In populations with high rates of human immunodeficiency virus (HIV)-coinfection, the nature of the relationship between human papillomavirus (HPV)-16 and -18  antibodies and cervical cancer is still uncertain. We measured the association between seropositivity to HPV  proteins and cervical cancer among black South African women with and without HIV co-infection.We used questionnaire data and serum collected from consecutively recruited patients with a newly diagnosed cancer from the Johannesburg Cancer Study from 1346 cervical cancer cases and 2532 controls (diagnosed with other non-infection related cancers). Seropositivity to HPV proteins was measured using a multiplex serological assay based on recombinant glutathione S-transferase (GST) fusion proteins. We measured associations between their presence and cervical cancer using unconditional logistic regression models and evaluated the sensitivity and specificity of these HPV biomarkers.Among controls, HIV-negative women from rural areas compared to urban had significantly higher HPV seroprevalence, HPV16 E7 (8.6% vs 3.7%) and HPV18 E7 (7.9% vs 2.0%). HPV16 E6 and E7 antibodies were positively associated with cervical cancer in HIV-positive (Adjusted Odds Ratio (AOR) = 33; 95% CI 10–107) and HIV-negative women . In HIV-positive women, HPV E6/E7 antibodies had low sensitivity (43.0%) and high specificity (90.6%) for cervical cancer detection. In HIV-negative women, HPV E6/E7 antibodies sensitivity was 70.6% and specificity was 89.7%.Our data show that HPV  antibody positivity is associated with cervical cancer in both HIV-positive and HIV-negative women. Nonetheless, being HIV-positive plays an important role in the development of cervical cancer.The online version contains supplementary material available at 10.1186/s13027-022-00418-2. Globally, in 2018, about 70% of cervical cancers were attributable to high-risk human papillomavirus (HPV) types 16 and 18 [The HPV early (E6 and E7) oncoproteins and the late (L1) protein are encoded by the HPV genome. The HPV oncoproteins play an important role in the tumorigenesis of cervical cancer . HumoralPrevious studies have shown that HPV types 16 and 18 L1, E6 and E7 antibody proteins are associated with cervical cancer susceptibility –13 howevLess is known about the role of high-risk HPV oncoproteins among cervical cancer patients in black African women who are HIV-positive and HIV-negative. In South Africa, despite high HIV prevalence (24.1%) among black South African women , studiesThe study population were participants recruited into the Johannesburg Cancer Study (JCS) between 1995 and 2016. The aims of JCS included measuring the relative importance of known and emerging risk factors for cancer in a black African population in Johannesburg, South Africa. The details of the JCS have been described elsewhere . BrieflyThe JCS is amenable to a case–control design and analysis by selecting controls that are unrelated to the exposures of interest. The current study was restricted to women aged 25 to 54 years because a large proportion of the older women did not have serology samples available. Cases were 1346 women with newly diagnosed cervical cancer (C53). Controls were 2532 women with newly diagnosed infection unrelated cancers (breast (C50) (n = 1953), colon (C18-20) (n = 197), oesophagus (C15) (n = 48), endometrium (C54-55) (n = 75), lung (C33-34) (n = 76), pancreas (C25) (n = 21) and minor cancer types (n = 162) ) in Heidelberg, for antibody testing for HPV16 and 18  using a multiplex serological assay. This was based on a glutathione S-transferase (GST) capture immunoassay in combination with fluorescent beads on a Luminex platform , 20 and Data on demographic characteristics were summarized using frequencies and percentages for the categorical variables, medians and the interquartile range (IQR) for the continuous variable that was not normally distributed. A Pearson's Chi-squared test  and t-test (for age) were used for the comparison of demographics between cases and controls. To assess cross-reactivity between the proteins, a tetrachoric correlation coefficient rank test  with BonWe used an unconditional logistic regression model to assess the association by calculating adjusted Odds Ratios (AOR) and 95% confidence intervals between HPV16 and 18 (E6 and E7) and L1 proteins seropositivity and the risk of cervical cancer. We stratified by HIV status to assess if the seroprevalence of the HPV proteins differs in HIV-positive and HIV- negative patients. We adjusted for age, education level, number of sexual partners, marital status, period of interview and place of residence. To assess whether the clinical performance of HPV-16 and -18 antibodies as a diagnostic marker for cervical cancer we performed the same in HIV-positive and HIV-negative cancer patients. We calculated the sensitivity, specificity of the various HPV antibodies for detecting cervical cancer using the "diagti” command in STATA. In addition, the area under the ROC curve (AUC) of the receiver operator characteristics was computed to compare the performance of the best combination of HPV E6 and E7 antibodies to discriminate cervical cancer from controls . At least two-thirds of both cases (63.5%) and controls (72.4%) had a secondary school education  aged 25–54 years were included  and controls HPV16 E6 (3.0%) as compared to HIV-positive women cases HPV16 E6 (26.8%) and controls HPV16 E6 (2.8%)  and for combined HPV18 E6&E7 0.2%) . Among HIV-negative controls, the prevalence of HPV16 E7 antibody was higher among women that lived in rural areas (8.6%) as compared to women who lived in urban areas (3.7%)  . Among HIV-positive controls, the prevalence of HPV16 E6 &E7 antibodies decreased with an increase in number births up to 2 births   antibodies by demographic and sexual/reproductive factors (5) Table . A similan areas .7% , HPV16 E6 , HPV16 E7  and HPV16 L1 . For HPV18, antibody seroprevalence ORs for cervical cancer ranged from AOR = 38.61 (95% CI 15.13–98.53) for combined HPV18 E6&E7, AOR = 8.94 (95% CI 6.64–12.03) for HPV18 E7, AOR = 4.67 (95% CI 3.30–6.50) for HPV18 E6 and AOR = 1.31 (95% CI 1.10–1.56) for HPV18 L1  in HIV-negative, and 33.10 (95% CI 10.22–107.20) in HIV-positive women , and L1 protein and calculated their association with cervical cancer. While the seroprevalence of HPV16 L1 in the previous JCS study among HIV-seronegative women was higher  than in The higher seroprevalence of HPV16 E6, HPV16 E7 and HPV18 E7 in women from rural areas might indicate a greater number of women with early undetected cervical or related cancer lesions. In rural areas of South Africa, women have poorer access to health care services, are less likely to present themselves to cervical cancer screening services and have less access to cancer diagnostic facilities, which are mainly found in tertiary hospitals in urban areas .The high seroprevalence of HPV16 E6 35.9%) antibodies in cervical cancer cases found in our study are similar to the seroprevalence of HPV16 E6 (32%) in cervical cancer cases reported from the United Kingdom (35%) and India and Algeria (32%) .9% antib. We founAntibodies to the E6 and E7 oncoproteins are late markers of invasive cervical cancer . In our Individuals with suppressed immune systems are susceptible to chronic infection, including HPV . Thus, HUnexpected findings in our study were that HPV-16 and -18 (E6 and E7) oncoproteins seropositivity and cervical cancer risk were higher in HIV-negative cancer patients compared to HIV-positive cancer patients. Similar findings have been observed in previous studies of HPV antibodies among HIV-positive and HIV-negative patients –38. In oIn the new guidelines for screening cervical cancer, the World Health Organization (WHO) has included HPV antibodies and oncoproteins as a future potential screening test . We, theThere are strengths to our study. The seroprevalence of HPV antibodies was conducted on a large sample size, and we used a high throughput multiplex serology so all tests were done under the same laboratory conditions. The laboratory tests were conducted ‘blind’ without prior knowledge of the case/control status of the participants. Nonetheless, our study has some limitations. Serology data on exposure and cervical cancer diagnoses  were collected at the same time. We did not have tumor HPV Deoxyribonucleic Acid (DNA) data to determine the causative type(s). Since only 50–70% of women with detectable HPV DNA in the cervix seroconvert , our stuOur data contribute to the evidence on the importance of HPV-16 and -18 E6 and E7 oncoproteins antibodies in discriminating cervical cancer from controls in a black South African population. HPV L1 antibodies show to be exposure markers of past HPV infection. HPV E6 and E7 show to be important markers of invasive cervical cancer. Furthermore, antibodies to HPV-16 and-18 E6 and E7 seropositivity are strongly associated with cervical cancer in both HIV-positive and HIV-negative patients.Additional file 1: Table S1: Comparison of HPV16 and 18  antibodies in cervical cancer Cases and Controls among young and older women. Table S2: Seroprevalence of HPV16 and 18 L1. Table S3: Seroprevalence of antibodies against HPV 16 and 18  by HIV-Status. Table S4: Clinical performance of HPV16 and 18 antibodies as a diagnostic marker for cervical cancer. Fig. S1: Age-adjusted seroprevalence of HPV related antibody markers in cervical cancer cases and other infection unrelated cancer controls and p-value for heterogeneity among the infection unrelated cancer controls . The seropositivity of the age-adjusted HPV L1 and (E6 and E7) antibodies in each of the infection unrelated cancer patients (controls) was similar, (p-heterogeneity > 0.05). Fig. S2: Correlation between HPV16 and 18 proteins L1, E6 and E7 antibodies and HIV antibodies, R-values > 0.8 shows high correlation. (* Significance at 0.05). The colour indicates the intensity of correlation. Green indicate positive values, red indicate negative values, orange shows R-values that are greater than 0.05 and dark orange indicate R-values < 0.05 but not statistically significant.


Given that “cross-border e-commerce + live streaming” has become an important driver of global trade but limited attention has been paid to this area, this study examines the impacts of live streaming features on the consumers’ cross-border purchase intention from the perspectives of consumers’ overall perceived value and overall perceived uncertainty based on the SOR theory. In addition, through investigating the moderating effects of saving money, this study reveals the impacts of amazing bargains in live streaming commerce. A total of 272 samples were collected by a questionnaire survey to test the proposed research model. The results show that live streaming features significantly increase consumers’ overall perceived value and purchase intention, and significantly reduce consumers’ overall perceived uncertainty; in addition, saving money further increases the impact of live streaming features on consumers’ overall perceived value. This study provides a theoretical basis and reference for cross-border e-commerce platforms and merchants to effectively leverage live streaming to influence consumers’ perception and purchase intention. According to the new released “Global Cross-Border B2C E-Commerce 2021” report , cross-bExisting research on cross-border e-commerce mainly focuses on traditional e-commerce elements . LimitedDespite the arising of both cross-border e-commerce and live streaming e-commerce, it is still unclear about the influencing mechanism of “cross-border e-commerce + live streaming” on the consumers’ purchase intention. Compared with traditional domestic e-commerce, “cross-border e-commerce + live streaming” has its own features. Firstly, given the complexity of cross-border transaction, the new “cross-border e-commerce + live streaming” mode enables consumers to fully understand the cross-border product and purchase process in real time, intuitively and in detail, which further improves consumers’ satisfaction. It is widely known that the transactions in cross-border e-commerce are more complex than domestic e-commerce. For instance, the transactional processes usually involve delivery risks and crossing language barriers, which may increase consumers’ perceived risks and uncertainties and deter consumers from taking full advantage of cross-border e-commerce . LuckilyTo address the research questions, this study examines the impacts of cross-border e-commerce live streaming features on the consumers’ purchase intention from the perspectives of consumers’ overall perceived value and overall perceived uncertainty based on the SOR theory. At the same time, through investigating the moderating effects of saving money, this study reveals the impacts of amazing bargains in the live streaming. A total of 272 samples were collected by a questionnaire survey, and then statistical analysis and hypothesis testing were carried out through structural equation models. The results show that live streaming features significantly increase consumers’ overall perceived value and purchase intention, and significantly reduce consumers’ overall perceived uncertainty. In addition, saving money further increases the impact of live streaming features on consumers’ overall perceived value. This study provides a theoretical basis and reference for cross-border e-commerce platforms and merchants to effectively leverage live streaming to influence consumer perception and purchase intention.The findings of our study provide the following contributions to the existing literature. First, this study enriches the research by interpreting how live streaming can be used to affect consumers’ cross-border purchase intention based on SOR theory. In particular, we examined the influencing mechanism of “cross-border e-commerce + live streaming” on the consumers’ purchase intention from the perspectives of consumers’ overall perceived value and overall perceived uncertainty. Second, our study unveils the moderating effect of saving money on cross-border live streaming features affecting consumers’ overall perception. The results show that saving money can strengthen the positive impact of live streaming features on the overall perceived value while has no effect on the relationship between live streaming features and overall perceived uncertainty. Therefore, saving money is indeed a useful measure but should be used appropriately and carefully in live streaming. Our study also provides practical suggestions for cross-border e-commerce platforms and sellers to promote the continuous and healthy development of cross-border live streaming e-commerce.The SOR (Stimulus-Organism-Response) model was proposed by Existing research mainly focuses on domestic live streaming e-commerce, and there has been a limited understanding of the impact mechanism of live streaming in the context of cross-border e-commerce. Therefore, based on the SOR theory, our study will use live streaming feature (S) as an external stimulus, and explore the mechanism of its influence on consumers’ cross-border purchase intentions from the perspectives of consumers’ overall perceived value and overall perceived uncertainty. In addition, considering the widely used promotion tools of saving money in the current live streaming scenarios, this article will also explore the moderating effect of saving money on cross-border live streaming features affecting consumers’ overall perception. The research model is shown in Live streaming features refers to the functions and features that live streaming could achieve real-time interaction through the comprehensive use of text, sound and image, and live streaming could deliver true and reliable information to consumers from multiple aspects, enabling consumers to clearly evaluate products’ performance  . Cross-bAccording to the SOR theory, the live streaming features as an external stimulus will affect the cognitive response of consumers. Previous studies have pointed out that cognition can be divided into two dimensions: positive cognition and negative cognition in nature . Guo . In the end, we totally received 300 questionnaires. After removing questionnaires with too short answer time and failing the validity test, there are 272 valid questionnaires remaining.In this paper, in order to ensure the accuracy and practicability of the questionnaire, all measurement items are based on the previous maturity scale and modified according to our research scenario. Among them, items of live streaming features refers to N = 50) to explore the validity and readability of the questionnaire structure, and made appropriate revisions to the questionnaire based on the feedback to ensure the validity of the content of the scale.Since the survey was carried out for Chinese participants, this article conducts a forward-backward translation method to ensure the accuracy and consistency of the questionnaire presentation . At the In the 272 valid survey samples, there are a total of 192 females and 82 males. More than 90.81% of the samples have a bachelor’s degree or above, 76.47% are people aged 20–29, and 77% of the samples have an annual household income of less than RMB 0.2 million. In the past 3 months, most people spent an average of less than 2 h on Tmall Global/Taobao Global e-commerce every days. The descriptive statistics of our survey samples are shown in We use Cronbach’s alpha (CA) and composition reliability (CR) in the SmartPLS 3.0 software to test the consistency and stability of the scale. The results of the reliability test are shown in In this paper, the rationality and validity of the questionnaire are verified by structural validity test. The convergent validity is tested by using the average extracted variance value (AVE) and factor loadings. As shown in Common method bias refers to the spurious variance between predictor variables and benchmark variables caused by the same data source, the same measurement environment, project context, and the characteristics of the project itself. Through reasonable design of our research process, the common method bias is controlled and reduced. At the same time, we also use the Harman’s single-factor method to identify common method bias. If the majority of the covariance can be explained by a single factor or a general factor, it is indicated that the common method bias is present. Principal component analysis extracted a total of 10 factors, of which the explanatory variance of the first principal component was 26.496%, which was lower than the standard of 40% , indicat2 of the related constructs was calculated, and the results are shown in 2 of overall perceived value, overall perceived uncertainty, and purchase intention are 36.5, 4.8, and 40.6%, respectively. The results show that live streaming features is positively associated with overall perceived value  and purchase intention  while negatively associated with overall perceived uncertainty  in cross-border e-commerce. That is, H1, H2, and H3 are supported. In addition, the results show that the overall perceived value  positively affects purchase intention in cross-border e-commerce, that is, H4 is supported. And the overall perceived uncertainty negatively affects purchase intention , that is, H5 is established.In order to obtain stable and reliable results, we used the bootstrapping algorithm of SmartPLS 3.0 to run 5,000 times to study the path coefficient and significance of each hypothesis. At the same time, the R∗SMV refers to the moderating effect of saving money on the relationship between live streaming features and overall perceived value and LSF∗SMU refers to the moderating effect of saving money on the relationship between live streaming features and overall perceived uncertainty).The results of the moderating effect are shown in 6 = 0.157, P < 0.05), that is, the H6 hypothesis is supported. However, contrary to our hypothesis, the moderating effect of saving money on the relationship between live streaming features and overall perceived uncertainty is not significant , that is, the H7 hypothesis does not hold.Based on the SOR model, this article explores how live streaming features affect consumers’ overall perceived value, overall perceived uncertainty, and purchase intention in cross-border e-commerce. We proposed 7 hypotheses, of which H7 is not supported, and the other hypotheses are consistent with the analysis results. In view of the empirical results, further discussion is as follows.The findings that live streaming features can directly increase consumers’ purchase intention in the context of cross-border e-commerce are consistent with those of prior studies in the domestic e-commerce context e.g., . In addiFurthermore, the hypothesis test shows that the overall perceived value of consumers has a positive impact on purchase intention while the overall perceived uncertainty of consumers has a negative impact on purchase intention. That is, H4 and H5 are established. This is in line with the conclusions of The research conclusion also shows that saving money can strengthen the positive impact of live streaming features on the overall perceived value, that is, H6 is established. This is consistent with the conclusion of The important implications of this research is to enrich the research of live streaming in the field of cross-border e-commerce and expand the application scope of SOR theory. The empirical results show that cross-border e-commerce platforms can indeed increase the overall perceived value of consumers through live streaming and reduce overall perceived uncertainty, thereby increasing consumers’ purchase intention. At the same time, the research also provides the following enlightenment for promoting the healthy development of “cross-border e-commerce + live streaming” mode.First, this study verifies the important role of live streaming in cross-border e-commerce so that the practitioners should accelerate the construction of live streaming of cross-border e-commerce platforms, and actively explore optimization methods in live streaming to enhance consumer experience. Our study found that compared with traditional cross-border e-commerce operation models such as web pages or short videos, live streaming has features of higher authenticity and interactivity through the streamers’ description of the product’s feeling, appearance, or scent and other information. As a consequence, live streaming is able to increase consumers’ overall perceived value and reduce consumers’ overall perceived uncertainty, which in turn can increase consumers’ purchasing intentions. In addition, provided that live streaming is more mature in domestic e-commerce, the cross-border e-commerce market should draw on and learn from the successful experience of domestic live streaming e-commerce, accelerate the expansion of live streaming in cross-border e-commerce, and thereby improve and enrich consumers’ cross-border shopping experience. At the same time, the uniqueness of cross-border e-commerce live streaming should also be considered. Due to uncertain factors such as supply of goods, brand reputation, logistics and distribution capabilities in cross-border consumption, cross-border e-commerce platforms should strengthen the audit of cross-border products and improve the access threshold of live streaming products. Second, given that live streaming features can indeed increase consumers’ purchase intention in both direct and indirect ways, practitioners should make good use of the tool of live streaming. Our results show that live streaming features can effectively enhance consumers’ perceived value while reducing consumers’ perceived uncertainty. And those reminds cross-border e-commerce platforms and merchants that when embracing live streaming, they must strengthen the selection and professional training of cross-border e-commerce live streaming personnel, and pay attention to the output of live streaming content. More specifically, streamers should enrich the output content of live streaming and make high-quality content to attract consumers and eliminate consumers’ worries.Third, our study would facilitate practitioners’ understanding regarding the effect of saving money in cross-border live streaming e-commerce. Our results indicate that saving money can indeed positively moderate the relationship between live streaming features and the overall perceived value of consumers in cross-border e-commerce, while the moderating effect on the relationship between live streaming features and the overall perceived uncertainty of consumers is not obvious. Therefore, saving money is more like icing on the cake and cross-border e-commerce platforms and streamers should take measures of saving money appropriately and carefully in live streaming. For example, cross-border e-commerce platforms and merchants should further strengthen their product quality control, so that consumers can trust low-priced products in cross-border live streaming e-commerce, and formulate reasonable money-saving strategies to stimulate consumers’ willingness to buy cross-border products.There are still some limitations in this study. First, the cross-border e-commerce platforms selected in this research are relatively mature cross-border e-commerce platforms, and future study could further expand and enrich the types of research subjects. Second, factors such as product types and streamers types can be introduced in future research to deeply explore and analyze the underlying mechanisms between live streaming and consumers’ perception and behavior. Last but not least, researchers can further explore the impacts of different degrees and methods of promotion tools in cross-border live streaming e-commerce.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by the Secretariat of Academic Committee, Zhejiang University of Technology. The patients/participants provided their written informed consent to participate in this study.JG, YL, YX, and KZ contributed conception and design of the study. JG and YX organized the data collection. YL performed the statistical analysis, wrote the first draft, and revised sections of the manuscript. JG, YX, and KZ polished the manuscript and contributed to the writing of manuscript revision. All authors contributed to the article and approved the submitted version.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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


However, the prognosis of some tumors is dismal, and validated prognostic factors are missing in clinical practice. The present work aimed to validate the prognostic significance of our published three-cluster model and to compare its prognostic value with those of the 8NCT02832102) were considered as validation cohort. Patients were treated in seven European centers, with expertise in the multidisciplinary management of patients with head and neck cancer. The median follow-up was 46.2 months , and data collection was concluded in September 2019. The primary end point of this study was overall survival (OS). Three-clustering models and seven prognostic signatures were compared with our three-cluster model.Patients with HPV DNA-positive OPCs with locoregionally advanced nonmetastatic disease treated with curative intent . For the high-risk cluster, we observed an area under the curve = 0.832 for 2-year OS, significantly outperforming TNM 8th edition (area under the curve = 0.596), and functional and biological differences were identified for each cluster.The study population consisted of 235 patients. The three-cluster model confirmed its prognostic value. Two-year OS in each cluster was 100% in the low-risk cluster, 96.6% in the intermediate-risk cluster, and 86.3% in the high-risk cluster (The rigorous clinical selection of the cases included in this study confirmed the robustness of our three-cluster model in HPV-positive OPCs. The prognostic value was found to be independent and superior compared with TNM8. The next step includes the translation of the three-cluster model in clinical practice. This could open the way to future exploration of already available therapies in HPV-positive OPCs tailoring de-escalation or intensification according to the three-cluster model. However, expectations were in contrast with the results because this approach was associated with poorer outcomes. Thus, standard of care has not been changed.6 Therefore, there is still a strong need for trustable prognostic factors.8 Different preclinical and clinical studies have been performed leading to the identification of several genomic, epigenomic, transcriptomic, and proteomic characteristics of HPV-positive OPCs.14 At present, the most relevant clinical prognostic factors are stage, extranodal extension (ENE), and smoking exposure.15 ENE is currently part of the AJCC and UICC staging system for HPV-negative HNSCCs, but not for HPV-positive ones. In particular, in p16-negative OPC and non-OPC HNSCCs, clinical or radiologic ENE is considered for cN staging, and histopathologic ENE for pN one. Nonetheless, its negative prognostic impact was found in HPV-positive OPC as well, so some authors suggested its implementation in refining the cN of the 8th edition of the tumor-node-metastasis staging system (TNM8).16 In the field of gene expression (GE) profiling, the pioneering studies of Slebos9 and Pyeon17  and numerous omics characteristics of HPV-positive OPCs were identified in preclinical and clinical studies.14 Additionally, the analysis of HNSCC transcriptomic data highlighted the existence of HPV-positive distinctive prognostic clusters. In particular, we published a meta-analysis of publicly available transcriptomic data sets of HPV-positive HNSCC, in which three different clusters were characterized. Our three-cluster model was commented and compared with previous HPV-positive HNSCC subtypes in a recent comprehensive review.18 Moreover, Dhawan19 performed a meta-analysis of OPC data sets with available survival data to determine whether currently available GE signatures could prognosticate outcome more accurately than established clinicopathologic predictors.Among head and neck squamous cell carcinomas (HNSCCs), the incidence of oropharyngeal cancer (OPC) has been increasing in the past few decades. This is mainly due to the increasing number of human papillomavirus (HPV)–related OPCs.Key ObjectiveNCT02832102).To validate the prognostic value of a three-cluster gene expression model for human papillomavirus (HPV)–related oropharyngeal squamous cell carcinoma in an independent multicenter case material included in the BD2Decide observational study  and treated with curative intent had been included in the project Big Data and Models for Personalized Head and Neck Cancer Decision Support (BD2Decide).20 The study was approved by institutional review boards and ethical committee in March 2016, and patients consented to enrollment. The study population included 1,537 patients diagnosed and treated between 2008 and 2017, and the follow-up closed in September 2019. In this work, data and analyses are focused on patients with HPV-positive OPC. To reduce confounding variables affecting oncologic outcome and consequentially prognostic accuracy of the proposed model, we excluded (1) patients with p16-positive but HPV DNA-negative OPC22 and (2) patients receiving unimodal treatment (surgery without postoperative radiation or exclusive radiotherapy without concomitant systemic treatments) for clinical stage T1N > 1, T2N > 1, and T3-T4 any N disease.Patients with HNSCC with locoregionally advanced disease , p16-positive cases were tested using the GP5+/6+ DNA PCR assay, aimed at detecting 14 high-risk HPV types . If DNA PCR was negative, HPV16 E7 primers were used to exclude L1 integrations.In case of in situ hybridization, p16-positive OPC specimens were tested using the INFORM HPV III Family 16 Probe, able to identify 10 high-risk genotypes . When the DNA was not evaluable through in situ hybridization, the E6/E7 mRNA of high-risk HPV was assessed through the RNA scope Probe HPV HR18, identifying HPV 16, 18, 26, 31, 33, 35, 39, 45, 51, 52, 53, 56, 58, 59, 66, 68, 73, and 82.23 GE data sets had been generated using Affymetrix human Clariom D microarrays .20 MIAME-compliant data are deposited in the GEO repository (GSE163173).Positive results in both p16 immunohistochemistry and HPV DNA testing were considered evidence of a transcriptionally active HPV infection.24 Tumor microenvironment, the immune and stroma scores, and other cell components were inferred by xCell.25 Pairwise gene set enrichment analysis (GSEA)26 comparisons were performed to discern which Hallmark gene sets27 were differentially enriched. In the final data set, we assessed the overall survival (OS) prognostic discrimination ability of our three-cluster model by area under the curve (AUC) at 2 years, and its performance was challenged against TNM8 and publicly available prognostic models and signatures:28 and (A2) Chen29;(A) HPV-positive OPC signatures: (A1) Gleber-Netto30 and (B2) De Cecco Hypoxia10 signature able to identify aggressive tumors; and(B) HNSCC signatures: (B1) De Cecco 172 genes31 directly proportional to radioresistance and (C2) Buffa Hypoxia.32 Moreover, three already described signatures , clustering HPV-positive OPC, were applied to our final data set and compared with our three-cluster model. Three signatures  were applied following the linear model provided in the original studies. Regarding the other models, a metagene approach was applied: A score was computed in our data set by ssGSEA using the GSVA R package33 providing an unsupervised method for estimating variation of gene set enrichment through the samples. AUC at 2 years was assessed through timeROC R package.34(C) multiple cancers signatures: (C1) Torres-Roca RSIAfter microarray data normalization, the HPV-positive OPC selected cohort was classified according to the three-cluster model.To enable a better understanding of strengths and limits of the available signatures, studies and their characteristics are summarized in the Data Supplement.Differences between the survival curves of the three clusters were assessed using the log-rank test and R package survival. Primary end point was OS, and secondary end point was disease-free survival (DFS). For survival analyses, we set 2 years of observation. Further details are provided in the Data Supplement.35 Two thirds of patients were current or previous smokers at diagnosis, and 71% of them had a tobacco exposure of > 10 pack-years. According to the prognostic stratification of 36 from the work of Ang et al, 68% of patients with HPV-positive OPCs had a low-risk disease and the remaining 32% of cases were at intermediate risk . According to the current TNM staging system (TNM8), disease stage was I in 48% of cases (112 patients), II in 27% (64 patients), and III in 25% (59 patients). By applying the three-cluster model to the 235 data set, the following distribution was observed: low risk or Cl1, 108 (46%) cases; high risk or Cl2, 30 (13%) cases; and intermediate risk or Cl3 97 (41%) cases. The clinical characteristics and treatment modalities were not significantly different, with the exception of the frequency of cases with ENE-positive regional lymph node metastases: low risk 12.5%, high risk 37%, and intermediate risk 18%  OPC were included, and 377 patients were p16-positive. For validation analysis, we analyzed the cohort composed of 286 p16-positive cases with informative transcriptomics. Among them, 235 p16-positive and HPV-positive cases  were suitable as a final data set for clinical correlations . Considering low risk as a reference group, hazard ratio for death was 9.15  for high versus low risk and 5.67  for intermediate versus low risk. AUC for 2-year OS was 0.832 (Data Supplement). Considering 2-year OS, AUC was 0.754 for TNM8 versus 0.596 for TNM7 (Data Supplement).The prognostic stratification according to the three-cluster model was tested in both the validation (Data Supplement) and final data sets Fig A and con32 and RSI31) outperformed TNM8 and were able to significantly separate high-risk versus low-risk HPV-positive OPC cases. Box plot distribution (Data Supplement), according to the scores of the seven selected prognostic signatures in each of the three clusters, confirmed that the high risk exhibited significantly the highest RSI and hypoxia expression. The clustering was not influenced by TNM staging also at multivariate analysis , and the combination of three-cluster model and TNM8 provided AUC = 0.842 for OS and AUC = 0.809 for DFS (Data Supplement) at 2 years. At bivariate analysis, the three clusters maintained their prognostic power  independently of ENE status . Using low risk as reference, hazard ratio for disease recurrence was 6.1  for high versus low risk and 3.67  for intermediate versus low risk. AUC for 2-year DFS was 0.777 (Data Supplement). The highest AUCs were observed for the three-cluster model. Ang classification was prognostic for DFS (P = .039), not for OS .Survival and recurrence probability were predicted with statistical significance by TNM8 Fig B, not by37 these signatures and their performance in stratifying HPV tumors were investigated and compared with our three-cluster model , essentially confirming the results obtained in the original study.24 The highest level of immune score was recorded in low risk  excluded from the validation set, because of HPV DNA-negative or suboptimally treated, were part of the high-risk cluster. Thus, the results obtained on OPC final data set indicated that, after removal of potential confounding factors, high risk maintained the worst prognosis. The present work definitely confirmed the prognostic value of the three-cluster model in HPV-positive OPCs. The prognostic accuracy of the three-cluster model (AUC = 0.832 for 2-year OS) outperformed the TNM8, the current gold standard for prognostic stratification in oncology, and at bivariate analysis, its prognostic role was independent. In addition to the three-cluster model, three prognostic signatures, even if developed in all sites HNSCC or multiple cancers or OPC HPV-negative cases, were also able to outperform TNM8. They significantly separate the OPC HPV-positive cases with an AUC > 0.76. Interestingly, these signatures were obtained by meta-analysis of more than a 1,000 samples and/or were validated in different published studies. On the contrary, the other three signatures and models, built on smaller or heterogeneous HNSCC cohorts, did not show a prognostic role, suggesting the importance of larger or homogeneous study design in the context of the omics studies. The prognostic performance of the three-cluster model was not influenced by underlying clinical factors. The only difference in terms of clinical characteristics among the three clusters was ENE prevalence. Indeed, high-risk patients had a higher frequency of ENE plus disease, reflecting a more aggressive disease.35 This consistent association corroborates the robust independent prognostic ability of the proposed three-cluster model. Low risk was characterized by the best prognosis and included 46% of patients. These tumors expressed a high immune score and significant enrichment of immune active cells . They were characterized by a low RSI score and the lowest hypoxia scores. Our low-risk cluster is probably similar to the HPV-IMU identified by Zhang et al,37 also confirmed by the experimental comparison of Qin et al.18 The worst prognosis was observed in high-risk patients (13% of the study cohort). This group, characterized by the highest keratinocytic differentiation status, is similar to the HPV-KRT cluster of Zhang et al37 and was confirmed in the comparison of Qin et al.18 Moreover, the high-risk cluster was characterized by the lowest immune score and an enrichment in GSEA pathways associated with the immune-exhausted HNSCC tumors,38 which is also defined as cold immune.18 The enrichment in hypoxia hallmark, consistent with the immune suppression and radioresistance (high RSI), was confirmed by the highest expression of hypoxia signatures.This is an independent validation of a three-cluster model, previously developed through meta-analysis of publicly available data sets.16 Despite our efforts, this was the less biologically and functionally characterized cluster. Nevertheless, biologically we were able to separate this group from the patients with good (low risk) or poor (high risk) prognosis. In detail, it expressed an intermediate immune score not associated with exhausted immune cells, a marginal radioresistance and low expression of De Cecco hypoxia signature. Notably, we observed an evident enrichment in metabolic pathways in both high and intermediate risks. Further investigation and deeper comments about possible treatments applicable to patients with HPV-positive OPC are reported in the review of Qin et al18 on the basis of the experimental comparison of the three-cluster model24 data with the other published HPV-positive two-cluster models.39 In addition, we observed that in our study population, the majority of current or previous smokers had a relevant tobacco exposure (> 10 pack-years in 71% of cases). Nevertheless, the frequency of current or previous smokers in our study population (66%) was lower than the one reported in previously published studies . This is consistent with the observed smoking reduction in Western countries, where cigarette smoking rates have been reducing in the past 50 years. Moreover, future projections are forecasting a further reduction in smoking prevalence.40 These epidemiologic variations imply that the observations found in our study population might need further updates in the next decades, to study whether behavioral changes will be reflected by different biological alterations, with possible clinical impact. Potential limitations of the three-cluster model are the observed dropout rate (25%) in our GE case material compared with the original clinical set and the lack of specification of the viral genotype for each case. The first limitation could be due to the fact that for most OPC cases, where chemoradiation is usually preferred over surgery, the analyzed specimen was an initial small biopsy. However, independent studies show that an increase in sample size, corresponding to our dropout rate, had limited effect on the clustering performance.37 The second drawback could be attributed to the HPV DNA tests used. However, this limitation is mitigated by the fact that the vast majority of HPV-positive OPCs are known to be related to the HPV16 genotype.41 Indeed, we do not anticipate major negative impacts of the cited drawbacks on our analysis.The novelty introduced by our work was the identification of the intermediate-risk cluster (41% of the study cohort), never characterized before by other clustering models.In conclusion, in patients with HPV-positive OPC with locoregionally advanced disease treated with curative intent, there is still a strong need for defining trustable prognostic factors, and our results seem to fulfill this necessity. The rigorous clinical selection of the cases included in the BD2Decide study corroborates the robustness of the proposed three-cluster model, which resulted in an independent and superior prognostic factor compared with TNM8, the current gold standard for prognostic forecasting in clinical practice. The next step includes the required translation of this GE clustering in clinical practice, following a framework applied in other tumors. This could open the way to future exploration of already available therapies in HPV-positive OPCs tailoring de-escalation or intensification according to the three-cluster model.


The L1 gene, encoding the major surface protein (MSP), is used to classify HPV types (lineages and sublineages), genotypes, and intratypic variants. Therefore, this study aimed to investigate the lineages, sublineages, genetic variabilities, and mutation effects on transcription factor binding sites by using partial sequences of the HPV 16 and HPV 18 long control regions (LCRs) in these samples.  Human papillomavirus  After DNA isolation from 56 positive samples, the LCR of HPV 16 and HPV 18 were amplified using specific primers, and phylogenetic trees were drawn through MEGA X. Compared to the reference sequences, single nucleotide polymorphisms (SNPs) were identified. The transcription binding sites were also evaluated using the online PROMO database.  The LCRs of 52 samples were successfully sequenced. Overall, 81.58% of all HPV 16 variants belonged to the D1 sublineage, followed by A4 (13.16%), A1 (2.63%), and C1 (2.63%) sublineages. All HPV 18 isolates belonged to A sublineage, 92.85% to A3 sublineage, and 7.15% to A4 sublineage. Out of 27 SNPs in the HPV 16 LCR, A7382T, T7384G, C7387T, C7393G, A7431G, T7448C, and C7783A were HPV 16-specific. Also, among 14 SNPs in the HPV 18 LCR, C7577A and A7943T were not previously reported. An insertion (C) between 7432 and 7433 positions was identified in all studied HPV 16 variants. Besides, most of the HPV 16 mutations were embedded in the YY1, TFIID, Oct-2, and NF-1 binding sites, while c-Fos and MBF1, as the most common binding sites, were affected by HPV 18 LCR mutations.  The present results showed that D1 and A3 were the dominant sublineages of HPV 16 and HPV 18, respectively. Therefore, women infected with these variants need to be examined in further longitudinal studies to obtain more information about the oncogenic potential of these dominant variants in Iran. Besides, YY1, TFIID, Oct-2, NF-1, c-Fos, and MBF1 were the most frequent binding sites, which were influenced by the mutations. Human papillomavirus (HPV) 16 and HPV 18 are well-known viruses, responsible for cervical cancer and associated with some other cancers . HPV 16 Moreover, three major phylogenetic lineages have been identified for HPV 18: A (European and Asian-Amerindian), B, and C (African). Overall, lineages A and B each have four sublineages . While HDifferent genome segments have been used to classify HPV 16 and HPV 18 into lineages, including long control region (LCR), E6, and L1 –11. The Due to the importance of LCR in the viral life cycle and reports of mutations in some nucleotide positions of the LCR, causing changes in the viral oncogenic potency  , 15, thi56 samples were used in this study. Indeed, a total of 2,756 ThinPrep samples were collected from women (age range: 16–48 years) in 12 provinces of Iran for the national HPV screening and genotyping program. The participants were referred to the papillomavirus reference laboratory of Masih Daneshvari Hospital Virology Research Center, Tehran, Iran [DNA was isolated from ThinPrep samples using the High Pure Viral Nucleic Acid Kit , according to the manufacturer's instructions. The target regions of HPV 16 and HPV 18 LCRs  were amplified by nested polymerase chain reaction (PCR) (for HPV 16) and conventional PCR (for HPV 18). The HPV 16 primers included 5′CTTGTGTAACTATTGTGTCATGC3′ and 5′AGTTGCTTGTAAATGTGTAACCC3 as outer primers and 5′CAACACCTACTAATTGTGTTGTGG3′ and 5′AAATCGGTTTGCACACACCCATGT3′ as inner primers.β-globin gene was also used to evaluate the sample quality. Amplification of PCR products was confirmed by 1.5% agarose gel electrophoresis.The profile PCR reaction was set up in 95°C for 300 s, 95°C for 60 s, 55°C for 60 s, 72°C for 90 s, and final extension in 72°C for 300 s for 35 cycles with outer primers, which led to the production of 600-nucleotide amplimers. The same thermocycler profile was used with inner primers to amplify the final products (530 nucleotides). The HPV 18 primers included 5′TCGGTTGCCTTTGGCTTAT3′ and 5′TCCGTGCACAGATCAGGTAG3'. Similar to HPV 16, a PCR program was performed for HPV 18. The The partial sequences of the HPV 16 and HPV 18 LCRs were analyzed in BioEdit software  and blasAfter sequencing, to identify SNPs, the studied HPV 16 and HPV 18 LCR sequences were aligned with the reference sequences  using MEGA X software. Besides, the online PROMO database was used to evaluate the transcription binding sites .n = 52), a 530-nucleotide genotype  and a 555-nucleotide genotype  from LCRs were successfully amplified and sequenced.Among 56 DNA-positive samples for both HPV genotypes, two samples of each virus (HPV 16 and HPV 18) were excluded due to poor amplification quality. In the remaining samples (The studied HPV-16 variants mainly belonged to D lineage (D1 sublineage), which accounted for 81.58% of all HPV 16-positive samples, followed by A4 (13.16%), A1 2.63%), and C1 (2.63%). All HPV 18 isolates belonged to A lineage (92.85% to A3 sublineage and 7.15% to A4 sublineage) . The sub.63%, andOut of 41 SNPs found in this study, 27 were in the HPV 16 LCR and 14 in the HPV 18 LCR  are able to bind to the target region in the HPV 18 LCR, and seven factors  could bind to the HPV 16 LCR. Compared to the HPV 18 reference, except for STi119 isolate, C7486T led to the emergence of binding sites for c-Fos and MBF1 in 93.0% of the samples. Also, in 100% of the samples, a T7595C mutation corresponded to the disappearance of binding sites of TFIID and TBP transcription factors. In the HPV 16 LCR, the most common mutations were embedded in the YY1, TFIID, Oct-2, and NF-1 binding sites , and consequently, the increased expression of E6 and E7 oncogenes . Among mCompared to the reference sequences, mutations within LCR in all subjects had more binding sites for some transcription factors, such as YY1, NF-1, Oct-2.1, TFIID, E2F, and TEF-1. Pande et al. reported that some mutations in the HPV 16 LCR, especially in YY1 binding sites, such as G7519A (the most common mutation in YY1 binding site), A7634C, C7687A, T7712G, C7790T, G7824A, A7837C, T7741, and C7762T, led to increased p97 activity by three to six folds . Among tCompared to c-Jun family members, C-Fos is an AP-1 transcription factor subunit. Overall, AP-1 is one of the factors, which plays a crucial role in the primary stages of neoplastic changes. All these factors regulate the miR-21 genes in cervical cancer cells, associated with HPV 18 and HPV 16 . MoreoveThe present study had several limitations. First, this study had a cross-sectional design, with no demographic information available regarding the cancer status of the samples; therefore, more detailed longitudinal studies are suggested at a molecular level. Second, in this study, samples collected in the first national HPV screening program in Iran were used, while the diversity of HPV genotypes in all provinces of Iran was not comprehensively studied. Finally, although LCR is an important regulatory sequence of HPV genome, according to a study by Qu et al., in which HPV sequences were examined in Chinese women, the accuracy of sublineage classification based on the LCR was 94.02% and 100% for HPV 16 and HPV 18, respectively; they suggested that E2 was the best region for HPV 16 sublineage classification . NeverthThe present study showed that D1 and A3 were the dominant sublineages of HPV 16 and HPV 18, respectively. Also, YY1, TFIID, Oct-2, NF-1, c-Fos, and MBF1 were the most frequent binding sites, influenced by mutations. Regarding the importance of mutations in the LCR of non-A variants in developing higher grades of neoplasia (CIN grade 2/3) or invasive cervical cancer, women infected with these variants should be examined in future longitudinal studies to obtain further information about the oncogenic potential of these dominant variants in Iran.


Previous studies have shown that individuals with human papillomavirus (HPV)‐related cervical lesions have different prognoses according to the HPV genotype. However, these studies failed to account for possible diagnostic misclassification. In this retrospective cohort study, we aimed to clarify the natural course of cervical lesions according to HPV genotype to account for any diagnostic misclassification.Our cohort included 729 patients classified as having cervical intraepithelial neoplasia (CIN). HPV was genotyped in all patients, who were followed up or treated for cervical lesions at the University of Tokyo Hospital from October 1, 2008 to March 31, 2015. Hidden Markov models were applied to estimate the diagnostic misclassification probabilities of the current diagnostic practice (histology and cytology) and the transitions between true states. We then simulated two‐year transition probabilities between true cervical states according to HPV genotype.Compared with lesions in patients with other HPV genotypes, lesions in HPV 16‐positive patients were estimated to be more likely to increase in severity ; over 2 years, 17.7%  and 27.8%  of those with HPV 16 progressed to CIN3/cancer from the true states of CIN1 and CIN2, respectively, whereas 55%–70% of CIN1/2 patients infected with HPV 52/58 remained in the CIN1/2 category. Misclassification was estimated to occur at a rate of 3%–38% in the current diagnostic practice.This study contributes robust evidence to current literature on cervical lesion prognosis according to HPV genotype and quantifies the diagnostic misclassification of true cervical lesions. In this retrospective cohort study, hidden Markov models were applied to clarify the natural course of cervical lesions according to human papillomavirus (HPV) genotype to account for any diagnostic misclassification. We revealed: (i) the current diagnostic practice  was subject to diagnostic misclassification, and (ii) HPV 16‐positive patients were more likely to progress to more severe lesions than those with other HPV genotypes.  We aimed to confirm the robustness of the current literature, including a previous study that used a Markov model, on the CIN characteristics according to HPV genotype. Using this model, we also quantified the misclassification probability in CIN diagnosis.22.1Between October 1, 2008 and March 31, 2015, 1427 female patients underwent HPV genotyping at the Obstetrics and Gynecology Department of the University of Tokyo Hospital . Patients with mild cervical lesions were also followed up at this hospital instead of being referred to other clinics. We reviewed the electronic medical records (EMRs) of those patients and extracted information on pathological  examinations and treatment of cervical lesions as previously described.To clarify the natural course of cervical lesions according to the CIN classification, we constructed a dataset that included patients (i) diagnosed with normal cervical lesions, CIN1, or CIN2 at the time of entry and (ii) who visited the Obstetrics and Gynecology Department at least twice during the follow‐up period. Patients were excluded if they had HPV 6‐single‐positive lesions with the sole diagnosis of condyloma during the follow‐up period and if they had only glandular lesions. Patients with multiple HPV genotypes were excluded. One patient with malignant lymphoma was also excluded. Patients were followed up until they received treatment, until they were diagnosed with CIN3 or cervical cancer, until they were moved to another hospital, or until March 31, 2018, whichever occurred first. Finally, 729 patients (6082 observations) were included in the dataset .2.22.2.1A cervical swab sample was collected from each patient at the time of entry or at the first visit when the HPV DNA genotype was determined. DNA was extracted from the cervical samples with a DNeasy Blood Mini Kit (Qiagen), the procedure for which has been previously described.2.2.2The dates of visits and the trajectory of cytological and histological results were maintained in the EMRs of each patient. At the patient’s first visit, we collected a histological sample via colposcopy. Thereafter, we performed repeated cytological and/or histological examinations in line with each patient’s visits. The histological examination was performed at the gynecologists’ discretion, especially when colposcopic findings indicated severe lesions compared with the previous diagnosis, the disease had progressed since the previous assessment, or when lesions that tended to exhibit discrepancies in cytological and histological diagnoses were observed.Based on the cytological and histological results obtained after each visit, we grouped the pathological diagnoses at each visit into one of the following four CIN categories: normal, CIN1, CIN2, and CIN3/cancer. For some controversial records, the investigators (gynecologic oncology experts) discussed and determined the following: (i) CIN1–2 was classified as CIN1, (ii) CIN2–3 was classified as CIN2, (iii) uncertain diagnoses  were excluded from diagnostic reliability, and (iv) if the histological and cytological results were not identical, we accepted the more severe result as the diagnosis. We classified CIN1–2 as CIN1 and CIN2–3 as CIN2 in order to mitigate the overdiagnosis from the fourth protocol.Furthermore, based on the dates of patients’ visits, we calculated the follow‐up time at the time of each examination. The age of the patients at the time of entry was extracted from the EMRs.2.3We applied the continuous‐time multistate hidden Markov model to account for the possibility that pathological examinations were subject to misclassification and for the natural bidirectional course of cervical lesions. This statistical model contains two parts: (i) the transition between the “true” pathological states and (ii) the probabilities of the “observed” diagnosis conditional on the “true” pathological states (misclassification probabilities).λij represents the transition intensity, which can be interpreted as an instantaneous rate of transition from the true pathological state i to the true pathological state j . Based on the clinical assumption that adjacent misclassifications could account for most diagnostic misclassifications, we assumed the following misclassification matrix for the estimation . In other words, we allowed for just a “one‐step” misclassification adjacent to the true state.We assumed transitions of the “true” pathological states and the misclassification patterns as shown in Figure 2.4First, we reported the summary statistics of patients according to HPV genotype  and observed diagnoses at the time of entry. We also showed the transition of diagnoses according to HPV genotype over two successive examinations.λij and ers using the msm package in R.λij. Furthermore, we simulated the probabilities of transitions among the true states for up to 2 years. We selected the span of 2 years for two reasons. First, a two‐year transition prediction is considered a good benchmark for the prognosis of hrHPV‐related cervical lesions. At least half of those lesions have been reported to regress to a normal state and approximately 10% progress to CIN3 within 2 years.Next, a maximum likelihood procedure was applied to estimate the parameters 2.5e34 in the misclassification matrix to zero. We performed this sensitivity analysis because the estimation of the parameter e43 jointly with e34 in the CIN analysis was supposedly unstable due to the nature of our dataset. Since the analysis of patients in our dataset with the CIN categorization was truncated once they were diagnosed with CIN3/cancer, the available observations to estimate e43 were reasonably scarce. Using this sensitivity analysis, we aimed to stabilize the estimation of e43 to examine whether the estimates in the primary analysis were subject to this instability.To confirm the robustness of our primary analysis, we performed two different sensitivity analyses. First, we assumed another misclassification matrix for the CIN categorization. Specifically, we set Second, to clarify the natural course of cervical lesions according to the two‐tier classification ,33.1Table Table 3.2Table Table 3.3Tables For the two‐tier classification, dataset characteristics and visit‐wise transitions of observed lesions are shown in Tables Table 4In this study, we applied the continuous‐time multistate hidden Markov model and successfully estimated the transition probabilities of cervical lesions according to HPV genotype, which accommodated the misclassification probabilities of pathological lesions. Adopting a latent variable approach  as in previous medical research, we revealed the following two points: (i) the current diagnostic practice  was subject to diagnostic misclassification at a rate of 3%–38% and (ii) even when the diagnostic misclassification was accounted for, HPV 16‐positive patients were more likely to progress to more severe lesions  than those with other HPV genotypes, which was consistent with previous studies.Our results showed that even when we accounted for the diagnostic misclassification in current practice, the progression rate toward CIN3/cancer was higher among HPV 16‐ positive patients than among others. In contrast, patients with HPV 52/58 tended to remain in the CIN1/2 category. Moreover, the progression and regression rates were similar between patients with other hrHPVs and those with no hrHPVs. These results are consistent with those seen in the literature and corroborate the finding that patients with HPV 16 are more likely to develop more severe lesions than those with HPV 52, HPV 58, other hrHPVs, or no hrHPVs.Our prognostic prediction was different from that in a previous study, which used a continuous‐time multistate Markov model.Our results estimated that diagnosis through histological and cytological examinations was subject to misclassification at a rate of 3%–38%. These misclassifications can be explained by two mechanisms. First, histological and cytological examinations may be subject to sampling errors. The diagnostic precision of histological examination has been shown to depend on the quality of specimen processing.To the best of our knowledge, this is the first study to apply a hidden Markov model to quantify the misclassification probabilities of the cervical diagnostic procedure as well as the natural history of HPV infections; Kang and Lagakos applied a hidden Markov model only to the natural history of HPV infections under the prespecified misclassification probability.Some limitations of this study should be acknowledged. First, we could not accommodate the effect of concurrent multiple HPV infections on the progression and regression of cervical lesions. Even for interaction terms between two different HPV genotypes, our cohort was too small to account for multiple HPV infections. Compared with single infections, coinfections with multiple α9 species have been shown to be associated with an increased risk of CIN2 or more severe lesions.e43) and the probability of observing CIN3/cancer in patients with CIN2  in the same model. Furthermore, only “one‐step” misclassifications were allowed in this study, although other misclassifications were possible. Misclassification heterogeneity may have been present due to different diagnostic procedures  or physicians in charge of patients. In our preliminary analyses, most of the more generous misclassification patterns did not achieve estimation convergence. Despite these concerns, our analyses should provide reliable estimates: (i) we confirmed that our results were robust to the alternative specification of the misclassification matrix, where the confidence intervals were much smaller, and (ii) our model specification with just “one‐step” misclassifications is an appropriate abstraction of the diagnostic reality if other misclassifications were sufficiently rarer than these misclassifications.Fourth, our model specification might not be optimal. Our estimation in the analysis of the CIN categorization was unstable due to the nature of our dataset. Specifically, the confidence intervals were wide for the misclassification probability with the true underlying state CIN3/cancer, since the analysis of patients in our dataset with the CIN categorization was truncated once they were diagnosed with CIN3/cancer; this dataset structure increased the difficulty in estimating both the probability of observing CIN2 in patients believed to have CIN3/cancer , which was performed in accordance with the Declaration of Helsinki.All the patients included in this study provided consent for the publication of the research findings.Fig S1Click here for additional data file.Fig S2Click here for additional data file.Fig S3Click here for additional data file.Fig S4Click here for additional data file.Table S1‐S6Click here for additional data file.AppendixClick here for additional data file.


Using a text mining process and qualitative content analysis of 549 comments posted to a LinkedIn online discussion board, we identified six key themes; three were tied to camera and microphone issues, two involved eating and meeting management issues, and one dealt with work-from-home issues. These themes are discussed in relationship to media naturalness theory and meeting science. Because widespread use of videoconferencing will likely continue, we provide guidance for workplace policies/practices and suggest directions for future research.This study focuses on  The COVID-19 pandemic and the resulting stay-at-home orders have led to significant changes in the way people work. One of these changes involves increased use of video conferencing as a means of communicating or holding work meetings. Zoom, for instance, had 10 million daily meeting participants in December 2019, but by April 2020, that number had risen to over 300 million . Other vZoom fatigue or feeling mentally and physically exhausted by video conferencing , exposing one’s private living space, and lacking security .Similarly, State of Meetings Report  assumes that the human brain has evolved over time to facilitate face-to-face communication and that the more similar a communication mode is to face-to-face communication, the more natural it is and the lower the cognitive effort required to use it . MNT ideWhile MNT has much in common with other theories such as media richness theory  and sociBecause of the widespread use of videoconferencing as the primary medium for work communication during the COVID-19 pandemic and the likelihood that it will continue to be widely used in the workplace, it is important to understand what about videoconferencing is working, and what is not working, for individuals who are working remotely. In other words, the focus of this study is on the “good, the bad, and the ugly” of using videoconferencing for work-related meetings, where “bad” refers to anything that deters from the meeting process and “ugly” is something that is visually distracting to participants and impedes meeting effectiveness. More specifically, based on our literature review, we are pursuing the following research questions:RQ1: In what ways does the use of videoconferencing enhance the user experience or meeting effectiveness?RQ2: In what ways are the frustrations faced by virtual meeting participants similar or different from those experienced by participants in face-to-face meetings?RQ3: Are these frustrations related to the technology, participant behavior, or the situation ?N = 549) were cut and pasted into an Excel spreadsheet and included in the analysis. All comments were posted in July/August of 2020.The data for this study was collected from a LinkedIn website dealing with Zoom or video meeting etiquette, entitled “Chewing while on Zoom? Oh dear.” In addition to the title article, LinkedIn members posted four additional articles on the site including: “When It Comes to Zoom Etiquette, What’s Your Pet Hate?,” “Seven Rules of Zoom Meeting Etiquette from the Pros,” “Video Meeting Etiquette,” and “Zoom Call Etiquette.” All comments posted on the website  in SAS Enterprise Miner which is a powerful text mining method capable of uncovering the underlying semantic concepts  in a corpus. LSA is an algorithm based on singular value decomposition (SVD) to reduce the dimensional matrix of latent semantics to extract knowledge from the textual corpus  and has First, we preprocessed and cleansed the comments by eliminating numbers and punctuations from the data. Because some words  are generally not useful in identifying the discussed topics, we used the Standard English stop word dictionary to exclude these from the data and reduce its dimensionality. Consistent with Following Because the matrix created by the TF-IDF weighting scheme is very large and sparse, we eliminated the terms that appeared in less than four comments. We also applied the Singular Value Decomposition (SVD) method to reduce the dimensionality of the data while still retaining most of the meaningful information . The finN = 130), meeting management issues (N = 113), camera issues (N = 111), eating during meetings (N = 99), microphone issues (N = 93), and work from home issues (N = 93). Below, we review each of these themes, and tie the findings to media naturalness theory and the meeting science literature.After reviewing all comments appearing under each of the six topics, we identified labels for each. These six topic labels included camera on versus off, lurking  from distracting other participants. As an example, one contributor stated, “not everyone has the bandwidth to use video consistently.” Another stated, “Not being on video does not make you a “lurker.” Some people love being on video, some of us do not.” These comments are also consistent with media naturalness theory. Lack of bandwidth interferes with the meeting transmission, thereby disrupting the synchronicity of communication exchanges and often results in participants turning off their camera and using audio only. Discomfort with being on-camera is another issue. In face-to-face communication, individuals see those to whom they are speaking, they do not see themselves. Many find that seeing their own image on their computer screen is unnatural and distracting. There was also recognition among some contributors that the pandemic may be impacting individuals’ decisions to have their camera off, such as to prevent others in their environment  from disrupting the meeting or distracting other meeting participants. For example, one stated, “To anyone who chooses “not turning video on,” I encourage you to “assume positive intent” . . . they may have kids running around.”This theme included comments related to characteristics of “bad” meetings and problems with meeting management. Comments related to “bad” meetings included concerns about participants who show up late, lack of an agenda, meetings are too long, too many meetings, back-to-back meetings, and participants who multi-task. An example of a contributor who complained of too many meetings or back-to-back meetings is as follows, “Multiple zoom meetings. . . I didn’t like multiple in person meetings, now I can spend an entire day on virtual calls. There is no lunch time or break time, just jump from meeting to meeting.” Existing research in the Meeting Science literature shows that meeting load, or the frequency and time spent in meetings , can increase employee stress, fatigue, and perceived workload .“those who multi-task during a zoom meeting are not giving their utmost attention to the meeting. . . . Let the organizers put forward ground rules on the invitation of attendance.” Previous research on face-to-face meetings suggests that both meeting satisfaction and effectiveness are enhanced when participants avoid engaging in activities unrelated to the topic of the meeting  Always set an agenda and goals for the meeting. Are you merely disseminating information so you wouldn’t need people to be turning on their videos or participating unless they need to ask questions? Or is it a meeting wherein inputs of attendees will have bearing on decisions to be made? (2) Set the time and manage the time well. Zoom fatigue sets in if meetings go beyond 1.5 hours and one has to be in those meetings four times a day. (3) Consider the number of attendees. Just because zoom premium account allows 200 participants in a meeting room, it doesn’t mean you maximize the room space. Of course webinars are a different matter. (4) Online meetings is still part of work, it requires professionalism. Being on time and coming to meetings prepared are still required.A contributor comment that addressed meeting management issues, with suggestions for improvement, is as follows:To support meeting management, some contributors noted that the chat function and polling could be used to enhance participant involvement and engagement in the meeting. As an example, one contributor stated, “There’s also an onus on people running zoom meetings to keep the audience engaged, e.g., by using polls and questions in the chat box.” Taken together, these comments reflect the importance of attention to effective meeting management, ranging from how virtual meetings are planned and scheduled to how they are conducted .my pet peeve is floating heads at the bottom of the screen. Tilt your camera so your head is near the top of the screen and you basically fill the frame. . . .Second is bad lighting. We’re all doing this regularly now, so read some articles on how to get decent lighting for your video calls. Good video setup is the new business suit.” Another person said, “I feel like I’m on a roller coaster when people walk with the camera on, it’s so distracting, and you can’t help but be drawn to watching it!Several contributors voiced frustration about camera issues including the camera angle, proximity of the camera to a participant’s face, bad lighting, participants who do not look at the camera, and participants who walk around with the camera. For example, one participant stated,These complaints are consistent with media naturalness theory, which assumes any form of communication that moves away from face-to-face interaction leads to extra cognitive effort. Face-to-face communication involves being able to make direct eye contact and to see the other persons’ entire face.I had a manager that would book google meetings and then be eating the whole time I felt like I was not valued and that the meeting was a waste of her time. . . .Not very professional! Eat before you have a call!Most of the comments in this theme focused on meetings that were scheduled over the lunch hour and, while many were irritated by participants who were eating on camera, others were more accepting and believed that this was necessary. To illustrate, one contributor stated,If you schedule a meeting over lunch, you should be ok with people eating during that call. People need to eat.” Likewise, another stated: So, please STOP scheduling meetings during lunch hour! . . .Previously at the workplace, if the occasional meeting needed to be scheduled at noon, lunch was provided for participants. Don’t I deserve a break to eat? If you want me on a call during the lunch hour, prepare to see me eat!Others voiced the opposite opinion. For example,If people have to eat during a video call, turning off the camera until they are done can save the awkwardness of having to watch somebody eat. Back when we all sat in conference rooms together, lunch meetings were common and nobody thought it was so awful to watch their colleagues chew–mostly because they didn’t watch.Still others recommended that individuals turn off their camera if they must eat. A sample comment is:Those who complained about their coworkers eating during meetings clearly saw the behavior as distracting and rude. In contrast to many face-to-face meetings, it is likely that virtual meetings scheduled over the lunch hour had no expectation or norm that everyone would be eating. Also, due to the positioning of cameras, others’ faces appear much closer and less natural in virtual meetings, so that if someone is eating, it is highly visible. Given the findings of Another frustration faced by participants in virtual meetings was coworkers who failed to mute their microphones. Sample comments include: “Not muting. Echoes and background noises can completely drown out the speaker, so keep it muted until you’re ready to speak” and “I really dislike when people have a commotion on their end and don’t mute themselves. I don’t want to hear their dogs, kids, or arguments.These comments are also supported by media naturalness theory since the ability to convey and listen to speech is a key characteristic of face-to-face communication. Furthermore, We should be mindful that WFH is not like it used to be. In households where there is more than one person . . . there is no way to control some background distractions or noise. You now have all working from home with kids learning from home . . . there is now a new normal as it pertains to working from home and flexibility, empathy, understanding for others’ situations is key.This theme was largely comprised of comments related to the unrealistic expectations  that employers had regarding working from home during a pandemic. As an example, one contributor stated,A global pandemic creates a scenario in which mass amounts of people who’ve never or rarely worked from home now have to adjust to doing so, often in spaces not bought or rented for doing so, and often with a partner in the same situation.This comment clearly reflects the contributor’s frustrations that workplace meetings  and videoconference meetings, especially during a pandemic, are not the same. Likewise, another contributor wrote,While most comments in this theme agreed that meeting etiquette is important and necessary in the workplace, the comments cited above, as well as many others, imply that the COVID-19 pandemic has created a unique situation which, at least in the short run, may require some leniency and understanding about others and their ability to control distractions in their work/home environment.To answer the first research question we posed earlier, the results of our analysis suggest that some individuals believe that videoconferencing is, in some ways, better than face to face meetings. The perceived positive benefits include the use of polling, the chat function, and the ability to enhance relationships by seeing, and thereby learning, more about coworkers’ personal lives . In response to our second research question, we found that many of the frustrations faced by participants in videoconference meetings are consistent with those experienced by participants in face-to-face meetings. Starting late, lack of an agenda, having meetings that are too long, and having participants show up late or multi-task were mentioned in comments posted by contributors. These are all problems that the meeting science literature has identified in face-to-face meetings and have been found to reduce both meeting satisfaction and effectiveness. However, our results showed there were also important differences in the experiences faced by videoconference participants working from home.In response to our third research question, these frustrations were associated with all three of the expected factors: technology, participant behavior, and the unique situation resulting from the COVID-19 pandemic. An examination of our text mining results suggests that most contributors’ frustrations stem largely from issues related to how others were using the technology. Over 60% of the total comments focused on camera issues , whether the camera was on or off, and microphone issues . Another common comment was displeasure with having to watch others eating on camera. However, several stated that eating was often necessary due to many meetings being scheduled over the lunch hour. Some contributors also noted that seeing or hearing others’ background noises was distracting. This was largely a result of the COVID-19 pandemic in which employees found themselves forced to work from home and, at the same time, the home had become the school, playground, sports facility, and sanctuary.With the initial onset of the COVID-19 pandemic, many employees had to learn almost overnight how to use videoconferencing, and our findings suggest many appear to have merely “muddled through.” Given research evidence showing that employee satisfaction with meetings is a distinct component of their overall satisfaction and a significant source of job-related stress and well-being , it is iOur findings also suggest that many employees were unaware of social norms or meeting etiquette, thus organizations should provide expectations about how employees should present and/or conduct themselves in virtual work meetings. In addition, employees should be provided with training on ways to improve meeting structure by utilizing an agenda and establishing ground rules on meeting facilitation . Managers and senior organizational leaders play a key role in reinforcing the importance of this training, as well as modeling appropriate meeting structure and behaviors. Because some of the comments in this study cited problems with Zoom fatigue and back-to-back meetings, organizations should carefully consider whether videoconferencing is being overused. In some instances, an email, phone call, or use of a messaging system  may be more effective.While our research has contributed to the literature by highlighting the frustrations participants have with using videoconferencing platforms for work-related meetings, there are some notable limitations to our study. First, more participant information would have been helpful in determining whether frustrations differ for participants based on their occupation, managerial status, marital and family status, type of meeting , or hours spent per day in videoconference meetings. Secondly, those who contributed the comments in our analysis were not randomly selected, rather they were self-selected in that they made the choice to leave comments on the LinkedIn site. It is possible that their opinions may not be representative of all videoconference participants. However, our intent was not to test existing theory, but instead to tie our findings to relevant theories and provide direction for future research. In part, our findings contribute to the meeting science literature by identifying issues that are unique to videoconferencing. Using a lens of media naturalness, this study also provides new insight into many of the specific challenges with using this mode of communication . Yet, much remains unknown regarding how to maximize the satisfaction, engagement, and effectiveness of videoconferencing as means for work communication. Given that widespread use of this communication medium is expected to continue in the future, we believe that it is important to address that gap by providing an agenda for future research. More specifically, we developed three avenues  to guide future research see .While most of our proposed research questions relate to our findings, others expand on existing research. For example, a concern of remote workers is that lack of visibility will lead to slower career progression and fewer mentoring opportunities . We recoIn a face-to-face work setting, teams often have impromptu meetings as they pass each other in the hall or at the water cooler . Since s


This cohort study compares high-risk human papillomavirus (HPV) detection using menstrual blood testing with capture sequencing vs cervical HPV testing. Is menstrual blood high-risk human papillomavirus (hrHPV) capture sequencing a feasible and accurate approach for HPV detection?In this cohort study of 120 women with hrHPV, menstrual blood hrHPV capture sequencing had a high concordance rate with cervical HPV testing and offered advantages in the detection of additional hrHPV genotypes and true negative samples.These findings suggest that menstrual blood hrHPV capture sequencing is a feasible and accurate self-collected approach for hrHPV detection. High-risk human papillomavirus (hrHPV) persistent infection is the major etiology of cervical precancer and cancer. Noninvasive self-sampling HPV testing is a promising alternative cervical cancer screening for avoiding stigma and improving patient willingness to participate.To investigate the feasibility and accuracy of menstrual blood (MB) hrHPV capture sequencing in hrHPV detection.This cohort study collected 137 sanitary pads from 120 women who were premenopausal and had hrHPV as detected by cervical HPV GenoArray testing. Patients were recruited from September 1, 2020, to April 1, 2021, at Central Hospital of Wuhan, China. Target capture sequencing was performed to determine hrHPV genotypes in MB. Sanger sequencing was performed as the criterion standard for detecting hrHPV genotypes among enrolled women. Data were analyzed from April 1 through June 1, 2021.Complete concordance, incomplete concordance, and discordance of MB hrHPV capture sequencing and conventional HPV testing were defined according to genotype overlapping levels. Concordance of the 2 detection methods and comparative power of MB hrHPV capture sequencing during different menstrual cycle days (MCDs) were the main outcomes.P < .001). Among 24 samples with incomplete concordance or discordant results, 11 samples with additional hrHPV genotypes (45.8%), 5 true-negative samples (20.8%), and the correct hrHPV genotypes of 2 samples (8.3%) were correctly identified by MB hrHPV capture sequencing. MB hrHPV detection of hrHPV was equivalent on different MCDs, with an MB hrHPV–positive rate of 27 of 28 patients (96.4%) for MCD 1, 52 of 57 patients (91.2%) for MCD 2, 27 of 28 patients for MCD 3, 4 of 4 patients (100%) for MCD 4, and 3 of 3 patients (100%) for MCD 5 (P = .76). The sensitivity of the MB hrHPV capture sequencing was 97.7% .A total of 120 enrolled women with hrHPV  provided 137 sanitary pads. The overall concordance rate of MB hrHPV capture sequencing and cervical HPV testing was 92.7% , with a κ value of 0.763 (These findings suggest that MB hrHPV capture sequencing is a feasible and accurate self-collected approach for cervical cancer screening. This study found that this method is associated with superior performance in identification of HPV genotypes and true-negative events compared with cervical HPV testing. Given that it is a biological fluid with periodic expulsion, MB is easy to collect. This suggests that HPV testing based on sanitary pads may be a convenient and noninvasive approach. More importantly, next-generation sequencing (NGS) for HPV detection, emerging as a highly sensitive method for HPV genotyping, has not yet been applied to MB HPV testing, to our knowledge. This study was designed to investigate whether MB hrHPV capture sequencing may be a feasible and accurate approach to detecting hrHPV infection among women who are premenopausal.STROBE) reporting guideline.Ethics approval was obtained from the institutional review board of the Central Hospital of Wuhan. All patients agreed to participate and provided signed informed consent before enrollment. This study is reported following the Strengthening the Reporting of Observational Studies in Epidemiology . The 21 HPV GenoArray Diagnostic Kit (Hybribio) was used to detect hrHPV infection in cervical smears. This kit has been used in many cervical screening studies, with approval and recommendation from the China National Medical Products Administration for HPV testing.15 The diagnosis of cervical intraepithelial neoplasia (CIN) and cervical cancer were confirmed by the pathology of cervical biopsies or excisions.We excluded recruited patients who refused to participate in this study, had no menstruation within 3 months of hrHPV testing, or had a total menstrual bloodstain area on a sanitary pad of less than 3 cm × 3 cm . EnrolleSelf-provided commercial sanitary pads were used to collect MB from enrolled patients. The discarded sanitary pads were preserved in sterile sealed plastic bags that we distributed to enrolled patients in advance; pads were then placed in the refrigerator at −20 °C within 1 hour after being removed and stored until further testing. The menstrual cycle day (MCD) was recorded according to patient self-report. Patients were encouraged to provide multiple sanitary pads for different MCDs of their current menstrual cycle.A commercial Tiangen dried blood spot DNA extraction kit (Tiangen Biotech) was used to extract MB DNA from sanitary pads according to the manufacturer’s protocol. The concentration of DNA was confirmed using the Qubit 4.0 fluorometer and Qubit dsDNA high-sensitivity (HS) assay kit (Invitrogen by Thermo Fisher Scientific), and the purity of DNA was determined by NanoDrop One spectrophotometer (Thermo Fisher Scientific). Extracted MB DNA was stored at −20 °C.NC_001526.4(HPV16), AY262282.1(HPV18), HQ537687.1(HPV31), HQ537688.1(HPV33), HQ537730.1(HPV35), LR862071.1(HPV39), EF202167.1(HPV45), LR862072.1(HPV51), HQ537751.1(HPV52), LR862079.1(HPV53), EF177181.1(HPV56), HQ537777.1(HPV58), EU918767.1(HPV59), EF177191.1(HPV66), and FR751039.1(HPV68). We designed a custom capture panel using the Integrated DNA Technologies (IDT) target capture probe design website and ordered the biotinylated RNA probe library from IDT. Probe sequences were subjected to deduplication, and those homologous to human sequences were removed. The resulting probe library comprised 120-nucleotide RNAs complementary to 1 strand of 1 of the 15 types of hrHPV at 2-fold coverage. Readers interested in the biotinylated RNA probe library should please contact the corresponding authors for more detailed information.Whole-genome sequences of 15 types of hrHPV were obtained from GenBank. The accession numbers were as follows: Mechanical disruption by Bioruptor Pico (Diagenode) was performed to shear MB DNA. Agencourt AMPure XP beads (Beckman Coulter) were used to purify sheared DNA fragments. MB DNA libraries were prepared using the TargetSeq enrichment kit (iGeneTech) according to the manufacturer’s protocol.Hybridization capture with the previously listed 15 types of hrHPV probes was performed at 65 °C for 16 hours. After polymerase chain reaction (PCR) amplification, the concentration of PCR products was confirmed using Qubit 4.0 fluorometer and Qubit dsDNA HS assay kit (Invitrogen); the size of PCR products was confirmed using Qsep100 bioanalyzer (BIOptic). Products in the final library ranged from 270 base pairs to 320 base pairs in length. Sequencing was performed using Illumina NovaSeq PE150.17 provided details on the HPV genotyping method. Briefly, after filtering of low-quality reads and duplicated reads, all clean reads were aligned to the merged 15 hrHPVs whole-genome sequence. HPV-positive genotypes were then identified with mapping coverage of 50% or more and effective mean depth of ×30 or more. Next, we compared genotyping results of MB hrHPV capture sequencing with those of conventional HPV testing. Here, we defined the degree of detection concordance between MB hrHPV capture sequencing and conventional HPV testing as follows: if there was at least 1 overlapping hrHPV genotype between testing methods among all genotypes found in 1 patient's sample, it was defined as concordance. If the 2 were identical, it was defined as complete concordance; otherwise, it was defined as incomplete concordance. If there was no overlapping hrHPV genotype between testing methods, it was defined as discordance. Sanger sequencing of cervical smears was performed as the criterion standard for hrHPV genotypes  was used for statistical analysis. Normal distribution data were shown as mean (SD). A total of 120 patients with hrHPV detected by cervical HPV testing were enrolled  among 141 recruited patients. Among all recruited patients, 12 individuals (8.5%) refused to participate in the study, 4 patients (2.8%) left Wuhan for job transfer, 3 patients (2.1%) were too busy to attend the study, 2 patients (1.4%) went to other hospitals for personal reasons, 2 patients (1.4%) lived too far away from our hospital to participate, and 1 patient (0.7%) did not provide a reason for not participating. We excluded 3 patients because they had no menstruation within 3 months of hrHPV testing and 6 patients because they had a menstrual bloodstain area of less than 3 cm × 3 cm.By cervical HPV testing in the study population, 20 patients were positive for HPV 16 (16.7%), 12 patients were positive for HPV 18 (10.0%), and 93 patients were positive for other hrHPV genotypes (77.5%). The 3 most common hrHPV genotypes were HPV 52 , HPV 58 , and HPV 16. Multiple hrHPV infection was detected among 20 patients (16.7%).There were 43 patients referred to colposcopy and cervical biopsies according to 2019 ASCCP consensus guidelines, and 5 patients underwent cervical conization. Additionally, CIN 1, CIN 2, and CIN 3 were confirmed in 7, 3, and 2 patients by pathology, respectively. There was no evidence of CIN or cervical cancer among the other 108 patients.P = .16) (P < .001) (P = .85) (There were 113 patients (94.2%) who tested positive for MB hrHPV by capture sequencing. In MB hrHPV capture sequencing, 22 patients were positive for HPV 16, 12 patients were positive for HPV 18, and 79 patients were positive for other hrHPV genotypes. Distributions of HPV 16 and HPV 18 vs other hrHPV genotypes were not significantly different in cervical HPV testing (27 patients vs 93 patients) compared with MB hrHPV capture sequencing (34 patients vs 79 patients) (P = .16) A. In MB  < .001) B. DistriP = .85) C.There were sanitary pads from 28 patients (23.3%) for MCD 1, 57 patients (47.5%) for MCD 2, 28 patients (23.3%) for MCD 3, 4 patients (3.3%) for MCD 4, and 3 patients (2.5%) for MCD 5. The sanitary pads of MCD 2 were preferred because there was typically a larger amount of bleeding.P = .76).The MB hrHPV–positive rate was 27 of 28 patients (96.4%) for MCD 1, 52 of 57 patients (91.2%) for MCD 2, 27 of 28 patients for MCD 3, 4 of 4 patients (100%) for MCD 4, and 3 of 3 patients (100%) for MCD 4. The MB hrHPV–positive rates for different MCDs were not statistically significantly different (P = .71).Additionally, 14 patients provided 2 or 3 sanitary pads from different MCDs during a single menstrual period. Among these individuals, 12 patients (85.7%) tested positive by MB hrHPV for each MCD, and the overall MB hrHPV–positive rate for any MCD was 14 patients (100%) . There wP < .001).A total of 137 sanitary pads were provided by 120 enrolled patients. The complete concordance rate of the detection methods was 113 pads (82.5%), and the incomplete concordance rate was 14 pads (10.2%). Thus, the overall concordance rate was 92.7% , with a κ value of 0.763 , 5 true-negative samples (20.8%), and the correct hrHPV genotype of 2 samples (8.3%). However, MB hrHPV capture sequencing also yielded 3 false-positive results and 3 false-negative results. Among 11 samples with additional hrHPV genotypes, conventional HPV testing missed 4 HPV 16 infections and 1 HPV 18 infection. Missed detection of HPV 16 or 18 may be associated with omission of colposcopy that should have been performed. Among 6 samples with false-positive or false-negative results detected by MB hrHPV capture sequencing, none were misidentified as HPV 16 or HPV 18 .Overall, MB hrHPV capture sequencing produced 126 true positive events, 3 false positive events, 3 false negative events, and 5 true negative events. The method had a sensitivity of 97.7%  .15 Menstruation is a physiological bleeding process during childbearing age. Tampons, sanitary pads, and menstrual cups used by women during menstrual periods may be adapted as convenient medical devices to collect MB. In this cohort study, 8.5% of recruited patients refused the invitation to participate in the study without giving any reasons, suggesting that the approach using tampons, sanitary pads, and menstrual cups was associated with decreased practical and psychological barriers to undergoing cervical cancer screening. Even in India, where there are several negative myths associated with menstruation, a study19 reported that 54% to 76% of eligible women volunteered to provide their menstrual pads and participate in MB HPV testing.According to the ASCCP consensus guidelines, it is recommended that women aged 25 to 65 years undergo cervical cancer screening; this population largely overlaps with the population of women at childbearing age.21 To our knowledge, our study was the first to detect MB HPV with NGS technology and found a high sensitivity of 97.7%. Moreover, strengths of capture sequencing included detection of additional hrHPV infections and multiple hrHPV infections, identification of true-negative samples, and identification of the real hrHPV genotypes among those misidentified by conventional HPV testing. These results were all validated by a third testing method, Sanger sequencing.Accurate hrHPV genotyping may play a crucial role in risk stratification and appropriate management of hrHPV. Compared with conventional HPV genotyping methods, NGS was associated with detection of HPV genotypes with high sensitivity.Our study also found that MB hrHPV–positive rates on different MCDs, from MCD 1 to MCD 5, were equivalent. Additionally, MB hrHPV–positive rates were similar among patients who provided 1 sanitary pad and those who provided more than 1 sanitary pad. These findings suggest that self-collected MB at any day of the menstrual cycle is acceptable, which also suggests the convenience of MB hrHPV capture sequencing. However, we recommend using 1 sanitary pad from MCD 2 for MB hrHPV capture sequencing because of this day usually has a larger amount of bleeding.There are several limitations to this study. First, self-collection of MB could be performed only during the menstrual period; thus, self-sampling time was subject to certain restrictions. Second, there were slight differences in the materials used to make the sanitary pads. We found that certain materials may affect DNA extraction. Third, the proportion of women who did not have hrHPV and who had CIN or cervical cancer was relatively low in our study. Expanding the sample size and further exploring the value of MB hrHPV capture sequencing in the detection of women who do not have hrHPV and have CIN or cervical cancer is needed in future studies.This study’s findings suggest that sanitary pads with MB may serve as medical devices for HPV detection. With the obvious convenience of this method, MB hrHPV capture sequencing may be associated with decreased stigma of gynecological examination and increased participation in cervical cancer screening. MB hrHPV capture sequencing was associated with superior performance compared with cervical HPV testing not only in detection of additional hrHPV infections and multiple hrHPV infections, but also in identification of true negative events and hrHPV genotypes misidentified by conventional HPV testing. These results suggest that MB hrHPV capture sequencing may be a feasible and accurate self-collected approach for cervical cancer screening.