluation of cervical images taken with a smartphone camera

AbstractWe examined whether automated visual evaluation (AVE), a deep learning computer application for cervical cancer screening, can be used on cervix images taken by a contemporary smartphone camera. A large number of cervix images acquired by the commercial MobileODT EVA system were filtered for acceptable visual quality and then 7587 filtered images from 3221 women were annotated by a group of gynecologic oncologists (so the gold standard is an expert impression, not histopathology). We tested and analyzed on multiple random splits of the images using two deep learning, object detection networks. For all the receiver operating characteristics curves, the area under the curve values for the discrimination of the most likely precancer cases from least likely cases (most likely controls) were above 0.90. These results showed that AVE can classify cervix images with confidence scores that are strongly associated with expert evaluations of severity for the same images. The results on a small subset of images that have histopathologic diagnoses further supported the capability of AVE for predicting cervical precancer. We examined the associations of AVE severity score with gynecologic oncologist impression at all regions where we had a sufficient number of cases and controls, and the influence of a woman's age. The method was found generally resilient to regional variation in the appearance of the cervix. This work suggests that using AVE on smartphones could be a useful adjunct to health‐worker visual assessment with acetic acid, a cervical cancer screening method commonly used in low‐ and middle‐resource settings.

Modelling cervical cancer elimination using single‐visit screening and treatment strategies in the context of high HIV prevalence: estimates for KwaZulu‐Natal, South Africa

AbstractIntroductionIn settings with high HIV prevalence, cervical cancer incidence rates are up to six‐fold higher than the global average of 13.1 cases per 100,000 women‐years. To inform strategies for global cervical cancer elimination, we used a dynamic transmission model to evaluate scalable screening and treatment strategies, accounting for HIV‐associated cancer risks and weighing prevention gains against overtreatment.MethodsWe developed a dynamic model of HIV‐HPV co‐infection and disease progression, which we calibrated to KwaZulu‐Natal, South Africa. Our baseline scenario reflects the current practice of HPV vaccination with a multi‐visit screening and treatment strategy involving cytology and colposcopy triage. We evaluated 13 comparator scenarios with increased vaccination coverage and one‐time, two‐time or repeat HIV‐targeted cervical cancer screening with the following single‐visit strategies: HPV DNA testing, HPV genotyping, automated visual evaluation (AVE) and HPV DNA with AVE triage. In all scenarios, HIV antiretroviral therapy, condom use and voluntary male medical circumcision continue at baseline levels. We simulated cancer incidence under each scenario from 2020 to 2120 using the 25 best‐fitting parameter sets. We present the median and range of model output from these simulations to account for parameter uncertainty.ResultsWe estimate that cervical cancer incidence will decrease by 87% with the continuation of current cervical cancer and HIV prevention strategies, from an age‐standardized rate per 100,000 women of 80.4 (range 58.2, 112.1) in 2020 to 10.7 (4.2, 29.9) in 2120. Scenarios scaling up vaccination and single‐visit strategies resulted in near‐ and long‐term gains. With repeat HIV‐targeted screening, incidence rates were projected to be 29–34% lower in 2030 relative to the baseline scenario, and elimination (incidence <4/100,000) was achieved with HPV DNA testing in 2095 and with AVE in 2114. A strategy of HPV DNA with AVE triage optimized the tradeoff between cancer cases averted and overtreatment.ConclusionsSingle‐visit screening strategies could avert a substantial burden of cervical cancer and accelerate progress towards elimination in settings with a high burden of HIV. Increasing the screening frequency among women with HIV and reducing loss‐to‐follow‐up for treatment will be key components of a successful elimination strategy.

Brian Befano

Darcy W Rao

Federica Inturrisi

Gui Liu

Kanan T. Desai

Li C Cheung

Mark Schiffman

Monisha Sharma

Nicolas Wentzensen

Nicole G Campos

Silvia de Sanjosé

Syed Rakin Ahmed

Zhiyun Xue