Age-specific prevalence of human papilloma virus infection among Nigerian women

Background: Inconsistent trends in HPV prevalence by age have been described in Africa. We examined the age prevalence pattern and distribution of 37 HPV-DNA types among urban Nigerian women. Methods: The study population was a sample of 278 women who presented to cervical cancer screening programs in Abuja, Nigeria, between April and August 2012. Using a nurse administered questionnaire, information on demographic characteristics and risk factors of cervical cancer was collected and samples of cervical exfoliated cells were obtained from all participants. Roche Linear Array HPV Genotyping Test® was used to characterize prevalent HPV and log-binomial regression models were used to examine the association between potential correlates and the prevalence of HPV infection. Results: The mean age (SD) of the women enrolled was 38 (8) years. The overall prevalence of HPV was 37%. HPV 35 was the most prevalent HPV type in the study population. Among women age ≤ 30 years, 52% had HPV infection compared to 23% of those women who were older than 45 years (p = 0.006). We observed a significant linear association between age and the prevalence of HPV infections. The prevalence ratio (PR) and 95% confidence interval (CI) was 2.26 (1.17, 4.34) for any HPV infection, 3.83 (1.23, 11.94) for Group 1 HPV (definite carcinogens), and 2.19 (0.99, 4.84) for Group 2a or 2b HPV (probable or possible carcinogens) types, among women aged 18–30 years, compared to women who were older than 45 years. Conclusion: The prevalence of HPV infection was highest among younger women and decreased steadily with age among this population of urban Nigerian women

Polygenic risk modeling for prediction of epithelial ovarian cancer risk

Funding Information: ADF has received a research grant from AstraZeneca, not directly related to the content of this manuscript. MWB conducts research funded by Amgen, Novartis and Pfizer. PAF conducts research funded by Amgen, Novartis and Pfizer. He received Honoraria from Roche, Novartis and Pfizer. AWK reports research funding to her institution from Myriad Genetics for an unrelated project. UM owns stocks in Abcodia Ltd. Rachel A. Murphy is a consultant for Pharmavite. The other authors declare no conflicts of interest. Publisher Copyright: © 2021, The Author(s).Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, “select and shrink for summary statistics” (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28–1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08–1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21–1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29–1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35–1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.publishersversionPeer reviewe

Test-Retest Reliability of Self-Reported Sexual Behavior History in Urbanized Nigerian Women.

BACKGROUND: Studies assessing risk of sexual behavior and disease are often plagued by questions about the reliability of self-reported sexual behavior. In this study, we evaluated the reliability of self-reported sexual history among urbanized women in a prospective study of cervical HPV infections in Nigeria. METHODS: We examined test-retest reliability of sexual practices using questionnaires administered at study entry and at follow-up visits. We used the root mean squared approach to calculate within-person coefficient of variation (CVw) and calculated the intra-class correlation coefficient (ICC) using two way, mixed effects models for continuous variables and [Formula: see text] statistics for discrete variables. To evaluate the potential predictors of reliability, we used linear regression and log binomial regression models for the continuous and categorical variables, respectively. RESULTS: We found that self-reported sexual history was generally reliable, with overall ICC ranging from 0.7 to 0.9; however, the reliability varied by nature of sexual behavior evaluated. Frequency reports of non-vaginal sex (agreement = 63.9%, 95% CI: 47.5-77.6%) were more reliable than those of vaginal sex (agreement = 59.1%, 95% CI: 55.2-62.8%). Reports of time-invariant behaviors were also more reliable than frequency reports. The CVw for age at sexual debut was 10.7 (95% CI: 10.6-10.7) compared with the CVw for lifetime number of vaginal sex partners, which was 35.2 (95% CI: 35.1-35.3). The test-retest interval was an important predictor of reliability of responses, with longer intervals resulting in increased inconsistency (average change in unreliability for each 1 month increase = 0.04, 95% CI = 0.07-0.38, p = 0.005). CONCLUSION: Our findings suggest that overall, the self-reported sexual history among urbanized Nigeran women is reliable

Vaginal microbiota diversity and paucity of Lactobacillus species are associated with persistent hrHPV infection in HIV negative but not in HIV positive women.

Funder: Maryland Department of Health and Mental Hygiene; doi: http://dx.doi.org/10.13039/100006671The vaginal microbiota is thought to play a role in modulating risk of high-risk human papillomavirus (hrHPV) infection. We examined the relationship between the vaginal microbiota and persistent hrHPV infection in HIV-negative and HIV-positive women. We used 16S-rRNA sequencing to characterize the vaginal microbiota of two serial samples taken six months apart from 211 Nigerian women (67%, 142/211 HIV-positive and 33%, 69/211 HIV-negative) and evaluated the association between the vaginal microbiota and persistent hrHPV infection using generalized estimating equation logistic regression models and linear discriminant analysis effect size (LEfSe) algorithm to identify phylotypic biomarkers of persistent hrHPV infection. The high diversity microbiota, Community State Type IV-B, was the most prevalent in both HIV-negative (38% at baseline, 30% at the follow-up visit) and HIV-positive (27% at baseline, 35% at the follow-up visit) women. The relationship between the vaginal microbiota and persistent hrHPV was modified by HIV status. In HIV-negative women, women with Lactobacillus dominant microbiota had lower odds (OR: 0.35, 95% CI 0.14-0.89, p = 0.03) of persistent hrHPV compared to women with Lactobacillus deficient microbiota. While among HIV-positive women, the odds of being persistently infected with hrHPV was higher in women with Lactobacillus dominant microbiota (OR: 1.25, 95% CI 0.73-2.14 p = 0.41). This difference in effect estimates by HIV was statistically significant (p = 0.02). A high diversity vaginal microbial community with paucity of Lactobacillus species was associated with persistent hrHPV infection in HIV-negative women but not in HIV-positive women

Polygenic risk modeling for prediction of epithelial ovarian cancer risk

Clinical genetics; Genetic markers; Risk factorsGenética clínica; Marcadores genéticos; Factores de riesgoGenètica clínica; Marcadors genètics; Factors de riscPolygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, “select and shrink for summary statistics” (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28–1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08–1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21–1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29–1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35–1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs

HIV associated high-risk HPV infection among Nigerian women

Background: In developed countries, the incidence of cervical cancer has remained stable in HIV+ women but the prevalence and multiplicity of high-risk HPV (hrHPV) infection, a necessary cause of cervical cancer, appears different comparing HIV+ to HIV- women. Little is known about HIV and HPV co-infection in Africa. Methods: We enrolled women presenting at our cervical cancer screening program in Abuja, Nigeria between April and August 2012, and collected information on demographic characteristics, risk factors of HPV infection and samples of exfoliated cervical cells. We used Roche Linear Array HPV Genotyping Test® to characterize prevalent HPV and logistic regression models to estimate the association between HIV and the risk of hrHPV infection. Results: There were 278 participants, 54% (151) were HIV+, 40% (111) were HIV-, and 6% (16) had unknown HIV status. Of these, data from 149 HIV+ and 108 HIV- women were available for analysis. The mean ages (±SD) were 37.6 (±7.7) years for HIV+ and 36.6 (±7.9) years for HIV- women (p-value = 0.34). Among the HIV+ women, HPV35 (8.7%) and HPV56 (7.4%) were the most prevalent hrHPV, while HPV52 and HPV68 (2.8%, each) were the most prevalent hrHPV types among HIV- women. The multivariate prevalence ratio for any hrHPV and multiple hrHPV infections were 4.18 (95% CI 2.05 – 8.49, p-value <0.0001) and 6.6 (95% CI 1.49 – 29.64, p-value 0.01) respectively, comparing HIV + to HIV- women, adjusted for age, and educational level. Conclusions: HIV infection was associated with increased risk of any HPV, hrHPV and multiple HPV infections. Oncogenic HPV types 35, 52, 56 and 68 may be more important risk factors for cervical pre-cancer and cancer among women in Africa. Polyvalent hrHPV vaccines meant for African populations should protect against other hrHPV types, in addition to 16 and 18

Influence of Spirituality and Modesty on Acceptance of Self-Sampling for Cervical Cancer Screening.

INTRODUCTION: Whereas systematic screening programs have reduced the incidence of cervical cancer in developed countries, the incidence remains high in developing countries. Among several barriers to uptake of cervical cancer screening, the roles of religious and cultural factors such as modesty have been poorly studied. Knowledge about these factors is important because of the potential to overcome them using strategies such as self-collection of cervico-vaginal samples. In this study we evaluate the influence of spirituality and modesty on the acceptance of self-sampling for cervical cancer screening. METHODOLOGY: We enrolled 600 participants in Nigeria between August and October 2014 and collected information on spirituality and modesty using two scales. We used principal component analysis to extract scores for spirituality and modesty and logistic regression models to evaluate the association between spirituality, modesty and preference for self-sampling. All analyses were performed using STATA 12 (Stata Corporation, College Station, Texas, USA). RESULTS: Some 581 (97%) women had complete data for analysis. Most (69%) were married, 50% were Christian and 44% were from the south western part of Nigeria. Overall, 19% (110/581) of the women preferred self-sampling to being sampled by a health care provider. Adjusting for age and socioeconomic status, spirituality, religious affiliation and geographic location were significantly associated with preference for self-sampling, while modesty was not significantly associated. The multivariable OR (95% CI, p-value) for association with self-sampling were 0.88 (0.78-0.99, 0.03) for spirituality, 1.69 (1.09-2.64, 0.02) for religious affiliation and 0.96 (0.86-1.08, 0.51) for modesty. CONCLUSION: Our results show the importance of taking cultural and religious beliefs and practices into consideration in planning health interventions like cervical cancer screening. To succeed, public health interventions and the education to promote it must be related to the target population and its preferences

Polygenic risk modeling for prediction of epithelial ovarian cancer risk

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.Peer reviewe

Polygenic risk modeling for prediction of epithelial ovarian cancer risk

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs