Ethical issues in vaccine trial participation by adolescents: qualitative insights on family decision making from a human papillomavirus vaccine trial in Tanzania.

Background: Research in children is essential for them to benefit from the outcomes of research but involvement must be weighed against potential harms. In many countries and circumstances, medical research legally requires parental consent until the age of 18 years, with poorly defined recommendations for assent prior to this. However, there is little research exploring how these decisions are made by families and the ethical implications of this.

A cervical cancer control strategy for lower-resource settings: interventions to complement one-dose HPV vaccination.

One-dose prophylactic HPV vaccination of pre-adolescents may reduce cervical cancer deaths dramatically in lower-resource settings, but the benefits of achieving immediate high coverage among pre-adolescents would not be realized for 20 to 40 years. Prophylactic vaccine efficacy is reduced after sexual debut, and current therapeutic intervention candidates designed to treat existing HPV infections or precancerous lesions have yielded insufficient evidence to warrant widespread use. However, we are developing a feasible, scalable, high-quality cervical screening approach that could prevent hundreds of thousands of deaths, while we work to achieve high coverage of one-dose vaccination for adolescent cohorts.

Assessing generalizability of an AI-based visual test for cervical cancer screening.

A number of challenges hinder artificial intelligence (AI) models from effective clinical translation. Foremost among these challenges is the lack of generalizability, which is defined as the ability of a model to perform well on datasets that have different characteristics from the training data. We recently investigated the development of an AI pipeline on digital images of the cervix, utilizing a multi-heterogeneous dataset of 9,462 women (17,013 images) and a multi-stage model selection and optimization approach, to generate a diagnostic classifier able to classify images of the cervix into "normal", "indeterminate" and "precancer/cancer" (denoted as "precancer+") categories.

Criteria for second generation comparator tests in validation of novel HPV DNA tests for use in cervical cancer screening.

While HC2 and GP5+/6+ PCR-EIA were pivotal in test validation of new HPV assays, they represent the first generation of comparator tests based upon technologies that are not in widespread use anymore. In the current guideline, criteria for second-generation comparator tests are presented that include more detailed resolution of HPV genotypes. Second-generation comparator tests should preferentially target only the 12 genotypes classified as carcinogenic (IARC-group I), and show consistent non-inferior sensitivity for CIN2+ and CIN3+ and specificity for ≤CIN1 compared to one of the first-generations comparators, in at least three validation studies using benchmarks of 0.

Meeting report: Considerations for trial design and endpoints in licensing therapeutic HPV16/18 vaccines to prevent cervical cancer.

Cervical cancer is a major cause of morbidity and mortality globally with a disproportionate impact on women in low- and middle-income countries. In 2021, the World Health Organization (WHO) called for increased vaccination, screening, and treatment to eliminate cervical cancer. However, even with widespread rollout of human papillomavirus (HPV) prophylactic vaccines, millions of women who previously acquired HPV infections will remain at risk for progression to cancer for decades to come.

Proof of Concept Study: Comparability of Microbiome Diversity in Self- and Physician-Collected HPV-Positive and HPV-Negative Cervicovaginal Samples.

Recent studies have revealed the impact of human papillomavirus (HPV) infections on the cervicovaginal microbiome; however, few have explored the utility of self-collected specimens (SCS) for microbiome detection, obtained using standardised methods for HPV testing. Here, we present a proof-of-concept analysis utilising Oxford Nanopore sequencing of the 16S rRNA gene in paired samples collected either by the patient using an Evalyn Brush or collected by a physician using liquid-based cytology (LBC). We found no significant differences in the α-diversity estimates between the SCS and LBC samples.

Impact of the COVID-19 pandemic on cervical cancer screening participation, abnormal cytology prevalence and screening interval in Catalonia.

Background: The COVID-19 pandemic led to a national lockdown and the interruption of all cancer preventive services, including cervical cancer screening. We aimed to assess the COVID-19 pandemic impact on opportunistic screening participation, abnormal cytology (ASCUS+) prevalence and screening interval in 2020 and 2021 within the Public Health System of Catalonia, Spain.

Methods: Individual data on cytology and HPV testing of women aged 25-65 from 2014 to 2021 were retrieved from the Information System for Primary Care Services (SISAP).

Squamocolumnar junction visibility, age, and implications for cervical cancer screening programs.

Visual assessment is currently used for primary screening or triage of screen-positive individuals in cervical cancer screening programs. Most guidelines recommend screening and triage up to at least age 65 years old. We examined cervical images from participants in three National Cancer Institute funded cervical cancer screening studies: ALTS (2864 participants recruited between 1996 to 1998) in the United States (US), NHS (7548 in 1993) in Costa Rica, and the Biopsy study (684 between 2009 to 2012) in the US.

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.

Benefits and harms of cervical screening, triage and treatment strategies in women living with HIV.

To support a strategy to eliminate cervical cancer as a public health problem, the World Health Organisation (WHO) reviewed its guidelines for screening and treatment of cervical pre-cancerous lesions in 2021. Women living with HIV have 6-times the risk of cervical cancer compared to women in the general population, and we harnessed a model platform ('Policy1-Cervix-HIV') to evaluate the benefits and harms of a range of screening strategies for women living with HIV in Tanzania, a country with endemic HIV. Assuming 70% coverage, we found that 3-yearly primary HPV screening without triage would reduce age-standardised cervical cancer mortality rates by 72%, with a number needed to treat (NNT) of 38.

Benefits, harms and cost-effectiveness of cervical screening, triage and treatment strategies for women in the general population.

In 2020, the World Health Organization (WHO) launched a strategy to eliminate cervical cancer as a public health problem. To support the strategy, the WHO published updated cervical screening guidelines in 2021. To inform this update, we used an established modeling platform, Policy1-Cervix, to evaluate the impact of seven primary screening scenarios across 78 low- and lower-middle-income countries (LMICs) for the general population of women.

Reproducible and clinically translatable deep neural networks for cervical screening.

Cervical cancer is a leading cause of cancer mortality, with approximately 90% of the 250,000 deaths per year occurring in low- and middle-income countries (LMIC). Secondary prevention with cervical screening involves detecting and treating precursor lesions; however, scaling screening efforts in LMIC has been hampered by infrastructure and cost constraints. Recent work has supported the development of an artificial intelligence (AI) pipeline on digital images of the cervix to achieve an accurate and reliable diagnosis of treatable precancerous lesions.

Treatment of Cervical Precancers is the Major Remaining Challenge in Cervical Screening Research.

Deepening understanding of cervical cancer pathogenesis has yielded one-dose prophylactic human papillomavirus (HPV) vaccines and accurate HPV-based cervical screening tests. Knowing the heterogeneous carcinogenic potential of the individual high-risk HPV types permits prioritization of vaccination and screening strategies. However, "correct" (i.

Agreement on Lesion Presence and Location at Colposcopy.

Objectives/purpose: The reproducibility and sensitivity of image-based colposcopy is low, but agreement on lesion presence and location remains to be explored. Here, we investigate the interobserver agreement on lesions on colposcopic images by evaluating and comparing marked lesions on digitized colposcopic images between colposcopists.

Methods: Five colposcopists reviewed images from 268 colposcopic examinations.

Validation in Zambia of a cervical screening strategy including HPV genotyping and artificial intelligence (AI)-based automated visual evaluation.

Background: WHO has recommended HPV testing for cervical screening where it is practical and affordable. If used, it is important to both clarify and implement the clinical management of positive results. We estimated the performance in Lusaka, Zambia of a novel screening/triage approach combining HPV typing with visual assessment assisted by a deep-learning approach called automated visual evaluation (AVE).

A rapid HPV typing assay to support global cervical cancer screening and risk-based management: A cross-sectional study.

The World Health Organization recommends human papillomavirus (HPV) testing for cervical screening. Extended genotyping can identify the highest-risk HPV-positive women. An inexpensive, rapid, mobile isothermal amplification assay (ScreenFire HPV RS test) was recently redesigned to yield four channels ordered by cancer risk (ie, hierarchical approach): HPV16, HPV18/45, HPV31/33/35/52/58 and HPV39/51/56/59/68.

Artificial intelligence-based image analysis in clinical testing: lessons from cervical cancer screening.

Novel screening and diagnostic tests based on artificial intelligence (AI) image recognition algorithms are proliferating. Some initial reports claim outstanding accuracy followed by disappointing lack of confirmation, including our own early work on cervical screening. This is a presentation of lessons learned, organized as a conceptual step-by-step approach to bridge the gap between the creation of an AI algorithm and clinical efficacy.