The proxy marker for human papillomavirus (HPV), p16, is included in the new AJCC 8th/UICC 8th staging system, but due to incongruence between p16 status and HPV infection, single biomarker evaluation could lead to misallocation of patients. We established nomograms for overall survival (OS) and progression-free survival (PFS) in patients with oropharyngeal squamous cell carcinoma (OPSCC) and known HPV-DNA and p16 status, and validated the models in cohorts from high- and low-prevalent HPV countries.Consecutive OPSCC patients treated in Denmark, 2000–2014 formed the development cohort. The validation cohorts were from Sweden, Germany, and the United Kingdom. We developed nomograms by applying a backward-selection procedure for selection of variables, and assessed model performance.In the development cohort, 1313 patients, and in the validation cohorts, 344 German, 503 Swedish and 463 British patients were included. For the OS nomogram, age, gender, combined HPV-DNA and p16 status, smoking, T-, N-, and M-status and UICC-8 staging were selected, and for the PFS nomogram the same variables except UICC-8 staging. The nomograms performed well in discrimination and calibration.www.orograms.org.Our nomograms are reliable prognostic methods in patients with OPSCC. Combining HPV DNA and p16 is essential for correct prognostication. The nomograms are available at  Consequently, p16 was included in the newly proposed American Joint Committee on Cancer/Union for International Cancer Control (AJCC-8/UICC-8) staging system. However, an estimated 10–20% of all OPSCCs are p16-positive, but HPV-negative, due to alternative cellular events leading to p16 overexpressionA nomogram is a graphical illustration of a statistical model for calculating the cumulative effect of several variables on a particular outcome, and nomograms have been developed to predict clinical endpoints for patients with several types of malignancies. In this study, we aimed to identify OPSCC- and patient-related factors associated with OS and PFS, and to construct and externally validate predictive nomograms. Moreover, this is the first study addressing patients treated for an OPSCC encompassing high and low HPV-prevalent countries in validation cohorts, and incorporating the newly published AJCC-8/UICC-8 staging system refining prognostication by employing both HPV-DNA and p16 status.20 Using the unique resident code from the Danish Civil Registration System, we linked the Danish Head and Neck Cancer Group (DAHANCA)21 database and the Danish Pathology Data Registry (DPDR),22 to identify patients. Patient characteristics were retrieved from these databases as well as from medical records. Curative radiotherapy regimens consisted of 66–68 Gy, divided into 33–34 fractions given 6 days a week. From 2007, stage III–IV (UICC 7th) patients were offered concurrent chemotherapy (primarily weekly cisplatin 40 mg/sqm), if tolerated, whilst a minority were treated with cetuximab.Consecutive patients diagnosed with OPSCC and treated with curative intent in eastern Denmark between 2000 and 2014 were included in the development cohort.23 Immunohistochemistry for p16 was performed using the Ventana Benchmark Ultra autostainer with the UltraView detection kit and the p16 monoclonal antibody E6H4 ready-to-use with CC1 as a pretreatment .An expert head-and-neck pathologist re-validated a haematoxylin–eosin (H&E)-stained section of each tumour. p16 staining was considered positive if there was a strong and diffuse nuclear and cytoplasmic reaction in more than 70% of the tumour cells.1 The remaining samples were analysed by HPV PCR.20 The GP5+/GP6+ primers used24 are known to amplify at least 37 mucosal HPV types,25 namely 14 high-risk HPV types 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66 and 68, and 23 low-risk HPV types 6, 11, 26, 34, 40, 42, 43, 44, 53, 54, 55, 57, 61, 70, 71, 72, 73, 81, 82/MM4, 82/IS39, 83, 84 and 89. The specific HPV types can then be identified by, e.g. sequencing of the resulting amplicons.1DNA was isolated from two to four 10-μm sections using the DSP DNA Mini Kit and the QIAsymphony SP kit , according to the manufacturers’ instructions. HPV DNA PCR was performed using the general primers GP5+/6+ and Platinum Taq DNA polymerase . All GP5+/6+ PCR negative samples were subject to a GAPDH (housekeeping gene) PCR to confirm DNA quality. HPV DNA amplicons were run on the QIAxcel Advanced System using the QX DNA Screening Gel  according to the manufacturer’s instructions. The expected amplicon sizes were ~150 base pairs (bp) for GP5+/6+ and 200 bp for GAPDH. Negative samples were resolved on a 2.5% agarose gel stained with ethidium bromide to compare the sensitivity of the current assay with the standard. Approximately 50% of all samples were analysed by HPV PCR and the HPV+ cases were subsequently sequenced for HPV typing.Three independent cohorts formed the external validation cohorts. The populations consisted of patients with OPSCC treated with curative intent at Karolinska University Hospital , Giessen University Hospital  and The Predictr Consortium, United Kingdom (UK) (2001–2012).9 The Magpix instrument is known to amplify the 27 HPV types: HPV 6, 11, 16, 18, 26, 30, 31, 33, 35, 39, 42, 43, 44, 45, 51, 52, 53, 56, 58, 59, 66, 67, 68, 69, 70, 73 and 82.The Swedish cohort was classified using p16 immunohistochemistry  and high-risk HPV-DNA detection by a bead-based multiplex assay on a Magpix instrument .26 This assay detects the following 24 HPV types: 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 68, 73 and 82, three putative high-risk types  and six low-risk types .The German cohort was classified using p16 immunohistochemistry  and high-risk HPV-DNA detection by PCR followed by bead-based hybridisation .3 INFORM HPV III Family 16 probe B detects HPV-16, -18, -31, -33, -35, -39, -45, -51, -52, -56, -58 and 66.The UK cohort was classified using p16 immunohistochemistry  and high-risk HPV DNA in situ hybridisation .Overexpression of p16 (>70% positive staining) was classified similar to the Danish cohort for all three validation cohorts. Treatment modalities for the validation cohorts are presented in more detail in Table Covariates available for adjustment are described in Table 27 All models are multivariable, i.e. factors are mutually adjusted, and thus the effect estimates cannot be interpreted marginally. In a subanalysis, we evaluated the effect of fitting a spline for age in the development model. This sub-analysis was for the nonlinear part of the spline considered as non-significant; e.g. OS (p = 0.92) and PFS (p  = 0.85).To evaluate which covariates influenced survival, we fitted multivariate Cox regression analyses with all factors in Table 28 None of the final models violated the proportional hazards assumption. Based on the final models, nomograms were constructed to predict overall survival and PFS at 1, 3 and 5 years after diagnosis. We considered only complete cases . p values less than 5% were considered significant and all analyses were performed in R version 3.0.3.29To test whether the assumption of proportional hazards was violated, we tested for trends in the scaled Schoenfeld residuals of the final models.30 calibration plots31 and discrimination (Harrell’s C index).32 In addition, we fitted a Weibull calibration model, as suggested by van Houwelingen and Putter, in which shifts in baseline cumulative hazard , the effect of the prognostic index (the linear predictor in the Cox model) and the shape of the cumulative baseline hazard were tested.33 A smoothed version of the cumulative baseline hazard was used in the calibration model, where smoothing was done by linear interpolation.We conducted external validation by applying our nomograms to the patient cohorts from Sweden, United Kingdom and Germany. We assessed nomogram model performance by examining overall accuracy (Brier score),N+), with small primary tumours (68% T1 or T2), and in early UICC8 stage (65% UICC8 stage I or II). OS was for the HPV+/p16+ patients 95% (95% CI 93–96%) after 1 year, 86% (95% CI 84–89%) after 3 years and 80% (95% CI 77–83%) after 5 years of follow-up, and for the HPV–/p16– patients 71% (95% CI 65–74%) after 1 year, 46% (95% CI 41–51%) after 3 years and 34% (95% CI 29–39%) after 5 years  during follow-up (Table Five-year OS for the HPV+/p16+ patients in the Swedish cohort was 81% (95% CI 77–85%) and for the HPV–/p16– patients 40% (95% CI 31–52%); for the German cohort 81% (95% CI 72–91%) and 35% (95% CI 30–42%) and in the UK cohort it was 82% (95% CI 77–87%) and 42% (95% CI 34–52%) Fig. .The backwards elimination procedure left the model for overall survival unchanged, i.e. the model included age, gender, combined HPV and p16 status, smoking, T-, N-, and M-classification and UICC-8 staging Table . The OS Figure C index for the OS nomogram was 0.787 (95% CI 0.753–0.817), 0.772 (95% CI 0.747–0.817) and 0.766 (95% CI 0.746–0.788) for 1, 3 and 5 years, respectively. Similarly, external validation after 1, 3 and 5 years, gave C-indexes for the Swedish cohort of 0.836 (95% CI 0.775–0.881), 0.793 (95% CI 0.749–0.833) and 0.780 (95% CI 0.743–0.815); for the German cohort 0.712 (95% CI 0.655–0.764), 0.722 (95% CI 0.683–0.759) and 0.707 (95% CI 0.671–0.741) and for the UK cohort 0.815 (95% CI 0.775–0.864), 0.797 (95% CI 0.755–0.832) and 0.791 (95% CI 0.751–0.822). Brier plots for OS are presented in Suppl. Fig. Harrell’s p < 0.001). Crude cumulative incidence of progression or death in the development cohort was at 5 years, 28% (95% CI 25–32%) for the HPV+/p16+ patient group and 71% (95% CI 66–75%) for the HPV–/p16– patient group  patients in the development cohort experienced disease progression or death, with 187 (24%) patients in the HPV+/p16+ subgroup vs. 274 (66%) patients in the HPV–/p16– subgroup (C index of the development cohort was 0.733 (95% CI 0.703–0.760), 0.728 (95% CI 0.704–0.750) and 0.725 (95% CI 0.703–0.747) at 1, 3 and 5 years. External validation of the nomogram for PFS after 1, 3 and 5 years, gave C-indexes of 0.805 (95% CI 0.745–0.852), 0.763 (95% CI 0.722–0.802) and 0.764 (95% CI 0.724–0.801), respectively, for the Swedish cohort; 0.714 (95% CI 0.663–0.761), 0.711 (95% CI 0.671–0.748) and 0.704 (95% CI 0.667–0.738), respectively, for the German cohort and 0.797 (95% CI 0.739–0.842), 0.778 (95% CI 0.735–0.812) and 0.771 (95% CI 0.731–0.805), respectively, for the UK cohort. The parameter regressing the log cumulative baseline hazard in the development cohort on the log cumulative baseline hazard in the German cohort was 0.88 (95% CI: 0.69–1.07), in the Swedish cohort 1.16 (95% CI: 0.97–1.36) and in the UK cohort 1.20 (95% CI: 0.99–1.40). The specification of the model for all cohorts appeared correct with confidence intervals all including unity. Calibration plots for internal and external validation of PFS are shown in Fig. The nomogram for prediction of PFS at 1, 3 and 5 years is shown in Fig. www.orograms.org) can be used for more precise calculations than drawing lines on the nomogram.This study presents multinational-validated nomograms for OS and PFS for patients with OPSCC. One of the main findings includes the identification of combined HPV-DNA and p16 status as an important and independent predictor for OS and PFS. The nomograms performed well in external validation across areas with high and low HPV prevalence. These models may facilitate discussions in clinical settings and aid in identifying lower-risk patients who could be candidates for de-escalation therapy, as well as higher-risk patients eligible for treatment-escalation trials. The online nomogram , the development cohort was not from a population-based, non-selected setting when constructing nomograms for OS and PFS in OPSCC patients.In this study, we chose overall survival instead of disease-specific survival as a primary endpoint because it represents the cumulative effect of competing diseases, treatment morbidity and age on patient survival. As disease progression is associated with significantly poorer outcome and consequently a decrease in quality of life, we developed a nomogram with PFS as the endpoint. The PFS nomogram therefore complements the overall survival nomogram well.Although our training cohort is population based and selection bias is minimised, the nomograms have limitations. With respect to accuracy, the CIs at the various predicted probabilities of recurrence should be considered if using these nomograms in clinical settings. The final models performed well in calibration and discrimination, but the level (risk of outcomes) is––as expected––not identical across cohorts. This is most evident in the German cohort, and this risk should be taken into account when using the models. The German cohort might perform worse due to several factors; partly a significantly lower HPV prevalence, higher smoking, higher share of patients who experience progression and a greater share of patients in advanced stage (e.g. stage 3 and 4). Although this is adjusted for, it should be considered whether these nomograms are best suitable in HPV-high-risk areas. A possible other bias in this model is the number of censored patients, as observed in the crude-survival analysis. The Danish, UK and Swedish centres have ~60–70% censorship opposed to the German with merely 45% censored patients.These nomograms are only applicable for patients who underwent evaluation at multidisciplinary head and neck cancer centres, as performance of the nomograms is likely to be worse for patients who do not attend multidisciplinary evaluation.47 But notably, p16 overexpression is also present in a number of non-HPV-driven tumours probably related to RAS and BRAF mutations48 although not in KRAS.49 Other head and neck carcinomas have proven to be HPV–/p16+ likely related to misconfigurations in the p16–Rb–cyclin-D1 pathway inducing cell cycle activation in HPV-negative carcinomas.50p16 overexpression is a standard surrogate biomarker for high-risk HPV-associated OPSCC.The prevalence of HPV-associated OPSCC ultimately depends on the sensitivity and specificity detection method employed, and using different methods between cohorts as in this study, might lead to discordant results in HPV/p16 testing. All four centres employed different p16 and HPV-testing tools, which is a potential shortcoming. All methods cover the most relevant HR-HPV types . However, the Ventana in situ method (UK cohort) is highly sensitive but less specific opposed to amplification of HPV DNA by general primers (GP5+/6+) with presumed high sensitivity and specificity , and the subsequent detection of the PCR products with type-specific probes, e.g. bead-based multiplex, might differ. A limitation of this study is also the use of different p16 antibodies across centres, potentially leading to a discrepancy in p16 positivity. Notably, more than 90% of all tumours in this study are examined with the use of the same antibody (clone E6H4). Preferably, a subset of tumours should be tested with all methods to uncover potential shortcomings.In conclusion, we developed and validated nomograms for OPSCC patients and known HPV-DNA and p16 status. The nomograms are applicable for both high and low HPV areas. Combining HPV-DNA and p16 status is essential for accurate prognostication. Future work might focus on validating our results and incorporating additional prognostic factors, including nomograms specific for salvage treatment for relapsed disease, as well as including outcome measures which have shown to influence outcome  and outcomes such as histopathological evaluations.Supplementary


Background: The aim of this study was to explore the Human Papillomavirus (HPV) genotype composition and intra-genotype variants within individual samples of low- and high-grade cervical cytology by deep sequencing. Clinical, cytological, sequencing, and functional/structural data were forged into an integrated variant profiling pipeline for the detection of potentially vaccine-resistant genotypes or variants.Methods: Low- and high-grade intraepithelial lesion (LSIL and HSIL) cytology samples with +HPV were subjected to amplicon (L1 gene fragment) sequencing by dideoxy (Sanger) and deep methods. Taxonomic, abundance, diversity, and phylogenetic analyses were conducted to determine HPV genotypes/sub-lineages, relative abundance, species diversity and phylogenetic distances within and between samples. Variant detection and functional analysis of translated L1 amino acid sequences determined structural variations of interest.Results: Pure and mixed HPV infections were common among LSIL (n = 6) and HSIL (n = 6) samples. Taxonomic profiling revealed loss of species richness and gain of dominance by carcinogenic genotypes in HSIL samples. Phylogenetic analysis showed excellent correlation between HPV-type specific genetic distances and carcinogenic potential. For combined LSIL/HSIL samples (n = 12), 11 HPV genotypes and 417 mutations were detected: 375 single-nucleotide variants (SNV), 29 insertion/deletion (indel), 12 multi-nucleotide variants (MNV), and 1 replacement variant. The proportion of nonsynonymous mutations was lower for HSIL (0.38) than for LSIL samples (0.51) (p < 0.05). HPV variant analysis pinpointed nucleotide-level mutations and amino acid-level structural modifications.Conclusion: HPV L1 intra-host and intra-genotype variants are abundant in LSIL and HSIL samples with potential functional/structural consequences. An integrated multi-omics approach to variant analysis may provide a sensitive and practical means of detecting changes in HPV evolution and dynamics within individuals or populations. Since t rapidly  and the  rapidly  to allow rapidly .The PV is believed to have co-evolved with their hosts over 350 million years . ThroughThe HPV genome is a ∼8,000 base pair (bp), double stranded, circular DNA packaged within a protein capsid. The prototypical genome encodes 6 early genes  and 2 late genes (L1 and L2) . SpecifiRecently, whole-genome Sanger and deep sequencing studies have shown a surprisingly high level of intra-host diversity of HPV-16, -18, -52, and -58 . ExtensiUsing a multi-omics approach, we aimed to explore the HPV genotype composition and intra-genotype variants within individual samples of low and high-grade cervical cytology. We also focused on the genetic and translated amino acid sequence variations of L1 informed by next-generation sequencing (NGS) for mapping onto the structure of HPV antigenic loops as a means of variant profiling and visualization.n = 6) and HSIL (n = 6) for characterization and comparison of viral diversity and variant analysis.Residual liquid-based cervical cytology samples were consecutively procured from the Department of Pathology after completion of cytological diagnosis. Demographic and cytohistological data were abstracted from the electronic health record (AHLTA) of the Department of Defense (DoD) and linked to each sample. In our previous study, three categories of samples, i.e., negative for intraepithelial lesion or malignancy (NILM), low-grade squamous intraepithelial lesion (LSIL) and high-grade squamous intraepithelial lesion (HSIL) were collected for HPV genotyping and DNA methylation analysis . For thi2, to determine the HPV genotype(s)  .The PCR products were concurrently subjected to dideoxy (Sanger) sequencing for validation of deep-sequenced results. Briefly, amplicons (∼200 ng DNA/sample) were sequenced using primer MY11 at Eurofins Operon (United States). The resulting quality sequences were BLAST aligned for HPV genotyping as described above.The pre-configured, automated Quality Control (QC) workflow implemented in Illumina MiSeq output a series of QC metrics including the summary statistics of the reads, and the Phred quality scores Q which correspond to the base-calling error probabilities . The rean was the number of HPV genotypes found in the sample, and ip was the proportion of reads that were identified as the thi HPV genotype. β-diversity analysis was performed with the principle coordinate analysis (PCoA) of Bray-Curtis distances  i and i in samples A and B, to measure the dissimilarity or “distance” of HPV genotype composition between samples. Principal component analysis (PCA) was used to determine the correlative relationship between variables (HPV genotypes) in the LSIL or HSIL group. PCA was performed on the covariance matrix of natural log-transformed abundance data [ln (n +1)] of HPV genotypes within each sample . α-diversity of the HPV communities was computed to measure within-sample variation by (1) the Simpson’s index : SI = 1  entropy : H = ∑1nistances : B = ∑i=h sample . Log traMultiple alignment of consensus sequences of each HPV genotype detected in the HSIL and LSIL samples was obtained using the T-coffee program . The evoVariants were detected by comparing to reference sequences of each HPV type, using the Low Frequency Variant Detection Module in the CLC Bio Genomics Workbench 11.0.1 (QIAGEN), where an error model was included to exclude variants that were likely due to sequencing errors. Variants were classified into four categories: SNV, MNV, indel, or replacement of one or more bases.3 (nS = [δn+4-i]∗(0.37)-6 where nS is the surface probability of amino acid n equating to the normalized product of fractional surface probabilities (xδ) of six amino acids flanked by positions n -2 and n+ 3 (nS of a random hexapeptide is 1.0 (threshold); a value >1.0 indicates increased surface probability.The functional consequences of detected variants in each sample were inferred based on the predicted changes at the codon level. These changes were classified as nonsynonymous (with amino acid changes), synonymous , or indels which can lead to reading frame shift or early stop codon. To map the amino acid changes to protein structure, BLAST searches were conducted to identify the homologous HPV L1 structure(s) collected in the Protein Data Bank (PDB)3 . 3D modeand n+ 3 . The Sn The genotype classification of PV is based on the DNA sequence of the L1 gene . The defThe World Health Organization (WHO) International Agency for Research on Cancer (IARC) Working Group assessed carcinogenic potential of HPV types and classified them into three categories  (1) carcn = 6) and HSIL (n = 6)  . The med (n = 6) .Both traditional Sanger and NGS platforms were used to detect HPV genotypes and sub-lineages within each sample. Sanger sequencing resolved the single dominant HPV genotype within each sample. Compared to Sanger sequencing, NGS achieved a better resolution in detection of mixed genotypes (up to four in this cohort) and low-abundance genotypes . CompariThe composition of HPV genotypes in each sample is illustrated in We analyzed the HPV diversity, dominance and community structure between LSIL and HSIL samples. A total of 10 different genotypes were found in single and mixed-infected LSIL samples, whereas seven different genotypes were identified in HSIL samples. The respective Shannon Entropy Indices for LSIL and HSIL samples were 0.32 and 0.16, suggesting reduced diversity in HSIL samples . The domWe further examined the diversity of each sample estimated through read counts and Simpson-Index . The redDissimilarity of HPV communities across HSIL and LSIL samples was visualized by principle coordinate analysis (PCoA) of Bray-Curtis distances . PCoA shPrototypical HPV genome based on the genetic information of HPV-16 (GenBank ID: K02718) is created using the CLC Bio Genomics Workbench 11.0.1 (QIAGEN) and shown in n = 12), a total of 417 mutations were detected, including 375 SNVs, 29 indels, 12 MNVs, and one replacement variant. The distribution of these variants for the 12 samples by Pap grade and HPV genotype is shown in p = 0.017, Fisher’s exact test)  . On the It is important to identify mutations that is potentially driven by vaccine- or natural infection-induced host immune response. To visualize mutations in 3D, first the structural model of HPV-16 L1 (PDB ID: 2R5H)  was recoThis study revealed the complex genetic diversity of HPV viromes within low- and high-grade Pap samples. Both pure and mixed infections were common as shown by deep amplicon sequencing. Taxonomic profiling revealed the difference between LSIL and HSIL viral communities with loss of species richness and gain of dominance by carcinogenic genotypes, particularly HPV-16, in HSIL samples. Deep sequencing allowed the detection of carcinogenic HPVs constituting a minor component of a virome which was undisclosed by Sanger sequencing or cytological grading. Phylogenetic inference of the patient-derived L1 sequences showed excellent correlation between HPV type-specific distances and IARC-defined carcinogenic potential. Together with taxonomic profiling, this “Taxo-Phylo” approach holds promise as a molecular taxonomy-based classifier of cervical cytology.in silico modeling of mutations may direct laboratory testing and confirmation of its significance through antigen-antibody binding assays. For example, hepatitis B virus (HBV) genotypes are known to vary by ethno-geography. Mutations in the major hydrophilic regions (MHR) of the hepatitis B surface antigen (HBSAg) have resulted in stable, vaccine-escape mutant virions that are infectious and pathogenic  of low abundance may later dominate the virome if it is inherently more carcinogenic or confers a selective advantage with ensuing clonal expansion. Current published literature on HPV L1 variant analysis is scarce. As noted previously, a high intra-type L1 sequence variability was discovered in 35 HPV genotypes by deep sequencing. These investigators also found unique genotypes and its variants associating with distinct anatomical sites supporting the notion of viral niche-adaptation as shapers of viral evolution . HoweverThe strength of this study lies in the multi-omics approach developed herein. Integration of clinical metadata, genomic data, and functional/structural information to reveal patient-specific metagenomic profiles and variant structures in 3D is novel and practical. Such individualized virome profiling may provide guidance to clinicians on the risk of cervical cancer and potentially deleterious viral variants/mutations. We acknowledge that our study has limitations in that the sample size was small and a fragment of L1 was studied so overreaching generalizable conclusions cannot be drawn. However, an integrated, holistic approach was established from this dataset to further HPV metagenomics research. Our future direction will be to conduct a large scale, whole-genome or full-sequence L1 variant analysis to survey type-specific variant patterns by cytological grades.In this pilot study, NGS provided a cost-effective platform for an unbiased discovery of HPV communities in clinical samples. The HPV genotype composition was shown to be correlated with clinical severity and the carcinogenic risk for cervical cancer. Multi-omics analyses afforded an unprecedented opportunity to better characterize the L1 complexity in clinical samples. Ultimately, this approach will lead to greater understanding of the dynamic interplay between virus and host in HPV pathogenesis.This paper has undergone PAO review at Brooke Army Medical Center and was cleared for publication. The opinions or assertions contained herein are the private views of the authors and are not to be construed as official or reflecting the views of the U.S. Department of the Army, U.S. Department of Defense, or the U.S. government.This study was approved by the institutional review board of Brooke Army Medical Center, Fort Sam Houston, Texas.JS-G and YW conceived and designed the study and participated in the acquisition of data. JS-G, YW, HC, and HZ analyzed and interpreted the data. JS-G, YW, and HC wrote the manuscript. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


DNA, extracted from cells collected from the anorectum, oropharynx and urethra of 346 participants, was investigated for the presence of EBV, HPV and HSV using real-time PCR. Demographic data from the participants were analyzed.P = 0.001) and 46–60 years . EBV infection of the urethra was significantly correlated with age group 21–30 years . EBV/HPV co-infection of the anorectum  and urethra  was also associated with this age group. Among HIV-positive MSM, there was a significant association between age-group  in HPV infection of the anorectum. A failure to use condoms was significantly associated with HPV infection of the anorectum  and urethra . Similarly, lack of condom use was significantly associated with EBV infection of the urethra .All three viruses were found in all sampled sites. EBV was the commonest virus, being detected in the anorectum (47.7% of participants), oropharynx (50.6%) and urethra (45.6%). HPV and HSV were found in 43.9% and 2.9% of anorectum samples, 13.8% and 3.8% of oropharynx samples and 25.7% and 2% of urethra samples, respectively. HPV infection of the anorectum was significantly associated with age groups 21–30  contains supplementary material, which is available to authorized users. Men who have sex with men (MSM) are at higher risk of sexually transmitted diseases (STDs) than other groups. Incidence has been rising due to the practice of various sexual acts including penile–anal, oral–anal, and/or penile–oral contact , 2. HPV Other viruses are also found in MSM. Epstein-Barr virus (EBV) is one of the most common human viruses found in B-cells and epithelial cells of healthy persons . The preHerpes simplex virus (HSV) is one of the commonest sexually transmitted viral infections worldwide. The usual sites of HSV infection are skin and mucosal membranes. Primary infection sites of HSV-1 and HSV-2 are the oropharynx and genital tract, respectively. Infection is often asymptomatic. Even though HSV-2 is predominantly spread via the genital route (in contrast to HSV-1) and its seroprevalence is higher in HIV-positive (> 80%) than HIV-negative MSM , HSV-1 iTo explore the prevalence and anatomical site distribution of HPV, EBV and HSV infecting asymptomatic MSM in Northeast Thailand, real-time polymerase chain reaction (RT-PCR) was used to detect these viruses from 346 participants at anatomical sites including the oropharynx, urethra and anorectum.Neisseria gonorrhea infection by anatomic distributions among men who have sex with men, and multidrug resistant patterns of Neisseria gonorrhea” at M-Reach STDs clinic in Chatapadung Contracting Medical Unit, and the ARV Clinic, Khon Kaen Hospital, Khon Kaen Province, Thailand from September 2014 to July 2015. Prevalence of Neisseria gonorrhea in urethra was published [In total, 358 asymptomatic MSM were enrolled under a cross-sectional study project title of “Factors associated to ublished , 24, butGAPDH gene using specific primers (GAPDH forward: 5′-TCATCAGCAATGCCTCCTGCA-3′ and reverse: TGGGTGGCAGTGATGGCA-3′ by RT-PCR. Quantity of DNA was assessed using the NanoDrop™ (Thermo Scientific) [Cells from swab samples were pelleted and washed with phosphate buffered saline by centrifugation at 2000 rpm for 5 min. Cells were lysed using lysis buffer  supplemented with 50 mg/ml of proteinase K and then incubated at 60 °C for 30 min. Protein was precipitated by addition of protein precipitation buffer , and then removed by centrifugation at 13,500 rpm for 5 min at 4 °C. DNA was precipitated with an equal volume of isopropanol and collected by centrifugation at 13,500 rpm for 5 min at 25 °C and washed with 70% ethanol. Finally, the DNA pellet was dried at 37 °C for 15–30 min and then resuspended in distilled water. The quality of DNA was checked by amplifying the HPV infection was investigated using GP5+/GP6+ primers (forward: 5′-TTTGTTACTGTGGTAGATACTAC-3′ and reverse: 5′-GAAAAATAAACTGTAAATCATATTC-3′) by RT-PCR  to ampliHSV infection was detected using specific primers: HSV DNA polymerase forward: 5′- GTGTTGTGCCGCGGTCTCAC-3′ and reverse: 5′-GGTGAACGTCTTTTCGAACTC-3′. EBV was detected using EBV DNA polymerase forward: 5′- GGAGAAGGTCTTCTCGGCCTC-3′ and reverse: 5′-TTCAGAGAGCGAGACCCTGC-3′ , 28. Thew/v) 1-ethy-3-(3-dimethylaminopropyl) carbodimide (EDAC) solution  at room temperature for 10 min, rinsed with distilled water and placed on a mini blotter. Thirty-seven HPV type-specific 5′-amino linked oligonucleotide probes, including 13 high-risk HPV types ; 12 low-risk HPV types ; and other HPV types , were dropped onto the Biodyne C membrane through the wells of the mini blotter in parallel lines. Subsequently, biotin-labeled PCR products were added into the channels of the mini blotter perpendicular to the oligonucleotide probe lines, then hybridized and incubated with streptavidin-peroxidase-conjugate. The HPV types present were detected using chemiluminescence.HPV L1 gene fragments in HPV-positive samples were amplified using GP5/ GP6+ primers labeled with biotin and genotyped by reverse line blot hybridization (RLBH) . BiodyneP–value < 0.05 was considered statistically significant.Bivariate analysis (for comparisons of proportions) was used to investigate the association between EBV, HPV and/or HSV infection and age, number of sex partners, condom usage and HIV status of participants using SPSS software . Any Table Swab samples were obtained from each anatomical site  of 346 asymptomatic MSM participants. HPV, EBV and HSV infection were detected in all three anatomical sites Fig. . EBV infThe prevalence of high-risk HPV types were higher than of low-risk HPV in all anatomical sites Fig. . Double/The highest prevalence of double or multiple infections of any type of HPV was in the anorectum 67/152, 44.1%) followed by the urethra  and oropharynx . Infections with double and multiple HPV types were more common than with single HPV types in the anorectum , but not in the oropharynx  or urethra  . HPV infection in the anorectum was significantly associated with the 21–30 years-old group  and also the 46–60 years-old group . HSV infection in the oropharynx was mostly found in the 46–60 years-old group. EBV infection in the oropharynx and urethra was significantly higher among HIV-positive MSM than among HIV-negative MSM . Likewise, HPV infection in the anorectum was significantly associated with HIV-infected MSM . In contrast, the incidence of HSV did not differ according to HIV status. This result suggested that HIV-infected MSM might act as reservoirs for transmission of EBV and HPV.There were often significant differences between age groups in prevalence and anatomical sites, as shown in Table P = 0.035; and for the 46–60 years-old group, odds = 21.000, 95% CI = 1.777–248.103, P = 0.016. Co-infection of HIV with HPV-infected anorectum , urethra  or EBV-infected urethra  was significantly associated with an absence of condom usage. HPV infection in the oropharynx wasn’t associated with any demographic factors (data not shown). In addition, no association was found between demographic factors and EBV infection in the anorectum and oropharynx among HIV-infected and uninfected MSM (data not shown). This result demonstrated that lack of condom usage was an important factor for HPV infection in the anorectum and urethra as well as EBV infection in the urethra among HIV-positive MSM.Table Co-infection with EBV and HPV was common, especially in the anorectum 17.3%) , as shown in Additional file Co-infection of HPV with EBV or HSV in all three anatomical sites has not been reported previously. We investigated the association of EBV, HPV and/or HSV co-infection in anorectal, oropharyngeal or urethral sites with demographic factors. Interestingly, co-infection with EBV and HPV at both the anorectum and urethra was significantly associated with the 21–30 years-old group  of 346 MSM in Northeast Thailand. Demographic information was collected from participants, and especially HIV status. Several previous reports exist about the prevalence of EBV in the same anatomical sites of MSM from other countries. EBV infection was found in the anorectum of 29.6% and 32% of HIV-positive German and Swedish MSM, respectively , 31. OroMany studies have demonstrated a high prevalence of HPV infection in the anorectum, ranging from 34.8 to 65.3% –39, and In Peruvian MSM, the five most common HPV genotypes from the anorectum were 53, 6, 16, 58 and 54 . SimilarMost studies of HSV infection in MSM have reported only seroprevalence (82.5–90%) , 48. HowOur report is the first to find that EBV infection is present in anorectal, oropharyngeal and urethral sites of northeast Thai MSM at higher prevalence than are HPV and HSV. A previous study found high-risk HPV at higher prevalence (90.8%) in the anorectal canal than low-risk-HPV (73.8%), HSV-1 (7.7%), HSV-2 (16.9%) and EBV (7.7%) among HIV-positive Brazilian men . This agHPV was also the most common virus found in anal swabs (44%), followed by semen (7.1%) and pharyngeal swabs (3.8%) in American MSM , consistIt is well known that HIV-infected MSM have an increased risk of sexually transmitted infections (STIs) and STDs . In addiA few studies have reported co-infection of EBV, HPV and/or HSV in asymptomatic MSM. For example, high-risk HPV/HSV-2 co-infections were present in the anorectum of 55% of Brazilian MSM. Corresponding values for other combinations in that study were 27% (high-risk HPV/low-risk HPV/EBV), 9% (high-risk HPV/low-risk HPV/HSV2/EBV) and 9% (high-risk HPV/low-risk HPV/HSV-1/HSV-2/EBV) . HPV andNeisseria gonorrhea detection compared with urine sample [Different results in prevalence in anatomical sites of three viruses and in the association with any risk factors among various countries may depend on the technique used, site and equipment of sample collection, sample size, sexual behavior, nationality, geography, and particularly questionnaire pattern, etc. (such as a self-report or community based). The strength of our study is that 1) we used swab sample in urethra because this can increase sensitivity of e sample  whereas e sample , 36; adde sample . This liHere, we also investigated HIV status among EBV, HPV or HSV-positive MSM. We found that HPV infection of the anorectum increased with age among HIV-infected MSM Table . In addiEBV and HPV were detected in asymptomatic MSM in Northeast Thailand and were found more frequently than HSV in all three anatomical sites . Oncogenic high-risk HPV genotypes were highly prevalent at these three sites in this population. Therefore, molecular detection and HPV genotyping may be useful for identifying these viruses and facilitating interventions to limit their spread among MSM, especially HIV-infected MSM.Additional file 1:Table S1. Single and double/multiple infections of different HPV types in the anorectum, oropharynx and urethra. (DOCX 15 kb) (DOCX 16 kb)Additional file 2:Table S2. The association of demographic factors and co-infection of EBV, HPV and/or HSV in the anorectal site. (DOCX 16 kb) (DOC 44 kb)Additional file 3:Table S3. The association of demographic factors and co-infection of EBV, HPV and/or HSV in the urethral site. (DOCX 16 kb) (DOC 43 kb)Additional file 4:Table S4. The association of demographic factors and co-infection of EBV, HPV and/or HSV in the oropharyngeal site. (DOCX 16 kb) (DOC 45 kb)


Analysis revealed that high-skilled players had higher sensitivity than low-skilled players and this was consistent across all spatial occlusion conditions. Low-skilled players were more biased toward judging actions to be genuine. Receiver Operating Characteristic (ROC) curves revealed that accuracy on deceptive trials in the lower body and full body conditions most accurately classified participants as high-skilled or low-skilled. The results highlight the value of using signal detection analysis in studies of deceptive actions. They suggest that information from the lower body or upper body was sufficient for differentiating genuine and deceptive actions and that global information concurrently derived from these sources was not necessary to support the expert advantage.The ability to differentiate genuine and deceptive actions was examined using a combination of spatial and temporal occlusion to examine sensitivity to lower body, upper body, and full body sources of visual information. High-skilled and low-skilled association football players judged whether a player genuinely intended to take the ball to the participant’s left or right or intended to step over the ball then take it in the other direction. Signal detection analysis was used to calculate measures of sensitivity ( The ability to judge the intentions of an opponent using advance visual information confers an advantage in many competitive sport encounters . A potenAn important question in the perception of deceptive intent concerns the information sources used by skilled and less-skilled performers to discriminate between genuine and deceptive actions. Researchers have shown that experts use information from distributed sources to anticipate action outcomes . For exaboth the lower and upper body so implies that skilled judgments of deceptive intent rely on global processing rather than enhanced local processing of specific sources. If this is the case then the ability to differentiate genuine and deceptive actions should be attenuated when this information is unavailable, for example when only the lower body or upper body is visible.Instructions for executing common deceptive actions such as the football stepover and rugby sidestep refer to movements of the lower and upper body. To perform sidesteps, expert coaches instruct players to “step wide with the outside leg at the same time leaning your body weight directly over the top of that foot… drive off the outside leg back inside” , p. 36. The aim of the present study is to test whether concurrent use of lower and upper body sources of information is necessary for judging deceptive intent in a common deceptive action: the football stepover. To address this question, high-skilled and recreational football players judged the direction an opponent would take the ball under three levels of spatial occlusion in which (1) the whole player, (2) only the player’s upper body, and (3) only their lower body, were visible. To ensure results could be attributed to player motion, full-video and point-light tests were constructed. Point-light displays present key joint centers against a dark background and were developed by both the proportion of correct responses for genuine trials and the proportion of ‘correct rejections’ in deceptive trials. A second limitation of analyzing genuine and deceptive trials separately is that differences in accuracy might reflect different biases toward judging an action to be genuine or deceptive. For example, higher-skilled performers might obtain higher accuracy scores than lesser-skilled performers on deceptive actions because they are more biased toward judging actions to be deceptive, perhaps born of greater exposure to deceptive actions in competitive play. Analysis originating in signal detection theory  is genuine  or deceptive . This ability is captured by a measure of sensitivity that is derived from n theory  enables actions such as the football stepover, in which the goal of the actor is to ‘fool’ an observer into judging an action to be genuine when it is in fact deceptive. In these tasks the extent to which participant responses are biased toward judging the action to be genuine are an additional measure of the effectiveness of deception and can be assessed at different time points as the action unfolds.To the best of our knowledge, the only study to date to employ signal detection analysis in judgments of deceptive actions in sport was conducted by Another feature of signal detection analysis is that one can quantify the degree to which test results differentiate participants on a binary classifier such as membership of a high-skilled and low-skilled group. To do this, Receiver Operating Characteristic (ROC) curves are plotted that depict the rate of true positive identifications  against the rate of false positives  as one progresses through the list of ranked test scores. The area under the curve (AUC) measures the degree to which the test ‘diagnoses’ group membership. This and associated ROC analyses that compare the rates of true positives and false positives for different decision criteria have been extensively applied in a diverse range of fields including medical diagnosis and eye witness identification .d′) and response bias (c). ‘Hits’ were defined as correct responses on genuine trials and ‘false alarms’ were defined as incorrect responses on deceptive trials. In the analysis that follows, a d′ value of 0 indicates an inability to distinguish between genuine and deceptive actions, which can result from any proportion of ‘hits’ on genuine trials as long as it is matched by the same proportion of ‘false alarms’ on deceptive trials. When the proportion of ‘hits’ is greater than the proportion of ‘false alarms’ this will yield positive values of d′; conversely, fewer ‘hits’ on genuine trials than ‘false alarms’ on deceptive trials will result in negative d′ values. In regard to bias, negative values of c reflect a bias toward judging actions to be genuine and positive values of c reflect a bias toward judging an action to be deceptive. Last, we conducted ROC analysis to examine which elements of the test best differentiated high-skilled and low-skilled participants.In the present study, we used response accuracy scores to calculate measures of  sensitivity (d′), we hypothesize that (1) sensitivity will be greater for high-skilled players than low-skilled players, reflecting their greater ability to distinguish between genuine and deceptive actions. Consistent with the global processing hypothesis we further hypothesize that (2) sensitivity, and (3) the difference in sensitivity between high-skilled and low-skilled players, will be greater when the whole body is visible than when the upper and lower body are seen in isolation. In regard to the measure of response bias (c), we hypothesize that (4) low-skilled players will have a stronger bias toward judging actions to be genuine than high-skilled players. We further hypothesize that (5) bias will be stronger, and (6) the difference in bias between high-skilled and low-skilled players will be greater, in the whole body condition than in the lower body and upper body conditions. In regard to the ROC analysis, we hypothesize that (7) group membership will be better ‘diagnosed’ by judgment accuracy on deceptive trials than genuine trials, and that (8) the AUC will be greatest for the deceptive trials in the full body condition.In regard to the measure of sensitivity  participated in the experiment. High-skilled participants were competing in the Football Association Women’s Super League at the time of the experiment and had a mean of 12.3 years (SD = 3.8) of competitive football experience. Low-skilled participants had a mean of 5.1 years (SD = 3.5) of recreational football experience. High-skilled and low-skilled participants were randomly allocated to the ‘full video’ and ‘point-light’ test formats. Power analysis was conducted in G∗Power , alpha set at 0.05, and power set at 0.80, the mixed-factor ANOVA calculation yielded a recommended total sample size of 40 for the interaction between group (four levels) and spatial occlusion (three levels), and of 36 for the interaction between group and time of occlusion (four levels).Forty-eight female football players  mounted on a tripod at a height of 1.4 m recording at 25 frames per second. For each video clip, the player ran from a starting position located 11.5 m from the video camera and was instructed to change direction in the region of a marker placed 5.3 m from the point directly beneath the video camera lens. At this point, the player moved toward one of two training cones placed at an angle of 45 degrees to the left and right of the initial approach. In the non-deceptive condition, the player was instructed to change direction to the left or right of the camera, while in the deceptive condition the player was instructed to perform a ‘stepover’ by moving their lead foot in front of and across the ball before taking the ball in the opposite direction. The task for participants was to judge whether the approaching player intended to take the ball to their left or right, which required them to judge whether the initial intention conveyed by a movement to the left or right was genuine or deceptive. Participants were told that there would be an equal number of action outcomes to the left and right and an equal number of genuine and deceptive actions.To select the highest quality actions for the test, three UEFA ‘B’ License football coaches rated each video clip for speed, straightness of approach, and technical execution. The two highest-rated clips for each player changing direction to the left and right with and without a stepover were included in the final test. This generated 16 unique clips, which were then digitally edited using Pinnacle Studio and Jasc Paint Shop Pro software to create three levels of spatial occlusion and four times of occlusion. For simplicity, the three levels of spatial occlusion refer to the information sources that were visible: (A) full body: original video with no areas removed, (B) lower body: each player’s head, arms, hands and torso above the hips were removed, and (C) upper body: each player’s legs, feet and torso from the hips down were removed.To create the spatial occlusion conditions, each frame of the 16 video sequences was edited by cloning a background image of the experiment set up to ‘paint over’ the relevant region of the player. The edited images from consecutive frames were then recombined to create a new video clip. The resulting 48 video stimuli were cropped at four time points relative to the frame before the foot made contact with or passed in front of the ball: t1 (−240 ms), t2 (−120 ms), t3 (0 ms), and t4 (+120 ms)  point-light representations consisting of 19 small disk markers corresponding to principal body joints and extremities . In addition, the ball was represented in each frame by a white disk of the same circumference such that the looming effect was retained as the player approached the camera. The 10 markers corresponding to the hips, knees, ankles, and feet of the player were retained to create the ‘lower body’ stimuli. The remaining nine markers were retained to create the ‘upper body’ stimuli . To familiarize participants with the test format and response requirements, they were shown 16 practice trials in their designated display format (full video or point-light) comprised of eight video clips from each player. These contained examples of each level of deception, spatial occlusion, and temporal occlusion and were generated from different clips to those used in the test.d′) and bias (c), which were calculated for each group in each combination of spatial and temporal occlusion. To calculate d′, the proportions of correct responses on genuine trials (‘hits’) and incorrect responses on deceptive trials  were converted to z-scores. The values for deceptive trials were then subtracted from the values for genuine trials. To calculate c, the z-scores for deceptive trials were added to those for genuine trials and multiplied by −0.5. To account for the possibility of infinite z-scores, values of 0 and 1 were replaced with 1/2n and (n−0.5) ÷ n, respectively, where n is the number of trials in the relevant condition  rather than one of deceptive intent (genuine or deceptive) the latter is implicit in the former so is subject to analysis for sensitivity and bias. Specifically, a correct response to a genuine action (whether to the left or right) implies a correct judgment that the action was genuine (a ‘hit’). An incorrect response to a deceptive action  implies an incorrect judgment that the action was genuine when it was in fact deceptive . Conversely, an incorrect response to a genuine action (whether to the left or right) implies an incorrect judgment that the action was deceptive (a ‘miss’). Last, a correct response to a deceptive action  implies a correct judgment that the action was deceptive (a ‘correct rejection’).d′ and c variables, with expertise and test display entered as between-participant factors, and spatial and temporal occlusion serving as within-participant factors. Alpha was set at 0.05 for all analyses and partial eta squared  × 2  × 3  × 4  mixed-factor analysis of variance (ANOVA) was conducted for the F = 24.26, p < 0.001, M = 0.68, SE = 0.01) and point-light  tests, F = 3.27, p = 0.08, The combined accuracy data across the two tests for non-deceptive and deceptive trials in the three spatial occlusion conditions are displayed in Figure d′ = 1.11, SE = 0.04) than for the point-light test ; however, the difference was non-significant, F = 3.97, p = 0.053, F = 0.30, p = 0.59. Consistent with Hypothesis 1, analysis of sensitivity (d′) revealed that the ability to distinguish genuine and deceptive actions was substantially greater in high-skilled players  than low-skilled players , F = 175.73, p < 0.001, F = 296.38, p < 0.001, F = 7.28, p = 0.001, Overall discriminability was slightly higher for the full-video test  than the upper body condition , F = 16.26, p < 0.001, d′ = 0.98, SE = 0.04), F = 21.91, p < 0.001, F = 11.79, p < 0.001, d′ = 1.35, SE = 0.11) and upper body  conditions than in the lower body condition , and that sensitivity increased more in the full body and lower body conditions than the upper body condition after the foot had been seen contacting or passing in front of the ball  = 1.10, p = 0.34, Consistent with Hypothesis 2, sensitivity was higher in the full body condition  had a stronger bias toward judging actions to be genuine than the high-skilled players , F = 22.86, p < 0.001, F = 7.87, p < 0.001, Consistent with Hypothesis 4, analysis of response bias revealed that the low-skilled players  = 1.35, p = 0.26, F = 17.12, p < 0.001, The hypotheses that response bias would be strongest and the expertise effect greatest in the full body condition were not supported. As can be seen in Figure To determine the elements of the test that best categorized high-skilled and low-skilled performers, we conducted ROC analyses on the accuracy scores for genuine and deceptive trials in each spatial occlusion condition at each of the four times of occlusion. The AUC values are displayed in Table Expertise in perceiving deceptive intent has been linked to an ability to attend to ‘honest’ signals, such as center of mass, while ignoring deceptive signals . This fid′. This contrasts with the overall performance of low-skilled participants, who made fewer correct responses to genuine actions than incorrect responses to deceptive actions on trials occluded at t1 and t2, resulting in negative values of d′. Negative sensitivity values are uncommon in most of the tasks in which signal detection analysis is used; however, they can be accounted for by use of exaggerated movements to convey a false intention . Averaged across all spatial occlusion conditions they made proportionately more correct responses to genuine actions (‘hits’) than they made incorrect responses to deceptive actions , which yielded positive values of ntention . Exaggerntention  so when ntention . Collectntention .The analysis also revealed a clear pattern of results with respect to response bias. There was support for the hypothesis that low-skilled performers would show a stronger bias toward judging actions to be genuine than would high-skilled performers. Moreover, the strength of this bias in the low-skilled group increased from t1 to t2, and in both groups weakened considerably after the player’s foot contacted or passed in front of the ball. Combined with the instructions participants received regarding the equal number of genuine and deceptive trials, this implies that the main source of bias was perceptual, which reflects the goal of the actor in conveying a false intention. Low-skilled participants were fooled more frequently so made more ‘false alarm’ responses, peaking at trials occluded at t2 and decreasing considerably after veridical information became available. High-skilled players were fooled less frequently and bias peaked earlier in the action sequence (t1), which supports the interpretation of earlier differentiation of genuine and deceptive actions.In regard to the sources of information that support accurate judgments of deceptive intent, high-skilled players had the same advantage in sensitivity over low-skilled participants in the full body, lower body, and upper body occlusion conditions  bias toward judging actions to be genuine. Last, ROC analysis revealed that, within the context of a task that contains both genuine and deceptive actions, judgment accuracy for deceptive actions strongly differentiates high-skilled and low-skilled performers. How information from different sources is used to resolve genuine and deceptive actions, and the extent to which the present results relate to esponses  while otesponses . In addiesponses . How sucThis study was carried out in accordance with the recommendations of Brunel University London Institutional Ethics Committee with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki. The protocol was approved by the Brunel University London Institutional Ethics Committee.RJ led design of the study, analysis, and writing of the paper. HB contributed to the design of the study and drafting of the paper. KA and BA contributed to the design of the study and writing of the paper.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Post hoc mathematical modeling predicted a durability ≥50 years for anti-HPV-16 and anti-HPV-18. For the non-vaccine humoral type response, all initially seronegative subjects had seroconverted at M7, with anti-HPV-31 GMT of 2030.5 EU/mL (95% CI: 1766.2–2334.4) and anti-HPV-45 GMT of 2300.8 EU/mL (95% CI: 2036.8–2599.0). At M120, 87.7% and 85.1% remained seropositive for anti-HPV-31 with GMT of 242.9 EU/mL (95% CI: 201.4–293.0) and anti-HPV-45 with GMT of 204.7 EU/mL (95% CI: 170.0–246.6). During the 10-year follow-up, no SAEs or abnormal pregnancy outcomes were causally related to vaccination. Three doses of the AS04-HPV-16/18 vaccine induced high and sustained antibody response against HPV-16,18,31 and 45 in girls aged 10–14 years during the 10-year follow-up, with an acceptable long-term safety profile.This study assessed long-term immunogenicity and safety following 3 doses of AS04-adjuvanted human papillomavirus (HPV)-16/18 L1 virus-like particle (VLP) vaccine in females 10–14 years old. Girls included in the immunogenicity subset in the primary controlled, observer-blinded, randomized study (NCT00196924) who received 3 doses were invited for a 10-year follow-up (NCT00316706 and NCT00877877). Serum antibody responses against HPV-16/18 (vaccine types) and HPV-31/45 (non-vaccine types) were measured by enzyme-linked immunosorbent assay (ELISA) using type-specific VLP as coating antigens. Serious adverse events (SAEs) and pregnancy information were recorded. At Month (M) 120, all subjects  were seropositive for anti-HPV-16/18 antibodies. Geometric mean titers (GMTs) were 1589.9 ELISA Units [EU]/mL  for anti-HPV-16 and 597.2 EU/mL (95% CI: 541.7–658.5) for anti-HPV-18 in subjects seronegative at baseline for the type analyzed.  It contains L1 recombinant proteins from HPV-16 and HPV-18, each assembled as virus-like particles and adjuvanted with AS04. The AS04-HPV-16/18 vaccine was shown to be highly efficacious in protecting against HPV-16 and HPV-18 infections and related pre-cancerous cervical lesions as well as protective against some non-vaccine oncogenic HPV types in adolescents and young adults aged 15–25 years.14 In this age population, the vaccine-induced immune response was shown to persist at a substantial level up to at least 10 years.17The AS04-adjuvanted HPV-16/18 vaccine , the follow-up of which lasted for 10 years (NCT00316706 and NCT00877877). Previous results showed that the vaccine was highly immunogenic and well tolerated, and the high immune response persisted up to 6 years after primary vaccination.19 1,035 adolescent girls received at least one dose of the HPV-16/18 AS04-adjuvanted vaccine. Of these, a total of 625 (60.4%) participants who were included in the immunogenicity subset and enrolled from 26 centers in Taiwan, Germany, Honduras, Panama and Colombia participated in the 4-year follow-up (NCT00316706).20 All 625 subjects were invited, and of these, 557 (53.8%) subjects participated in this extended follow-up study (NCT00877877) and were included in the total vaccinated cohort (TVC). Four hundred and ninety-five (47.8%) participants completed the study up to 120 months. The mean age of these 495 subjects at Month 120 was 22.0 years (standard deviation [SD]: ±1.4); 46.1% were Hispanic, 32.9% were Caucasian/White and 20.0% were of Asian origin. The demographic characteristics of the participants who completed the 120-month follow-up study were similar to those of the participants enrolled in the primary study.19In the primary study (NCT00196924),At Month 120, 418 subjects were included in the according-to-protocol (ATP) cohort for immunogenicity and 77 subjects were eliminated for ATP analysis for various reasons .10.1080/post hoc analysis on the humoral response against the non-vaccine type HPV-31 and HPV-45, 150 subjects with residual serum volume greater than 300 µL were randomly selected from the ATP cohort.For the Among the 418 subjects who were included in the ATP immunogenicity cohort, anti-HPV-16 antibody data and anti-HPV-18 antibody data were available for 416 and 415 subjects, respectively. At the baseline, 393 (94.5%) out of the 416 subjects were seronegative for anti-HPV-16 antibodies and 395 (95.2%) out of the 415 subjects were seronegative for anti-HPV-18 antibodies. At Month 120 post vaccination, all subjects who were included in the ATP immunogenicity cohort were still seropositive for anti-HPV-16 and anti-HPV-18 antibodies. The geometric mean titer (GMT) values at Month 120 of initially seronegative subjects were 1,589.9 enzyme-linked immunosorbent assay unit [EU]/mL  for HPV-16 and 597.2 EU/mL (95% CI: 541.7–658.5) for HPV-18. The GMT values at Month 120 of initially seropositive subjects were 1,950.1 EU/mL  for HPV-16 and 866.0 EU/mL  for HPV-18. The Month 120 antibody GMTs between the initially seronegative and seropositive subjects were not significantly different as the 95% CIs were largely overlapping for both anti-HPV-16 and -18.21 The HPV-16 and HPV-18 antibody titers at Month 120 were 3.8-fold [95% CI: 3.1–4.6] and 2.5-fold [95% CI: 2.0–3.1] higher, respectively, than those measured 9.4 years after vaccination in subjects vaccinated at the ages of 15–25 years (NCT00518336) .21 The H00518336).1510.108post hoc analysis on the serum antibody response against the non-vaccine type HPV-31 and HPV-45, 150 subjects with residual serum volume greater than 300 µL were randomly selected from the ATP cohort. Among them, 138 (92%) were seronegative for anti-HPV-31 antibodies and 141 (94%) were seronegative for anti-HPV-45 antibodies at the baseline. All of those who were seronegative for the type analyzed at baseline had seroconverted for HPV-31 and HPV-45 antibodies at Month 7; at Month 120, 87.7% and 85.1% remained seropositive for HPV-31 and HPV-45 antibodies, respectively  reported 155 serious adverse events (SAEs). One case of SAE  was reported 4 days after the first dose of vaccination. Four cases of SAE were reported between the second and third dose of vaccination: injury with time-to-onset (TTO) of 7 days, gunshot wound (TTO: 41 days), bacterial pneumonia (TTO: 42 days) and abdominal pain (TTO: 54 days). Five cases of SAE were reported within 6 months after the third dose of vaccination: dehydration, gastroenteritis and upper respiratory tract infection developed in one subject (TTO: 15 days), herpangina (TTO: 16 days) and syncope (TTO: 26 days). One hundred forty-five cases of SAE were reported during the follow-up period of Years 2–10; the most commonly reported SAE during this period was appendicitis (n = 9). None of these 155 SAEs was considered causally related to vaccination and none of them had a fatal outcome. No participants withdrew from the study because of an adverse event (AE)/SAE.Among the 557 subjects who participated in the 10-year follow-up, a total of 161 pregnancies were reported by 128 subjects. All pregnancies started at least one year after the third dose of HPV-16/18 vaccination. Among these pregnancies, 134 (83.2%) pregnancies resulted in live infants with no congenital anomaly, 2 pregnancies resulted in live infants with congenital anomalies , 1 pregnancy resulted in stillbirth, 11 pregnancies resulted in spontaneous abortions , and 5 pregnancies were terminated electively , 2 were ectopic pregnancies, and 6 pregnancies were either ongoing or lost to follow-up at the end of the study. None of the abnormal pregnancy outcomes including the congenital anomalies was considered causally related to the vaccination by the investigators.Because of the prophylactic nature of HPV vaccines, the primary target populations in many national immunization programs are young adolescent girls. To our knowledge, this is the longest follow-up study in girls aged 10–14 years who received three doses of the AS04-HPV-16/18 vaccine.23Ten years after the initial vaccination, all subjects remained seropositive for anti-HPV-16 and anti-HPV-18 antibodies. The kinetic profiles of anti-HPV-16 and anti-HPV-18 antibody titer, as well as the non-vaccine type HPV-31 and HPV-45 antibody titer, were similar: a peak response in antibody GMTs one month after administration of Dose 3 (i.e. Month 7), followed by a decline from Month 18 to Month 24 and thereafter reaching a plateau level till Month 120. Such antibody kinetics were also observed in other age populations.15 There is no established immune correlate of protection for prophylactic HPV vaccines. However, the sustained high antibody levels are particularly relevant in supporting the long-lasting protection provided by HPV-vaccination that mainly targets young adolescents, with the intent of rendering protection at the time of exposure.24The anti-HPV-16 and anti-HPV-18 antibody plateau levels in young girls aged 10–14 years at first vaccination according to a 3-dose schedule remained several fold higher than the plateau levels observed in young women aged 15–25 years, the age population in which prophylactic vaccine efficacy was demonstrated against high-grade lesions.25 In a Phase III clinical trial setting, efficacy against non-vaccine types HPV-31 and HPV-45 has been observed up to 7 years in women vaccinated at 26 years of age and above.26 In two studies investigating the 2-dose schedule, cross-reactivity of the vaccine against HPV-31/45 was found similar after 2 doses (girls aged 9–14 years) or 3 doses (young women aged 15–25 years) and lasted for at least 5 years.27 Recently, results from observational studies in Scotland and in the Netherlands reported vaccine effectiveness of the AS04-HPV-16/18 vaccine against HPV-31/33/45 and HPV-31/35/45/52, respectively.29 The sustained immune response that we observed in this study against HPV-31/45 is aligned with these real-life data that are of crucial importance to assess the potential health impact of AS04-HPV16/18 vaccination programs.Aside from its high efficacy against persistent HPV-16/18 infections, results from AS04-HPV-16/18 vaccine trials showed a protective effect of the vaccine against non-vaccine types.30 These observations evidence the immune memory against HPV-16/18/31/45 induced by the AS04-HPV-16/18 vaccination.Results from a vaccine trial conducted in North America to assess the immune memory in women who received three doses of the AS04-HPV-16/18 vaccine 7 years earlier showed an increase in the antibody titers of vaccine types (HPV-16/18) as well as non-vaccine types (HPV-31/45) following administration of the challenge dose.18 At the end of the 10-year follow-up, we found that the observed antibody titers were lower than those predicted by the modified power-law model but higher than those predicted by the piecewise model (data not shown). In this report, we introduced a fourth break point (i.e. Month 48) in the piecewise model, as such the predicting period could be extended to 50 years. To validate this piecewise modeling with four break points , we performed the model prediction of 10-year antibody kinetics using the 6-year observed data. The predicted antibody kinetic curves fitted well with the observed 10-year antibody kinetic curves (see supplementary section), suggesting that this piecewise modeling with four break points  provided a good prediction. With this model, it has been predicted that the serum anti-HPV-16 and anti-HPV-18 antibody response induced by HPV-16/18 AS04-adjuvanted vaccine remains substantially above the antibody response induced by the natural infection among the young adolescent population for at least 50 years. The durability of the anti-HPV-16 and anti-HPV-18 antibodies among the majority of this population would last for approximately 70 years. These predictions are informative until long-term observational data are available. Due to the lack of serum samples at important time points Month 12 and Month 48, necessary for building the model, the prediction of non-vaccine type anti-31 and anti-45 antibody response beyond 10 years was not performed.Long-lasting protection is crucial as women are at risk of HPV infection throughout their active sexual life. Conducting a follow-up for several decades in a clinical trial setting is operationally unfeasible as patient retention in clinical trials cannot be maintained over such a long period due to reasons including subjects’ relocation and loss of interest. Therefore, we adopted mathematic models to predict the long-term persistence of anti-HPV-16 and anti-HPV-18 antibodies. Previously, we had performed prediction on antibody persistence using the observed 6-year data, with modified power-law model and piecewise model.35 These observations are in line with results from pooled analyses and post-marketing studies conducted so far to assess pregnancy outcomes after exposure to AS04-HPV-16/18 vaccine.39The vaccine was generally well tolerated with a clinically acceptable safety profile during the 10 years of follow-up. There were neither SAEs reported to be causally related to the vaccination nor fatalities. During the entire ten-year follow-up, no adverse pregnancy outcome was considered as related to the vaccine by the investigators. Although a direct comparison was difficult, rates of pregnancy outcomes observed in this trial were found to be close to the reported rates available in the literature.41 Studies following vaccinated individuals for 6–12 years suggested that 3-dose HPV vaccines offer long-term protection against HPV infection and HPV-related diseases.44 However, whether the duration of protection can cover the entire sexually active life expectancy and whether a boost dose is required remained to be studied. As a matter of fact, a previous study demonstrated that the 3-dose regimens in young adolescent girls could induce an immune response at least two folds higher than those in 15–25 years-old females,The study has some limitations. Notably, the study assessed the 3-dose vaccination schedule, while current vaccination programs in most countries recommended the 2-dose schedule in adolescent girls aged younger than 15 years. The reduced dose schedule from 3-dose to 2-dose for the young adolescent population was based on the evidence that the 2-dose regimens in young adolescent girls showed an equivalent immune response to the 3-dose regimen in 15–25 years old females in terms of magnitude and durability of the immune response.In conclusion, this study showed that 3 doses of the HPV-16/18 AS04-adjuvanted vaccine induced high and sustained levels of antibodies against HPV-16, 18, 31 and 45 with an acceptable safety profile for at least 10 years after initial vaccination in young adolescent girls aged 10–14 years. The novel prediction of immunogenicity persistence for the vaccine against HPV-16 and -18 for at least 50 years is of significance. Even though no correlate of protection was established, such level of antibody titers may be indicative of protection against HPV-16/18 for a woman up to her sixties and potentially lifelong, should she have received the HPV vaccine in her early teens, suggesting that a subsequent booster dose may not be required. These findings support the feasibility of organized vaccination programs in young adolescents prior to their sexual debut and first HPV exposure.Cervarix, GSK) or a hepatitis A virus control vaccine  at Months 0,1 and 6. Dosage and route of administration of both vaccines can be found in the primary publication.19 The subjects who received 3 doses of the HPV-16/18 vaccine during the initial study (from June 2004 to August 2005) were included in the immunogenicity subset  and had participated in the 4-year follow-up  were invited to participate in the current long-term follow-up study (NCT00877877) for up to 10 years after initial vaccination (from May 2009 to January 2015).The primary randomized controlled, observer-blinded study (NCT00196924) included female subjects aged 10–14 years at the time of first vaccination who received three doses of the AS04-adjuvanted HPV-16/18 vaccine  of an HPV vaccine during the follow-up period.www.clinicalstudydatarequest.com.The guidelines of the Declaration of Helsinki, the International Conference on Harmonization-Good Clinical Practices were followed while conducting the study. The study was in accordance with the regulatory requirements of all countries in which the study was conducted, and all subjects provided written informed consents before participating. For subjects below the legal age of consent, written informed consent was obtained from parents or legal representatives as well as assent from the subjects themselves. Subjects were re-consented when having reached the legal age of consent. The study protocol and amendment, as well as informed consent and assent, were reviewed and approved by the independent ethics committee or institutional review board of each study center. Anonymized individual participant data and study documents can be requested for further research from 45 Seropositivity was defined as antibody titers ≥8 EU/mL for anti-HPV-16 or ≥7 EU/mL for anti-HPV-18 between Year 0 and Year 7. From Year 8 onwards, the lower limit of quantification of the assays was reviewed, and a new seropositivity cut-off defined as antibody titers ≥19 EU/mL or ≥18 EU/mL for anti-HPV-16 and anti-HPV-18, respectively, was used.26 These changes in the assay had no impact on the overall analysis since the antibody titers were higher than both the old and new cut-off values at all time points for all subjects evaluated.In this 10-year follow-up, blood samples were collected at baseline, Months 7, 12, 18, 24, 36, 48, 60, 72, 84, 96, 108, and 120. Antibody titers for anti-HPV-16 and anti-HPV-18 were measured in serum using enzyme-linked immunosorbent assay (ELISA) with type-specific L1 virus-like particles as coating antigen that was produced on a Hi-5 cell line using a baculovirus expression vector system.A post hoc analysis was performed to measure anti-HPV-31 and anti-HPV-45 antibody titers in serum at baseline, at Months 7, 24, 72, and 120 by ELISA using in-house type-specific L1 virus-like particles produced from baculovirus expression system.46 Seropositivity was defined as antibody titers ≥59 EU/mL for both anti-HPV-31 and for anti-HPV-45.Statistical analyses were performed using the Statistical Analysis Systems (SAS) version 9.2. Safety analyses were conducted on the TVC, which included all participants who had received 3 doses of the HPV-16/18 AS04-adjuvanted vaccine in the primary study NCT00196924 and whose data were available for at least one study visit in NCT00196924, NCT00316706, and NCT00877877.15 the population in which the vaccine efficacy had been demonstrated, as well as the descriptive comparison with the antibody levels elicited in subjects having mounted a detectable immune response after natural infection (NCT00122681).21The primary immunogenicity analyses were performed on the ATP cohorts for immunogenicity at different time-points that included subjects who met all eligibility criteria for enrollment without violation of the protocols during the follow-up and for whom results were available. A supplementary immunogenicity analysis was performed on the TVC. Seropositivity rates and GMTs were calculated with exact 95% CI for HPV type-specific antibodies. GMT calculations were performed by taking the anti-log of the mean of the log titer transformations. The primary endpoint was the assessment of serum anti-HPV-16 and anti-HPV-18 antibody titers and seropositivity rates in the ATP cohort up to Month 120. The secondary endpoint included the descriptive comparison of anti-HPV-16/18 antibody titers detected in young adolescents vaccinated at the ages of 10–14 years in this study with those who were vaccinated at the ages of 15–25 years (NCT00518336),post hoc analysis assessed the humoral response against the non-vaccine type HPV-31 and HPV-45, i.e. serum anti-HPV-31 and anti-HPV-45 antibody titers and seropositivity rates in a subset of subjects from the HPV group at baseline, at Months 7, 24, 72, and 120. Timepoints were selected to allow building a kinetic profile of the immune response. Samples with available volume greater than 300 µL from subjects having agreed to the future use of their samples were randomly selected to account for all participating countries.A Post hoc mathematical modeling evaluated the durability of vaccine-induced immune response via two different mixed-effects models: piecewise and modified power-law. The piecewise model used a linear function on the logarithmic scale in which the data were fitted on four non-overlapping time intervals  that corresponded to the observed decay of humoral antibodies. The previous modeling with 6-year data included three break points  in piecewise modeling that predicted population antibody responses above natural infection antibody level up to approximately 20 years.18 As our current results provided data for up to 10 years, one more piece or break point was defined for the piecewise model considering the duration for up to 50 years. The selection of this additional break point, i.e. Month 48, was based on the Akaike Information Criteria for the whole model .47 The modified power-law method that estimated the antibody decay over time after vaccination was based on the dynamic populations of B-cells (activated and memory B-cells) that account for the long-term persistence and antibody plateau. The piecewise and modified power-law models were fitted using MIXED and NLMIXED statistical analyses system procedures, respectively.SAEs reported during the entire ten-year follow-up period (Month 0 to Month 120) were recorded. Pregnancies and pregnancy outcomes were recorded during the ten-year follow-up period.


This study investigated the distribution of HPV types in Korean women and evaluated the carcinogenic risk of individual HPV types and the potential effects of HPV vaccines. A total of 4,081 HPV-positive samples between 2014 and 2017 were included. The most prevalent genotypes were HPV 16, 58, 68, and 56. Among them, HPV 16 was significantly higher in high-grade squamous intraepithelial neoplasia or worse (HSIL+ ) group. In cytologically evaluating the risk for HSIL+ by individual HPV types, HPV 16 was associated with the highest risk of HSIL+ , followed by HPV 33, 31, 52, 18, 58, 51, and 35, in descending order (OR = 3.50 [type 33] to 2.62 [type 35]). Among those types, HPV 16, 18, 31, 33, and 58 were also significantly associated with HSIL+ on histologic evaluation. The analysis of the HPV subgroups covered by the different vaccines revealed that the HPV types covered by the 9-valent vaccine had a high association with HSIL+ . Our findings highlight the different carcinogenic risks posed by the high risk HPV genotypes and the positive potential effects of the 9-valent HPV vaccine in reducing HPV-associated cervical cancer in Korea. Of the more than 200 identified HPV types2, approximately 40 infect the genital area3. Of those, 13–15 high risk (HR) HPV types are known to be carcinogenic4. According to worldwide data, HPV 16 and 18 account for more than 70% of cervical cancers, and six other types  account for an additional 20%7. However, the contribution of specific HPV types to cervical cancer differs by region, possibly because of geographic variations in HPV type-specific prevalence in different populations9. For example, the prevalence of HPV 16 and 18 is relatively low in East Asia in both cervical cancer patients and healthy women compared to the worldwide prevalence10. Therefore, it is important to understand the prevalence of specific HPV types on a population-specific basis when developing strategies to prevent cervical cancer.Human papillomaviruses (HPVs) are a well-known cause of cervical intraepithelial neoplasia (CIN) and invasive cervical cancer6, their preventive effects need to be evaluated on a regional basis.Three types of vaccines are currently available to prevent cervical cancer: 2-valent , 4-valent , and 9-valent  vaccines. The 2- and 4-valent vaccines protect against HPV 16 and 18, which are the two major carcinogenic types, and the 9-valent vaccine further protects against HPV 31, 33, 45, 52, and 58. Although these vaccines are expected to address approximately 70% and 90% of cervical cancers, respectively7. The International Agency for Research on Cancer (IARC) Working Group defined HPV types as carcinogenic if their prevalence in cancers was significantly greater than that of HPV type 6, the archetype low risk (LR) HPV type, and if they were significantly more common in cancer patients than in the general population11. Although a number of studies have reported the distribution of HPV types in cervical cancer patients or healthy women, few studies have evaluated the carcinogenic potential of individual HPV genotypes by analyzing case-controlled differences, as in the IARC definition14. Moreover, case-control studies rarely provide statistically valid results because of the low prevalence of HPV infection in the cohort population. Therefore, it could be beneficial to estimate the association between individual HPV types and cervical cancer in an HPV-positive group. In this study, we evaluated the distribution of HPV types in Korean women and estimated the carcinogenic potential of individual HPV types by considering the association between specific HPV types and cervical cancer or precancerous lesions. In addition, we evaluated the potential effects of HPV vaccines in Korea.The risk that an HPV infection will progress to cervical cancer varies according to the HPV genotype15. For our analysis, we used three subgroups based on the cytologic diagnoses: NILM, LSIL (including ASCUS and LSIL), and HSIL+ .Among women who underwent HPV genotyping at Samsung Medical Center between October 2014 and March 2017, we retrieved the anonymized records of patients with co-tested cervical cytology and HPV genotyping results. For the cytology specimens, Papanicolaou-stained liquid-based tests were performed with using a ThinPrep 5000 Processor  according to the manufacturer’s protocol. Pathologists diagnosed the cytology slides according to the 2001 Bethesda system for cervicovaginal cytology: negative for intraepithelial lesions or malignancy (NILM); atypical squamous cells of undetermined significance (ASCUS); low-grade squamous intraepithelial neoplasia (LSIL); atypical squamous cells-cannot exclude high-grade squamous intraepithelial neoplasia (ASC-H); high-grade squamous intraepithelial neoplasia (HSIL); squamous cell carcinoma (SCC); and adenocarcinoma (ADC)Of the 28,834 women with cervical cytology and HPV results, 91.5% received HPV genotyping as part of a routine health check-up, and 8.5% were referred from clinics due to abnormal cervical cytology results or other gynecologic problems. Among the 24,753 (85.8%) HPV-negative women, 0.9% had abnormal cytology results, including ASCUS (0.7%), LSIL (0.2%), ASC-H (<0.1%), and HSIL (<0.1%). Among the 4,081 HPV-positive patients, 3,242 patients had a single HPV result with a matched cytology result, and 839 patients had one or more follow-up results. We analyzed 4,081 (14.2%) HPV-positive results, including both single and initial results . Cytologic diagnoses were NILM in 72.2%, ASCUS in 6.4%, LSIL in 14.2%, ASC-H in 0.5%, HSIL in 5.9%, SCC in 0.5%, and ADC in 0.3%. The most common HPV type was HPV 16 (8.7%), followed by HPV 58 (7.8%), HPV 68 (7.6%), and HPV 56 (6.9%). The distributions of patient ages and HPV genotypes are summarized in Table Of all HPV-tested women, 5,262 (18.2%) received one or more follow-up tests. Of them, 3,745 women were HPV-negative and 1,517 patients were HPV-positive in their initial tests. Among initially HPV-positive patients, 839 patients (55.3%) were also HPV positive in their follow-up tests, whereas HPV infection of the remaining 678 patients (44.7%) had been cleared. In addition, cytologic subgroups of 209 patients (16.7%) had changed in their follow-up results , HPV 58 (7.3%), and HPV 16 (6.3%). In the LSIL group, HPV 56 was the most common HPV type (11.3%), followed by HPV 51 (8.7%), HPV 52 (7.7%), and HPV 58 and 16 (7.6%). In the HSIL+ group, HPV 16 (36.2%) was most frequently identified, followed by HPV 58 and 52 . The proportion of HR HPV infections increased significantly moving through the NILM, LSIL, and HSIL+ groups, with percentages of 53.1%, 66.0%, and 95.6%, respectively . Among the HR HPV types, HPV 16, 18, 31, 33, 35, 39, 51, 52, 56, 58, and 66 were differently distributed in the cytologic subgroups   of having HSIL+ (compared to NILM/LSIL) according to the individual HPV types. After adjusting for age and all other HPV types, HPV 16 was associated with the highest risk of HSIL+ . In addition, HPV 33, 31, 52, 18, 58, 51, and 35, in descending order, were significantly associated with an increased risk of HSIL+ (OR ranged from 3.50 [HPV 33] to 2.62 [HPV 35]). Those data are summarized in Table 16: 0.7% of NILM patients, 3.1% of ASCUS patients, 55.3% of LSIL patients, 4.8% of ASC-H patients, 89.5% of HSIL patients, and 100% of SCC and ADC patients. Among patients with HSIL+ cytology, 84.3% were histologically confirmed as HSIL+. The correlations between histology and cytology diagnoses is shown in Table Among HPV-positive patients, 596 underwent a follow-up biopsy according to the “Practice guidelines for the early detection of cervical cancer in Korea”We further analyzed the HR HPV types according to vaccine coverage. HPV 16 and 18, which are covered by all HPV vaccines, were present in 12.0% of our HPV-positive patients Table . Our anaAmong all of the women in our study cohort, the overall HPV prevalence was highest 28.4%) in the ≤34 years age group, and the prevalence tended to decrease steadily with age  covered by the 9-valent vaccine were associated with twice the risk for HSIL+ than the HR HPV types (HPV 35/39/51/56/59/66/68) not covered by the vaccine. Thus, the 9-valent vaccine could be effective at preventing cervical cancer in the Korean population. In Korea, the 2-valent and 4-valent vaccines are currently included in the national immunization program as a 2-dose schedule for 12-year old girls. The 9-valent vaccine was approved by the Ministry of Food and Drug Safety in January 2016 and can be given as a non-national immunization program vaccine. Huh 29. Because women start being infected with HR HPV when they become sexually active, and HR HPV can cause HSIL in approximately 7 years, HSIL most commonly happens to women in their early 30s30. In addition, the age-specific prevalence of CIN is attributable to the coverage of cervical cancer screening32. Because cervical cancer screening is registered as a national cancer screening program in Korea, the screened population could receive timely therapeutic intervention, allowing the prevalence of HSIL+ to decrease in the older age groups.Among HPV-positive patients, the median age was youngest in the HSIL+ group, gradually increasing in the LSIL and NILM cytology groups. The prevalence of HSIL+ peaked in the 35–44 years group and decreased with age. These findings are in line with other recent studies in Korea35, no direct comparison of these two tests has been performed, so there could be discordance between them. Instead, we compared the results of the study periods covered by the different HPV genotyping methods. Of the total 28,834 cytology/HPV co-tested women, 13,697 patients (47.5%) were tested using the DNA chip and 15,137 patients (52.5%) were tested using the GeneFinder. The prevalence of HPV was 17.5% in the first period and slightly but not significantly increased to 18.3% in the second period. The prevalence of HSIL+ was 6.6% in the first period and 5.6% in the second period, while HPV 16 was identified in 1.8% and 1.5% in the first and second periods, respectively. Although the prevalence of HSIL+ and individual HPV types did differ in the two periods, the genotyping tests were performed in different populations, making it difficult to identify any significant differences between the two methods. Nonetheless, this large-scale study identified the distribution of individual HPV types in Korean women and used risk stratification to assess the carcinogenic potential of specific HPV types. In addition, we found a high correlation between cytology and histology diagnoses, indicating that our results are reliable. This study thus provides guidance for improving the HPV-related national immunization program and management guidelines for individual HPV types.This study has some limitations. First, it is a retrospective cross-sectional study. In addition, the HPV genotyping was performed with two different methods—the HPV 9G DNA Chip Test and the GeneFinder in the first and second halves of the study period, respectively. Although both methods have been validatedAll specimens and related data were obtained with approval from the Institutional Review Board of Samsung Medical Center (SMC 2018-07-104) with a waiver of informed consent in accordance with HHS regulation 45CFR46.116(f). All methods were carried out according to the ethical standards of the institutional and national research committees and the Declaration of Helsinki.HPV genotyping was performed with an HPV 9G DNA chip  or a GeneFinder HPV Liquid Bead MicroArray Genotype kit . The HPV 9G DNA chip test was used from October 2014 to December 2015, and the GeneFinder was used from January 2016 to March 2017.34. Briefly, HPV genomic DNA was extracted from cervicovaginal cytology samples and amplified via polymerase chain reaction (PCR). The PCR product was mixed with hybridization solution and loaded on the HPV 9G DNA chip. The DNA chip was then hybridized and washed at room temperature (25 °C). The final product was automatically scanned and analyzed.The HPV 9G DNA chip detects HPV genotypes via microarray, and the test was performed according to the manufacturer’s protocol36. After HPV genomic DNA was extracted, the specimen was mixed with HPV type-specific polystyrene microspheres dyed with specific intensities of fluorophores. After hybridization and PCR amplification, the microspheres were streamed using Luminex technology . HPV genotypes were detected by a Luminex analyzer based on a flow cytometry method.The GeneFinder is a microsphere bead–based test that is highly specific and sensitive for detecting HPV genotypes11, are regarded as HR HPV, whereas HPV 6, 11, 34, 40, and 42 are regarded as LR HPV. If patients had an HPV type identified by one method but not the other, the HPV type was categorized as “other.”The HPV 9G DNA chip detects 19 HPV types  and screens for 19 other types  without specific typing. The GeneFinder detects 32 HPV types . We analyzed the 19 HPV types  detected by both tests. Among them, 14 HPV types , including IARC Groups 1 and 2A2 test or Fisher’s exact test was used to evaluate the statistical significance of differences in categorical variables among groups. Post-hoc test was performed using Tukey’s Honestly Significant Difference test, and p-values from multiple comparisons were corrected by the Bonferroni method. Age was additionally analyzed as a continuous variable using the Kruskal-Wallis test followed by Dunn’s post-hoc test. To assess the association of HPV subtypes with HSIL+, we performed logistic regressions and calculated the OR and 95% CI. For HPV types, the OR was defined as the ratio between the odds of being in the HSIL+ group in the presence of an individual HPV type and the odds of being in the HSIL+ group in the absence of an individual HPV type. The results were visualized by forest plot using the SGPLOT procedure. For all analyses, p < 0.05 was considered statistically significant, and all analyses were two-sided. Data were analyzed using SAS version 9.4 .Patient ages were stratified into five subgroups: ≤34 years, 35–44 years, 45–54 years, 55–64 years, and ≥65 years. A χSupplementary Figure S1-S2, Table S1-S3


Mental health (MH) disorders are common among skilled nursing facility (SNF) residents and may inhibit rehabilitation goals. Moreover, discharges to the community from SNFs are periods of heightened suicide risk within the Veterans Health Administration (VHA), suggesting an urgent need for improved continuity of MH care. This paper presents results of medical records reviews indicating a potential gap in MH services at discharge from VHA SNFs. A quality improvement project (”Suicide Awareness for Veterans Exiting Community Living Centers” – SAVE-CLC), designed to address this gap, will also be discussed. Piloted in 3 sites (N = 66) in 2018, SAVE-CLC clinicians administered depression screens by phone to 47 Veterans (71%) after SNF discharge and helped connect Veterans to MH services. 24 Veterans (26%) received a second such call. Patients and caregivers expressed high satisfaction with SAVE-CLC . Implications for quality improvements in SNF care transitions will be discussed.