Association of Plasma Aflatoxin With Persistent Detection of Oncogenic Human Papillomaviruses in Cervical Samples From Kenyan Women Enrolled in a Longitudinal Study

Association of Plasma Aflatoxin With Persistent Detection of Oncogenic Human Papillomaviruses in Cervical Samples From Kenyan Women Enrolled in a Longitudinal Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association of Plasma Aflatoxin With Persistent Detection of Oncogenic Human Papillomaviruses in Cervical Samples From Kenyan Women Enrolled in a Longitudinal Study Yan Tong, Philip Tonui, Omenge Orang’o, Jianjun Zhang, Titus Maina, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2468599/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Jun, 2023 Read the published version in BMC Infectious Diseases → Version 1 posted 8 You are reading this latest preprint version Abstract Background Cervical cancer is common among Kenyan women and is caused by oncogenic human papillomaviruses (HR-HPV). Identification of factors that increase HR-HPV persistence is critically important. Kenyan women exposed to aflatoxin have an increased risk of cervical HR-HPV detection. This analysis was performed to examine associations between aflatoxin and HR-HPV persistence. Methods Kenyan women were enrolled in a prospective study. The analytical cohort for this analysis included 67 HIV-uninfected women (mean age 34 years) who completed at least two of three annual study visits and had an available blood sample. Plasma aflatoxin was detected using ultra-high pressure liquid chromatography (UHPLC)-isotope dilution mass spectrometry. Annual cervical swabs were tested for HPV (Roche Linear Array). Ordinal logistic regression models were fitted to examine associations of aflatoxin and HPV persistence. Results Aflatoxin was detected in 59.7% of women and was associated with higher risk of persistent detection of any HPV type (OR = 3.03, 95%CI = 1.08–8.55, P = 0.036), HR-HPV types (OR = 3.63, 95%CI = 1.30-10.13, P = 0.014), and HR-HPV types not included in the 9-valent HPV vaccine (OR = 4.46, 95%CI = 1.13–17.58, P = 0.032). Conclusions Aflatoxin detection was associated with increased risk of HR-HPV persistence in Kenyan women. Further studies are needed to determine if aflatoxin synergistically interacts with HR-HPV to increase cervical cancer risk. Introduction Cervical cancer is a common malignancy among Kenyan women [ 1 – 3 ]. The incidence rate of cervical cancer in Kenya is 31.3 per 100,000 women per year and the mortality rate is 25 per 100,000 women per year, figures considerably higher than those in wealthy countries [ 4 , 5 ]. Oncogenic types of human papillomaviruses (“high-risk”, or HR-HPV) are the causative agents of cervical cancer. However, only a small percentage of women infected with HR-HPV will develop cancer, indicating the importance of cofactors associated with HR-HPV persistence that contribute to the occurrence of cervical cancer [ 6 ]. Women with persistent infection with oncogenic HPV are at significantly higher risk of cervical cancer [ 7 ]. HIV infection is one cofactor that imparts a higher likelihood of HR-HPV persistence [ 2 , 8 , 9 ]. HR-HPV detection and persistence are also prevalent among Kenyan women who are not HIV-infected [ 10 , 11 ]. Dietary aflatoxin may be another risk factor for HR-HPV persistence that is additive with HIV infection. Aflatoxin is a potent carcinogen and immunosuppressive agent produced by certain strains of Aspergillus, a mold that infects corn crops [ 12 – 14 ]. Large percentages of people living in sub-Saharan African countries are exposed to aflatoxin. We previously showed in a cross-sectional analysis that plasma aflatoxin biomarkers were detected among 57% of HIV-uninfected Kenyan women enrolled in a prospective study of HPV epidemiology and associated with cervical detection of A9 HPV types [ 15 ]. An additional analysis was performed using longitudinal data from this cohort to examine associations between plasma aflatoxin detection and cervical HR-HPV persistence. Methods Study Population Kenyan women were enrolled from September 2015 to October 2016 at the Academic Model Providing Access to Healthcare (AMPATH) Cervical Cancer Screening Program (CCSP) at Moi Teaching and Referral Hospital in Eldoret, Kenya [ 16 ]. They were participants in a prospective cohort study investigating biological, behavioral, and environmental risk factors for oncogenic HPV persistence, a part of the East African Consortium for Human Papillomavirus and Cervical Cancer in Women Living with HIV/AIDS [ 16 ]. Details of study enrollment procedures have been previously published [ 11 ]. Briefly, women aged 18 to 60 years living within 30 km of Eldoret presenting for screening at the CCSP were asked to participate in the study if they had a normal visual inspection with acetic acid (VIA) of the uterine cervix that day. A total of 223 women consented to participation and enrolled in the study, including 116 HIV-infected and 107 HIV-uninfected women. Plasma obtained at enrollment was available for 87 of 107 HIV-uninfected women, but no plasma sample was available for the HIV-infected women. Of the 87 HIV-uninfected women with available plasma, 67 women had at least two adequate cervical swab samples (based on beta globin testing) obtained at enrollment and at 12- or/and 24-month follow-up visits. These 67 women represented the analytical cohort for this post-hoc analysis. Interview and questionnaire Structured face-to-face interviews of the participants by trained researchers were conducted at enrollment to capture social, behavioral, and biological information, including age, marital status, educational level, home ownership, walking distance to the local clinic, number of lifetime sexual partners, and age of first sex [ 11 ]. Cervical swab and plasma sample collection A cervical swab for HPV testing was collected by a nurse or physician as part of the inspection for cervical cancer screening. Swabs were placed in standard transport media and frozen at -80°C in the AMPATH Reference Laboratory. Plasma was collected and frozen at -20°C at the same laboratory. HPV testing Cervical specimens were transported on dry ice to the Kenya Medical Research Institute-University of Massachusetts Medical School (KEMRI-UMMS) Laboratory for processing, DNA extraction, and subsequent genotyping [ 11 ]. The Roche Linear Array was used to determine HPV types (Roche Molecular Systems, Inc., Branchburg, NJ USA) as previously described [ 17 ]. HPV 16-positive, negative, and human beta-globin (used to assess specimen adequacy) controls provided by the manufacturer were tested with each batch of samples. HPV types were grouped into “high-risk” (HR-HPV) and “low-risk” (LR-HPV) based on the designation in the Roche Linear Array instructions, or HR-HPV types as designated by the International Agency for the Research on Cancer (IARC) [ 18 ]. HPV types were further grouped into A9 and A7 types [ 19 ]. The specific HPV types included in each group are detailed in Results. Aflatoxin-albumin adduct (AFB 1 -lys) detection in plasma samples Plasma aflatoxin B1-lysine (AFB 1 -lys) was measured at the Department of Environmental Health and Engineering of the Johns Hopkins Bloomberg School of Public Health, using a minor variation of the method reported by McCoy and colleagues [ 15 , 20 ]. Briefly, plasma (150 µL) was spiked with an internal standard (0.5 ng AFB 1 -d4-lysine in 100 µL), combined with Pronase (EMD Millipore, Billerica MA, USA) protease solution (3.25 mg in 0.5 mL phosphate-buffered saline), and incubated for 18 hours at 37°C. Solid-phase extraction–processed samples (Oasis MAX columns; Waters, Milford, MA, USA) were analyzed with ultra-high pressure liquid chromatography (UHPLC)-isotope dilution mass spectrometry on a ThermoFisher Scientific (San Jose, CA, USA) system composed of a Vanquish UHPLC and a TSQ Quantis triple quadrupole mass spectrometer in positive electrospray ionization mode [ 21 , 22 ]. Persistent HPV detection Type-specific HPV testing results obtained from the enrollment, 12-month and 24-month cervical samples were combined to determine the detection category of each specific HPV type for each woman. Three categories of HPV detection were determined: No detection, Incident Detection, and Persistent Detection. To be included, two or three of a participant’s cervical samples (Enrollment, 12-month, or 24-month) had to be available; one of the three samples could be missing. The type-specific HPV detection categories were defined as follows: I. No detection: No detection for the specific HPV type at any of the three time-points; II. Incident detection: One sample positive for detection of a specific HPV type, but other samples were negative for that type; III. Persistent detection: Two samples taken one year apart, or two years apart were positive for detection of a specific HPV type. The third sample could be negative for that type (or missing). At the level of study participants, a woman’s HPV detection status was defined as the highest level of HPV detection category in the descending order of “Persistent detection,” “Incident detection,” and “No detection” among her type-specific HPV detection episodes within a combined group of specific HPV types. For example, a woman is classified as at the status of persistent detection in HR-HPV if any type-specific “persistence detection” episode is identified among the HR-HPV types. The subsequent analysis of HPV detection was conducted at the level of participant. Statistical analysis Demographic and behavioral characteristics of participants at enrollment (age, marital status, educational level, home ownership, walking distance to health care of ⩾60 min, number of lifetime sex partners, and age of first sex) were summarized by descriptive statistics and compared between women with and without detectable plasma AFB 1 -lys using t-tests, chi-square tests, or Wilcoxon rank sum tests. Frequencies and percentages of HPV detections (“No detection”, “Incident detection” and “Persistent detection”) in women were compared between those with and without detectable plasma AFB 1 -lys using chi-square tests or Fisher’s exact tests. Plasma AFB1-lys concentration (pg/uL) were summarized in mean, standard deviation (std), median and interquartile range (IQR) and compared among women with different HPV detection status using Wilcoxon rank sum tests. In addition, ordinal logistic regression models were fitted to examine associations of HPV detection (persistent detection vs. incident detection vs. no detection) with plasma aflatoxin detection, controlling for demographic and behavioral characteristics of the women as confounders. The proportional odds assumption was examined for each fitted ordinal logistic regression model to ensure validity of the model. All analyses were performed using SAS Version 9.4 (Cary, NC). Ethics considerations Results Overall characteristics of participants and aflatoxin (AFB 1 -lys) detection The median age (IQR) at enrollment of 67 participants with an available plasma sample and valid HPV testing results was 34.0 (30.0, 38.0) years (range 21 to 46 years) (Table 1 ). Of 67 women, 27 (40.3%) had no detection of AFB 1 -lys in plasma, and 40 women (59.7%) had AFB 1 -lys detected (Table 1 ). Women with and without detectable plasma AFB 1 -lys were not significantly different in age, being married, having more than secondary school education, home ownership, living at a walking distance to health care of ≥ 60 minutes, number of lifetime sex partners, or age of first sex (Table 1 ). Table 1. Demographic and behavioral characteristics of women with or without plasma AFB1-lys detection Characteristics Overall N=67 Plasma AFB1-lys Detection No N=27 Yes N=40 P value Median age in years (IQR) 34.0 (30.0, 38.0) 35.0 (30.0, 40.0) 33.5 (30.0, 38.0) 0.537 1 Married 49 (73.1%) 19 (70.4%) 30 (75.0%) 0.675 2 More than secondary school education 10 (14.9%) 2 (7.4%) 8 (20.0%) 0.185 3 Home ownership 20 (29.9%) 7 (25.9%) 13 (32.5%) 0.564 2 Walking distance to health care ≥60 mins 7 (10.4%) 2 (7.4%) 5 (12.5%) 0.693 3 Median number of lifetime sex partners (IQR) 3.0 (1.0, 4.0) 2.0 (1.0, 4.0) 3.0 (1.0, 4.0) 0.588 4 Median age of first sex (IQR) 18.0 (16.0, 20.0) 18.0 (17.0, 20.0) 18.0 (16.0, 20.0) 0.792 1 1 P-value from t-test 2 P-value from Chi-square test 3 P-value from Fisher’s exact test 4 P-value from Wilcoxon rank sum test A total of 87 women in the original cohort had plasma samples tested for AFB 1 -lys, including 67 women consisting of the analytical cohort and 20 women who did not complete at least two study visits. Comparisons between the 67 women in this analytical cohort and the 20 women who did not complete at least two visits were conducted with respect to the demographics/behavioral characteristics and plasma AFB1-lys detection/concentration. No significant differences in these variables were found between the two groups of women (data not shown). Association of plasma AFB 1 -lys detection with persistent HPV detection Frequencies and percentages of HPV detections (“no detection”, “incident detection” and “persistent detection”) in women with and without plasma AFB 1 -lys detection and mean (STD) and median (IQR) of plasma AFB 1 -lys concentration (pg/uL) among women with different HPV detections are shown in Table 2 . There was a trend of significantly increasing plasma AFB 1 -lys concentrations among women who had no detection, incident detection, or persistent detection for any HPV type (p = 0.036), HR-HPV types (p = 0.020), or vaccine-unprotected HR-HPV types (p = 0.017) (Table 2 ). Similar trends in increasing plasma AFB 1 -lys concentrations were observed for some other groups of HPV types, however, these were not significant (Table 2 ). Table 2. Frequency and percentage of HPV detection in 67 women with and without plasma AFB1-lys detection, and mean (standard deviation, or STD) and median (interquartile range, or IQR) of plasma AFB1-lys concentration (pg/uL). HPV HPV detection category Plasma AFB1-lys concentration (pg/uL) Plasma AFB1-lys detection N, Mean (STD) Median (IQR) P- Value 13 No (N=27) Yes (N=40) P-Value n (%) n (%) Any HPV 1 No Detection 23, 0.030 (0.042) 0.000 (0.000-0.066) 0.036 14 (51.9) 9 (22.5) 0.043 11 Incident Detection 32, 0.050 (0.043) 0.052 (0.000-0.088) 10 (37.0) 22 (55.0) Persistent Detection 12, 0.078 (0.068) 0.081 (0.014-0.098) 3 (11.1) 9 (22.5) HR-HPV 2 No Detection 30, 0.034 (0.044) 0.000 (0.000-0.065) 0.020 17 (63.0) 13 (32.5) 0.038 11 Incident Detection 26, 0.049 (0.041) 0.050 (0.000-0.091) 8 (29.6) 18 (45.0) Persistent Detection 11, 0.086 (0.066) 0.082 (0.027-0.098) 2 (7.4) 9 (22.5) IARC HR-HPV 3 No Detection 35, 0.046 (0.057) 0.035 (0.000-0.073) 0.410 17 (63.0) 18 (45.0) 0.361 12 Incident Detection 24, 0.048 (0.042) 0.046 (0.000-0.093) 8 (29.6) 16 (40.0) Persistent Detection 8, 0.058 (0.042) 0.078 (0.014-0.093) 2 (7.4) 6 (15.0) A9 HPV 4 No Detection 45, 0.045 (0.053) 0.035 (0.000-0.073) 0.395 20 (74.1) 25 (62.5) 0.567 12 Incident Detection 17, 0.055 (0.043) 0.067 (0.000-0.094) 5 (18.5) 12 (30.0) Persistent Detection 5, 0.054 (0.049) 0.082 (0.000-0.089) 2 (7.4) 3 (7.5) Non-HPV 16 A9 5 No Detection 48, 0.044 (0.052) 0.031 (0.000-0.073) 0.171 22 (81.5) 26 (65.0) 0.175 12 Incident Detection 15, 0.062 (0.041) 0.079 (0.023-0.095) 3 (11.1) 12 (30.0) Persistent Detection 9, 0.047 (0.054) 0.045 (0.000-0.093) 2 (7.4) 2 (5.0) A7 HPV 6 No Detection 55, 0.048 (0.050) 0.047 (0.000-0.085) 0.097 23 (85.2) 32 (80.0) 0.236 12 Incident Detection 8, 0.025 (0.029) 0.016 (0.000-0.050) 4 (14.8) 4 (10.0) Persistent Detection 4, 0.096 (0.067) 0.086 (0.050-0.142) 0 (0.0) 4 (10.0) Non-HPV 18 A7 7 No Detection 59, 0.049 (0.048) 0.047 (0.000-0.085) 0.090 23 (85.2) 36 (90.0) 0.661 12 Incident Detection 7, 0.024 (0.031) 0.000 (0.000-0.059) 4 (14.8) 3 (7.5) Persistent Detection 1, 0.186 (-) 0.186 (0.186-0.186) 0 (0.0) 1 (2.5) Vaccine-protected HR-HPV 8 No Detection 41, 0.046 (0.054) 0.040 (0.000-0.073) 0.505 18 (66.7) 23 (57.5) 0.625 12 Incident Detection 18, 0.047 (0.045) 0.042 (0.000-0.094) 7 (25.9) 11 (27.5) Persistent Detection 8, 0.058 (0.042) 0.078 (0.014-0.093) 2 (7.4) 6 (15.0) Vaccine-unprotected HR-HPV 9 No Detection 47, 0.038 (0.044) 0.023 (0.000-0.079) 0.017 23 (85.2) 24 (60.0) 0.064 12 Incident Detection 16, 0.054 (0.040) 0.063 (0.008-0.090) 4 (14.8) 12 (30.0) Persistent Detection 4, 0.137 (0.071) 0.133 (0.077-0.198) 0 (0.0) 4 (10.0) LR-HPV 10 No Detection 44, 0.045 (0.047) 0.038 (0.000-0.081) 0.414 19 (70.4) 25 (62.5) 0.284 12 Incident Detection 22, 0.057 (0.055) 0.058 (0.000-0.091) 7 (25.9) 15 (37.5) Persistent Detection 1, 0.000 (-) 0.000 (0.000-0.000) 1 (3.7) 0 (0.0) 1 Any HPV: HPV 6, 11, 16, 18, 26, 31, 33, 35, 39, 40, 42, 45, 51, 52, 53, 54, 55, 56, 58, 59, 61, 62, 64, 66, 67, 68, 70, 71, 72, 73, 81, 82, 83, 84, CP6108, IS39 2 HR-HPV (High-Risk HPV): HPV 16, 18, 26, 31, 33, 35, 39, 45, 51, 52, 53, 56, 58, 59, 66, 67, 68, 69, 70, 73, 82, IS39 3 IARC HR-HPV: HPV 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66 4 A9 HPV: HPV 16, 31, 33, 35, 52, 58 5 Non-HPV 16 A9: HPV 31, 33, 35, 52, 58 6 A7 HPV: HPV 18, 39, 45, 59, 68 7 Non-HPV 18 A7: HPV 39, 45, 59, 68 8 Vaccine-protected HR-HPV: HPV 16, 18, 31, 33, 45, 52, 58 9 Vaccine-unprotected HR-HPV: HPV 26, 35, 39, 51, 53, 56, 59, 66, 67, 68, 69, 70, 73, 82, IS39 10 LR-HPV (Low-Risk HPV): HPV 6, 11, 40, 42, 54, 55, 61, 62, 64, 71, 72, 81, 83, 84, CP6108 11 P-value from Chi-square test 12 P-value from Fisher’s exact test 13 P-value from Wilcoxon rank sum test In addition, compared with women without detectable plasma AFB 1 -lys, women with detectable plasma AFB 1 -lys demonstrated significantly higher percentages of detection for any HPV type (22.5% vs. 11.1% for persistent detection and 55.0% vs. 37.0% for incident detection, p = 0.043) and HR-HPV type (22.5% vs. 7.4% for persistent detection and 45.0% vs. 29.6% for incident detection, p = 0.038). Similar patterns of HPV detections between women with and without detectable plasma AFB 1 -lys were found for all other HPV combination types except for LR-HPV types. However these were not statistically significant, possibly due to small sample sizes. A total of 13 episodes of type-specific persistent HPV detections occurred in 12 women (Table 3 ). Among these episodes, 12 were HR-HPV types, including 10 episodes that occurred in 9 of 40 women with detectable plasma AFB 1 -lys, and 2 episodes occurring in 2 of 27 women without detectable plasma AFB 1 -lys (Table 3 ). HPV 18 was the most frequently detected persistent type (3 episodes), all occurring in women with detectable plasma AFB 1 -lys (Table 3 ). Table 3 Episodes of type-specific persistent HPV detection and corresponding plasma AFB1-lys detection/concentration. Subject ID Type-specific HPV Detection Plasma AFB1-lys Type Enrollment 12-month visit 24-month visit Persistent detection Detection Concentration (pg/uL) M028 HPV 16 2 pos missing pos 2-year yes 0.082 M060 HPV 18 2 neg pos pos 1-year yes 0.027 M120 HPV 18 2 pos pos pos 2-year yes 0.098 M189 1 HPV 18 2 neg pos pos 1-year yes 0.073 M069 HPV 52 2 neg pos pos 1-year no 0.000 M121 HPV 52 2 pos pos neg 1-year yes 0.097 M168 HPV 53 3 pos pos neg 1-year yes 0.080 M066 HPV 58 2 pos pos neg 1-year no 0.000 M154 HPV 58 2 neg pos pos 1-year yes 0.089 M114 HPV 68 2 neg pos pos 1-year yes 0.186 M173 HPV 70 2 pos pos neg 1-year yes 0.209 M189 1 HPV 70 2 pos pos neg 1-year yes 0.073 M155 HPV 83 2 pos pos neg 1-year no 0.000 1 M189 had two episodes of type-specific persistent HPV detections, one episode with HPV 18 and one episode with HPV 70 2 High-Risk HPV type 3 Low-Risk HPV type Ordinal logistic regression analysis revealed that detectable plasma AFB 1 -lys was associated with a higher risk of persistent detection for any HPV type (OR = 3.03, 95%CI = 1.08–8.55, P = 0.036), HR-HPV types (OR = 3.63, 95%CI = 1.30-10.13, P = 0.014), and HR-HPV types not included in the 9-valent HPV vaccine (Vaccine-unprotected HR-HPV types) (OR = 4.46, 95%CI = 1.13–17.58, P = 0.032) after adjustment for established and suspected confounders (Table 4 ). The proportional odds assumption was validated for each ordinal logistic regression model. There was no statistically significant association of detectable plasma AFB 1 -lys with persistent detection of sub-groups of HR-HPV types, for HR-HPV types protected by the 9-valent HPV vaccine (Vaccine-protected HR-HPV types), or for low-risk (LR) HPV types (Supplemental Table 1). Table 4 Ordinal logistic regression analyses of Any HPV, HR-HPV, Vaccine-protected HR-HPV, and Vaccine-unprotected HR-HPV detection (persistent detection vs. incidence detection vs. no detection) with plasma AFB1-lys detection and demographic/behavioral characteristics of women 5 . Variables included in the model Any HPV 1 HR-HPV 2 Vaccine-protected HR-HPV 3 Vaccine-unprotected HR-HPV 4 OR (95% CI) P-value OR (95% CI) P-value OR (95% CI) P-value OR (95% CI) P-value Plasma AFB1-lys detection 3.03 (1.08–8.55) 0.036 3.63 (1.30–10.13) 0.014 1.55 (0.54–4.44) 0.413 4.46 (1.13–17.58) 0.032 Age 0.88 (0.79–0.98) 0.017 0.92 (0.83–1.02) 0.127 0.93 (0.83–1.03) 0.180 0.91 (0.79–1.05) 0.188 Married 0.28 (0.08–0.94) 0.039 0.63 (0.20–2.03) 0.442 0.38 (0.11–1.32) 0.128 0.58 (0.15–2.28) 0.437 More than secondary school education 1.13 (0.27–4.76) 0.868 0.72 (0.17–2.95) 0.645 1.41 (0.33–5.98) 0.643 1.10 (0.17–6.98) 0.918 Home ownership 2.43 (0.71–8.31) 0.156 1.60 (0.48–5.30) 0.441 1.45 (0.41–5.18) 0.563 1.78 (0.38–8.34) 0.465 Walking distance to health care ≥ 60 mins 1.46 (0.27–7.77) 0.657 0.83 (0.16–4.18) 0.820 0.46 (0.08–2.74) 0.397 2.27 (0.36–14.06) 0.380 Number of lifetime sex partners 1.07 (0.86–1.34) 0.544 1.10 (0.88–1.36) 0.405 1.02 (0.81–1.29) 0.880 0.99 (0.77–1.27) 0.918 Age of first sex 1.16 (0.98–1.38) 0.088 1.08 (0.92–1.28) 0.351 1.18 (0.99–1.40) 0.066 0.74 (0.57–0.97) 0.031 1 Any HPV: HPV 6, 11, 16, 18, 26, 31, 33, 35, 39, 40, 42, 45, 51, 52, 53, 54, 55, 56, 58, 59, 61, 62, 64, 66, 67, 68, 70, 71, 72, 73, 81, 82, 83, 84, CP6108, IS39 2 HR-HPV (High-Risk HPV): HPV 16, 18, 26, 31, 33, 35, 39, 45, 51, 52, 53, 56, 58, 59, 66, 67, 68, 69, 70, 73, 82, IS39 3 Vaccine-protected HR-HPV: HPV 16, 18, 31, 33, 45, 52, 58 4 Vaccine-unprotected HR-HPV: HPV 26, 35, 39, 51, 53, 56, 59, 66, 67, 68, 69, 70, 73, 82, IS39 Discussion In this longitudinal study, women with detectable aflatoxin biomarkers in plasma had a higher risk of persistent detection of oncogenic cervical HPV. Although only a small percentage of HPV-infected women will eventually develop cervical cancer, women with persistent detection of HR-HPV are at the highest risk for this malignancy [ 23 , 24 ]. Aflatoxins are mycotoxins produced by certain Aspergillus species during growth or after harvesting of corn and several other crops [ 25 ]. These compounds are classified by the International Agency for Research on Cancer (IARC) as class I carcinogens [ 26 ]. In addition, aflatoxins are potent immunosuppressive agents [ 27 – 30 ]. Exposure to aflatoxins contributes heavily to the worldwide burden of hepatocellular carcinoma, but the contribution of aflatoxin exposure to other cancers is unknown [ 31 , 32 ]. This study revealed an association between aflatoxin exposure and persistent HR-HPV detection, the major risk factor for cervical cancer. A previous cross-sectional study showed significant associations between plasma aflatoxin biomarkers and detection of A9 HPV types in cervical samples among HIV-uninfected Kenyan women [ 15 ]. The current analysis employed a subset of the original cohort with the longitudinal follow-up data on HPV testing, disclosing the relationship of aflatoxins with persistent detections of HR-HPV, and raising the possibility that aflatoxin could be a contributing factor to cervical cancer. We are not aware of other studies describing an association of aflatoxin with HPV persistence, cervical dysplasia, or cancer. It is possible that HR-HPV types and dietary aflatoxin act synergistically in increasing the risk of cervical cancer in Kenyan women. Aflatoxins have been detected in cervical tissue and could potentially act directly on cervical cells in the carcinogenic process, but this hypothesis has not been studied [ 33 ]. It is also possible the immunosuppression caused by aflatoxin could lead to poor immune control of oncogenic HPV infections, leading to persistence. These hypotheses need to be further investigated. In addition, it has a tremendous public health impact to investigate the role of the interaction between aflatoxin exposure and persistent HPV infection in the etiology, pathogenesis, and prevention of cervical cancer and its precursor lesions in large epidemiological studies especially in developing countries. Aflatoxin exposure is widespread in many sub-Saharan African countries, largely due to consumption of contaminated corn, the major source of daily calories for many people, especially for poor families [ 34 – 36 ]. Leroy et al., showed higher serum aflatoxin levels from adult Kenyan women associated with lower household socio-economic status [ 37 ]. Women with the lowest socio-economic status also have the lowest rates of cervical cancer screening, and therefore bear the highest burden of cervical cancer [ 38 , 39 ]. Aflatoxin, as a potential environmental risk factor of cervical cancer, demands more recognition for public health emphasis. Some limitations of the present study include a modest sample size, as not all women initially analyzed for the association of aflatoxin detection and HR-HPV detection continued in the longitudinal study. However, our analysis showed that there were no significant differences in demographic/behavioral characteristics and plasma AFB 1 -lys detection/concentration between the women who remained in the original study and included in this analysis compared to those who did not continue in the original study. Another potential limitation is that dietary factors that modulate immune functions were not included as potential confounders in our data analysis, which could possibly distort the findings of the present study. For example, malnourishment may contribute to suppressed immunity and render such women more susceptible to the toxic effects of aflatoxin, and thus, more prone to persistent HPV infection [ 34 , 40 ]. In addition, the results of our study may be subject to multiple comparisons due to a relatively large number of the models presented. However, this is unlikely because all exposure and outcome variables included in the constructed models were carefully selected in terms of the findings of previous studies and biological relevance. In summary, detection of plasma aflatoxin biomarkers was associated with increased persistence of oncogenic HPV types, in cervical samples from HIV-uninfected Kenyan women. Further studies are needed to determine if exposure to aflatoxin interacts with HPV infection to modulate the risk of cervical cancer in Kenya and other developing countries. In addition, studies are underway to examine associations of aflatoxin exposure and HR-HPV infection on occurrence of cervical dysplasia in a cohort of HIV-infected sub-Saharan women, as HIV infection increases susceptibility to cervical cancer. Declarations Ethics approval and consent to participate Study approval was granted from the local review board at Moi Teaching and Referral Hospital (MTRH) and Moi University, Eldoret, Kenya, the Kenya Medical Research Institute’s Scientific and Ethics Review Unit (KEMRI-SERU) and the Institutional Review Board of Indiana University. All participants provided written informed consent, either in Swahili or English, for participation in the study and for use of clinical specimens. All study procedures were performed in accordance with relevant guidelines and regulations outlined by the Ethics Review Boards indicated above. Consent for publication The Authors give the Publisher the permission to publish this work. Availability of data and materials The data that support the findings of this study are available from the corresponding author (Dr. Brown and the additional authors) upon reasonable request and with permission of AMPATH. Competing interests Dr. Brown currently receives research funding and has received royalties and consulting fees in the past from Merck and Co., Inc. Dr. Brown serves on the Scientific Advisory Board for PDS, Inc. The other Authors do not possess any potential conflicts of interest. Funding National Cancer Institute, United States, 1U54CA190151-01, and National Cancer Institute, United States, P30 CA082709 Authors' contributions YT contributed to conceptualization, methodology, data curation, formal analysis, validation, writing (original, review and editing). PT contributed to study supervision, investigation, writing (review and editing). OO contributed to funding acquisition, project administration, and writing (review and editing). JZ contributed to funding acquisition, writing (review and editing). TM contributed to investigation (performance of laboratory tests). KM contributed to study supervision and writing (review and editing). JG contributed to methodology, formal analysis, resources, and writing (review and editing). JS contributed to investigation (performance of laboratory tests). EM contributed to investigation (performance of laboratory tests). AE contributed to study supervision, and writing (review and editing). PL contributed to funding acquisition, project administration, and writing (review and editing). DB contributed to funding acquisition, project administration, conceptualization, methodology, study supervision, writing (original draft, review and editing). Acknowledgements We thank the nurses at the Cervical Cancer Screening Program at Moi Referral and Teaching Hospital for their hard work, kindness, and attention to detail. References Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2018 . Stelzle D, Tanaka LF, Lee KK, et al. Estimates of the global burden of cervical cancer associated with HIV. The lancet global health 2020 . Mwenda V, Mburu W, Bor JP, et al. Cervical cancer programme, Kenya, 2011-2020: lessons to guide elimination as a public health problem. Ecancermedicalscience 2022 ; 16:1442. Organization WH. Cervical cancer Kenya 2021 country profile. Available at: https://www.who.int/publications/m/item/cervical-cancer-ken-country-profile-2021. Brower V. AIDS-related cancers increase in Africa. J Natl Cancer Inst 2011 ; 103:918-9. Walboomers JM, Jacobs MV, Manos MM, et al. Human papillomavirus is a necessary cause of invasive cervical cancer worldwide.[see comment]. Journal of Pathology 1999 ; 189:12-9. Kjaer SK, Frederiksen K, Munk C, Iftner T. Long-term absolute risk of cervical intraepithelial neoplasia grade 3 or worse following human papillomavirus infection: role of persistence. J Natl Cancer Inst 2010 ; 102:1478-88. Stelzle D, Tanaka LF, Lee KK, et al. Estimates of the global burden of cervical cancer associated with HIV. The lancet global health 2021 ; 9:e161-e9. Liu G, Sharma M, Tan N, Barnabas RV. HIV-positive women have higher risk of human papilloma virus infection, precancerous lesions, and cervical cancer. Aids 2018 ; 32:795-808. Ermel A, Tonui P, Titus M, et al. A cross-sectional analysis of factors associated with detection of oncogenic human papillomavirus in human immunodeficiency virus-infected and uninfected Kenyan women. BMC infectious diseases 2019 ; 19:352. Tong Y, Tonui P, Ermel A, et al. Persistence of oncogenic and non-oncogenic human papillomavirus is associated with human immunodeficiency virus infection in Kenyan women. SAGE Open Med 2020 ; 8:2050312120945138. Gong YY, Wilson S, Mwatha JK, et al. Aflatoxin exposure may contribute to chronic hepatomegaly in Kenyan school children. Environ Health Perspect 2012 ; 120:893-6. Seetha A, Monyo ES, Tsusaka TW, et al. Aflatoxin-lysine adducts in blood serum of the Malawian rural population and aflatoxin contamination in foods (groundnuts, maize) in the corresponding areas. Mycotoxin research 2018 ; 34:195-204. Watson S, Moore SE, Darboe MK, et al. Impaired growth in rural Gambian infants exposed to aflatoxin: a prospective cohort study. BMC public health 2018 ; 18:1247. Zhang J, Orang'o O, Tonui P, et al. Detection and Concentration of Plasma Aflatoxin is Associated with Detection of Oncogenic Human Papillomavirus in Kenyan Women. Open Forum Infect Dis 2019 ; 6. Tong Y, Orang'o E, Nakalembe M, et al. The East Africa Consortium for human papillomavirus and cervical cancer in women living with HIV/AIDS. Ann Med 2022 ; 54:1202-11. Brown DR, Shew ML, Qadadri B, et al. A longitudinal study of genital human papillomavirus infection in a cohort of closely followed adolescent women. The Journal of infectious diseases 2005 ; 191:182-92. WHO. Human papillomaviruses. IARC Working Group on the Evaluation of Carcinogenic Risks to Humans IARC Monograph 2007 ; 90:1-636. Munoz N, Bosch FX, de Sanjose S, et al. Epidemiologic classification of human papillomavirus types associated with cervical cancer. The New England journal of medicine 2003 ; 348:518-27. McCoy LF, Scholl PF, Sutcliffe AE, et al. Human aflatoxin albumin adducts quantitatively compared by ELISA, HPLC with fluorescence detection, and HPLC with isotope dilution mass spectrometry. Cancer Epidemiol Biomarkers Prev 2008 ; 17:1653-7. Smith JW, Kroker-Lobos MF, Lazo M, et al. Aflatoxin and viral hepatitis exposures in Guatemala: Molecular biomarkers reveal a unique profile of risk factors in a region of high liver cancer incidence. PloS one 2017 ; 12:e0189255. Groopman JD, Egner PA, Schulze KJ, et al. Aflatoxin exposure during the first 1000 days of life in rural South Asia assessed by aflatoxin B(1)-lysine albumin biomarkers. Food Chem Toxicol 2014 ; 74:184-9. Koshiol J, Lindsay L, Pimenta JM, Poole C, Jenkins D, Smith JS. Persistent Human Papillomavirus Infection and Cervical Neoplasia: A Systematic Review and Meta-Analysis. Am J Epidemiol 2008 . Stensen S, Kjaer SK, Jensen SM, et al. Factors associated with type-specific persistence of high-risk human papillomavirus infection: A population-based study. International journal of cancer Journal international du cancer 2016 ; 138:361-8. Bennett JW, Klich M. Mycotoxins. Clinical microbiology reviews 2003 ; 16:497-516. Wild CP, Gong YY. Mycotoxins and human disease: a largely ignored global health issue. Carcinogenesis 2010 ; 31:71-82. Turner PC, Moore SE, Hall AJ, Prentice AM, Wild CP. Modification of immune function through exposure to dietary aflatoxin in Gambian children. Environ Health Perspect 2003 ; 111:217-20. Meissonnier GM, Pinton P, Laffitte J, et al. Immunotoxicity of aflatoxin B1: impairment of the cell-mediated response to vaccine antigen and modulation of cytokine expression. Toxicol Appl Pharmacol 2008 ; 231:142-9. Jolly PE. Aflatoxin: does it contribute to an increase in HIV viral load? Future microbiology 2014 ; 9:121-4. Shirani K, Zanjani BR, Mahmoudi M, et al. Immunotoxicity of aflatoxin M1 : as a potent suppressor of innate and acquired immune systems in a subacute study. Journal of the science of food and agriculture 2018 ; 98:5884-92. Chu YJ, Yang HI, Wu HC, et al. Aflatoxin B1 exposure increases the risk of hepatocellular carcinoma associated with hepatitis C virus infection or alcohol consumption. Eur J Cancer 2018 ; 94:37-46. Rushing BR, Selim MI. Aflatoxin B1: A review on metabolism, toxicity, occurrence in food, occupational exposure, and detoxification methods. Food Chem Toxicol 2019 ; 124:81-100. Carvajal M, Berumen J, Guardado-Estrada M. The presence of aflatoxin B(1)-FAPY adduct and human papilloma virus in cervical smears from cancer patients in Mexico. Food additives & contaminants Part A, Chemistry, analysis, control, exposure & risk assessment 2012 ; 29:258-68. Williams JH, Phillips TD, Jolly PE, Stiles JK, Jolly CM, Aggarwal D. Human aflatoxicosis in developing countries: a review of toxicology, exposure, potential health consequences, and interventions. The American journal of clinical nutrition 2004 ; 80:1106-22. Wagacha JM, Muthomi JW. Mycotoxin problem in Africa: current status, implications to food safety and health and possible management strategies. International journal of food microbiology 2008 ; 124:1-12. Gnonlonfin GJ, Hell K, Adjovi Y, et al. A review on aflatoxin contamination and its implications in the developing world: a sub-Saharan African perspective. Crit Rev Food Sci Nutr 2013 ; 53:349-65. Leroy JL, Wang JS, Jones K. Serum aflatoxin B(1)-lysine adduct level in adult women from Eastern Province in Kenya depends on household socio-economic status: A cross sectional study. Social science & medicine 2015 ; 146:104-10. Ba DM, Ssentongo P, Musa J, et al. Prevalence and determinants of cervical cancer screening in five sub-Saharan African countries: A population-based study. Cancer Epidemiol 2021 ; 72:101930. Chirwa GC. Explaining socioeconomic inequality in cervical cancer screening uptake in Malawi. BMC public health 2022 ; 22:1376. Saeed F, Nadeem M, Ahmed R, Nadeem M, Arshad M, Ullah A. Studying the impact of nutritional immunology underlying the modulation of immune responses by nutritional compounds – a review, . Food and Agricultural Immunology 2016 ; 27:205-29. Additional Declarations Competing interest reported. Dr. Brown currently receives research funding and has received royalties and consulting fees in the past from Merck and Co., Inc. Dr. Brown serves on the Scientific Advisory Board for PDS, Inc. The other Authors do not possess any potential conflicts of interest. Supplementary Files Supptable112722.docx Cite Share Download PDF Status: Published Journal Publication published 06 Jun, 2023 Read the published version in BMC Infectious Diseases → Version 1 posted Editorial decision: Major revision 27 Feb, 2023 Reviews received at journal 21 Feb, 2023 Reviewers agreed at journal 31 Jan, 2023 Reviewers invited by journal 25 Jan, 2023 Editor assigned by journal 25 Jan, 2023 Editor invited by journal 25 Jan, 2023 Submission checks completed at journal 25 Jan, 2023 First submitted to journal 11 Jan, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2468599","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":170589701,"identity":"4494eea6-c836-48de-88ab-7d9c6caa02a6","order_by":0,"name":"Yan Tong","email":"","orcid":"","institution":"Indiana University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Tong","suffix":""},{"id":170589702,"identity":"f3eaac1c-1138-4175-a090-42d821f23696","order_by":1,"name":"Philip Tonui","email":"","orcid":"","institution":"Moi 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19:44:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2468599/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2468599/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12879-023-08323-8","type":"published","date":"2023-06-06T21:06:02+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":44731238,"identity":"a55550bf-ceaf-4f83-bef7-f4e1d78f94c4","added_by":"auto","created_at":"2023-10-16 21:40:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":450384,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2468599/v1/e04f5293-76a3-4b77-a777-88eb73bd1cdf.pdf"},{"id":32113469,"identity":"cdc95a4f-117e-46ec-83eb-4dd4f7581ae1","added_by":"auto","created_at":"2023-01-27 11:57:26","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":22091,"visible":true,"origin":"","legend":"","description":"","filename":"Supptable112722.docx","url":"https://assets-eu.researchsquare.com/files/rs-2468599/v1/0fea771c1afb69734c09eb83.docx"}],"financialInterests":"Competing interest reported. Dr. Brown currently receives research funding and has received royalties and consulting fees in the past from Merck and Co., Inc. Dr. Brown serves on the Scientific Advisory Board for PDS, Inc.\nThe other Authors do not possess any potential conflicts of interest.","formattedTitle":"\u003cp\u003eAssociation of Plasma Aflatoxin With Persistent Detection of Oncogenic Human Papillomaviruses in Cervical Samples From Kenyan Women Enrolled in a Longitudinal Study \u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCervical cancer is a common malignancy among Kenyan women [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The incidence rate of cervical cancer in Kenya is 31.3 per 100,000 women per year and the mortality rate is 25 per 100,000 women per year, figures considerably higher than those in wealthy countries [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Oncogenic types of human papillomaviruses (\u0026ldquo;high-risk\u0026rdquo;, or HR-HPV) are the causative agents of cervical cancer. However, only a small percentage of women infected with HR-HPV will develop cancer, indicating the importance of cofactors associated with HR-HPV persistence that contribute to the occurrence of cervical cancer [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Women with persistent infection with oncogenic HPV are at significantly higher risk of cervical cancer [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. HIV infection is one cofactor that imparts a higher likelihood of HR-HPV persistence [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. HR-HPV detection and persistence are also prevalent among Kenyan women who are not HIV-infected [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDietary aflatoxin may be another risk factor for HR-HPV persistence that is additive with HIV infection. Aflatoxin is a potent carcinogen and immunosuppressive agent produced by certain strains of Aspergillus, a mold that infects corn crops [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Large percentages of people living in sub-Saharan African countries are exposed to aflatoxin. We previously showed in a cross-sectional analysis that plasma aflatoxin biomarkers were detected among 57% of HIV-uninfected Kenyan women enrolled in a prospective study of HPV epidemiology and associated with cervical detection of A9 HPV types [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. An additional analysis was performed using longitudinal data from this cohort to examine associations between plasma aflatoxin detection and cervical HR-HPV persistence.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Population\u003c/h2\u003e \u003cp\u003eKenyan women were enrolled from September 2015 to October 2016 at the Academic Model Providing Access to Healthcare (AMPATH) Cervical Cancer Screening Program (CCSP) at Moi Teaching and Referral Hospital in Eldoret, Kenya [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. They were participants in a prospective cohort study investigating biological, behavioral, and environmental risk factors for oncogenic HPV persistence, a part of the East African Consortium for Human Papillomavirus and Cervical Cancer in Women Living with HIV/AIDS [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Details of study enrollment procedures have been previously published [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Briefly, women aged 18 to 60 years living within 30 km of Eldoret presenting for screening at the CCSP were asked to participate in the study if they had a normal visual inspection with acetic acid (VIA) of the uterine cervix that day.\u003c/p\u003e \u003cp\u003eA total of 223 women consented to participation and enrolled in the study, including 116 HIV-infected and 107 HIV-uninfected women. Plasma obtained at enrollment was available for 87 of 107 HIV-uninfected women, but no plasma sample was available for the HIV-infected women. Of the 87 HIV-uninfected women with available plasma, 67 women had at least two adequate cervical swab samples (based on beta globin testing) obtained at enrollment and at 12- or/and 24-month follow-up visits. These 67 women represented the analytical cohort for this post-hoc analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eInterview and questionnaire\u003c/h2\u003e \u003cp\u003eStructured face-to-face interviews of the participants by trained researchers were conducted at enrollment to capture social, behavioral, and biological information, including age, marital status, educational level, home ownership, walking distance to the local clinic, number of lifetime sexual partners, and age of first sex [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eCervical swab and plasma sample collection\u003c/h2\u003e \u003cp\u003eA cervical swab for HPV testing was collected by a nurse or physician as part of the inspection for cervical cancer screening. Swabs were placed in standard transport media and frozen at -80\u0026deg;C in the AMPATH Reference Laboratory. Plasma was collected and frozen at -20\u0026deg;C at the same laboratory.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eHPV testing\u003c/h2\u003e \u003cp\u003eCervical specimens were transported on dry ice to the Kenya Medical Research Institute-University of Massachusetts Medical School (KEMRI-UMMS) Laboratory for processing, DNA extraction, and subsequent genotyping [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The Roche Linear Array was used to determine HPV types (Roche Molecular Systems, Inc., Branchburg, NJ USA) as previously described [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. HPV 16-positive, negative, and human beta-globin (used to assess specimen adequacy) controls provided by the manufacturer were tested with each batch of samples.\u003c/p\u003e \u003cp\u003eHPV types were grouped into \u0026ldquo;high-risk\u0026rdquo; (HR-HPV) and \u0026ldquo;low-risk\u0026rdquo; (LR-HPV) based on the designation in the Roche Linear Array instructions, or HR-HPV types as designated by the International Agency for the Research on Cancer (IARC) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. HPV types were further grouped into A9 and A7 types [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The specific HPV types included in each group are detailed in Results.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eAflatoxin-albumin adduct (AFB\u003csub\u003e1\u003c/sub\u003e-lys) detection in plasma samples\u003c/h2\u003e \u003cp\u003ePlasma aflatoxin B1-lysine (AFB\u003csub\u003e1\u003c/sub\u003e-lys) was measured at the Department of Environmental Health and Engineering of the Johns Hopkins Bloomberg School of Public Health, using a minor variation of the method reported by McCoy and colleagues [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Briefly, plasma (150 \u0026micro;L) was spiked with an internal standard (0.5 ng AFB\u003csub\u003e1\u003c/sub\u003e-d4-lysine in 100 \u0026micro;L), combined with Pronase (EMD Millipore, Billerica MA, USA) protease solution (3.25 mg in 0.5 mL phosphate-buffered saline), and incubated for 18 hours at 37\u0026deg;C. Solid-phase extraction\u0026ndash;processed samples (Oasis MAX columns; Waters, Milford, MA, USA) were analyzed with ultra-high pressure liquid chromatography (UHPLC)-isotope dilution mass spectrometry on a ThermoFisher Scientific (San Jose, CA, USA) system composed of a Vanquish UHPLC and a TSQ Quantis triple quadrupole mass spectrometer in positive electrospray ionization mode [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePersistent HPV detection\u003c/h2\u003e \u003cp\u003eType-specific HPV testing results obtained from the enrollment, 12-month and 24-month cervical samples were combined to determine the detection category of each specific HPV type for each woman. Three categories of HPV detection were determined: No detection, Incident Detection, and Persistent Detection. To be included, two or three of a participant\u0026rsquo;s cervical samples (Enrollment, 12-month, or 24-month) had to be available; one of the three samples could be missing. The type-specific HPV detection categories were defined as follows: I. No detection: No detection for the specific HPV type at any of the three time-points; II. Incident detection: One sample positive for detection of a specific HPV type, but other samples were negative for that type; III. Persistent detection: Two samples taken one year apart, or two years apart were positive for detection of a specific HPV type. The third sample could be negative for that type (or missing).\u003c/p\u003e \u003cp\u003eAt the level of study participants, a woman\u0026rsquo;s HPV detection status was defined as the highest level of HPV detection category in the descending order of \u0026ldquo;Persistent detection,\u0026rdquo; \u0026ldquo;Incident detection,\u0026rdquo; and \u0026ldquo;No detection\u0026rdquo; among her type-specific HPV detection episodes within a combined group of specific HPV types. For example, a woman is classified as at the status of persistent detection in HR-HPV if any type-specific \u0026ldquo;persistence detection\u0026rdquo; episode is identified among the HR-HPV types. The subsequent analysis of HPV detection was conducted at the level of participant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eDemographic and behavioral characteristics of participants at enrollment (age, marital status, educational level, home ownership, walking distance to health care of ⩾60 min, number of lifetime sex partners, and age of first sex) were summarized by descriptive statistics and compared between women with and without detectable plasma AFB\u003csub\u003e1\u003c/sub\u003e-lys using t-tests, chi-square tests, or Wilcoxon rank sum tests. Frequencies and percentages of HPV detections (\u0026ldquo;No detection\u0026rdquo;, \u0026ldquo;Incident detection\u0026rdquo; and \u0026ldquo;Persistent detection\u0026rdquo;) in women were compared between those with and without detectable plasma AFB\u003csub\u003e1\u003c/sub\u003e-lys using chi-square tests or Fisher\u0026rsquo;s exact tests. Plasma AFB1-lys concentration (pg/uL) were summarized in mean, standard deviation (std), median and interquartile range (IQR) and compared among women with different HPV detection status using Wilcoxon rank sum tests. In addition, ordinal logistic regression models were fitted to examine associations of HPV detection (persistent detection vs. incident detection vs. no detection) with plasma aflatoxin detection, controlling for demographic and behavioral characteristics of the women as confounders. The proportional odds assumption was examined for each fitted ordinal logistic regression model to ensure validity of the model. All analyses were performed using SAS Version 9.4 (Cary, NC).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eEthics considerations\u003c/h2\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv class=\"Section2\" id=\"Sec12\"\u003e\n \u003ch2\u003eOverall characteristics of participants and aflatoxin (AFB\u003csub\u003e1\u003c/sub\u003e-lys) detection\u003c/h2\u003e\n \u003cp\u003eThe median age (IQR) at enrollment of 67 participants with an available plasma sample and valid HPV testing results was 34.0 (30.0, 38.0) years (range 21 to 46 years) (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Of 67 women, 27 (40.3%) had no detection of AFB\u003csub\u003e1\u003c/sub\u003e-lys in plasma, and 40 women (59.7%) had AFB\u003csub\u003e1\u003c/sub\u003e-lys detected (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Women with and without detectable plasma AFB\u003csub\u003e1\u003c/sub\u003e-lys were not significantly different in age, being married, having more than secondary school education, home ownership, living at a walking distance to health care of \u0026ge;\u0026thinsp;60 minutes, number of lifetime sex partners, or age of first sex (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eTable 1. Demographic and behavioral characteristics of women with or without plasma AFB1-lys detection \u0026nbsp;\u003c/p\u003e\n \u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"39.49579831932773%\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"17.647058823529413%\"\u003e\n \u003cp\u003eOverall\u003cbr\u003e\u0026nbsp;N=67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" width=\"42.857142857142854%\"\u003e\n \u003cp\u003ePlasma\u0026nbsp;AFB1-lys\u0026nbsp;Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" width=\"39.21568627450981%\"\u003e\n \u003cp\u003eNo\u003cbr\u003e\u0026nbsp;N=27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"35.294117647058826%\"\u003e\n \u003cp\u003eYes\u003cbr\u003e\u0026nbsp;N=40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.49019607843137%\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.49579831932773%\"\u003e\n \u003cp\u003eMedian age in years (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"17.647058823529413%\"\u003e\n \u003cp\u003e34.0 (30.0, 38.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.80672268907563%\"\u003e\n \u003cp\u003e35.0 (30.0, 40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.126050420168067%\"\u003e\n \u003cp\u003e33.5 (30.0, 38.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"10.92436974789916%\"\u003e\n \u003cp\u003e0.537\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.49579831932773%\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"17.647058823529413%\"\u003e\n \u003cp\u003e49 (73.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.80672268907563%\"\u003e\n \u003cp\u003e19 (70.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.126050420168067%\"\u003e\n \u003cp\u003e30 (75.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"10.92436974789916%\"\u003e\n \u003cp\u003e0.675\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.49579831932773%\"\u003e\n \u003cp\u003eMore than secondary school education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"17.647058823529413%\"\u003e\n \u003cp\u003e10 (14.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.80672268907563%\"\u003e\n \u003cp\u003e2 (7.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.126050420168067%\"\u003e\n \u003cp\u003e8 (20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"10.92436974789916%\"\u003e\n \u003cp\u003e0.185\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.49579831932773%\"\u003e\n \u003cp\u003eHome ownership\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"17.647058823529413%\"\u003e\n \u003cp\u003e20 (29.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.80672268907563%\"\u003e\n \u003cp\u003e7 (25.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.126050420168067%\"\u003e\n \u003cp\u003e13 (32.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"10.92436974789916%\"\u003e\n \u003cp\u003e0.564\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.49579831932773%\"\u003e\n \u003cp\u003eWalking distance to health care \u0026ge;60 mins\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"17.647058823529413%\"\u003e\n \u003cp\u003e7 (10.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.80672268907563%\"\u003e\n \u003cp\u003e2 (7.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.126050420168067%\"\u003e\n \u003cp\u003e5 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"10.92436974789916%\"\u003e\n \u003cp\u003e0.693\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.49579831932773%\"\u003e\n \u003cp\u003eMedian number of lifetime sex partners (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"17.647058823529413%\"\u003e\n \u003cp\u003e3.0 (1.0, 4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.80672268907563%\"\u003e\n \u003cp\u003e2.0 (1.0, 4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.126050420168067%\"\u003e\n \u003cp\u003e3.0 (1.0, 4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"10.92436974789916%\"\u003e\n \u003cp\u003e0.588\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.49579831932773%\"\u003e\n \u003cp\u003eMedian age of first sex (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"17.647058823529413%\"\u003e\n \u003cp\u003e18.0 (16.0, 20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"16.80672268907563%\"\u003e\n \u003cp\u003e18.0 (17.0, 20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"15.126050420168067%\"\u003e\n \u003cp\u003e18.0 (16.0, 20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"10.92436974789916%\"\u003e\n \u003cp\u003e0.792\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003csup\u003e1\u003c/sup\u003eP-value from t-test\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e2\u003c/sup\u003eP-value from Chi-square test\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e3\u003c/sup\u003eP-value from Fisher\u0026rsquo;s exact test\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e4\u003c/sup\u003eP-value from Wilcoxon rank sum test\u003c/p\u003e\n \u003cp\u003eA total of 87 women in the original cohort had plasma samples tested for AFB\u003csub\u003e1\u003c/sub\u003e-lys, including 67 women consisting of the analytical cohort and 20 women who did not complete at least two study visits. Comparisons between the 67 women in this analytical cohort and the 20 women who did not complete at least two visits were conducted with respect to the demographics/behavioral characteristics and plasma AFB1-lys detection/concentration. No significant differences in these variables were found between the two groups of women (data not shown).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec13\"\u003e\n \u003ch2\u003eAssociation of plasma AFB\u003csub\u003e1\u003c/sub\u003e-lys detection with persistent HPV detection\u003c/h2\u003e\n \u003cp\u003eFrequencies and percentages of HPV detections (\u0026ldquo;no detection\u0026rdquo;, \u0026ldquo;incident detection\u0026rdquo; and \u0026ldquo;persistent detection\u0026rdquo;) in women with and without plasma AFB\u003csub\u003e1\u003c/sub\u003e-lys detection and mean (STD) and median (IQR) of plasma AFB\u003csub\u003e1\u003c/sub\u003e-lys concentration (pg/uL) among women with different HPV detections are shown in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. There was a trend of significantly increasing plasma AFB\u003csub\u003e1\u003c/sub\u003e-lys concentrations among women who had no detection, incident detection, or persistent detection for any HPV type (p\u0026thinsp;=\u0026thinsp;0.036), HR-HPV types (p\u0026thinsp;=\u0026thinsp;0.020), or vaccine-unprotected HR-HPV types (p\u0026thinsp;=\u0026thinsp;0.017) (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Similar trends in increasing plasma AFB\u003csub\u003e1\u003c/sub\u003e-lys concentrations were observed for some other groups of HPV types, however, these were not significant (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eTable 2. Frequency and percentage of HPV detection in 67 women with and without plasma AFB1-lys detection, and mean (standard deviation, or STD) and median (interquartile range, or IQR) of plasma AFB1-lys concentration (pg/uL).\u0026nbsp;\u003c/p\u003e\n \u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" summary=\"Procedure Print: Data Set WORK.CUMCELL\" width=\"923\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" width=\"21.343445287107258%\"\u003e\n \u003cp\u003eHPV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" width=\"14.95124593716143%\"\u003e\n \u003cp\u003eHPV detection category\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" width=\"38.353196099674975%\"\u003e\n \u003cp\u003ePlasma AFB1-lys\u0026nbsp;\u003c/p\u003e\n \u003cp\u003econcentration (pg/uL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" width=\"25.35211267605634%\"\u003e\n \u003cp\u003ePlasma AFB1-lys\u0026nbsp;\u003c/p\u003e\n \u003cp\u003edetection\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"24.489795918367346%\"\u003e\n \u003cp\u003eN, Mean (STD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"22.448979591836736%\"\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"13.26530612244898%\"\u003e\n \u003cp\u003eP- Value\u003csup\u003e13\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003eNo (N=27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.285714285714286%\"\u003e\n \u003cp\u003eYes (N=40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"11.224489795918368%\"\u003e\n \u003cp\u003eP-Value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003eAny HPV\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003eNo Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e23, 0.030 (0.042)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.000 (0.000-0.066)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e14 (51.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e9 (22.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\n \u003cp\u003e0.043\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003eIncident Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e32, 0.050 (0.043)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.052 (0.000-0.088)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e10 (37.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e22 (55.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003ePersistent Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e12, 0.078 (0.068)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.081 (0.014-0.098)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e3 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e9 (22.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003eHR-HPV\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003eNo Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e30, 0.034 (0.044)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.000 (0.000-0.065)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e17 (63.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e13 (32.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\n \u003cp\u003e0.038\u003csup\u003e11\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003eIncident Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e26, 0.049 (0.041)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.050 (0.000-0.091)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e8 (29.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e18 (45.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003ePersistent Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e11, 0.086 (0.066)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.082 (0.027-0.098)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e2 (7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e9 (22.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003eIARC HR-HPV\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003eNo Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e35, 0.046 (0.057)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.035 (0.000-0.073)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e0.410\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e17 (63.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e18 (45.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\n \u003cp\u003e0.361\u003csup\u003e12\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003eIncident Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e24, 0.048 (0.042)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.046 (0.000-0.093)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e8 (29.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e16 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003ePersistent Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e8, 0.058 (0.042)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.078 (0.014-0.093)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e2 (7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e6 (15.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003eA9 HPV\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003eNo Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e45, 0.045 (0.053)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.035 (0.000-0.073)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e0.395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e20 (74.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e25 (62.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\n \u003cp\u003e0.567\u003csup\u003e12\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003eIncident Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e17, 0.055 (0.043)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.067 (0.000-0.094)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e5 (18.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e12 (30.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003ePersistent Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e5, 0.054 (0.049)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.082 (0.000-0.089)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e2 (7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e3 (7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003eNon-HPV 16 A9\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003eNo Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e48, 0.044 (0.052)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.031 (0.000-0.073)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e0.171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e22 (81.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e26 (65.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\n \u003cp\u003e0.175\u003csup\u003e12\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003eIncident Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e15, 0.062 (0.041)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.079 (0.023-0.095)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e3 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e12 (30.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003ePersistent Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e9, 0.047 (0.054)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.045 (0.000-0.093)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e2 (7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e2 (5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003eA7 HPV\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003eNo Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e55, 0.048 (0.050)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.047 (0.000-0.085)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e0.097\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e23 (85.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e32 (80.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\n \u003cp\u003e0.236\u003csup\u003e12\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003eIncident Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e8, 0.025 (0.029)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.016 (0.000-0.050)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e4 (14.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e4 (10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003ePersistent Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e4, 0.096 (0.067)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.086 (0.050-0.142)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e4 (10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003eNon-HPV 18 A7\u003csup\u003e7\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003eNo Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e59, 0.049 (0.048)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.047 (0.000-0.085)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e0.090\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e23 (85.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e36 (90.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\n \u003cp\u003e0.661\u003csup\u003e12\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003eIncident Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e7, 0.024 (0.031)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.000 (0.000-0.059)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e4 (14.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e3 (7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003ePersistent Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e1, 0.186 (-)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.186 (0.186-0.186)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e1 (2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003eVaccine-protected HR-HPV\u003csup\u003e8\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003eNo Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e41, 0.046 (0.054)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.040 (0.000-0.073)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e0.505\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e18 (66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e23 (57.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\n \u003cp\u003e0.625\u003csup\u003e12\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003eIncident Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e18, 0.047 (0.045)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.042 (0.000-0.094)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e7 (25.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e11 (27.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003ePersistent Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e8, 0.058 (0.042)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.078 (0.014-0.093)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e2 (7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e6 (15.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003eVaccine-unprotected HR-HPV\u003csup\u003e9\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003eNo Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e47, 0.038 (0.044)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.023 (0.000-0.079)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e23 (85.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e24 (60.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\n \u003cp\u003e0.064\u003csup\u003e12\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003eIncident Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e16, 0.054 (0.040)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.063 (0.008-0.090)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e4 (14.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e12 (30.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003ePersistent Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e4, 0.137 (0.071)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.133 (0.077-0.198)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e4 (10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003eLR-HPV\u003csup\u003e10\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003eNo Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e44, 0.045 (0.047)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.038 (0.000-0.081)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e0.414\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e19 (70.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e25 (62.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\n \u003cp\u003e0.284\u003csup\u003e12\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003eIncident Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e22, 0.057 (0.055)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.058 (0.000-0.091)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e7 (25.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e15 (37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.343445287107258%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.95124593716143%\"\u003e\n \u003cp\u003ePersistent Detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601300108342361%\"\u003e\n \u003cp\u003e1, 0.000 (-)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.301191765980498%\"\u003e\n \u003cp\u003e0.000 (0.000-0.000)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.450704225352112%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e1 (3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.100758396533044%\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.150595882990249%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003csup\u003e1\u003c/sup\u003eAny HPV: HPV 6, 11, 16, 18, 26, 31, 33, 35, 39, 40, 42, 45, 51, 52, 53, 54, 55, 56, 58, 59, 61, 62, 64, 66, 67, 68, 70, 71, 72, 73, 81, 82, 83, 84, CP6108, IS39\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e2\u003c/sup\u003eHR-HPV (High-Risk HPV): HPV 16, 18, 26, 31, 33, 35, 39, 45, 51, 52, 53, 56, 58, 59, 66, 67, 68, 69, 70, 73, 82, IS39\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e3\u003c/sup\u003eIARC HR-HPV: HPV 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e4\u003c/sup\u003eA9 HPV: HPV 16, 31, 33, 35, 52, 58\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e5\u003c/sup\u003eNon-HPV 16 A9: HPV 31, 33, 35, 52, 58\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e6\u003c/sup\u003eA7 HPV: HPV 18, 39, 45, 59, 68\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e7\u003c/sup\u003eNon-HPV 18 A7: HPV 39, 45, 59, 68\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e8\u003c/sup\u003eVaccine-protected HR-HPV: HPV 16, 18, 31, 33, 45, 52, 58\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e9\u003c/sup\u003eVaccine-unprotected HR-HPV: HPV 26, 35, 39, 51, 53, 56, 59, 66, 67, 68, 69, 70, 73, 82, IS39\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e10\u003c/sup\u003eLR-HPV (Low-Risk HPV): HPV 6, 11, 40, 42, 54, 55, 61, 62, 64, 71, 72, 81, 83, 84, CP6108\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e11\u003c/sup\u003eP-value from Chi-square test\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e12\u003c/sup\u003eP-value from Fisher\u0026rsquo;s exact test\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e13\u003c/sup\u003eP-value from Wilcoxon rank sum test\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;In addition, compared with women without detectable plasma AFB\u003csub\u003e1\u003c/sub\u003e-lys, women with detectable plasma AFB\u003csub\u003e1\u003c/sub\u003e-lys demonstrated significantly higher percentages of detection for any HPV type (22.5% vs. 11.1% for persistent detection and 55.0% vs. 37.0% for incident detection, p\u0026thinsp;=\u0026thinsp;0.043) and HR-HPV type (22.5% vs. 7.4% for persistent detection and 45.0% vs. 29.6% for incident detection, p\u0026thinsp;=\u0026thinsp;0.038). Similar patterns of HPV detections between women with and without detectable plasma AFB\u003csub\u003e1\u003c/sub\u003e-lys were found for all other HPV combination types except for LR-HPV types. However these were not statistically significant, possibly due to small sample sizes.\u003c/p\u003e\n \u003cp\u003eA total of 13 episodes of type-specific persistent HPV detections occurred in 12 women (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Among these episodes, 12 were HR-HPV types, including 10 episodes that occurred in 9 of 40 women with detectable plasma AFB\u003csub\u003e1\u003c/sub\u003e-lys, and 2 episodes occurring in 2 of 27 women without detectable plasma AFB\u003csub\u003e1\u003c/sub\u003e-lys (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). HPV 18 was the most frequently detected persistent type (3 episodes), all occurring in women with detectable plasma AFB\u003csub\u003e1\u003c/sub\u003e-lys (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u0026nbsp;\u003c/p\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab3\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eEpisodes of type-specific persistent HPV detection and corresponding plasma AFB1-lys detection/concentration.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSubject\u003c/p\u003e\n \u003cp\u003eID\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eType-specific HPV Detection\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePlasma AFB1-lys\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEnrollment\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e12-month\u003c/p\u003e\n \u003cp\u003evisit\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e24-month\u003c/p\u003e\n \u003cp\u003evisit\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePersistent\u003c/p\u003e\n \u003cp\u003edetection\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDetection\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003cp\u003e(pg/uL)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHPV 16\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2-year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.082\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHPV 18\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eneg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1-year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHPV 18\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2-year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.098\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM189\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHPV 18\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eneg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1-year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.073\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM069\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHPV 52\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eneg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1-year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHPV 52\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eneg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1-year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.097\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHPV 53\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eneg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1-year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.080\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHPV 58\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eneg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1-year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHPV 58\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eneg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1-year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.089\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHPV 68\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eneg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1-year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.186\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHPV 70\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eneg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1-year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.209\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM189\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHPV 70\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eneg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1-year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.073\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHPV 83\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eneg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1-year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003e\u003csup\u003e1\u003c/sup\u003e M189 had two episodes of type-specific persistent HPV detections, one episode with HPV 18\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003eand one episode with HPV 70\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003e\u003csup\u003e2\u003c/sup\u003e High-Risk HPV type\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003e\u003csup\u003e3\u003c/sup\u003e Low-Risk HPV type\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003eOrdinal logistic regression analysis revealed that detectable plasma AFB\u003csub\u003e1\u003c/sub\u003e-lys was associated with a higher risk of persistent detection for any HPV type (OR\u0026thinsp;=\u0026thinsp;3.03, 95%CI\u0026thinsp;=\u0026thinsp;1.08\u0026ndash;8.55, P\u0026thinsp;=\u0026thinsp;0.036), HR-HPV types (OR\u0026thinsp;=\u0026thinsp;3.63, 95%CI\u0026thinsp;=\u0026thinsp;1.30-10.13, P\u0026thinsp;=\u0026thinsp;0.014), and HR-HPV types not included in the 9-valent HPV vaccine (Vaccine-unprotected HR-HPV types) (OR\u0026thinsp;=\u0026thinsp;4.46, 95%CI\u0026thinsp;=\u0026thinsp;1.13\u0026ndash;17.58, P\u0026thinsp;=\u0026thinsp;0.032) after adjustment for established and suspected confounders (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). The proportional odds assumption was validated for each ordinal logistic regression model. There was no statistically significant association of detectable plasma AFB\u003csub\u003e1\u003c/sub\u003e-lys with persistent detection of sub-groups of HR-HPV types, for HR-HPV types protected by the 9-valent HPV vaccine (Vaccine-protected HR-HPV types), or for low-risk (LR) HPV types (Supplemental Table 1).\u0026nbsp;\u003c/p\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab4\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eOrdinal logistic regression analyses of Any HPV, HR-HPV, Vaccine-protected HR-HPV, and Vaccine-unprotected HR-HPV detection (persistent detection vs. incidence detection vs. no detection) with plasma AFB1-lys detection and demographic/behavioral characteristics of women\u003csup\u003e5\u003c/sup\u003e.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eVariables included in the model\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eAny HPV\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eHR-HPV\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eVaccine-protected\u003c/p\u003e\n \u003cp\u003eHR-HPV\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eVaccine-unprotected\u003c/p\u003e\n \u003cp\u003eHR-HPV\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePlasma AFB1-lys detection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.03 (1.08\u0026ndash;8.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.63 (1.30\u0026ndash;10.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.55 (0.54\u0026ndash;4.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.413\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.46 (1.13\u0026ndash;17.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.88 (0.79\u0026ndash;0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.92 (0.83\u0026ndash;1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.93 (0.83\u0026ndash;1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.91 (0.79\u0026ndash;1.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.188\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.28 (0.08\u0026ndash;0.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.63 (0.20\u0026ndash;2.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.442\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.38 (0.11\u0026ndash;1.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.58 (0.15\u0026ndash;2.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.437\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMore than secondary school education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.13 (0.27\u0026ndash;4.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.868\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.72 (0.17\u0026ndash;2.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.645\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.41 (0.33\u0026ndash;5.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.10 (0.17\u0026ndash;6.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.918\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHome ownership\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.43 (0.71\u0026ndash;8.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.60 (0.48\u0026ndash;5.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.441\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.45 (0.41\u0026ndash;5.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.563\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.78 (0.38\u0026ndash;8.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.465\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWalking distance to health care\u0026thinsp;\u0026ge;\u0026thinsp;60 mins\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.46 (0.27\u0026ndash;7.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.657\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.83 (0.16\u0026ndash;4.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.820\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.46 (0.08\u0026ndash;2.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.397\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.27 (0.36\u0026ndash;14.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.380\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumber of lifetime sex partners\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.07 (0.86\u0026ndash;1.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.544\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.10 (0.88\u0026ndash;1.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.405\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.02 (0.81\u0026ndash;1.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.880\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.99 (0.77\u0026ndash;1.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.918\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge of first sex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.16 (0.98\u0026ndash;1.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.088\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.08 (0.92\u0026ndash;1.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.351\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.18 (0.99\u0026ndash;1.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.74 (0.57\u0026ndash;0.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003e\u003csup\u003e1\u003c/sup\u003eAny HPV: HPV 6, 11, 16, 18, 26, 31, 33, 35, 39, 40, 42, 45, 51, 52, 53, 54, 55, 56, 58, 59, 61, 62, 64, 66, 67, 68, 70, 71, 72, 73, 81, 82, 83, 84, CP6108, IS39\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003e\u003csup\u003e2\u003c/sup\u003eHR-HPV (High-Risk HPV): HPV 16, 18, 26, 31, 33, 35, 39, 45, 51, 52, 53, 56, 58, 59, 66, 67, 68, 69, 70, 73, 82, IS39\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003e\u003csup\u003e3\u003c/sup\u003eVaccine-protected HR-HPV: HPV 16, 18, 31, 33, 45, 52, 58\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003e\u003csup\u003e4\u003c/sup\u003eVaccine-unprotected HR-HPV: HPV 26, 35, 39, 51, 53, 56, 59, 66, 67, 68, 69, 70, 73, 82, IS39\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this longitudinal study, women with detectable aflatoxin biomarkers in plasma had a higher risk of persistent detection of oncogenic cervical HPV. Although only a small percentage of HPV-infected women will eventually develop cervical cancer, women with persistent detection of HR-HPV are at the highest risk for this malignancy [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Aflatoxins are mycotoxins produced by certain Aspergillus species during growth or after harvesting of corn and several other crops [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. These compounds are classified by the International Agency for Research on Cancer (IARC) as class I carcinogens [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In addition, aflatoxins are potent immunosuppressive agents [\u003cspan additionalcitationids=\"CR28 CR29\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Exposure to aflatoxins contributes heavily to the worldwide burden of hepatocellular carcinoma, but the contribution of aflatoxin exposure to other cancers is unknown [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. This study revealed an association between aflatoxin exposure and persistent HR-HPV detection, the major risk factor for cervical cancer.\u003c/p\u003e \u003cp\u003eA previous cross-sectional study showed significant associations between plasma aflatoxin biomarkers and detection of A9 HPV types in cervical samples among HIV-uninfected Kenyan women [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The current analysis employed a subset of the original cohort with the longitudinal follow-up data on HPV testing, disclosing the relationship of aflatoxins with persistent detections of HR-HPV, and raising the possibility that aflatoxin could be a contributing factor to cervical cancer. We are not aware of other studies describing an association of aflatoxin with HPV persistence, cervical dysplasia, or cancer.\u003c/p\u003e \u003cp\u003eIt is possible that HR-HPV types and dietary aflatoxin act synergistically in increasing the risk of cervical cancer in Kenyan women. Aflatoxins have been detected in cervical tissue and could potentially act directly on cervical cells in the carcinogenic process, but this hypothesis has not been studied [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. It is also possible the immunosuppression caused by aflatoxin could lead to poor immune control of oncogenic HPV infections, leading to persistence. These hypotheses need to be further investigated. In addition, it has a tremendous public health impact to investigate the role of the interaction between aflatoxin exposure and persistent HPV infection in the etiology, pathogenesis, and prevention of cervical cancer and its precursor lesions in large epidemiological studies especially in developing countries.\u003c/p\u003e \u003cp\u003eAflatoxin exposure is widespread in many sub-Saharan African countries, largely due to consumption of contaminated corn, the major source of daily calories for many people, especially for poor families [\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Leroy et al., showed higher serum aflatoxin levels from adult Kenyan women associated with lower household socio-economic status [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Women with the lowest socio-economic status also have the lowest rates of cervical cancer screening, and therefore bear the highest burden of cervical cancer [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Aflatoxin, as a potential environmental risk factor of cervical cancer, demands more recognition for public health emphasis.\u003c/p\u003e \u003cp\u003eSome limitations of the present study include a modest sample size, as not all women initially analyzed for the association of aflatoxin detection and HR-HPV detection continued in the longitudinal study. However, our analysis showed that there were no significant differences in demographic/behavioral characteristics and plasma AFB\u003csub\u003e1\u003c/sub\u003e-lys detection/concentration between the women who remained in the original study and included in this analysis compared to those who did not continue in the original study. Another potential limitation is that dietary factors that modulate immune functions were not included as potential confounders in our data analysis, which could possibly distort the findings of the present study. For example, malnourishment may contribute to suppressed immunity and render such women more susceptible to the toxic effects of aflatoxin, and thus, more prone to persistent HPV infection [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. In addition, the results of our study may be subject to multiple comparisons due to a relatively large number of the models presented. However, this is unlikely because all exposure and outcome variables included in the constructed models were carefully selected in terms of the findings of previous studies and biological relevance.\u003c/p\u003e \u003cp\u003eIn summary, detection of plasma aflatoxin biomarkers was associated with increased persistence of oncogenic HPV types, in cervical samples from HIV-uninfected Kenyan women. Further studies are needed to determine if exposure to aflatoxin interacts with HPV infection to modulate the risk of cervical cancer in Kenya and other developing countries. In addition, studies are underway to examine associations of aflatoxin exposure and HR-HPV infection on occurrence of cervical dysplasia in a cohort of HIV-infected sub-Saharan women, as HIV infection increases susceptibility to cervical cancer.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eEthics approval and consent to participate\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eStudy approval was granted from the local review board at Moi Teaching and Referral Hospital (MTRH) and Moi University, Eldoret, Kenya, the Kenya Medical Research Institute\u0026rsquo;s Scientific and Ethics Review Unit (KEMRI-SERU) and the Institutional Review Board of Indiana University. All participants provided written informed consent, either in Swahili or English, for participation in the study and for use of clinical specimens. All study procedures were performed in accordance with relevant guidelines and regulations outlined by the Ethics Review Boards indicated above.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cem\u003eConsent for publication\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe Authors\u0026nbsp;give the Publisher the permission to publish this work.\u003cbr\u003e \u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author (Dr. Brown and the additional authors) upon reasonable request and with permission of AMPATH.\u0026nbsp;\u003cbr\u003e \u003cem\u003eCompeting interests\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eDr. Brown currently receives research funding and has received royalties and consulting fees in the past from Merck and Co., Inc. \u0026nbsp;Dr. Brown serves on the Scientific Advisory Board for PDS, Inc. \u0026nbsp;The other Authors do not possess any potential conflicts of interest. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunding\u0026nbsp;\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNational Cancer Institute, United States, 1U54CA190151-01, and National Cancer Institute, United States, P30 CA082709\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cem\u003eAuthors\u0026apos; contributions\u003c/em\u003e \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eYT contributed to conceptualization, methodology, data curation, formal analysis, validation, writing (original, review and editing). \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePT contributed to study supervision, investigation, writing (review and editing).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOO contributed to funding acquisition, project administration, and writing (review and editing).\u003c/p\u003e\n\u003cp\u003eJZ contributed to funding acquisition, writing (review and editing).\u003c/p\u003e\n\u003cp\u003eTM contributed to investigation (performance of laboratory tests).\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eKM contributed to study supervision and writing (review and editing).\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eJG contributed to methodology, formal analysis, resources, and writing (review and editing).\u003c/p\u003e\n\u003cp\u003eJS contributed to investigation (performance of laboratory tests).\u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEM contributed to investigation (performance of laboratory tests).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAE contributed to study supervision, and writing (review and editing).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePL contributed to funding acquisition, project administration, and writing (review and editing).\u003c/p\u003e\n\u003cp\u003eDB contributed to funding acquisition, project administration, conceptualization, methodology,\u003c/p\u003e\n\u003cp\u003estudy supervision, writing (original draft, review and editing).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the nurses at the Cervical Cancer Screening Program at Moi Referral and Teaching Hospital for their hard work, kindness, and attention to detail. \u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. 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Aflatoxin B1 exposure increases the risk of hepatocellular carcinoma associated with hepatitis C virus infection or alcohol consumption. Eur J Cancer \u003cstrong\u003e2018\u003c/strong\u003e; 94:37-46.\u003c/li\u003e\n\u003cli\u003eRushing BR, Selim MI. Aflatoxin B1: A review on metabolism, toxicity, occurrence in food, occupational exposure, and detoxification methods. Food Chem Toxicol \u003cstrong\u003e2019\u003c/strong\u003e; 124:81-100.\u003c/li\u003e\n\u003cli\u003eCarvajal M, Berumen J, Guardado-Estrada M. The presence of aflatoxin B(1)-FAPY adduct and human papilloma virus in cervical smears from cancer patients in Mexico. Food additives \u0026amp; contaminants Part A, Chemistry, analysis, control, exposure \u0026amp; risk assessment \u003cstrong\u003e2012\u003c/strong\u003e; 29:258-68.\u003c/li\u003e\n\u003cli\u003eWilliams JH, Phillips TD, Jolly PE, Stiles JK, Jolly CM, Aggarwal D. Human aflatoxicosis in developing countries: a review of toxicology, exposure, potential health consequences, and interventions. The American journal of clinical nutrition \u003cstrong\u003e2004\u003c/strong\u003e; 80:1106-22.\u003c/li\u003e\n\u003cli\u003eWagacha JM, Muthomi JW. Mycotoxin problem in Africa: current status, implications to food safety and health and possible management strategies. International journal of food microbiology \u003cstrong\u003e2008\u003c/strong\u003e; 124:1-12.\u003c/li\u003e\n\u003cli\u003eGnonlonfin GJ, Hell K, Adjovi Y, et al. A review on aflatoxin contamination and its implications in the developing world: a sub-Saharan African perspective. Crit Rev Food Sci Nutr \u003cstrong\u003e2013\u003c/strong\u003e; 53:349-65.\u003c/li\u003e\n\u003cli\u003eLeroy JL, Wang JS, Jones K. Serum aflatoxin B(1)-lysine adduct level in adult women from Eastern Province in Kenya depends on household socio-economic status: A cross sectional study. Social science \u0026amp; medicine \u003cstrong\u003e2015\u003c/strong\u003e; 146:104-10.\u003c/li\u003e\n\u003cli\u003eBa DM, Ssentongo P, Musa J, et al. Prevalence and determinants of cervical cancer screening in five sub-Saharan African countries: A population-based study. Cancer Epidemiol \u003cstrong\u003e2021\u003c/strong\u003e; 72:101930.\u003c/li\u003e\n\u003cli\u003eChirwa GC. Explaining socioeconomic inequality in cervical cancer screening uptake in Malawi. BMC public health \u003cstrong\u003e2022\u003c/strong\u003e; 22:1376.\u003c/li\u003e\n\u003cli\u003eSaeed F, Nadeem M, Ahmed R, Nadeem M, Arshad M, Ullah A. Studying the impact of nutritional immunology underlying the modulation of immune responses by nutritional compounds \u0026ndash; a review, . Food and Agricultural Immunology \u003cstrong\u003e2016\u003c/strong\u003e; 27:205-29.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-2468599/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2468599/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eCervical cancer is common among Kenyan women and is caused by oncogenic human papillomaviruses (HR-HPV). Identification of factors that increase HR-HPV persistence is critically important. Kenyan women exposed to aflatoxin have an increased risk of cervical HR-HPV detection. This analysis was performed to examine associations between aflatoxin and HR-HPV persistence.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eKenyan women were enrolled in a prospective study. The analytical cohort for this analysis included 67 HIV-uninfected women (mean age 34 years) who completed at least two of three annual study visits and had an available blood sample. Plasma aflatoxin was detected using ultra-high pressure liquid chromatography (UHPLC)-isotope dilution mass spectrometry. Annual cervical swabs were tested for HPV (Roche Linear Array). Ordinal logistic regression models were fitted to examine associations of aflatoxin and HPV persistence.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAflatoxin was detected in 59.7% of women and was associated with higher risk of persistent detection of any HPV type (OR\u0026thinsp;=\u0026thinsp;3.03, 95%CI\u0026thinsp;=\u0026thinsp;1.08\u0026ndash;8.55, P\u0026thinsp;=\u0026thinsp;0.036), HR-HPV types (OR\u0026thinsp;=\u0026thinsp;3.63, 95%CI\u0026thinsp;=\u0026thinsp;1.30-10.13, P\u0026thinsp;=\u0026thinsp;0.014), and HR-HPV types not included in the 9-valent HPV vaccine (OR\u0026thinsp;=\u0026thinsp;4.46, 95%CI\u0026thinsp;=\u0026thinsp;1.13\u0026ndash;17.58, P\u0026thinsp;=\u0026thinsp;0.032).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eAflatoxin detection was associated with increased risk of HR-HPV persistence in Kenyan women. Further studies are needed to determine if aflatoxin synergistically interacts with HR-HPV to increase cervical cancer risk.\u003c/p\u003e","manuscriptTitle":"Association of Plasma Aflatoxin With Persistent Detection of Oncogenic Human Papillomaviruses in Cervical Samples From Kenyan Women Enrolled in a Longitudinal Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-01-27 11:57:21","doi":"10.21203/rs.3.rs-2468599/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2023-02-27T07:56:26+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-02-22T02:46:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"ad95a3b6-d4ea-489e-974f-d49959ff0a6e","date":"2023-02-01T03:54:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-01-25T18:38:04+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-01-25T10:28:48+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2023-01-25T10:25:54+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-01-25T10:22:13+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2023-01-11T19:31:24+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"466c2589-a21b-4b35-84ca-e02bee4318f3","owner":[],"postedDate":"January 27th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-10-16T21:24:53+00:00","versionOfRecord":{"articleIdentity":"rs-2468599","link":"https://doi.org/10.1186/s12879-023-08323-8","journal":{"identity":"bmc-infectious-diseases","isVorOnly":false,"title":"BMC Infectious Diseases"},"publishedOn":"2023-06-06 21:06:02","publishedOnDateReadable":"June 6th, 2023"},"versionCreatedAt":"2023-01-27 11:57:21","video":"","vorDoi":"10.1186/s12879-023-08323-8","vorDoiUrl":"https://doi.org/10.1186/s12879-023-08323-8","workflowStages":[]},"version":"v1","identity":"rs-2468599","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2468599","identity":"rs-2468599","version":["v1"]},"buildId":"wLkW0s4AflPzk-lpfg-fK","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}