Vaccination
Volume 38, Number 40,
11 september 2020
, pages 6312-6319
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Abstract
Make accurate assessments of potential and actual impactsHPV vaccinationPrograms require accurate estimates of genotype-specific disease contributions for pre- and post-vaccination populations. The final determination of lesion-specific genotypes, especially when multiple genotypes are detected in one sample, can be technically challenging and labor intensive; Therefore, most prevalence studies use mathematical algorithms to adjust the detection of multiple genotypes. There are currently several algorithms that can produce genotype estimates within a wide range of variability. Use this forCervical cytologyRecently, samples have been evaluated for precision against a definitive reference standard, but a full biopsy sample with multiple genotypes has not yet been evaluated. wearLaser-Capture-Microdissectie(LCM) aBiopsieprobenLesion-specific genotype prevalence data were generated for a cohort of 516 young Australian women (aged 18-32 years).Cervical intra-epithelial neoplasiaGrade 3 adenocarcinomaand the Ort. Using genotype data from whole tissue sections from the same cohort, including 71 (13.7%) with multiple genotypes, the prevalence of lesion-associated genotypes was estimated using four different attribution algorithms. The proportion of lesions attributable to HPV16 andVPH18after LCM they were 58.4% and 5% respectively; Rank, proportional, single type/minimum, and any type/maximum assignment estimates were comparable between genotypes. For analyzes using whole cervical tissue biopsies, attribution estimates are appropriate to estimate the proportional contribution of individual genotypes to lesions in a population.
introduction
Genotype-specific HPV prevalence changes are commonly estimated to measure the efficacy and impact of HPV vaccination on vaccine-borne HPV infection and HPV vaccine-associated disease in a given population. In women, the main endpoints of the disease are precancerous cervical cancer, grade 3 cervical intraepithelial neoplasia (CIN3), or cervical cancer itself. Since cervical cancer takes decades to developConditionIn persistent HPV infection, CIN3 is the most direct and practical endpoint to measure the effect of vaccination in preventing disease, initially in a population or as part of a clinical trial.
It has been established that a single genotype is the causative agent of each cervical lesion: they are clonal [1]. However, multiple HPV infections often occur at the same time because all HPV types are transmitted in the same way. Cervical HPV infection is very common in sexually active women and does not necessarily indicate the presence of underlying cellular abnormalities. In general, in a subset of cancers that are more likely to respond positively to a single causative genotype, multiple genotypes will be detected on biopsy [2], [3]. The most accurate method for determining lesion-specific genotypes is lesion-specific tissue genotyping. The two tools currently available to achieve this are laser capture microdissection (LCM) to isolate lesion-specific tissue from biopsy sections, followed by HPV genotyping [1], andand the OrtHybridization of biopsy sections with genotype-specific nucleic acid probes [4], [5]. Both techniques are technically demanding, time-consuming and labor intensive, and thus not suitable for large-scale, high-throughput surveys.
An alternative and commonly used method is to identify the genotypes present in cervical cytology samples or whole biopsy sections from a population with confirmed disease, and then estimate the proportion of disease-related genotypes using one of several mapping algorithms. of genotypes [6]. ], [7], [8]. The simplest of these algorithms uses only the results of a single genotype. The most complex method ranks each genotype based on its prevalence within the population, then assigns each case the most likely genotype based on the highest ranked genotype present in each sample [7], [8 ] . The use of these algorithms facilitates the use of data generated by simpler higher throughput genotyping and sampling assays. The caveat is that large differences in the estimates have been observed depending on the algorithm used and the population to which it is applied [8], [9]. So far, there are discrepancies in the published studies regarding the algorithm used, making cross-study comparisons difficult. Two of these algorithms (hierarchical and proportional) have recently been evaluated in cervical cytology samples in comparison to LCM genotyping of concurrent biopsy samples, noting that the assignment of HPV16 was overestimated by both algorithms [10]. None of the algorithms have been evaluated on biopsy samples using a reference standard. Our aim was to use lesion-specific genotyping data generated with LCM as a reference standard and to assess the accuracy of four attribution algorithms performed on genotyping data obtained from whole biopsy sections of high-quality cervical lesions.
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ethics
The study protocol was approved by the Human Research and Ethics Committees of the Royal Women's Hospital. Consent to use biopsy samples was waived to ensure a generalizable population sample and reduce selection bias.
Recruitment and study population
The study protocol, including the recruitment strategy, has already been published [11]. The study population included a cohort of 529 women born after 30 June 1981 who were therefore eligible for the Australian Government funded HPV6/11/16/18 vaccine. All participants
Study population and genotype prevalence using WTS and LCM
The participants were between the ages of 18 and 32 at the time of the biopsy. A total of 516 lesions with evaluable DNA results were included in the analysis and 15 were excluded from the analysis (13 invalid DNA results, 2 could not be resolved in a single genotype by LCM). Of the 516 lesions, all but one tested positive for HPV from LCM. MCL was required in 89 cases (17.2%) because multiple genotypes were detected in VTS (n=73, 14.1%), no genotype was detected in VTS (n=13, 2.5%), or because only one genotype was detected.
discussion
Genotype assignment has been used to estimate the true prevalence of lesion-specific genotype, using the genotype of a full cervical biopsy or the genotype of a cervical smear, for several large studies, including vaccine efficacy studies. and global estimates of genotype prevalence associated with cancer [6], [7], [8], [9], [18], [19]. To our knowledge, this is the first study to assess the accuracy of lesion-specific HPV genotyping algorithms in a population consisting of:
Declaration of Competitive Interest
The authors declare that they have no competing financial interests or known personal relationships that may have influenced the work described in this article.
Thank you
The VACCINE Study Group consists of Garland SM, Tabrizi SN, Brotherton JML, Cornall AM, Wark JD, Wrede CD, Jayasinghe Y, Gertig DM, Pitts M, Saville M (VCS Foundation), Pyman J (Department of Anatomical Pathology, Royal Women's hospital), Tan J (Department of Oncology and Dysplasia, Royal Women's Hospital), Callegari ET (Melbourne University), Osborne SL.
This work was supported by funding from the Victorian Cancer Agency (VCA) (Australia). The source of funding played no role in the design or design of the study
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Quoted by (5)
HPV Genotyping in Biopsies of HSIL and Invasive Cervical Cancer in Women with HIV: A Cohort and Nested Case-Control Study
2022 vaccine
Quote excerpt:
We found multiple HPV infection in 43.5% of our WLGH patients, confirming the results of other authors: Carlander et al. (2020) reported 41% multiple HPV genotypes in CIN3 biopsies from seropositive women from sub-Africa de Sahara living in Sweden [18] and Clifford et al. reported 41.4% multiple HPV infections in WLWH HSIL compared to 6.7% in HIV negative women [4]. To find out which HPV causes a specific HSIL lesion, some authors performed laser capture microscopy (LCM) analysis on HSIL from HIV-negative women and confirmed the presence of a single HPV genotype in each CIN3 lesion [9, 19.20]. Unfortunately, this technique was not available for our study.
Characterization of HPV genotype distribution in HSIL and ICC biopsies of WLWH in Europe compared to HIV negative women.
Examination of cohort and nested cases and controls.
We characterized the HPV genotype distribution by performing PCR on HSIL and ICC biopsies of WLWH (n=170). 85 cases were compared to 85 matched HIV-negative controls. The percentage of patients who could be protected by HPV vaccines has been estimated.
Among WLWH (mean age 36 years, mean HIV infection duration 70.5 months, 79% on cART): The most commonly detected HPVs were HPV16 (30%), HPV35 (16%), HPV58 (14.7%), HPV31 ( 13.5%). and HPV52 (11.7%). HPV16 was found less frequently in WLWH and originated in Central Africa (20.5%) compared to other African regions (35.5%) (Page=0.05) or world regions (38.8%) (Page=0.007). Multiple versus single high-risk HPV infection was associated with younger age (≤ 35 years) (odds ratio (OR) 2.65 (95% CI: 1.3-5.2).Page=0.002), CD4 lymphocyte count <350 cells/µL (OR 2.7 (95% CI: 2-8.5;Page=0.005), use of cART for <18 months OR 2.2 (95% CI: 1.1-4.5),if =0.04) or a cumulative time with undetectable HIV viral load of less than 12 months (OR 4.2 (95% CI: 2-8.5,Page=0.001). HPV 31, 33 and 35 were detected more frequently in WLWH samples than in HIV negative controls (Page<0.05). The 9-valent vaccine would increase protection against HPV in seropositive and seronegative women (Page<0,001).
WLWH are more likely to be infected with high-risk HPVs other than 16 and 18 than with HIV-negative ones. Using the 9-valent vaccine can prevent HSIL or CHF in up to 85% of women. Inclusion of HPV 35 in the HPV vaccine panel could improve vaccine efficacy in WLWH.
Surveillance systems for monitoring efforts to eliminate cervical cancer: focus on HPV infection, cervical dysplasia, cervical cancer screening and treatment
2021, Preventive Medicine
Quote excerpt:
Pooling of data has confirmed lower HSIL rates in vaccinated than unvaccinated women and lower HSIL rates in women who received one or two doses of HPV vaccine compared to unvaccinated women in Australia (Brotherton et al., 2019b ; Gertig et al., 2013). A research study examined the HPV type in CIN3/AIS from vaccination (Cornall et al., 2020; Young et al., 2013) to inclusion in routine surveillance (Communicable Diseases Network Australia (CDNA), 2013). Surveillance of Australia's new HPV-based screening program uses revised national indicators (Australian Institute of Health and Welfare, 2019).
Achieving the global eradication of cervical cancer as a public health problem requires close monitoring of public health progress and clinical activities and outcomes across the three pillars of vaccination, screening and treatment. Ideally, monitoring should take place within an integrated system that is regularly planned, funded and evaluated to ensure it provides timely, accurate and actionable feedback. In this paper, we conceptualize the main goals of public health surveillance as process and outcome measures in each of the three pillars. Process actions include coverage/participation actions for vaccination, screening and treatment, and ongoing assessment of the quality and coverage of these programs and activities. Outcomes related to the natural course of human papillomavirus (HPV) infection included the prevalence of HPV infection, cervical precursor lesions, and cervical cancer (including diagnosis stage, cancer incidence, and mortality). These outcome measures can be used to monitor the effectiveness of the three main activities in the short, medium and long term and to assess whether these interventions are effective in reducing their occurrence. We discuss possible methods to monitor these actions in the context of country capacity, drawing on examples from Australia, the US and low- and middle-income countries.
HPV type-specific trends in precervical cancer in the United States, 2008 to 2016
2023, International Journal of Cancer
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