Research has shown that Veterans with Substance/Alcohol Use Disorders (SUDs/AUDs) are at a greater risk for employment-related issues , and interventions such as Vocational Rehabilitation (VR) have been used as a tool to reduce employment obtainment and maintenance. The purpose of the current study was to evaluate acceptance rates and employment rates at closure for Veterans with SUDs/AUDs prior to the implementation of VHA Policy Directive 1163 (mandated that Veterans are not refused services based on prior or current SUD/AUDs). SUD/AUDs were coded to reflect DSM 5-TR criteria of active use and in-remission.Data from a VHA Vocational Rehabilitation program in the Veterans Integrated Service Network 12 network were obtained for the purpose of the current study.Findings showed that Veterans with AUDs were less likely to be accepted for VR services prior and after implementation of VHA Policy Directive 1163.When examining active and inactive SUDs/AUDs, findings showed that implementation of VHA Policy Directive 1163 was not effective for Veterans with AUDs. One factor that was not explored but could explain disparities in program acceptance rates is duration of program entry. If a Veteran has a consult placed for VHA Vocational Rehabilitation services, and their program entry date (date accepted) is a significant duration, then perhaps Veterans with active AUDs start drinking again given that they are waiting for vocational assistance. Thus, it would be important to assist Veterans with active AUDs into services in a timely manner (perhaps prior them being discharged from SUD treatment). Specifically, the current study will include an examination of the implementation of VHA Policy Directive 1163 and its impact for Veterans with SUDs.Vocational Rehabilitation (VR) is a program that assists people with disabilities in obtaining and maintaining employment that is compatible with their skills, abilities, functional limitations, and interests.4 and has also been referred to as Compensated Work Therapy (CWT).5 Per Policy Directive 1163, all VHA Medical facilities are required to provide supported-employment (SE) and transitional work (TW), and it is strongly encouraged the community-based employment services (CBES) be offered. Some programs are also encouraged to provide supported education , supported self-employment , and vocational assistance .The VHA VR program was formerly known as Therapeutic and Supported Employment (TSES),5 where Veterans with severe mental illness  or medical conditions  are eligible for the SE program. This programs following the Individual Placement and Support (IPS) evidence-based model, which incorporates 8 CORE functions: (1) open to all who want work, (2) competitive employment emphasis, (3) quick job search, (4) directed job development, (5) the individuals preferences guide decision making, (6) individualized supports that are long-term, (7) treatment integration, and (8) benefits counseling. Specific services may include (1) integration of vocational supports within clinical treatment, (2) assistance with obtaining competitive employment, (3) rapid job search, (4) systematic job development, (5) follow-along supports, (6) focus on Veteran preferences based on their strengths, skills, and interests, and (7) benefits counseling.6Program eligibility for each program is based on clinical need,7 VHA Directive 11635 specifically references 38 U.S.C. 1718, in that “program participants must not be held or considered employees of the United States for any Purpose. . .and program participants are not subject to criminal background investigations, including fingerprint checks as a condition of acceptance for services” (p.42). Veterans are paid an hourly wage (minimum wage or higher) for the time spent on their assigned worksite. CBES is designed for Veterans with a history of sporadic employment, issues with job retention, or difficulty with job searching.5 This program assists Veterans in locating employment and completing the application process, résumé development, practicing for interviews, and other employment-related barriers. The 2019 policy directive mandates that there is a zero-exclusion policy, which indicates that Veterans will receive CBES services regardless of clinical symptoms, legal histories, or other job readiness criteria. However, research has not yet investigated the impact of implementation of Policy Directive 1163 within the Veteran Health Administration (VHA) as it relates to services provided to Veterans with SUDs.Veterans without a severe mental illness or serious medical condition can be deemed eligible for either TW or CBES. TW is a clinical pre-employment VR program in VA medical center and/or business and industry in which Veterans are assigned a real work assignment for a specific and restricted time for the experience.8 Having an employment emphasis is important when working with Veterans with SUDs since employment status has been shown to be a strong predictor of treatment compliance.9 Given that individuals undergoing treatment for alcohol and substance abuse have poor work histories and low employment rates,10 the effectiveness that VR can have on a Veteran’s life is well documented.1114 Prior research has shown that employment at closure from VHA Vocational Rehabilitation is impacted by greater treatment intensity (higher weekly mean earnings and longer treatment duration), higher vocational functioning prior to admission (shorter length of time since employed for at least a month), and participation in Transitional Work (TW) within the VA medical facility where they earn tax-free financial incentive to engage in work-therapy.15 However, this study did not control for diagnosis  which is a variable that can impact the findings within this prior study.8 Moreover, prior research has shown that military Veterans continue to struggle with addiction even after receiving treatment for substance use disorders, and Veterans that are unemployed/not in the labor force were more likely to relapse than employed Veterans.16An estimated 1.1 million Veterans meet criteria for Substance Use Disorders (SUDs), with prevalence rates between 2016 and 2019 showing alcohol use was 57% to 68% and illicit drugs were 2.7% to 3.5%.17 disability,18 or limited labor force per residing geographic location. Moreover, Veterans with SUDs may not obtain competitive employment because they endorse high levels of agreement with statements that working (competitive employment) would lead to loss of benefits , and Veterans with SUDs agreed more strongly that they would rather turn down a job offer than lose financial benefits.19 Other factors that might impact labor force participation for Veterans with SUDs is because they not being provided services that can help reduce or eliminate employment-related barriers .Several reasons as to why a Veteran might have difficulty in obtaining employment may include co-occurring substance and psychiatric disorders,5 has been updated in August 2019 and has strictly indicated that no discriminatory practices are acceptable for Veterans with substance or alcohol use disorders (AUDs) “regardless of duration of sobriety, routine vocational testing, or required time in a treatment program or clinical services prior to participation in VHA Vocational Rehabilitation” (p. 43). The prior version of the Policy Directive4 also stated that “there are no required pathways to participation in any program component such as duration of sobriety, routine vocational testing, or required time in IT prior to placement in another modality” (p. 6). Despite these clear distinctions in the most recent version and prior version of Policy Directive 1163, research has not yet examined the role these policies have in acceptance rates. If disparities do exist for Veterans with SUD/AUD, then further evaluation is needed to determine if it is due to discriminatory practices or other factors where interventions/protocols are needing to be developed or modified.VHA Policy Directive 11635 on VHA VR program acceptance rates for Veterans with and without SUDs/AUDs. Furthermore,20 discussed the benefits of splitting SUD/AUD rather than combing both diagnoses, as findings have shown disparities in employment rates at closure for Veterans with SUD. Furthermore,20 found differences in employment status at closure for Veterans with active SUDs compared to Veterans with inactive SUDs (in remission). Although many factors may contribute to these discrepancies, the current study focused on disparities in acceptance rates at program entry. Thus, the purpose of the current study is to (a) determine if barriers related to acceptance into VR services through the Veteran Health Administration are impacted by SUDs/AUDs (both active and inactive), and (b) to study the impact of the implementation of VHA Policy Directive 1163 on acceptance rates, and (c) study the impact of implementation of VHA Policy Directive 1163 on employment rates at closure. The following research questions helped guide the study:The current study will focus on evaluating the impact of VHA Policy Directive 1163How does SUDs/AUDs predict acceptance rates for Veterans referred to a VHA VR program?How does active versus inactive SUDs/AUDs predict acceptance rates for Veterans referred to a VHA VR program?How has the implementation of VHA Policy Directive 1163 predicted acceptance rates for Veterans with SUDs/AUDs?How has the implementation of VHA Policy Directive 1163 predictive acceptance rates for Veterans with active and inactive (in remission) SUDs/AUDs?How has implementation of VHA Policy Directive 1163 predicted employment rates for Veterans with and without SUDs/AUDs, including active and inactive status?A total of 2620 Veterans served by a VHA VR program located within the Veterans Integrated Service Network 12 (VISN-12) were obtained for the current study. Only Veterans who were enrolled in the program once during the timeframe of 2016 to 2021 were included in the study due to updated variables/information being included in the intake forms following 2016 (post accreditation obtainment from the Commission on Accreditation of Rehabilitation Facilities (CARF)). However, Veterans on supplemental security income (SSI) or social security disability insurance (SSDI) were also excluded, given that there was a small percentage of program participants that were enrolled in either program, and it would not be appropriate to attempt to control for these variables (SSDI or SSI recipient) within our statistical analysis given the low frequencies.The final dataset consisted of 923 Veterans with the following SUD/AUD categories. Approximately half the Veterans  did not have an AUD or SUD diagnosis, and when examining active versus inactive, descriptive analysis revealed the following frequencies, including: including active SUD , inactive SUD , active AUD , and inactive AUD . The average age of the sample was 57.67 (SD = 12.50), and most of the sample were of the male sex . The majority of the sample had a high school diploma or GED . Prior to the completion of any participation within this current study, the primary researcher submitted the proposal to Institutional Review Board (IRB) for the U.S. Department of Veteran Affairs. A letter was provided and indicated that no formal review process was required to use this data because there was no identifying information  and that the researcher was approved for this study. A co-author on the current study received the same response from their University’s IRB, and therefore the data was analyzed to answer the research questions.2 are offered at every medical center within the 18 Veterans Integrated Services Network (VISN), which is a regional system designed to work together to meet local health care needs.21 A program within VISN 12 was utilized in the current study. The program continuously collects information into a data base (Microsoft Access), which includes intake information such as demographic information, treatment team members, educational and employment history, core vocational objectives, family/culture/community background, military service, legal issues, medical and mental health diagnoses and treatment, and employment goals (long-term/short-term). This information is collected via the Computerized Patient Record System (CPRS) and an intake interview (self-report). A veteran may be denied program entry for the following reasons: (1) unable to contact, (2) obtained a job prior to program entry—between consult and initial meeting, (3) pursuing SSI/SSDI, (4) future medical procedure preventing a delay in ability for services, (5) lack of medical clearance from the medical provider, and (6) not interested in obtaining competitive employment—Veteran is referred by their provider but not really interested.VHA Vocational Rehabilitation Services22 which indicates a person has met criteria for less than 3 months (active usage), and remission status indicates the person who had once met criteria for SUD/AUD has not met criteria for more than 12 months (not counting the presence of cravings). Early remission . The date of August 19, 2019 was used to split the data, and to avoid crossover effects, we eliminated Veterans from the data analysis inclusion that started prior to the implementation of VHA Policy Directive 1163 but continued to be served after implementation. The program used for the current study incorporated the guidelines from the new Policy Directive on the date of release.Initially, the data was downloaded into excel, and medical records within CPRS was reviewed to verify information was entered accurately . Active and inactive (in remission) SUD/AUD were reviewed within the problem list and associated medical records to determine if the problem list was accurate (sometimes this information is not updated). For example, recent mental health notes will often times indicate active problems and a biopsychosocial narrative that is not reflected in the problem list. Active and in-active (in remission status) were defined using the DSM 5-TR,5 Analyses were completed using IBM SPSS Statistics (version 27) software. Descriptive statistics were obtained, and the variables were analyzed within each of the research questions.Prior to analyzing any data [years 2012-2021], the data was limited so that it would reflect Veterans served between 2016 and 2021. The data was coded so that acceptance rates  and employment rates at closure  were dichotomous. Additionally, the independent variables were dummy coded into a dichotomous variable: active alcohol use disorder (yes/no), inactive alcohol use disorder (yes/no), active substance use disorder (yes/no), inactive substance use disorder (yes/no). Inactive substance/alcohol use disorder are Veterans that have these diagnoses in remission (no symptoms other than cravings for more than 12 months as indicated per the DSM 5 TR). The VHA VR policy directive variable was represented by splitting the data into before and after August 13, 2019, which was the date of official implementation.23For all research questions, binary logistic regressions were performed to evaluate how the outcome variables of acceptance rates and employment rates at closure were impacted by the implementation of VHA Policy Directive 1163. Within SPSS, the variables were inserted as categorical variables within the binary logistic regression analysis feature, and ODD ratios were obtained for significant findings. For the summary of descriptive information contained within the results section prior to the research questions, the equity gap was calculated by taking the difference between each subgroup’s acceptance rate and the overall acceptance rate to show the percentage point gap.Descriptive analysis revealed that a total of 363 (39.3%) of Veterans were accepted for VHA VR services between 2016 and 2021. From this total, there were 70 (7.58%) Veterans with active SUDs and 75 (8.13%) with active AUDs that were accepted for VHA VR. Visually, there appears to be an equity gap of 31.72% (SUDs) and 31.17% (AUDs) for acceptance into the program. The descriptive analysis also revealed that approximately 35.18% (SUDs) and 41.21% (AUDs) are accepted for services, when compared to Veterans without these diagnoses. The following research questions provide more specific information as to the significance of substance/AUDs on acceptance into the VHA VR program.2 = 0.557, P = .456), AUD , and the interaction of SUD/AUD  were not significant. When removing the interaction from the logistic regression model, AUD  was significant. See A binary logistic regression analysis was performed to determine if SUD or AUD significantly predicted program acceptance. Findings showed that SUD , inactive AUD , and inactive AUD  = 2.256, P = .133) were not significant. Veterans with active AUD were less likely to be accepted into the VHA VR program . A separate binary logistic regression was used to measure interactions and simple main effects for the following categories: none, active AUD/SUD , inactive AUD/SUD , active AUD / inactive SUD , and active SUD / inactive AUD . See A binary logistic regression analysis was performed was performed to examine active SUD, inactive SUD, active AUD, inactive AUD on program acceptance rates. Findings showed that the active SUD . No other significant findings were shown, including the implementation of policy directive for Veterans with SUDs  and Veterans diagnoses with both an SUD and AUD . A binary logistic regression showed no significant differences in acceptance rates between Veterans with and without a diagnosis of SUD , AUD , or both an SUD/AUD diagnosis  prior to the implementation of VHA Policy Directive 1163. As shown in A binary logistic regression analysis was performed to determine if the implementation of VHA Policy Directive 1163 influenced acceptance rates for Veterans with SUDs, AUDs, and both SUDs/AUDs combined. Findings showed that Veterans with AUDs were less likely to be accepted for program services after implementation of the directive . As shown in 2 = 1.087, P = .297), inactive SUD , and inactive AUD .A binary logistic regression analysis was performed was performed to examine the impact of implementation of VHA Policy Directive 1163 on program acceptance rates for Veterans with active and inactive SUD/AUD. Findings showed that Veterans with active AUDs were more likely to be accepted prior to implementation , inactive SUD , and inactive AUD . Veterans with active AUDs were less likely to be accepted for services prior to implementation of VHA Policy Directive 1163 . As shown in A binary logistic regression showed no significant differences in acceptance rates between Veterans with and without a diagnosis of active SUD , AUDs , or Veterans with both SUD/AUD diagnoses . A separate binary logistic regression model was performed with SUD and AUD dichotomized into active and inactive (in-remission). Findings showed that Veterans with active SUD were more likely to exit with employment prior to implementation of VHA Policy Directive 1163 . No significant findings were shown for inactive SUD , active AUD , or inactive AUD  = 0.889, P = .346). A binary logistic regression showed no significant differences in employment rates at closure prior to the implementation of VHA Policy Directive 1163 for Veterans with SUDs  = 0.390, P = .406), AUDs , or Veterans with both SUD/AUD diagnoses . As shown in A binary logistic regression analysis was performed was performed to examine the impact of implementation of VHA Policy Directive 1163 on employment rates at closure for Veterans with SUDs and/or AUDs. There were no differences in employment rates prior to and after implementation for Veterans with SUDs .Initial descriptive statistics revealed that Veterans with SUDs and AUDs are less likely to be accepted for VHA VR services compared to people without these diagnoses. This was also evident for Veterans that had active diagnoses (not in remission) for both disorders. Meshberg-Cohen et alAs evident in research question 1, Veterans with SUD, AUD, and both SUD/AUD diagnoses had no differences acceptance rates for VHA Vocational Rehabilitation services. However, after dichotomizing each of these variables into active and non-active (in-remission), findings in research question 2 showed that Veterans with active AUD were less likely to be accepted into the VHA VR program. Given this significant finding, the implementation of VHA Policy Directive 1163 was examined to determine if differences existed. Findings showed that Veterans with AUD were less likely to be accepted for program services after implementation (research question 3). Again, this variable was examined by dichotomizing the variable into active and in-active (in remission) status, and findings showed acceptance rates were higher prior to the implementation of the policy directive.16 or (d) co-occurring psychiatric/medical diagnosis may have influenced additional barriers that prevent acceptance into the program . Other possibilities could be that (a) Veterans thought employment would impact their service-connected disability rating, (b) the COVID-19 pandemic limited employment options and Veterans elected to stay home to prevent contracting the virus, (c) transportation became an issue for attending appointments, or (d) the use of VA Video Connect (VVC) was not the preferred method of care for the Veterans.The exact reasoning for these findings are unknown, but possible explanations include that (a) perhaps during the consult meeting, these Veterans indicated they were in a position to conduct their own job searches, (b) the length to be placed on a transitional worksite may have influenced relapse potential, and (c) the Veteran re-entered treatment,20 was consistent with current study findings. The effectiveness that VR can have on a Veteran’s life is well documented,1114 and research is informative in that longer treatment duration, higher vocational functioning prior to admission (shorter period of last employed) and participation in the TW program is beneficial in improving employment outcomes.15 However, some explanations to the current study findings may include co-occurring SUD and psychiatric disorders,17 disability,18 limited labor force per residing geographic location, or Veterans that are unemployed/not in the labor force were more likely to relapse than employed Veterans,16 or fear that they would lose financial benefits so Veterans with SUDs will turn down job offers.19Prior research showing the Veterans with SUDs are less likely to be employedThe aforementioned findings described are somewhat surprising, given that Veterans with active AUD had disparities in acceptance rates, and results from research question 5 showed disparities in employment rates at closure for Veterans with active SUDs. Further exploration is necessary for both ends of the VHA VR program, as perhaps earlier intervention  would allow for work-related issues  to be addressed during treatment. Other suggestions might include having benefit counseling incorporated within early meetings with Veterans to discuss how employment may or may not influence their loss of financial benefits . It is evident that more research is needed to determine which interventions will have the most impact on decreasing program acceptance and employment status at closure disparities.16 it is necessary for the intervention of VHA VR to be available to all Veterans. Further research should also focus on differences in employment and job retention rates, as the quality of the job may have impact on whether a Veteran retains employment. If the quality of the position obtained is rated differently for Veterans with and without SUDs, this may explain relapse and other issues for Veterans. This will likely result in a policy directive update.Given the several findings from the analyses ran, it appears that the implementation of VHA Policy Directive 1163  may have contributed to the inequities of program acceptance (active AUD) and employment rates at closure active SUD) for Veterans. Since prior research has shown that relapse potential is higher for Veterans with SUDs and are unemployed,24 Other variables that might influence acceptance and employment rates at closure from VHA Vocational Rehabilitation may include other factors such as medical disability and co-occurring psychiatric conditions. As such, demonstrating causality was a limitation of the study.The study is not without limitations. First, this study was used on one VHA VR program due to the difficulty of collecting consistent program evaluation data. Each program collects information pertaining to acceptance dates, program assigned to, closure dates, there are not mandatory policies that dictate what additional variables are collected. For example, some programs may collect data as to whether a Veteran is currently enrolled in substance abuse treatment, whereas other programs may not. Due to the inconsistency in program related data collection processes, it was more appropriate to focus on one program at the current time. Another limitation is data entry errors. Veteran information is entered within the data collection database and verified within the medical management system (CPRS) at the VA, but errors may have still occurred in terms of data entry. Lastly, even though the findings appear promising in terms of the impact of the VHA Policy Directive 1163, other variables may influence the findings, thus impacting the influence of showing causality. In order to demonstrate causality, (1) the cause must come before the effect, (2) the variables must co-vary (be related), and (3) there must not be any confounding variables that could explain the relationship on the dependent variable.2530 and the implementation of telemedicine (VA Video Connect) occurred during the COVID-19 pandemic.3133The current study was unable to determine if this was also a factor as to whether Veterans were not accepted into the program . Additionally, the impact of COVID-19 may explain disparities in employment rates at closure during the post-implementation phase of Policy Directive 1163, as a little over 1 year the COVID-19 pandemic changed the landscape of the United States, and Vocational Rehabilitation service delivery models in the public sector5 has strictly indicated that no discriminatory practices are acceptable for Veterans with substance or alcohol use disorders (AUDs) “regardless of duration of sobriety, routine vocational testing, or required time in a treatment program or clinical services prior to participation in VHA Vocational Rehabilitation” (p. 43). However, when examining active and inactive SUDs/AUDs, findings showed that implementation of VHA Policy Directive 1163 was not effective for Veterans with AUDs. One factor that was not explored but could explain disparities in program acceptance rates is duration of program entry. If a Veteran has a consult placed for VHA Vocational Rehabilitation services, and their program entry date (date accepted) is a significant duration, then perhaps Veterans with active AUDs start drinking again given that they are waiting for vocational assistance. Thus, it would be important to assist Veterans with active AUDs into services in a timely manner (perhaps prior them being discharged from SUD treatment).There were several findings from the current study that showed VHA policy directive 1163 was effective in reducing the acceptance rate inequities for Veterans with and without SUDs/AUDs. This appears promising as VHA Policy Directive 1163There are several directions that future research can focus on for Veterans with SUDs/AUDs receiving VHA VR services. Given these results at the micro-level, conducting a national-level study would add strength and clarity as to whether the policy directive was effective across all VHA VR programs. Other research could include comparing active/inactive (in remission) SUDs/AUDs on closure status  would be important to see the impact of VHA Policy Directive 1163 and COVID-19. Examining co-occurring psychiatric conditions with SUDs/AUDs would determine if additional supports are needed depending on psychiatric groupings . Given that there are 3 primary programs contained within VHA VR , examining the VHA policy directive and COVID-19 pandemic would be an important component to determine if policy changes are necessary to assist in reducing the inequities (if they exist) within each program for acceptance and closure status.


Background: Each year 604,127 new cases of cervical cancer (CC) are diagnosed, and 341,831 individuals die from the disease. It is the fourth most common cancer among women and the fourth most common cause of death from female cancers worldwide. The pathogenesis of CC is associated with human papillomavirus (HPV) infections and consists of several steps involving cell proliferation outside the human body’s control mechanisms. Strategies to prevent CC are based on screening and vaccination. Scope of the Review: The aim of this paper was to collect and analyze the available literature on the issue of CC prevention and the impact of the COVID-19 pandemic on its implementation. For this purpose, PubMed and Google Scholar databases were searched using keywords, such as “cervical cancer”; “HPV”; “prevention”; “prophylaxis”; “vaccination”; “screening” and “COVID-19” in different variations. Only articles published since 2018 were included in the study. Conclusions: Selected European countries have different CC prevention programs funded by national budgets. This translates into observed differences in the risk of death from CC . COVID-19 pandemic due to disruption of CC screening may exacerbate these differences in the future. To improve the situation, new screening methods, such as p16/Ki67, HPV self-testing, and the use of artificial intelligence in colposcopic assessment, should be disseminated, as well as free HPV vaccination programs implemented in all countries. The search for new solutions is not without significance and entails ultra-sensitive screening tests for risk groups , HPV vaccines with shorter dosing schedules, and new therapeutic pathways using nanotheranostics.  Each year 604,127 new cases of cervical cancer (CC) are diagnosed and 341,831 individuals die from the disease. It is the fourth most common cancer among women and the fourth most common cause of death from female cancers worldwide [The pathogenesis of CC is associated with human papillomavirus (HPV) infections and consists of several steps involving cell proliferation outside the human body’s control mechanisms. This process results in a cascade of malignantly transformed cells in the following order: hyperplasia, dysplasia, carcinoma in situ, and invasive carcinoma . HPV invThe aim of this paper was to collect and analyze the available literature on the issue of CC prevention and the impact of the COVID-19 pandemic on its implementation. For this purpose, PubMed and Google Scholar databases were searched using keywords, such as “cervical cancer”; “HPV”; “prevention”; “prophylaxis”; “vaccination”; “screening”, and “COVID-19” in different variations. Only articles published since 2018 were included in the study.HPV oncoproteins E6 and E7, which prevent tumor suppressor genes from functioning properly by disrupting cell cycle checkpoints, play a key role in CC oncogenesis. The E6 protein degrades p53, which allows cells to continue replicating. The E7 protein causes an early entry into the S phase of the cell cycle through the degradation of pRb . The aboResults from a study published in 2021 of 40,509 women showed that E6/E7 mRNA detection had the highest sensitivity among conventional cytology and p16/Ki-67 testing. Considering these findings, the E6/E7 mRNA assay appears to be a very good candidate for ultra-sensitive screening. The scientific consensus on the optimal sensitivity of tests used in CC screening remains an open question ,11. PoteThe HPV oncoprotein E7 affects cell growth processes by interacting with histone deacetylases (HDACs). Under physiological conditions, HDACs remove acetyl residues that inhibit transcription . NeverthIn conclusion, the process of CC oncogenesis is a target for new methods of prevention, prognosis of its severity, and creation of targeted therapies. Biomarkers p16/Ki-67 are being used increasingly and incorporated into standard protocols for conducting CC screening. E6/E7 mRNA tests and SOX1/SOX14 detection may become the starting points for making recommendations using ultra-sensitive screening tests especially in at-risk groups. Genetic aspects of CC oncogenesis warrant attention to the 6p21.3 HLA locus associated with heritable CC incidence. The above correlation can be used to develop special surveillance programs in genetically predisposed individuals. The apoptosis of cancer cells is an area of interest in terms of developing new therapies. HDAC inhibitors in CC can be used in combination treatment giving a similar therapeutic effect with fewer side effects. The JAK/STAT and Notch signaling pathways are responsible for the process of progression to CC. In the future, they may represent a predictive biomarker of treatment response and course of CC, as well as a point of interest for targeted therapies.p < 0.001) [Current tests used for CC screening include Pap smear-based cervical cytology, LBC, HPV DNA, and co-testing ,28. Pap < 0.001) . Despite< 0.001) . It is d< 0.001) .HPV infection can also be detected with a viral DNA test. HPV DNA tests are more sensitive than cervical cytology, so they can be performed less frequently (every 5 years). For the standard comparison test, the sensitivity is 98.7% and the specificity is 96% ,45. The There are currently 254 HPV molecular tests available with over 425 variants. They use several diagnostic methods, including polymerase chain reaction (PCR) with sequencing, restriction fragment length polymorphism (RFLP) analysis, and hybridization assays . A valid® , Cervarix® (against HPV16 and HPV 18 genotypes), and Gardasil 9® . Worldwide, at least one dose has been administered to nearly 118 million women [Current HPV vaccines include Gardasilon women . Global on women . Countrion women . Ninety on women . The spron women . It is eon women . Intereson women . Overcomon women .The beginnings of organized screening dates back to 1968, when Wilson and Jungner developed a catalog of criteria that a disease must have in order to be screened. In Europe, the key date for CC screening was 1993 with the publication of the European Guidelines for Quality Assurance in Cervical Cancer Screening, which set out the principles for CC screening. Another edition issued in 2015 precisely formulated the criteria that a screening program must meet, i.e., the age of the target group, the time intervals for receiving the screening test, and the algorithm for further management depending on the results . Table 2For both screening and HPV vaccination programs, there is no uniform regimen across Europe. Most of the countries listed base CC screening on Pap smears at intervals of every 3 years. The exception is Malta, which has included LBC in its screening program. HPV testing is applied in Belgium, Denmark, and some regions of Portugal. Of the European countries, the only country with full replacement of cytology in favor of HPV testing in the Netherlands. A program based on HPV testing has been launched in the country in 2017. Samples are collected by primary care physicians (GPs) and if women do not enroll, samples for self-testing are sent out . Almost The highest risk of death from CC among the countries shown is in Poland. The lack of a national HPV vaccination program is telling. The lowest risk of death among countries is in Malta, which, in addition to its HPV vaccination program, applies LBC-based screening. It seems reasonable to standardize the recommendations for CC prevention programs funded by budgets in European countries. There is an urgent need to implement HPV vaccination funding in countries like Poland. The reasons for the success of the prevention program implemented in Malta need to be evaluated in further studies.The COVID-19 pandemic has significantly affected the level of implementation of CC prevention. In the first few months after the pandemic outbreak, CC screening completion dropped by 90%, and HPV vaccination completion dropped by more than 70% (March 2020) compared to the pre-pandemic period. Removal of lockdown restrictions improved CC prevention implementation only slightly. Compared to the pre-pandemic period, 35% decrease in screening and 25–50% decrease in HPV vaccination implementation (June 2020) were observed . Estimat(a)No uniform standards of CC prevention for European countries;(b)Lack of implementation of a nationally funded HPV vaccination program in some European countries ;(c)Differences in risk of death from CC between European countries;(d)Continued widening of inequalities in CC prevention delivery due to disruptions caused by the COVID-19 pandemic.The presented arguments indicate that the path to the complete elimination of CC as a global public health problem by 2030 may prove extremely difficult:(a)The dissemination of new screening methods, such as LBC, HPV-Tests, p16/Ki67, self-testing, and use of AI in colposcopic evaluation;(b)The acceleration of the evaluation of the clinical utility of new diagnostics, e.g., ultra-sensitive E6/E7 mRNA assays, SOX1/SOX14, and new therapeutic pathways using JAK/STAT signaling pathways, Notch, or the concept of nanotheranostics;(c)The development of HPV vaccines with broader HPV genotype coverage and shorter dosing schedules.In conclusion, we would also like to highlight possible future directions to improve the implementation of CC prevention:


Human papillomavirus (HPV) negative cancers are associated with symptomatic detection, late-stage diagnosis, and worse prognosis. It is thus essential to investigate all possible infectious agents and biomarkers that could early identify these HPV negative cancers. We aimed to analyze and compare the metatranscriptome present in HPV positive and HPV negative cervical cancers. We analyzed the whole RNA sequencing files from 223 HPV negative cervical cancers , 223 HPV positive tumors and 11 blank paraffin block pools (used as controls) using Kraken2 software. Overall, 84 bacterial genera were detected, with 6/84 genera showing a positive median number of reads/sample and being present in both cervical tumor groups (HPV positive and negative). Viral reads belonged to 63 different viral genera, with 6/63 genera showing a positive median annotated read/sample value. No significant difference among genera was detected except for the presence of alpha-papillomaviruses. Metatranscriptome of bacteria and viruses present in HPV positive and HPV negative cervical cancers show no significant difference, except for HPV. Further studies are needed to early identify this biologically distinct group of cervical cancers. About 12 HPV types are nowadays classified as oncogenic, high-risk HPV genotypes, and persistent infection of these oncogenic HPV types is known to be a necessary cause for cervical cancer.Human papillomaviruses are a group of double-stranded DNA viruses which comprise up to 223 different types, with new types being continuously identified5. Cervical cancer is preventable, but it is still one of the most common cancers and causes of cancer-related death in women, worldwide.Although effective screening methods (cytology and HPV testing) exist and several effective prophylactic vaccines are available in the market to prevent cervical cancer, the annual number of new cases of cervical cancer is estimated to increase from 570,000 to 700,000 between 2018 and 2030, with the annual number of deaths rising from 311,000 to 400,0008. This percentage of HPV negative cancers may translate into women not being categorized correctly for the screening program and tumors being detected only when they had become symptomatic (very late). Of particular note, authors have shown that cervical cancer cases that appear to have lost HPV DNA seem to constitute a specific subgroup of cervical cancers with a different biological behavior (worse prognosis)10.Due to advances in molecular testing, the more sensitive method of HPV-based screening is now replacing cytology as the primary cervical cancer screening tool. This method translates into testing cervical samples for HPV DNA rather than morphological abnormalities and constitute a more automated and objective screening strategy. Women with a negative HPV test, have very low risk of subsequent cancer and may safely be re-called in three-seven years. Nevertheless, a significant proportion of cervical cancers (around 7%) appears to be HPV negative11.Efforts to find out and explain HPV negativity in cervical cancers have led scientists to reanalyze smears and retest these HPV negative tumors by using different approaches. Main explanations for HPV negativity have been sample inadequacy, false diagnosis, presence of cancers associated with types that were not targeted in the studies, and false negative results due to low sensitivity of the HPV detection methods13. However, these methods are biased to detect mostly known HPVs that bind specifically to designed primers and probes. Unknown HPV types, known HPV types that are distantly related as well as targeted HPV types presenting variations within probe/primer regions may escape amplification or hybridization17. To overcome this bottleneck, it is nowadays possible to perform unbiased metagenomic sequencing (not based on PCR) and detect all HPVs present in a sample, without prior knowledge on which types might be present19. Furthermore, if cDNA is sequenced, the data will reveal if there is viral transcriptional activity, essential for both initiation and maintenance of the malignant phenotype.Most HPV screening methods are focused on detecting high-risk HPV types and are based on PCR amplification of conserved regions in the L1 gene by consensus primers, followed by HPV genotyping identification by hybridization of amplicons to type-specific probesFollowing the three recommendations mentioned above, cervical tumors classified as HPV negative after (a) assuring sample adequacy, (b) reanalysis of corresponding slides/smears to confirm tumor diagnosis and (c) not revealing presence of HPV after performing an unbiased sequencing analysis, may be called truly HPV negative. Understanding the biology of truly HPV negative cervical cancers is urgently needed in the era of cervical cancer elimination.20. On the other hand, it is possible that another infectious agent may play a role in this specific subgroup of HPV negative cancers. Taking into consideration both possibilities, a search for an infectious cause/biomarker should focus on unbiased RNA sequencing of truly HPV negative cancers. We aimed to analyze and compare the metatranscriptome of HPV positive cervical cancers with the metatranscriptome of HPV negative cancers and assess whether there are differences that could act as biomarkers to early identify these HPV negative cancers.Cervical cancer is known to have an infection as cause, being HPV the primary predisposing factor. Truly HPV negative cervical cancers could have initially been caused by HPV but lost the virus as the tumor progressed. There is a very high proportion of cervical intraepithelial neoplasias (CIN) 3 that contains HPV and there are cases of HPV negative cancers that have been HPV positive in the earlier screening appointmentsE6/E7 genes instead of L1) was performed. Repeatedly negative samples decreased to 394/2850 . We then subjected all HPV negative carcinomas  to an unbiased RNA sequencing using Novaseq 6000 (Illumina Platform), generating high quality sequencing data with a median of 30 million reads per sample. RNA positivity was detected in 169/392, decreasing the percentage of cervical cancers negative for HPV from 18.5% to 7.8% (223/2850)15.In a previous study, we systematically genotyped all cervical cancer cases occurring in Sweden from 2002–2011 (n = 2850), and for those that were HPV negative , sample adequacy and correct diagnosis were analyzed and reanalyzed, respectively. After excluding samples that were not adequate (beta-globin negativity) and those whose diagnosis was not confirmed, a different PCR approach . A total of 11 blank paraffin blocks pools were used as negative controls. While sectioning each cervical tumor formalin-fixed paraffin-embedded (FFPE) block, blank paraffin blocks had been sectioned in between as control for contamination. These paraffin blocks were extracted in the same manner as the cervical tumors, pooled (each pool containing about 45 blank blocks) and sequenced together with the corresponding tumor blocks.21, which was run against a reference database containing all RefSeq bacterial and viral genomes (built in December 2020) with a 0.1 confidence threshold. A cut-off of 10 classified unique reads was used to discriminate positive genera for bacteria and viruses, and results reported all genera which comprised more than 1% of total bacterial or viral reads, respectively.High-quality non-human reads were classified using Kraken2 v. 2.1.121, with a 0.1 confidence threshold. A cut-off of 10 classified unique reads was used to discriminate positive species. Reads that corresponded to HPV genomes were subjected to visual inspection using Integrative Genomics Viewer to confirm mapping.As HPV was the key difference between the cervical tumors (and the only significant difference detected between the 2 groups), we also queried all high-quality non-human reads to a reference database containing all human papillomavirus nucleotide sequences deposited in GenBank until July 8th 2022  using Kraken2 v. 2.1.1Differences in bacterial/viral presence across the two groups (HPV positive and HPV negative cancers) were evaluated by comparing median unique reads with nonparametric Wilcoxon rank-sum test, and relative proportions of bacteria/viral communities among the HPV positive and HPV negative cervical cancers were analyzed using a two proportion Z-test and its associated p-value. Bonferroni correction was applied considering a 0.05 error rate  and statistical significance was then obtained if p < 0.0002.Ethical approval was granted by the Regional Ethical Review Board of Stockholm, Sweden (EPN-Dnr: 2012/1028/32). The Regional Ethical Review Board determined that, due to the population-based nature of the study, informed consent from study participants was not required (EPN-Dnr: 2011/1026–31/4). All methods were performed in accordance with the relevant guidelines and regulations.15. A total of 223 HPV negative cervical cancers were reported. The present study aimed to compare the metatranscriptome present in these 223 HPV negative cervical cancer specimens with the corresponding metatranscriptome present in 223 HPV positive cervical tumors.In a previous study, all cervical cancers diagnosed from 2002 to 2011 in the whole Sweden were collected and genotyped. HPV negativity was determined after sample adequacy confirmation, diagnose reanalysis and confirmation of cervical cancer, and not detecting HPV after both PCR and unbiased RNA sequencingThe median age at cancer diagnosis of the HPV negative cervical cases (n = 223) was 68 years (range 30–93 years) and the median age at cancer diagnosis of the HPV positive cervical cases (n = 223) was 56 years (range 24–95 years).The metatranscriptome analysis from RNA sequencing had a total number of 63.80 M annotated bacterial reads for the HPV positive specimens and 62.81 M annotated bacterial reads for the HPV negative specimens.A total of 84 different bacterial genera showing at least 10 reads and 1% of total bacterial annotated reads were detected within the 223 HPV positive and 223 HPV negative cervical tumors. Only 6/84 genera showed a positive median number of reads/sample for both specimen groups (HPV positive and HPV negative cancers) , Staphylococcus , Pasteurella , Burkholderia (5633 and 5643 reads), Paracoccus (4817 and 4955 median reads) and Bacillus (2898 and 3260 reads) were the genera detected in HPV positive and HPV negative specimens, respectively. All 6 genera were present in at least 87.89% of specimens. No statistical difference (p < 0.001) in median read level nor in proportion was detected when comparing any bacteria genera within HPV positive and HPV negative specimens , and the corresponding proportions were similar. From higher to lower number of median annotated reads/sample: Klebsiella, Staphylococcus, Pasteurella and Paracoccus being identified in 1/11 blank controls and Burkholderia and Bacillus in 5 and 3 blank controls, respectively.Analysis of controls (blank paraffin specimens) showed a total of 31 different genera with 28/31 genera being also detected in cervical cancer specimens. All 6 genera that showed positive median read values in cervical tumors, were also present in at least one of the blank controls, with The metatranscriptome analysis from RNA sequencing had a total number of 613,606 annotated viral reads for the HPV positive specimens and 575,734 annotated viral reads for the HPV negative specimens.Overall, 63 different viral genera were detected when analyzing the RNA metatranscriptome within HPV positive and HPV negative tumors, with 6/28 genera showing a positive median annotated read/sample value  was only detected for the Alphapapillomavirus genus . Alphapapillomavirus genus was detected in 142/223 HPV positive specimens and in 3/223 HPV negative specimens according to established cutoffs and reporting parameters .Three out of these 6 generaFurther analysis of HPV presence was performed by subjecting high-quality non-human reads to a more “complete” database containing thousands of human papillomavirus sequences deposited in GenBank using Kraken. The analysis revealed HPV positivity (considered when samples showed more than 10 reads/species) in all 223 HPV positive cervical tumors, 7/10 controls blank pools and 30/223 HPV negative cervical tumors. Visual inspection of reads using Integrative Genomics Viewer showed that the blank controls and HPV negative cervical tumors that turned out to be HPV positive with this analysis did in fact show more than 10 reads, but reads were very short (< 50 bp) and viral coverage was below 10%. All 223 HPV positive cervical tumors showed more than 10 reads and HPV coverage was above 10% for all specimens.Locarnavirus, Chlorovirus, Gemycircularvirus, Orthobunyavirus and Betabaculovirus, were present in 6/11, 9/11, 9/11, 10/11 and 11/11 blank pools, respectively.Analysis of controls (blank paraffin specimen pools) revealed presence of 74 different viral genera, with 30/74 genera being also present in HPV negative and/or HPV positive cervical cancer samples. Most of the genera (25/30) were present in less than half of the blank controls, while Cervical HPV negative cancers exist and have unique properties such as late stage diagnosed cancers with poor prognosis. In this paper, we compared the metatrascriptome from 223 HPV negative cervical cancers with the metatranscriptome corresponding to 223 HPV positive cancers to inspect if there was any difference between them.L1, E6/E7 as well as unbiased RNA sequencing. Furthermore, blank paraffin controls were used to assess possible contamination as well as presence of environmental communities, and Bonferroni correction was applied to prevent data from incorrectly appearing to be statistically significant (a common event when performing multiple comparisons).Strengths of this study include the use of HPV negative cancers whose diagnosis, sample adequacy and HPV result had been confirmed and analyzed with different methods in order to dismiss false negativity. FFPE specimens were reanalyzed by an expert pathologist and confirmed to indeed contain invasive cervical cancer tissue. Beta-globin was present in all specimens included in the study and HPV detection was performed by using PCR targeting 22. Literature agrees on reporting that “healthy” women show a vaginal microbiome with low diversity, dominated by Lactobacillus, and that one of the most prominent features of “disease” is an increase of pH (due to a decrease of lactate concentration), reduction of lactobacilli and a great diversity of bacterial vaginosis-related bacteria, which are primarily anaerobic bacteria23. Studies on HPV positive CIN and cervical cancers show higher diversity in vaginal microbiota, with depletion of Lactobacillus crispatus and increase abundance of anaerobic bacteria25. While our results from cervical cancer cases agree with the literature , microbiome differences between HPV negative and HPV positive cervical cancers have not been studied yet. No significant difference among present genera was detected except for the presence of alpha-papillomaviruses, which is in line with the fact that HPV is the only reported infectious agent so far associated with cervical cancer, supporting the hypothesis that loss of HPV may occur as the tumor progresses and may be the reason for the occurrence of such cancer which is almost 7% of all cervical cancers diagnosed. A weakness from the present study may comprise not having previous screening specimens from the corresponding women to see if HPV presence was detectable prior cancer diagnosis.Bacterial and viral communities have been already analyzed and compared between health and disease, specially thanks to the effort of the Human Microbiome Project (HMP), the first large study to address the diversity of microorganisms present in the different organs of the human bodygammapapillomavirus) and 3/223 HPV negative cervical cancers when querying sequencing reads to the RefSeq database. Genera were reported when they presented more than 10 reads and comprised at least 1% of total bacterial/viral reads/sample. A further investigation of HPV presence using a broader HPV database identified HPV in all HPV positive tumors, as well as in 7/10 controls blank pools and 30/223 HPV negative cervical tumors. Visual inspection of these reads revealed questionable calling for both the blank pools as well as the 30/223 HPV negative cervical tumors, where the viral coverage was below 10%.Human papillomaviruses were initially reported in 143/223 HPV positive cervical cancers  as well as the genome coverage to achieve accurate identification (e.g. at least 10%). Accepting number of reads/k-mers as only parameter is not enough, as artefacts/background/noise may produce false positivity27.There is no consensus about which cut-offs to use for HPV “calling” when performing sequencing analysis and there is an urgent need to establish thoseAlphapapillomavirus). Further studies are needed to possibly find differences and/or biomarkers to early identify this biologically distinct subgroup of HPV negative cervical cancers. As the study is clear regarding that the metatranscriptome does not differ much between HPV negative and HPV positive cancers, we suggest that it may be more rewarding to look for differences in the human genome and transcriptome between the HPV positive and HPV negative cervical cancers.In conclusion, the present study reports the metatransciptome analysis of both HPV negative and HPV positive cervical tumors and does not detect any statistical difference in bacterial/viral communities´ expression when comparing HPV positive and HPV negative cervical cancers (except for


Human papillomavirus (HPV) is a common infection principally spread through sexual activity. Most HPV infections are asymptomatic and resolve spontaneously. However, persistent infection may progress to cervical cancer. Highly efficacious HPV vaccines have been available since 2006, yet uptake into national programs has been slow in part due to cost. WHO guidelines call for a two-dose  schedule for girls 9–14 years of age. Post-hoc analyses of randomized trials have found high vaccine effectiveness following a single dose of vaccine. In order to provide additional data on the potential impact of single dose HPV vaccination in a real-world setting, we are conducting an effectiveness study among Thai schoolgirls. This is an observational study of a single dose (SD) or two doses (2D) of the bivalent HPV vaccine CERVARIX® (GlaxoSmithKline plc.) administered in a school-based program to 8–9,000 Grade 8 female students in two provinces of Thailand beginning in 2018; one province is assigned the SD, and the other the standard 2D regimen. The reduction in HPV vaccine-type prevalence will be assessed in each province two and four years after vaccination by comparing HPV prevalence in urine samples obtained through cross-sectional surveys of the immunized grade cohort as they age and compared to a historical “baseline” HPV prevalence of same age students. Human Papillomavirus (HPV) infection of the reproductive tract is common, principally spread through sexual activity. The majority of HPV infections are asymptomatic and resolve spontaneously. However, persistent infection with specific HPV types (most frequently HPV 16 and 18) may lead to precancerous lesions which if untreated may progress to cervical and some other cancers . As a reAll available HPV vaccines are virus-like particle (VLP) vaccines and have been shown to have high efficacy in randomized controlled trials . CERVARIDespite reductions in the cost of these vaccines through the Global Alliance for Vaccine and Immunization (GAVI) or tiered-pricing, the uptake of HPV vaccines into national programs has been slow particularly in low- and middle-income countries (LMIC) . BarrierPost-hoc analyses of randomized trials have found high vaccine effectiveness following a single dose (SD) of bivalent or quadrivalent vaccine –9. HowevSD HPV vaccination would enable twice as many female students to be covered with the same amount of vaccine supply, facilitate catch-up vaccination campaigns, and alleviate the overall economic cost of vaccine supply and delivery, while averting treatment costs of disease. WHO acknowledges that more data are needed to issue such a recommendation .In order to provide additional data on the potential impact of SD HPV vaccination in a real-world setting, we are conducting an effectiveness study of the SD and the standard two-dose (2D) regimens in two provinces in Thailand. Vaccination is administered in schools, mirroring the already implemented national Grade 5 HPV immunization program, but targeting Grade 8 females outside the grade eligibility.Primary objectivesDemonstrate effectiveness of SD HPV vaccination by a reduction in vaccine-type HPV prevalence (HPV16 and/or 18) at two and four years post vaccination compared to the prevalence among unvaccinated same grade female students collected in a baseline survey.Demonstrate effectiveness of SD and 2D HPV vaccine regimens are similar by comparing reductions in vaccine HPV-type prevalence at four years post vaccination compared with the baseline prevalence in the two provinces.Secondary objectivesEstimate prevalence of HPV infection in female students in high school Grades 10 and 12  and vocational school years 1 and 3 Estimate the distribution of HPV types detectedAssess HPV type-specific antibody response pre- and post-vaccination in a subset of participantsExploratory objectivesAssess comparability of sexual behavior between the two provinces among female students in Grades 8, 10 and 12  and vocational school years 1 and 3 Assess comparability of risk for HPV infection between G10/V1 and G12/V3 female students at baseline and at years 2 and 4 post vaccinationAssess possible herd protection conferred by the HPV vaccination in unvaccinated female students“Effectiveness of Single Dose or Two Doses of Bivalent HPV Vaccine in Thailand (IVIHPV1)” and identifier NCT03747770. Additional information regarding the ethical, cultural, and scientific considerations specific to inclusivity in global research is included in the The protocol was first approved by the IVI IRB (IVI HPV1 2018–005 V1.3) on 20 Nov 2018, the Thailand Ministry of Health EC  on 29 Nov 2018, and the Chulalongkorn University IRB (IRB No. 495/61 V1.0) on 4 Dec 2018. The US CDC IRB deferred to the IVI IRB 7 May 2019. This paper is based on the protocol version 6.0 dated 15 Dec 2021 This is an observational community effectiveness study of SD or 2D of CERVARIX® (containing HPV16 and HPV18) administered in a voluntary school-based program to Grade 8 female students less than age 15 years in two provinces of Thailand, Udon Thani and Buri Ram. The overall study is divided into four independent parts:Part A–Grade 8 vaccination and sexual behavior questionnaire (SBQ)Part B–Baseline cross-sectional survey (CSS) of HPV prevalence based on self-collected urine samples and SBQ (G10/V1 and G12/V3)Part C–CSS of HPV prevalence based on self-collected urine samples and SBQ two years after vaccination (G10/V1)Part D–CSS of HPV prevalence based on self-collected urine samples and SBQ four years after vaccination (G12/V3)Vaccine effectiveness will be assessed as the reduction in vaccine HPV-type infection measured in a CSS two and four years after vaccination, compared to the Baseline CSS. A subset of students in each province (N = 200) will be invited to participate in a sub-study to evaluate immune response to vaccination. This study will be conducted in two provinces in North-East Thailand, Udon Thani and Buri Ram, selected by the Ministry of Public Health based on the similarity of criteria such as size of the female student population, socio-economic parameters, comparability of self-reported sexual activity in a national survey, logistics feasibility, and high degree of acceptance of the Grade 5 HPV vaccine program by local authorities and communities. Each province is further sub-divided into Districts, each with a District Hospital and subordinate Health Centers . This puAll aspects of recruitment and enrollment will be conducted according to ICH E6(R2) GCP guidelines. For each of the activities described below, eligibility is assessed according to the inclusion and exclusion criteria . ParentsOpen label vaccination with either SD (Udon Thani) or 2D regimen (Buri Ram) are offered to all Grade 8 students younger than age 15 years between December 2018-February 2019 on a voluntary basis. A subset of 1500 students in each province are selected by a proportional and systematic sampling method and invited to complete the SBQ. For Grade 8 students less than 15 years of age, both a parental consent and student assent form is completed prior to enrollment for vaccination, and a separate assent form is obtained for the SBQ.Cross-sectional surveys (CSS) are intended to sample a representative subset of students in the province, and all schools willing to participate are included in the surveys. As sexual activity is expected to be higher among vocational students , and the overall prevalence of vaccine-type HPV infections is expected to be low, vocational students will be over sampled to achieve ~50% of all enrolled subjects. Based on the overall province and school-type sample size, school-specific target enrollments will be calculated to be proportionate to their grade enrollments. At each school, students will be selected to participate in the CSS based on a systematic sampling from an eligibility list. When selected students are either not eligible because of exclusion criteria or decide not to participate in the study, additional students are selected by the field staff using the same method until the school target enrollment is reached. If the school target enrollment cannot be met, study staff can over enroll at another school of the same type in order to meet the province target enrollment. In order to ensure student confidentiality, only student assent is required for enrollment in the CSS and SBQ. In the Year 2 and Year 4 CSS, the student vaccination status is verified and documented at the time of enrollment.For practical purposes, a non-random subset of 200 Grade 8 students in each province consenting to vaccination and living in close proximity of a District Hospital will be invited to participate in this sub-study. A blood sample will be taken prior to vaccination and at the time of the Year 2 and Year 4 CSS. Eligibility criteria are re-assessed by District Health staff at the time of blood sample collection. Both parental consent and student assent forms are completed for each blood draw prior to vaccination, and at G10/V1 and G12/V3.Parents or guardians, and participants are informed that participation in each activity is voluntary and that they are free to withdraw their consent or assent at any time upon request, without justification and without prejudice. Subjects who withdraw may request destruction of samples and deletion of their data. The Principal Investigator may also discontinue participation in case of any occurrence that in her/his judgment might be detrimental to the participants well-being, and the reason for their withdrawal will be recorded.CERVARIX® is a bivalent HPV vaccine manufactured by GlaxoSmithKline plc. and presented as a suspension containing purified viral L1 protein for HPV types 16 and 18 and administered by intramuscular injection. It is produced using a baculovirus expression system. Each 0.5 mL dose of the bivalent vaccine contains 20 μg of HPV16 L1 protein and 20 μg of HPV18 L1 protein formulated with AS04  recorded through the national surveillance system and reported as per national guidelines. The investigators will exercise due diligence in ascertaining, and accurately recording all reportable AEFI that vaccinated study participants may experience. Reported AEFI are linked to the study ID of the students. AEFI may also be reported to the MOPH EC as per local regulations.Urine samples are self-collected by the students at school using a commercially available urine collection device, Colli-Pee®  pre-labeled with coded subject ID. The device contains 7 ml of UCM preservative and collects up to 20 ml of the initial void of urine. This collection method has been successfully used in Bhutan and Rwanda for HPV prevalence assessments, and demonstrated a high degree of comparability to physician-collected cervical swabs in a pilot study in Thailand –18. UrinCobas® (Roche), a high throughput, qualitative assay system will be used for detection of HPV16 and 18 and 12 other HPV types  –21. ResiThe purpose of the immunogenicity study is to verify that the vaccine administered is immunogenic for HPV16 and 18 and to assess response to non-vaccine types  with potential cross-immunogenicity. Blood (5 ml) will be collected via antecubital venipuncture by trained phlebotomist into serum tubes and allowed to clot at room temperature. Sera will be aliquoted into 1 ml cryovials and stored at -70°C and shipped on dry ice to the US CDC laboratory for testing using multiplex direct IgG ELISA against L1/L2 HPV virus-like particles on the Meso Scale Discovery platform with chemiluminescent detection as described with minor modifications .The primary outcome is the vaccine effectiveness, or reduction in vaccine-type HPV prevalence (HPV16 and/or 18) as measured by Cobas® in a single time point urine sample collected through a CSS two and four years after vaccination compared to unvaccinated same grade female students from the Baseline CSS in each of the provinces. Four years after vaccination a non-inferiority comparison of SD and 2D vaccine effectiveness will be made in the SD and 2D provinces. As the analysis will use a non-contemporaneous control group (Baseline survey), and the composition of the groups and/or their sexual behavior may differ, an adjusted analysis will be conducted to account for imbalances in the populations between the two time points within the province, and between the provinces. The main indicator for imbalance in sexual behavior will be the prevalence of 7 non-vaccine, non-cross-reactive high-risk HPV types .The assumed prevalence of HPV16 and/or 18 in G10/V1 and G12/V3 female students in the two provinces for Year 2 and Year 4 CSS are 2% and 3%, respectively. Due to lack of data on HPV prevalence in young female students in Thailand and the uncertainty of our assumption, the sample size for Year 2 and Year 4 CSS will be re-assessed based on the actual prevalence of HPV infection in G10/V1 and G12/V3 from the Baseline CSS prior to the Year 2 CSS. Assuming a 90% vaccine coverage of Grade 8 students, the sample size of N = 2600 per province at Year 2, and N = 2,000 per province at Year 4 are calculated to provide >80% power to show the vaccine effectiveness of SD or 2D is greater than 50% using one-sided test at a 0.025 significance. At four years post vaccination, this sample size is calculated to provide 80% power to demonstrate the VE of SD is non-inferior to VE of 2D with non-inferiority margin of 10% using one-sided test at 0.025 significance level.For the assessment of antibody response to the vaccine, the sample size N = 200 per province is based on keeping the coefficient of variation (CV) of mean titer of HPV16 or HPV18 less than 2.5, so that the geometric mean titer (GMT) estimate can be compared between provinces.Vaccination. A limited amount of data is collected on a field source document including name, national ID, date of birth and date of vaccination. Each student agreeing to vaccination (or any other study activity) is assigned a pre-printed subject number in numerical and bar-code format which codes for province, school, a unique number, grade, and activity type . The pre-printed barcodes are affixed to the consent and assent documents and the source document, which are maintained only by the MOPH staff. Only the complete subject number, date of birth, date of consent or assent and date of vaccination are entered into the EDC system by study staff.Cross-sectional surveys. Each student’s assigned subject number in numerical and bar-code format on pre-printed barcodes is affixed to documents and urine sample containers. The SBQ is a web-based, self-administered questionnaire with a limited set of questions derived from the MOPH national survey regarding sexual behavior. Using their own cell phone or via a tablet or phone provided by study staff, students scan their assigned subject number barcode at a weblink and privately enter their responses independent of study or school staff.Serology. The same enrollment procedures are followed as described above. The blood sample collection is performed at the local health center.Vaccination. Vaccine coverage is the estimated percentage of female students who have received an HPV vaccination. Two types of vaccine coverage will be calculated in this study:Total vaccine coverage of Grade 8 schoolgirls: the total number of Grade 8 students that received at least one dose of the study HPV vaccine, or self-report previously receiving any HPV vaccine/ the total number of students in Grade 8 in the provincesPer protocol vaccine coverage of Grade 8 schoolgirls: the number of students in Grade 8 enrolled in the vaccination activity that completed the HPV vaccine regimen per protocol/ the number of eligible Grade 8 schoolgirlsOnly students vaccinated per protocol will be eligible to enroll as vaccinated students in the Year 2 and Year 4 post-vaccination CSS. The AEFI as defined in the Thailand national guidelines will be summarized as reported after each vaccination and analyzed descriptively.HPV prevalence. Cobas® results for vaccine-type HPV16 and 18 prevalence and Anyplex™ results for prevalence of HPV types 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, 68 (among Cobas-positive samples) will be reported by grade and by school type. The prevalence of HPV types 6, 11, 26, 40, 42, 43, 44, 53, 54, 61, 69, 70, 73, 82 will be calculated based on the Anyplex™ results of Cobas-positive samples, and of a subset of Cobas-negative samples, in order to estimate the frequency of these types in the Cobas-negative population. Because the sampling by school type is not proportional to enrollment, the HPV prevalence by province will be reported as a weighted prevalence of the two school types in the total population using Horvitz-Thompson adjustment [justment .Vaccine Effectiveness (VE). The crude VE is defined as the percent reduction of HPV16 and/or 18 prevalence in a vaccinated group compared to an unvaccinated group and given by:p1 is the prevalence of HPV infection (HPV16 and/or 18) at Year 2 or Year 4 post vaccination and p2 is the prevalence of HPV infection (HPV16 and/or 18) of unvaccinated students in the Baseline CSS in the corresponding grade and province.p1 and p2 denote the weighted HPV 16 and/or 18 prevalence rates in the Baseline and Year 2 and Year 4 surveys, respectively. Similarly, q1 and q2 denote the weighted overall prevalence rates for the non-target genotypes in the Baseline and Year 2 and Year 4 surveys, respectively. The VE will also be adjusted using differences in the proportion of self-reported sexual activity from the SBQ.In addition, an adjusted VE will be computed by three methods as part of a sensitivity analysis and to account for the potential confounding effects of imbalance in age distribution and sexual activity between the non-contemporaneous groups. First, a simple adjusted VE will be calculated which adjusts only for the relative proportion of the 7 non-target HPV types  with no evidence of vaccine cross protection using the formula:Finally, a propensity score will be computed from a logistic regression that contained age and binary test result of each of 7 non-target HPV types as covariates. VE stratified by quintiles of propensity scores will be computed.Non-inferiority test. The VE difference between the SD and 2D regimens (SD minus 2D) with the corresponding 95% confidence intervals (CI) will be calculated to test the VE of SD is non-inferior to VE of 2D with non-inferiority margin of 10% at Year 4.Herd protection. This exploratory analysis will only be conducted if there is a sufficient number of unvaccinated students who enroll in the Year 2 and Year 4 surveys. The crude herd protection (HP) will be the percent reduction of HPV16 and/or 18 prevalence among unvaccinated students at Year 2 or Year 4 post vaccination as compared to the prevalence in the corresponding grade and province in the Baseline CSS. An adjusted HP will be calculated using the same methods as for adjusted VE.Serology. The HPV type-specific antibody titers at Baseline, Year 2 and Year 4 post vaccination will be logarithmically transformed to better approximate normality and reported as a weighted GMT average with two-sided 95% CI by province.CI for a single proportion will be defined using the Wilson method and a CI for a difference between independent proportions will be computed using the extension of the Wilson method and CI for a ratio of proportions will be derived using the delta method , 27. AllThe VE will be calculated using only subjects who met all protocol requirements, received the designated vaccine regimen in G8 and enrolled in a later CSS two and/or four years after vaccination. The unvaccinated Baseline CSS data set will be restricted to include only subjects who based on their date of birth would have been eligible to receive vaccine (<15 years of age) in G8 so that the vaccinated set and the unvaccinated comparator set have the same age distribution.Since the vaccine is already in use in the national immunization program and administered within the approved age range, the establishment of a Data and Safety Monitoring Board (DSMB) is not required. Because the schoolgirls in one province are offered a reduced dosing schedule, a futility assessment will be performed after the Year 2 survey with pre-determined criteria that, if met, would indicate no public health value to the SD regimen. If the futility criteria are met, a second dose of HPV vaccine will be offered to the vaccinated students in Udon Thani.The futility criteria for considering the administration of a second dose of vaccine are:The estimated effectiveness of two doses after cross-sectional survey in Buri Ram must have a lower bound >50% ANDThe estimated effectiveness of single dose after Year 2 cross-sectional survey in Udon Thani must have an upper bound of <50%, ANDBe inferior to 2D with a margin of >25% difference in vaccine effectiveness.The sponsor has contracted independent local clinical monitors to ensure that the study is conducted according to protocol, standard operating procedures, the principles of GCP, and to verify that investigators are collecting and reporting quality data. During periods of field activities in the year of vaccination and Baseline CSS, and during the Year 2 and Year 4 CSS, the monitors are present at site to observe the informed consent process, including 100% review of ICFs and assent forms, and to verify adherence to study protocol. Data quality is further verified by monitors through direct source document verification against data in the electronic data capture system of at least 10% of randomly selected study participants.All study-related information and data is being securely managed including use of physical security (locked rooms and cabinets) for source documents in Thailand, and secure servers for storage of digital data. The primary data to be used for analysis is located on a server at IVI, however a duplicate set of data is stored in Thailand. Only the PI and limited MOPH staff have access to personally identifiable information, and all data stored at IVI and Chulalongkorn University use only study ID number or a laboratory code number as an identifier. The serum samples, labeled with a laboratory code, will be sent outside the country for analysis at the US CDC. Both urine and serum samples will be stored for five years after study completion.Upon completion of each phase of the study , an analysis will be conducted, and a study report produced. The report will be submitted to the competent authority and ethics committees according to national regulations and publication sought in peer-reviewed journals. In order to shorten the time between availability of data and public health decision-making, study reports will be made available to national (Thailand) and international (WHO) public health policy makers. We will report the study in accordance with the Consolidated Standards of Reporting Trials guidelines, with authorship based on the ICMJE recommendations.S1 Checklist(DOC)Click here for additional data file.S1 File(PDF)Click here for additional data file.S2 File(PDF)Click here for additional data file. 6 Apr 2022A community intervention effectiveness study of single dose or two doses of bivalent HPV vaccine (CERVARIX®) in female school students in ThailandPONE-D-22-06291Dear Dr. Lynch,We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.As a Peer-Reviewed Funded Protocol, your submission is eligible for expedited review by in-house editors. Based on our evaluation, we are satisfied that your manuscript reports a protocol for a clinical trial that complies with our Study Protocol and Clinical Trial policies. Your Study Protocol is therefore considered to be suitable for publication subject to final journal requirements.Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at onepress@plos.org.If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact Kind regards,Marianne ClemenceStaff EditorPLOS ONEAdditional Editor Comments :Reviewers' comments: 19 Apr 2022PONE-D-22-06291 A community intervention effectiveness study of single dose or two doses of bivalent HPV vaccine (CERVARIX) in female school students in Thailan Dear Dr. Lynch:I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. onepress@plos.org.If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact plosone@plos.org. If we can help with anything else, please email us at Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staffon behalf ofDr Marianne Clemence Staff EditorPLOS ONE


The burden of Human Papilloma Virus (HPV)-associated cancer remains high in developing nations.To assess the impact of self-reported awareness and attitudes on vaccination practices, and the perception on self-sampling for cervical cancer screening.A 12-month survey using purposive sampling of females attending an urban public university was conducted. SPSS version 25 was used to compare the responses for students enrolled in health vs non-health related programmes.n = 127), and from the Hotel and Tourism, Business Management, and Art and Design (n = 113) faculties. About one-third (28.8%) had completed 3 shots, 19.6% received the first shot, 11.4% had scheduled appointments for first shots while 40.2% were both unvaccinated and had not scheduled any appointment. Most (71%) were aware of the HPV vaccines while 50.5% were unaware that HPV vaccines were also available for men. Students enrolled in health-related programmes were 3.2 times more perceptive to the benefits of vaccination particularly in preventing spread to their partners  than their counterparts. A weak-positive correlation was observed between knowledge and vaccination practices . The level of knowledge on HPV and its vaccine was greater for health-related (Mdn = 6.5) than for students of non-health related (Mdn = 1.5) programmes . Attitudes towards immunisation were influenced by perceived benefits versus risks for side effects, cost barriers, and influences of primarily their doctors and parents. The study was limited in that relationship statuses were used to estimate sexual history as direct questions were unanswered in the pilot survey.Of the 290 questionnaires distributed, 240 were returned (response rate = 83%) in approximately equal proportion from the faculties of Health Science and Pharmacy (HPV vaccine uptake for an immunisation-targeted young female population is low despite moderate knowledge levels. It is plausible that the low rates among females enrolled in particularly the non-health programmes were impacted by misperceived vaccine-associated risks, and misconception that testing and vaccination for HPV and cervical cancer were for those married or sexually active. Self-sampling could offer a potential alternative to sampling via pelvic examination, particularly for societies where premarital sex is seen as a taboo. In 2022, it is 16 years since the vaccine against human papillomavirus (HPV) was first introduced in the United States of America , 4.In the UK, the HPV vaccine was introduced in 2008 as part of the UK's HPV vaccination programme for those aged 12–13 years. The programme led to a reduction in the incidence of cervical cancer by 87% in women in their 20s in England who were offered the vaccine when they were in school . VaccinaWhile various strains of HPV exist, formation of genital warts is the most common characteristic. Few notable strains, such as HPV-16 and HPV-18, were frequently associated with the development of cancer. In men, if left untreated, these forms of the virus can lead to cancers of the penis, anus, and the oropharynx. The risks for such cancers were increased particularly among males-sex with males. Among females, in who nearly 60% of associated cancers were seen, there was a pronounced likelihood for untreated infections to develop into precancerous lesions which may metamorphose into full blown cervical cancers . The proTogether with vaccination, early detection has demonstrated a decline in the incidence of cervical cancer and related deaths, especially among women who received prompt treatment for precancerous lesions and whose prognosis for a 5-year chance of survival was nearly 100% . NeverthThe cross-sectional study was conducted at one of Malaysia’s leading higher learning institutions with one main and 35 satellite campuses. MARA University of Technology’s Puncak Alam campus was purposively selected for inclusion, as the location was feasible and allowed data collection to be conducted systematically.The study was conducted within a period of 12 months. Data were collected across the campus from July 2017 to June 2018 using structured questionnaires which were self-administered. Participants were chosen using a non-probability sampling technique.The data were collected by a researcher and assisted by a co-investigator [MAZ and NSMR]. Potential participants were approached outside lecture halls and tutorial rooms. Initially, those potential participants were invited to participate. Then, they were given the participant information sheet and informed consent form containing information on the study’s background, confidentiality aspects, procedures, and risks and benefits associated with the survey. After the participants had signed the informed consent forms and agreed to participate in the study, they were then handed the questionnaire.The cover letter attached to the questionnaire carried relevant instructions which aided respondents to self-administer. Once completed, the questionnaire was sealable in an envelope, thus ensuring confidentiality and anonymity of the respondents. The researcher then collected the sealed envelopes containing the completed questionnaires. None of the respondents could be traced to the returned questionnaires.Approval to conduct this study was obtained from the Research Ethics Committee of the university. Details on the ethical approval are available at the end of this article.The respondents were selected based on the following criteria:i.Malaysian females,ii.Age equal or more than 18 years,iii.University students present on campus.Inclusion criteria:i.Respondents who could not understand, read and write in the English language,ii.Incomplete questionnaires,iii.Not willing to participate in the study.Exclusion criteria:A single proportion formula was used to calculate the target sample size required for the purposive sampling. The formula used was:n = sample size, z = confidence level (z-score), p = proportion and e = margin of error.where z = 1.96, p = 0.5, and e = 0.07, the n was calculated as Thus, by using the said equation, where The questionnaire used in the study was adapted from previously published questionnaires of studies entitled, “Beliefs and attitudes regarding HPV vaccination among college-age women: an application of the health belief model”  and “KnoPart A—Demographic information about the respondents.Part B—Knowledge about the human papilloma virus, vaccines, and self-sampling.Part C—Attitudes and perception on HPV and the HPV vaccine.The questionnaire consisted of three parts:A pilot study of 15 students whose data were not included in the analysis was done. The necessary changes were then made to the questionnaire. The first part of the questionnaire included respondents’ demographic data and HPV immunisation history. The demographic details of the respondents included age, current year of study, and relationship statuses. Relationship statuses were used to estimate sexual history as direct questions were unanswered in the questionnaire from the pilot study. The HPV immunisation history included information on previous HPV vaccine uptake. The second part of the questionnaire assessed respondents’ knowledge about the virus, HPV vaccine, and self-sampling. The third part of the questionnaire evaluated respondents’ attitudes and perception on the HPV and HPV vaccines. The statements were presented as multiple-choice responses and true or false statements. The responses were assessed on a 5-point Likert scale from strongly agree to strongly disagree. Respondents who answered more than 70% of the questions accurately were considered to have had “good” knowledge, 50–70% accuracy were considered “moderate” while those with fewer than 50% of accurate answers were considered to have had “poor” knowledge. Those who were positive (answered strongly agreed and agreed) to 70% of the statements were considered to have had “good” attitudes and perception, 50–70% were considered “moderate” while respondents with fewer than 50% of positive answers were considered to have had “poor” attitudes and perception.Participants’ socio-demographic information—such as age, relationship statuses , education level, and family history of cervical cancer were obtained. Data relating to participants’ knowledge, attitudes, and vaccination practices for HPV, HPV testing and self-sampling were also obtained. Knowledge was construed as the respondents’ state of awareness about an HPV infection, its relationship with cervical cancer, asymptomatic nature, mode of transmission and prevention, vaccine availability and accessibility, and testing for HPV including self-sampling. Attitude was construed as the respondents’ perceptions (whether positive or negative) about the disease, and the practice of HPV testing and willingness to self-sample for the test.p = 0.05.Data collected from the survey were analysed using the Statistical Package for the Social Sciences Statistics (SPSS) Version 25. Mean ± SD or median (interquartile range) was used to express continuous variables. The Chi-square test or Fisher’s exact test was used to compare categorical variables which were expressed as proportions where appropriate. Associations between respondents’ demographic characteristics and the mean ranks of their knowledge on the HPV and vaccination, as well as their attitudes and perception on self-sampling were evaluated using Mann–Whitney, Spearman correlation and logistic regression. All statistical tests were performed at a priori significance level of n = 127), and from the non-health related Faculties of Hotel and Tourism, Business Management, and Art and Design (n = 113). The detailed characteristics of the respondents are presented in Table Of a total 290 questionnaires that were handed out, 240 questionnaires were completely filled and returned—thus, the response rate was 83%. The questionnaires were returned in almost equal proportions from the health-related Faculties of Health Sciences and Pharmacy n = 27, and fApproximately one-third of the students (28.8%) had completed their HPV immunisation through a series of 3 shots of the HPV vaccine. Approximately a fifth 19.6%) had received the first shot, 11.4% had scheduled appointments for their first shots, while the remaining 40.2% had neither received the HPV vaccine nor had they scheduled an appointment with their respective doctors for the HPV vaccine  were aware about the Human Papillomavirus even before answering the questionnaire while a minority  had never heard about the HPV prior to answering the questions. The remaining 6% (n = 15) were unsure about whether or not they had heard about the virus. Most females were also aware of the availability of vaccines  for the prevention of HPV infections, a small percentage  were unaware about the HPV vaccine and 17.5% (n = 42) indicated that they were unsure about their awareness of the HPV vaccine. Only 9.5% (n = 23) were aware that the HPV vaccine was also available for men while most  were unaware of such circumstances and the remainder  were unsure.As depicted in Table From a multiple choice of eight options, many respondents selected several options and  revealed that a large amount of  HPV and vaccine-related information were sourced from their healthcare providers (47.5%) followed by the internet (44.3%), television or radio (37.9%), school (37.4%), friends (28.3%), newspaper or magazines (23.3%), family (13.7%) and other sources 2.73%.Table As presented in Table Students enrolled in Health-related programmes also stated that HPV vaccines prevented the development of cervical cancer (78%), genital warts (57%), herpes (35%), oral cancer (10%), while 6% did not know the answer. In comparison, for the non-health related group, the percentages of females who agreed with the statements on cervical cancer (60%), genital warts (21%), herpes (10%), and oral cancer (7%) were decreased except for an increase seen in the numbers who did not know the answers (35%).Many respondents were unaware of the side effects that can arise from the administration of the HPV vaccine. A proportion (39%) did accurately identify that soreness at the site of the injection was the main side effect. A greater proportion of non-health related (54%) respondents versus 34.6% of their counterparts did not know the answer .Almost equal numbers in both groups (16% and 17%) thought that the HPV vaccine injection will be painful. A minority, 6.5% versus 14.5%, contemplated vaccination because getting a Gardasil© injection would have been against their belief systems Table .Table 9P® brush (62% versus 79%), both groups had positive perceptions and were impressed by the simple self-sampling alternative to using a speculum during pelvic examination. In addition, they were more willing to use self-sampling test kits at home rather than at clinics or health centres.Although a high percentage had not heard about the Evalynp = 0.006) than their counterparts. In addition, there were significant associations in the numbers between the two groups who thought that vaccination prevented oral cancer (p = 0.014), who were convinced that their doctors would approve of their decision to get vaccinated (p = 0.025), who would be embarrassed if others knew they got vaccinated against the HPV (p = 0.000), who thought that the vaccines were expensive (p = 0.016), and whose beliefs were against vaccination (p = 0.002). The health group fared better than the non-health group. A weak-positive correlation was observed between knowledge and vaccination practices . The level of knowledge on the HPV and its vaccines was greater for health-related (Mdn = 6.5) than for non-health related female students (Mdn = 1.5), U = 2790.5, p-value = 0.00).Students enrolled in health-related programmes were more perceptive to the benefits of getting vaccinated: in particular, they were 3.2 times more convinced that spread to partners can be prevented by vaccination  of the participants knew about the HPV transmission and prevention . More awAlthough cervical cancers are mostly preventable with screening and early detection, other HPV-associated cancers like anal, vaginal, oropharyngeal, vulvar, and penile are yet to have established screening guidelines . This hiIn Malaysia, cervical cancer, is still the second most frequently occurring cancer (after breast cancer) among women aged 15–44 years . The MinIn a recent study in Iraq, where molecular analysis using polymerase chain reaction was performed on cervical samples of women aged 32–78, the incidence of HPV-16 infection was higher in younger women, while infection rates declined in older women . In sevePrior to the introduction of vaccines in 2010 in Malaysia, cytology-based screening was the primary preventive measure for cervical cancer. Screening services using the Papanicolaou smear (Pap smear) was initially aimed at post-partum mothers in family planning clinics. In 1995, the services were also offered to women aged 20–65 years .The burden of cervical cancer in the Asia pacific region is moderately high due to the limitations conferred by cytology-based screening. Lower income countries might not get the best preventive healthcare or equitable access to the vaccines or diagnostic tests in comparison to the more advanced and higher income countries . The cosn = 17,997) or to undergo midwife-collected Pap smears for cytological testing . A higher number of women screened at a lower cost in the self-sampled versus midwife-collected Pap smears group  [Self-sampling for HPV testing can be a cost-effective alternative to clinic-based cervical screening. For detecting cervical intraepithelial neoplasia grade 2 or more (CIN2 +), repeated HPV self-sampling in comparison with cytology-based (pap smear) screening was a cost-effective alternative. The study involved a cost-effectiveness analysis of participants who were randomised to either undergo repeated HPV self-sampling of vaginal fluid  .The study has an added strength of having surveyed end-users’ perception on self-sampling as an alternative technique to sampling via pelvic examination. The study’s recruitment process however, had its disadvantages in that, sampling did not account for the proportion of students enrolled in each faculty. Nevertheless, the comparable number of samples in  both groups allowed for a comparison with statistical significance. In addition, the study was limited in that relationship statuses were used to estimate sexual history as direct questions were unanswered in the pilot survey.Despite moderate knowledge levels, the overall vaccination uptake for the human papillomavirus is low for a young female population. In comparison with students enrolled in health-related programmes, the non-health related students had lower knowledge levels. However, the attitudes and perception on self-sampling for screening were comparable for the two groups. Knowledge levels of students correlated with vaccination practices and this was evident in the more encouraging HPV vaccine uptake among health-related students when compared to their counterparts. Factors which plausibly impacted vaccination practices were misperceived risks associated with the vaccines and the misconception that, testing for HPV, cervical cancer screening and vaccination, were for the married or sexually active population. Finally, self-sampling could offer a potential alternative technique to sampling via pelvic examination. This would  address cultural barriers and in particular, benefit the societies where premarital sex is seen as a taboo.