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Epidemiology and Social

Prevalence of non-HIV cancer risk factors in persons living with HIV/AIDS

a meta-analysis

Park, Lesley S.; Hernández-Ramírez, Raúl U.; Silverberg, Michael J.; Crothers, Kristina; Dubrow, Robert

Author Information
doi: 10.1097/QAD.0000000000000922



Cancer is a leading cause of death among persons living with HIV/AIDS (PLWHA) in the United States and Europe [1–4]. Furthermore, incidence of both AIDS-defining and specific non-AIDS-defining cancers is elevated in PLWHA compared with the general population [5–13] (Table 1). Both impaired immune function and high prevalence of modifiable non-HIV cancer risk factors contribute to this substantial cancer burden [6,14–17]. In this meta-analysis, we estimated the prevalence of cancer risk factors [smoking, alcohol consumption, overweight/obesity, and infection with human papillomavirus (HPV), hepatitis C virus (HCV), and hepatitis B virus (HBV); Table 1] [18–37] among adult PLWHA in Western high-income countries (United States, Canada, Western Europe, Australia) in recent years (2000–2013) from cohort, cross-sectional, case-control, and experimental studies and compared these prevalence estimates with those among adults in the United States; we also compared prevalence estimates between PLWHA and uninfected comparison groups from the same study when such comparison groups were available.

Table 1:
Cancer risk factors and cancer types with elevated risk among persons living with HIV/AIDS (PLWHA), by cancer type [5–13,18–37].a


Study selection

We searched PubMed/MEDLINE to identify relevant references published in English during 2011–2013 and available in PubMed as of 17 April 2014. We cross-referenced Medical Subject Heading (MeSH) terms for each risk factor (Table 2) with MeSH terms ‘HIV infections’ or ‘acquired immunodeficiency syndrome’ and ‘adult.’ One author (R.U.H.R.) screened abstracts to remove clearly ineligible studies. Two authors (R.U.H.R. and R.D.) then independently performed full-text review of the remaining articles for eligibility, with discrepancies resolved by discussion.

Table 2:
PubMed Medical Subject Heading (MeSH) search terms and number of articles identified and contributing to the meta-analysis, by cancer risk factor.

We restricted prevalence estimates to those based on data collected during 2000–2013 [to reflect experience in the modern antiretroviral therapy (ART) era] with at least 100 adult PLWHA living in the United States, Canada, Western Europe, or Australia. We included prospective or retrospective cohort, cross-sectional, case-control, and experimental studies. We excluded publications for which severe selection bias could be anticipated (e.g., estimation of HBV prevalence among hepatocellular carcinoma patients). When eligibility was uncertain we queried authors for clarification.

If the prevalence of a risk factor from a given study was reported in more than one publication, in general we used the following hierarchy to decide which publication to include: availability of a comparison prevalence estimate from uninfected persons; availability of prevalence estimates by sex or high-risk behavior (i.e. MSM and IDU); and sample size. If more than one publication from a given study each presented unique information (e.g., sex-specific prevalence estimates in one publication, and an overall, unstratified prevalence estimate with a larger overall sample size in another publication), each publication contributed to the relevant meta-analysis (e.g., female, male, overall).

Data extraction

Three authors conducted data extraction (R.U.H.R., R.D., and L.S.P.), with independent extraction by a pair of these authors for each data element and with discrepancies resolved by discussion. For prevalence estimates, our denominator was the number of persons with known status for the risk factor. If an article presented a prevalence estimate that included unknowns in the denominator, we re-calculated the prevalence estimate, excluding unknowns. We examined eligible publications identified from each specific risk factor search for the presence of prevalence estimates for other risk factors and included these estimates in our analyses (e.g. if a publication identified in the smoking search, but not in the HCV search, reported HCV prevalence, we included the HCV prevalence estimate).

We extracted prevalence estimates for study samples unrestricted by sex or HIV transmission category (henceforth called the ‘overall’ group), as well as estimates for the following demographic groups: female, male (unrestricted by HIV transmission category), MSM, and IDU. We extracted prevalence estimates for internal uninfected comparison groups when available. For eligible publications (meaning that the publication included at least 100 adult PLWHA), we imposed no sample size restriction for demographic sub-groups or uninfected comparison groups.

We extracted data on country(ies), study design, prevalence estimate calendar year(s), sampling frame (e.g., clinic/hospital-based; geography-based), sex, age, race, HIV risk group, CD4+ cell count, ART, and method of measurement/definition of risk factors. For each risk factor reported in each publication, we assessed four indicators of potential for bias: whether or not (1) the aim of the study was to measure the prevalence of the risk factor or the risk factor was a predictor, outcome, or covariate in the study; (2) exclusion criteria might cause selection bias; (3) patients were excluded due to missing information on the risk factor; and (4) there were included patients with missing information on the risk factor. For the latter three indicators, we calculated the proportion excluded/missing, if known. We then classified a prevalence estimate to have higher potential for bias if the study did not aim to measure the risk factor and the risk factor was not a predictor, outcome, or covariate (indicator 1); or if the total of the proportions excluded/missing across indicators 2–4 was known to be more than 10%, or if any of these proportions was unknown.

We extracted prevalence estimates for the adult civilian noninstitutionalized population of the United States (henceforth called ‘US adults’) from the National Health Interview Survey (NHIS) [38,39], National Health and Nutrition Examination Survey (NHANES) [40–49], and Behavioral Risk Factor Surveillance System (BRFSS) [50–52], each during a calendar period between 2000 and 2010 for which data were reported. In NHANES, HIV prevalence was 0.5% in the age group 18–49 years during 2003–2006 [53]; there were no data on HIV prevalence from NHIS or BRFSS.

Statistical analysis

For each risk factor, we conducted a meta-analysis of prevalence for each demographic group with at least two individual study prevalence estimates. The summary prevalence estimate (sPrev) for each group was based solely on individual study prevalence estimates for that group. Thus, sPrev for ‘overall’ did not include individual study prevalence estimates from studies restricted according to sex or HIV transmission category. Using the Stata 12.1 metaprop module [54], we calculated sPrev and 95% confidence intervals (CI), as well as I2 values and Q statistic P-values to assess study heterogeneity [55]. To stabilize variances, we transformed individual study prevalence estimates using the Freeman–Tukey double arcsine transformation [56,57]. We used random-effects models [58] because we expected substantial study heterogeneity. Therefore, each sPrev estimate should be interpreted as an average prevalence across studies with true differences in target population prevalence, not a common prevalence across studies with the same target population prevalence [59]. If only one study reported a particular risk factor prevalence for a given group, we presented that individual estimate and Wilson score 95% CI. In sensitivity analyses, we calculated sPrev estimates excluding studies classified as having higher potential for bias. Finally, we assessed bias in study selection for each risk factor/group with at least 10 individual studies [60] through visual inspection of funnel plots and the Egger [61] and Begg [62] tests.


We identified 1573 unique references from the PubMed queries. After initial review of abstracts, we performed full-text review of 717 articles and found 113 eligible publications [63–175] (Table 2). Supplemental Table S1, presents characteristics of each eligible publication. The study design distribution was prospective cohort, 49; retrospective cohort, 10; cross-sectional, 46; case-control, 2; and experimental, 6. Most (87%) study samples were clinic/hospital-based; only one study sample was population-based. Among the 113 publications, the median number of patients was 388 [interquartile range (IQR), 192–905]. The geographic location distribution was United States, 59; Western Europe, 46; Canada, 4; and Australia, 4. Of 104 publications that reported sex distribution, the median percentage male was 75.4% (IQR, 65.0–85.4%). Of 91 publications that reported mean or median age, the median of the mean or median was 44.0 years (IQR, 41.6–46.5). Of 63 publications that reported mean or median CD4+ cell count, the median of the mean or median was 487.0 (IQR, 426.0–513.3). Of 75 publications that reported percentage on ART, the median was 84.0% (IQR, 73.0–93.9%). Fewer than 60% of publications reported race or HIV transmission group.

Table 3 presents results for each risk-factor-specific, group-specific meta-analysis. Forest plots for key meta-analyses are presented in Supplemental Figure S1, Individual study prevalence estimates are presented in Supplemental Tables S2–S7,

Table 3:
Meta-analysis and single study prevalence estimates, 95% confidence intervals (95% CI), I 2 values, and number of studies (N) for cancer risk factors among adult persons living with HIV/AIDS in Western high-income countries and US adult prevalence estimates.
Table 3:
(Continued) Meta-analysis and single study prevalence estimates, 95% confidence intervals (95% CI), I 2 values, and number of studies (N) for cancer risk factors among adult persons living with HIV/AIDS in Western high-income countries and US adult prevalence estimates.
Table 3:
(Continued) Meta-analysis and single study prevalence estimates, 95% confidence intervals (95% CI), I 2 values, and number of studies (N) for cancer risk factors among adult persons living with HIV/AIDS in Western high-income countries and US adult prevalence estimates.


Forty-five publications reported smoking prevalence [63–107], but most (84%) presented frequencies for ‘current,’ ‘former,’ and/or ‘ever’ smoker without precisely defining these terms (e.g., ever smoker: at least 100 cigarettes lifetime) (Supplemental Table S2, Overall current smoking sPrev was 54% (95% CI 49–59%; I2 = 99%), about 2.5 times the prevalence among US adults (Table 3) [39,41,51]. The majority of studies with uninfected comparison groups found higher smoking prevalence in PLWHA (Table 4). The highest current smoking sPrev was among IDU (74%; 95% CI 60–85%; I2 = 89%) (Table 3).

Table 4:
Prevalence of cancer risk factors among adult persons living with HIV/AIDS (PLWHA) compared with uninfected comparison groups from the same study.
Table 4:
(Continued) Prevalence of cancer risk factors among adult persons living with HIV/AIDS (PLWHA) compared with uninfected comparison groups from the same study.

Alcohol consumption

Twenty-six publications reported hazardous alcohol consumption prevalence [63,65,66,71,73,76,84,91,94,101,103,104,108–121]. Meta-analysis of hazardous alcohol consumption prevalence was hampered by the wide range of definitions over varying time spans (e.g., past 30 days, past 6 months) (Supplemental Table S3, Definition-specific meta-analyses yielded small numbers of studies and sPrev estimates with wide 95% CIs. We therefore chose not to stratify but to estimate sPrev of ‘hazardous alcohol consumption’ regardless of definition. Overall hazardous alcohol consumption sPrev was 24% (95% CI 15–33%; I2 = 100%) (Table 3) compared with 5–15% prevalence among US adults, depending on the definition [39,42,52]. Hazardous alcohol consumption prevalence did not meaningfully differ between PLWHA and uninfected comparison groups (Table 4).


Eighteen publications reported overweight (BMI: 25.0–29.9 kg/m2) and/or obesity (BMI: ≥30.0 kg/m2) prevalence [68,69,72,73,75,77,78,90,101,104,105,118,122–127]. In all publications, weight and height were directly measured; we therefore restricted our comparison with US adults to NHANES, the only nationally representative survey with directly measured weight and height. Overall overweight sPrev (32%; 95% CI 29–35%; I2 = 88%) was similar to the prevalence in US adults (34%), but obesity sPrev (17%; 95% CI 14–21%; I2 = 98%) was lower than the prevalence in US adults (34%) [43], as was overweight/obesity sPrev (53%; 95% CI 46–59%; I2 = 98%, versus 68%) (Table 3). Prevalence of overweight/obesity was consistently higher in uninfected comparison groups compared with PLWHA (Table 4).

Human papillomavirus infection

Eighteen publications reported HPV infection prevalence [91–93,95,96,98,128–139]. The number of HPV types tested varied from 15 to 47; the number of high-risk HPV types tested varied from 11 to 22 (Supplemental Table S5, Cervical HPV sPrev was 64% (95% CI 25–95%; I2 = 99%), compared with 43% prevalence among US females [44] (Table 3); cervical high-risk-type HPV sPrev was 46% (95% CI 34–58%; I2 = 96%) compared with 29% prevalence in US females [45]. Overall oral HPV sPrev was 34% (95% CI 26–42%; I2 = 68%), about five times the prevalence in US adults (7%) [46]; high-risk-type oral HPV sPrev was 16% (95% CI 10–23%; I2 = 71%), compared with 4% prevalence in US adults [46,47] (Table 3). Most studies of anal HPV prevalence were among MSM (sPrev = 91%; 95% CI 87–95%; I2 = 93% for any type and sPrev = 68%; 95% CI 57–79%; I2 = 98% for high-risk types) (Table 3); prevalence was similarly high in all groups. PLWHA generally had significantly higher oral and anal HPV prevalence than uninfected comparison groups (Table 4).

Hepatitis C virus infection

Sixty-three studies reported HCV infection prevalence [63–65,69,72,73,75,77,79–84,88,90,102–104,107,109,110,114,117–119,123,127,133,140–173]. We calculated sPrev for HCV-exposed, defined in 69% of individual studies as positive by HCV antibody test, and for chronic HCV infection, defined in 80% of studies as positive by HCV antibody and HCV RNA tests (see Supplemental Table S6, for all definitions). Overall HCV-exposed sPrev was 28% (95% CI 23–33%; I2 = 100%), compared with just 1.3% prevalence in US adults [48] (Table 3). Overall chronic HCV infection sPrev (26%; 95% CI 21–30%; I2 = 99%) was also much higher than the prevalence in US adults (0.9%) [48]. HCV sPrev was relatively low among MSM (HCV-exposed sPrev = 8%; 95% CI 6–11%; I2 = 93% and chronic HCV sPrev = 5%; 95% CI 2–10%; I2 = 94%), but was extremely high among IDU (HCV-exposed sPrev = 80%; 95% CI 68–89%; I2 = 97% and chronic HCV sPrev = 71%; 95% CI 55–86%; I2 = 94%). HCV prevalence was consistently higher in PLWHA than uninfected comparison groups (Table 4).

Hepatitis B virus infection

Twenty-six publications reported HBV infection prevalence [63,65,69,71,79–81,89,102,106,110,123,141,144,147,150,151,154,157,159,162,165,170,172,174,175]. HBV infection was defined in 72% of individual studies as positive by HBV surface antigen test (see Supplemental Table S7, for all definitions). Overall HBV sPrev was 5% (95% CI 4–5%; I2 = 87%) compared with just 0.3% in US adults [49] (Table 3).

Potential for bias

Across all risk factors summed over all publications, we classified 39% as having higher potential for bias, including smoking, 30%; alcohol, 42%; overweight/obesity, 37%; HPV, 49%; HCV, 38%; and HBV, 42%. Furthermore, across all risk factors summed over all publications we found that the study did not aim to measure the risk factor and the risk factor was not a predictor, outcome, or covariate in 8% of cases; there were exclusion criteria that might cause selection bias in 17%; there were excluded patients due to missing information on the risk factor in 8%; and there were included patients with missing information on the risk factor in 33% (only 13% with more than 10% missing information).

In sensitivity analyses excluding studies with higher potential for bias, the change in sPrev was both meaningful (i.e., |sPrevexc – sPrevall|/sPrevall>15%) and statistically significant (i.e., P-value for difference between sPrevlowerpotentialforbias and sPrevhigherpotentialforbias<0.05) for former smoker among females (15% for all studies, 18% for studies with higher potential for bias excluded); hazardous alcohol consumption among females (15 versus 18%) and among MSM (25 versus 32%); overweight/obesity among females (64 versus 44%) and males (55 versus 44%); cervical HPV, any type (64 versus 44%); and oral HPV, any type, among males (27 versus 40%).

We observed some funnel plot asymmetry (Supplemental Figure S2, for hazardous alcohol consumption (overall), with a deficit of smaller studies with higher prevalence; and for overweight/obesity (overall) and chronic HCV infection (overall), each with a deficit of smaller studies with lower prevalence. The Egger test for chronic HCV infection was the only statistically significant test for bias in study selection (P = 0.008).

The PLWHA and uninfected comparison groups in Table 4 generally had similar demographic characteristics. Exceptions that might have influenced comparisons included Morano et al. (2013) for alcohol and HCV (IDU: 43% in PLWHA, 14% in uninfected; mean age: 43.8 years in PLWHA; 35.9 years in uninfected); Raymond et al. (2012) for HCV (IDU: 32% in PLWHA, 12% in uninfected); and Wieland et al. (2011) for smoking (100% MSM in PLWHA; uninfected group was males, not restricted to MSM).


To our knowledge, this is the first comprehensive meta-analysis of the prevalence of cancer risk factors among PLWHA. There is one meta-analysis published on cervical HPV prevalence in PLWHA [176]. Our analyses quantified the continuing high prevalence of smoking and HPV, HCV, and HBV infections among PLWHA. Prevalence of overweight/obesity was lower than in US adults. Assessment of alcohol consumption was hampered by variability in assessment methods.

Overall, about half of PLWHA were current smokers, a prevalence 2.5 times higher than in US adults. This high prevalence often reflected the high prevalence in demographically similar uninfected persons, where, for example, IDU smoking prevalence was high, regardless of HIV status (Table 4). The prevalence of high-risk HPV infections remained distressingly high, with cervical sPrev of 46% (1.6 times the prevalence in US adults); oral prevalence of 10–16% (2.5–4 times the prevalence in US adults); and anal sPrev around 70% (no nationally representative prevalence estimate in US adults available). More than one quarter of PLWHA were infected with HCV (12–40 times higher than in US adults) and about 5% were infected with HBV (10–25 times higher than in US adults). Furthermore, 70–80% of IDU were infected with HCV, accounting for the fact that in the United States, about half of liver cancer cases among PLWHA occur in IDU [177], who constitute 22% of PLWHA [178].

With the introduction of ART and greater control of HIV wasting syndrome, the prevalence of overweight/obesity among PLWHA has increased [179,180]. However, our results showed that PLWHA have not yet reached the overweight/obesity prevalence of US adults (53 versus 68%) or of demographically similar uninfected persons. Finally, results for alcohol consumption were difficult to interpret due to considerable heterogeneity in measurement. Although the overall prevalence of hazardous alcohol consumption (regardless of definition) was 24%, roughly 1.5–4 times higher than in US adults, direct comparisons of PLWHA with demographically similar uninfected comparison groups, using the same definition, showed no differences.

We observed considerable study heterogeneity in prevalence estimates, with the majority of I2 values greater than 90%. This result was not surprising in our ‘overall’ group, which could vary across studies by sex and MSM and IDU status distribution, or in our male group, which could vary by MSM and IDU status distribution. However, heterogeneity was generally high even within our more narrowly defined demographic groups (females, MSM, IDU). Potential sources of heterogeneity included differences in study design, geographic location, sex, age, race/ethnicity, prevalence estimate calendar year(s), and risk factor measurement method/definition. Differences in CD4+ cell count [181] or number of HPV types tested could be sources of heterogeneity for HPV prevalence, and differences in amount of time on ART could be a source of heterogeneity for overweight/obesity [182].

Our goal was to provide a broad overview of cancer risk factor prevalence in PLWHA. Our random effects models, which appropriately penalized the precision of our estimates in the context of high study heterogeneity, provided reasonable approximations of average prevalence estimates. Future research focused on identifying risk-factor-specific sources of heterogeneity could identify high prevalence sub-groups to target for risk factor reduction efforts.

Our study had limitations. First, the individual study PLWHA samples were primarily clinic/hospital-based samples that may not have been representative of the overall PLWHA population. However, samples from a broad range of well-established cohorts and HIV treatment centers were represented in this meta-analysis (Supplemental Table S1,, suggesting that our results provide robust estimates of cancer risk factor prevalence among PLWHA receiving HIV care.

Second, risk factors often are included in descriptions of baseline characteristics or are used as covariates, without being central to the study and therefore without being indexed in PubMed. This phenomenon is illustrated by the fact that 42% of our publications reported the prevalence of one or more risk factors that were not identified in the searches for those risk factors. Recognizing that there most likely were other articles that reported the prevalence of one or more risk factors but were not identified in any of the searches, we aimed for a robust representation of publications indexed in PubMed, with the limitation that we would not identify all of them. Inspection of funnel plots provided limited evidence for bias in study selection for hazardous alcohol consumption, overweight/obesity, and chronic HCV infection; however, the only significant statistical test was the Egger test for chronic HCV infection.

Third, although our sensitivity analyses suggested that our sPrev estimates were not heavily distorted by bias, because most studies did not report participation rates, we were unable to include participation rates in our potential for bias measure.

Fourth, in our extraction of prevalence estimates we excluded unknowns from the denominator. This approach is valid if the prevalence of the risk factor is similar among the knowns and unknowns, but otherwise is biased. However, the alternative of including the unknowns in the denominator always underestimates prevalence unless the risk factor is absent in all of the unknowns. Fortunately, only 13% of risk factor-publication combinations had more than 10% of patients with missing values.

Finally, we need to consider the possibility of information bias in the individual studies. We know little about the smoking definitions. Determination of overweight/obesity should be accurate because weight and height were directly measured. There was variability in the number of HPV types tested; studies testing for fewer types might underestimate prevalence. Similarly, studies with narrower definitions of HCV or HBV infection (e.g. positive by HBV DNA test versus positive by DNA test or HBV surface antigen test) might underestimate prevalence.

Despite these potential sources of bias, the general consistency between comparisons of our sPrev estimates among PLWHA with prevalence estimates among US adults and comparisons of prevalence estimates among PLWHA and uninfected comparison groups from the same study (Table 4) provides validation for our essential findings.

Interventions to reduce the high prevalence of smoking and oncogenic virus infections among PLWHA can play a critical role in reducing the high cancer burden. Specific interventions include smoking cessation [183,184], HPV [185–188] and HBV vaccination [189,190], and HCV [191,192] and HBV [189,193] treatment. Research is needed to develop effective, tailored smoking cessation interventions, including for sub-populations (e.g., IDU, MSM), to effectively address the high prevalence of co-occurring risk factors, to identify potential adverse interactions between pharmacologic interventions and ART [184,189,194–196], and to overcome impaired immunogenicity [189,190,197,198] of or nonadherence [199] to vaccine regimens. Finally, epidemiologic studies to estimate the population attributable risk percent for various cancer types due to cancer risk factors among PLWHA would help guide both research and practice.


Authors’ contributions: L.S.P. and R.D. designed the study and wrote the first draft of the manuscript. R.U.H.R. conducted the literature review and the initial review of abstracts. R.U.H.R. and R.D. performed the full-text article reviews for eligibility. R.U.H.R., R.D., and L.S.P. performed data extraction. R.U.H.R. performed the meta-analysis with supervision from L.S.P. and R.D. All authors contributed to the overall intellectual content of the manuscript, read and edited subsequent drafts, and approved the final version.

Sources of funding: This work was funded by grants from the National Institute of Mental Health (5T32-MH020031, P30-MH062294), the National Institute on Alcohol Abuse and Alcoholism (1U01-AA020790), the National Cancer Institute (R01-CA165937, F31-CA180775, R01-CA173754), the National Institute of Allergy and Infectious Diseases (K01-AI071725), and the National Institute of Diabetes and Digestive and Kidney Diseases (3T32-DK007217).

Disclaimers: The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the Department of Veterans Affairs.

Conflicts of interest

No conflicts of interest declared.


1. Morlat P, Roussillon C, Henard S, Salmon D, Bonnet F, Cacoub P, et al. Causes of death among HIV-infected patients in France in 2010 (national survey): trends since 2000. AIDS 2014; 28:1181–1191.
2. Smith CJ, Ryom L, Weber R, Morlat P, Pradier C, Reiss P, et al. Trends in underlying causes of death in people with HIV from 1999 to 2011 (D:A:D): a multicohort collaboration. Lancet 2014; 384:241–248.
3. Weber R, Ruppik M, Rickenbach M, Spoerri A, Furrer H, Battegay M, et al. Decreasing mortality and changing patterns of causes of death in the Swiss HIV Cohort Study. HIV Med 2013; 14:195–207.
4. Antiretroviral Therapy Cohort Collaboration. Causes of death in HIV-1-infected patients treated with antiretroviral therapy, 1996–2006: collaborative analysis of 13 HIV cohort studies. Clin Infect Dis 2010; 50:1387–1396.
5. Calabresi A, Ferraresi A, Festa A, Scarcella C, Donato F, Vassallo F, et al. Incidence of AIDS-defining cancers and virus-related and non-virus-related non-AIDS-defining cancers among HIV-infected patients compared with the general population in a large health district of Northern Italy, 1999–2009. HIV Med 2013; 14:481–490.
6. Dubrow R, Silverberg MJ, Park LS, Crothers K, Justice AC. HIV infection, aging, and immune function: implications for cancer risk and prevention. Curr Opin Oncol 2012; 24:506–516.
7. Park LS, Tate JP, Rodriguez Barradas M, Rimland D, Goetz MB, Gibert C, et al. Cancer incidence in HIV-infected versus uninfected veterans: comparison of cancer registry and ICD-9 code diagnoses. J AIDS Clin Res 2014; 5:318.
8. Shiels MS, Cole SR, Kirk GD, Poole C. A meta-analysis of the incidence of non-AIDS cancers in HIV-infected individuals. J Acquir Immune Defic Syndr 2009; 52:611–622.
9. Gopal S, Achenbach CJ, Yanik EL, Dittmer DP, Eron JJ, Engels EA. Moving forward in HIV-associated cancer. J Clin Oncol 2014; 32:876–880.
10. Hleyhel M, Bouvier AM, Belot A, Tattevin P, Pacanowski J, Genet P, et al. Risk of non-AIDS-defining cancers among HIV-1-infected individuals in France between 1997 and 2009: results from a French cohort. AIDS 2014; 28:2109–2118.
11. Hleyhel M, Belot A, Bouvier AM, Tattevin P, Pacanowski J, Genet P, et al. Risk of AIDS-defining cancers among HIV-1-infected patients in France between 1992 and 2009: results from the FHDH-ANRS CO4 cohort. Clin Infect Dis 2013; 57:1638–1647.
12. Chaturvedi AK, Madeleine MM, Biggar RJ, Engels EA. Risk of human papillomavirus-associated cancers among persons with AIDS. J Natl Cancer Inst 2009; 101:1120–1130.
13. Silverberg MJ, Leyden W, Warton EM, Quesenberry CP Jr, Engels EA, Asgari MM. HIV infection status, immunodeficiency, and the incidence of non-melanoma skin cancer. J Natl Cancer Inst 2013; 105:350–360.
14. Grulich AE, Jin F, Poynten IM, Vajdic CM. HIV, cancer, and aging. Sex Health 2011; 8:521–525.
15. Engels EA. Non-AIDS-defining malignancies in HIV-infected persons: etiologic puzzles, epidemiologic perils, prevention opportunities. AIDS 2009; 23:875–885.
16. Borges AH, Dubrow R, Silverberg MJ. Factors contributing to risk for cancer among HIV-infected individuals, and evidence that earlier combination antiretroviral therapy will alter this risk. Curr Opin HIV AIDS 2014; 9:34–40.
17. Rubinstein PG, Aboulafia DM, Zloza A. Malignancies in HIV/AIDS: from epidemiology to therapeutic challenges. AIDS 2014; 28:453–465.
18. United States Public Health Service Office of the Surgeon General, National Center for Chronic Disease Prevention and Health Promotion (U.S.). The health consequences of smoking: a report of the Surgeon General, 2004. [Accessed 25 February 2015]
19. Botteri E, Iodice S, Bagnardi V, Raimondi S, Lowenfels AB, Maisonneuve P. Smoking and colorectal cancer: a meta-analysis. JAMA 2008; 300:2765–2778.
20. Trichopoulos D, Bamia C, Lagiou P, Fedirko V, Trepo E, Jenab M, et al. Hepatocellular carcinoma risk factors and disease burden in a European cohort: a nested case-control study. J Natl Cancer Inst 2011; 103:1686–1695.
21. Leonardi-Bee J, Ellison T, Bath-Hextall F. Smoking and the risk of nonmelanoma skin cancer: systematic review and meta-analysis. Arch Dermatol 2012; 148:939–946.
22. Boffetta P, Hashibe M. Alcohol and cancer. Lancet Oncol 2006; 7:149–156.
23. Calle EE, Kaaks R. Overweight, obesity and cancer: epidemiological evidence and proposed mechanisms. Nat Rev Cancer 2004; 4:579–591.
24. World Cancer Research Fund/American Institute for Cancer Research. Food, nutrition, physical activity, and the prevention of cancer: a global perspective. Washington, DC: AICR; 2007.
25. Renehan AG, Tyson M, Egger M, Heller RF, Zwahlen M. Body-mass index and incidence of cancer: a systematic review and meta-analysis of prospective observational studies. Lancet 2008; 371:569–578.
26. Trottier H, Burchell AN. Epidemiology of mucosal human papillomavirus infection and associated diseases. Public Health Genomics 2009; 12:291–307.
27. Iannacone MR, Gheit T, Waterboer T, Giuliano AR, Messina JL, Fenske NA, et al. Case-control study of cutaneous human papillomaviruses in squamous cell carcinoma of the skin. Cancer Epidemiol Biomarkers Prev 2012; 21:1303–1313.
28. Bouwes Bavinck JN, Neale RE, Abeni D, Euvrard S, Green AC, Harwood CA, et al. Multicenter study of the association between betapapillomavirus infection and cutaneous squamous cell carcinoma. Cancer Res 2010; 70:9777–9786.
29. Feltkamp MC, de Koning MN, Bavinck JN, Ter Schegget J. Betapapillomaviruses: innocent bystanders or causes of skin cancer. J Clin Virol 2008; 43:353–360.
30. Li X, Gao L, Li H, Gao J, Yang Y, Zhou F, et al. Human papillomavirus infection and laryngeal cancer risk: a systematic review and meta-analysis. J Infect Dis 2013; 207:479–488.
31. Anantharaman D, Gheit T, Waterboer T, Abedi-Ardekani B, Carreira C, McKay-Chopin S, et al. Human papillomavirus infections and upper aero-digestive tract cancers: the ARCAGE study. J Natl Cancer Inst 2013; 105:536–545.
32. Guo F, Liu Y, Wang X, He Z, Weiss NS, Madeleine MM, et al. Human papillomavirus infection and esophageal squamous cell carcinoma: a case-control study. Cancer Epidemiol Biomarkers Prev 2012; 21:780–785.
33. Sitas F, Egger S, Urban MI, Taylor PR, Abnet CC, Boffetta P, et al. InterSCOPE study: associations between esophageal squamous cell carcinoma and human papillomavirus serological markers. J Natl Cancer Inst 2012; 104:147–158.
34. El-Serag HB. Epidemiology of viral hepatitis and hepatocellular carcinoma. Gastroenterology 2012; 142:1264–1273.e1.
35. Perz JF, Armstrong GL, Farrington LA, Hutin YJ, Bell BP. The contributions of hepatitis B virus and hepatitis C virus infections to cirrhosis and primary liver cancer worldwide. J Hepatol 2006; 45:529–538.
36. Negri E, Little D, Boiocchi M, La Vecchia C, Franceschi S. B-cell non-Hodgkin's lymphoma and hepatitis C virus infection: a systematic review. Int J Cancer 2004; 111:1–8.
37. Nath A, Agarwal R, Malhotra P, Varma S. Prevalence of hepatitis B virus infection in non-Hodgkin lymphoma: a systematic review and meta-analysis. Intern Med J 2010; 40:633–641.
38. Division of Health Interview Statistics. About the National Health Interview Survey. [Accessed 25 February 2015]
39. Schoenborn CA, Adams PF. Health behaviors of adults: United States, 2005–2007. National Center for Health Statistics. Vital Health Stat 2010; 10 (No. 245):1–132.
40. Division of Health Interview Statistics. About the National Health and Nutrition Examination Survey. [Accessed 25 February 2015]
41. Huffman MD, Capewell S, Ning H, Shay CM, Ford ES, Lloyd-Jones DM. Cardiovascular health behavior and health factor changes (1988–2008) and projections to 2020: results from the National Health and Nutrition Examination Surveys. Circulation 2012; 125:2595–2602.
42. Guenther PM, Ding EL, Rimm EB. Alcoholic beverage consumption by adults compared to dietary guidelines: results of the National Health and Nutrition Examination Survey, 2009-2010. J Acad Nutr Diet 2013; 113:546–550.
43. Flegal KM, Carroll MD, Ogden CL, Curtin LR. Prevalence and trends in obesity among US adults, 1999–2008. JAMA 2010; 303:235–241.
44. Steinau M, Hariri S, Gillison ML, Broutian TR, Dunne EF, Tong ZY, et al. Prevalence of cervical and oral human papillomavirus infections among US women. J Infect Dis 2014; 209:1739–1743.
45. Hariri S, Unger ER, Sternberg M, Dunne EF, Swan D, Patel S, et al. Prevalence of genital human papillomavirus among females in the United States, the National Health and Nutrition Examination Survey, 2003–2006. J Infect Dis 2011; 204:566–573.
46. Gillison ML, Broutian T, Pickard RK, Tong ZY, Xiao W, Kahle L, et al. Prevalence of oral HPV infection in the United States, 2009–2010. JAMA 2012; 307:693–703.
47. Chaturvedi AK, Graubard BI, Pickard RK, Xiao W, Gillison ML. High-risk oral human papillomavirus load in the US population, National Health and Nutrition Examination Survey 2009–2010. J Infect Dis 2014; 210:441–447.
48. Ditah I, Ditah F, Devaki P, Ewelukwa O, Ditah C, Njei B, et al. The changing epidemiology of hepatitis C virus infection in the United States: National Health and Nutrition Examination Survey 2001 through 2010. J Hepatol 2014; 60:691–698.
49. Ioannou GN. Hepatitis B virus in the United States: infection, exposure, and immunity rates in a nationally representative survey. Ann Intern Med 2011; 154:319–328.
50. Behavioral Risk Factor Surveillance System. About BRFSS. [Accessed 25 February 2015]
51. Kahende J, Teplinskaya A, Malarcher A, Husten C, Maurice E. State-specific prevalence of cigarette smoking among adults and quitting among persons aged 18–35 years--United States, 2006. MMWR Morb Mortal Wkly Rep 2007; 56:993–996.
52. Paul LA, Grubaugh AL, Frueh BC, Ellis C, Egede LE. Associations between binge and heavy drinking and health behaviors in a nationally representative sample. Addict Behav 2011; 36:1240–1245.
53. McQuillan GM, Kruszon-Moran D, Granade T, Feldman JW. Seroprevalence of HIV in the US household population aged 18–49 years: The National Health and Nutrition Examination Surveys, 1999–2006. J Acquir Immune Defic Syndr 2010; 53:117–123.
54. Nyaga V, Arbyn M, Aerts M. METAPROP: Stata module to perform fixed and random effects meta-analysis of proportions, 2014. [Accessed 25 February 2015]
55. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ 2003; 327:557–560.
56. Barendregt JJ, Doi SA, Lee YY, Norman RE, Vos T. Meta-analysis of prevalence. J Epidemiol Community Health 2013; 67:974–978.
57. Freeman MF, Tukey JW. Transformations related to the angular and the square root. Ann Math Statist 1950; 21:607–611.
58. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials 1986; 7:177–188.
59. Riley RD, Higgins JP, Deeks JJ. Interpretation of random effects meta-analyses. BMJ 2011; 342:d549.
60. Anzures-Cabrera J, Higgins JP. Graphical displays for meta-analysis: An overview with suggestions for practice. Res Synth Methods 2010; 1:66–80.
61. Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ 1997; 315:629–634.
62. Begg CB, Mazumdar M. Operating characteristics of a rank correlation test for publication bias. Biometrics 1994; 50:1088–1101.
63. Baum MK, Sales S, Jayaweera DT, Lai S, Bradwin G, Rafie C, et al. Coinfection with hepatitis C virus, oxidative stress and antioxidant status in HIV-positive drug users in Miami. HIV Med 2011; 12:78–86.
64. Briongos Figuero LS, Bachiller Luque P, Palacios Martín T, González Sagrado M, Eiros Bouza JM. Assessment of factors influencing health-related quality of life in HIV-infected patients. HIV Med 2011; 12:22–30.
65. Broom J, Sowden D, Williams M, Taing K, Morwood K, McGill K. Moving from viral suppression to comprehensive patient-centered care: the high prevalence of comorbid conditions and health risk factors in HIV-1-infected patients in Australia. J Int Assoc Physicians AIDS Care 2012; 11:109–114.
66. Broyles LM, Gordon AJ, Sereika SM, Ryan CM, Erlen JA. Predictive utility of brief Alcohol Use Disorders Identification Test (AUDIT) for human immunodeficiency virus antiretroviral medication nonadherence. Subst Abus 2011; 32:252–261.
67. Bryant VE, Kahler CW, Devlin KN, Monti PM, Cohen RA. The effects of cigarette smoking on learning and memory performance among people living with HIV/AIDS. AIDS Care 2013; 25:1308–1316.
68. Capili B, Anastasi JK, Ogedegbe O. HIV and general cardiovascular risk. J Assoc Nurses AIDS Care 2011; 22:362–375.
69. Cervero M, Agud JL, García-Lacalle C, Alcazár V, Torres R, Jusdado JJ, et al. Prevalence of vitamin D deficiency and its related risk factor in a Spanish cohort of adult HIV-infected patients: effects of antiretroviral therapy. AIDS Res Hum Retroviruses 2012; 28:963–971.
70. Chander G, Stanton C, Hutton HE, Abrams DB, Pearson J, Knowlton A, et al. Are smokers with HIV using information and communication technology? Implications for behavioral interventions. AIDS Behav 2012; 16:383–388.
71. Collazos J, Cartón JA, Asensi V. Gender differences in liver fibrosis and hepatitis C virus-related parameters in patients coinfected with human immunodeficiency virus. Curr HIV Res 2011; 9:339–345.
72. Fabbiani M, Ciccarelli N, Tana M, Farina S, Baldonero E, Di Cristo V, et al. Cardiovascular risk factors and carotid intima-media thickness are associated with lower cognitive performance in HIV-infected patients. HIV Med 2013; 14:136–144.
73. Freiberg MS, Chang CC, Kuller LH, Skanderson M, Lowy E, Kraemer KL, et al. HIV infection and the risk of acute myocardial infarction. JAMA Intern Med 2013; 173:614–622.
74. Fitch KV, Looby SE, Rope A, Eneh P, Hemphill L, Lee H, et al. Effects of aging and smoking on carotid intima-media thickness in HIV-infection. AIDS 2013; 27:49–57.
75. Galli L, Salpietro S, Pellicciotta G, Galliani A, Piatti P, Hasson H, et al. Risk of type 2 diabetes among HIV-infected and healthy subjects in Italy. Eur J Epidemiol 2012; 27:657–665.
76. Huber M, Ledergerber B, Sauter R, Young J, Fehr J, Cusini A, et al. Outcome of smoking cessation counselling of HIV-positive persons by HIV care physicians. HIV Med 2012; 13:387–397.
77. Jarrett OD, Wanke CA, Ruthazer R, Bica I, Isaac R, Knox TA. Metabolic syndrome predicts all-cause mortality in persons with human immunodeficiency virus. AIDS Patient Care STDS 2013; 27:266–271.
78. Koethe JR, Dee K, Bian A, Shintani A, Turner M, Bebawy S, et al. Circulating interleukin-6, soluble CD14, and other inflammation biomarker levels differ between obese and nonobese HIV-infected adults on antiretroviral therapy. AIDS Res Hum Retroviruses 2013; 29:1019–1025.
79. Madeddu G, Fois AG, Calia GM, Babudieri S, Soddu V, Becciu F, et al. Chronic obstructive pulmonary disease: an emerging comorbidity in HIV-infected patients in the HAART era?. Infection 2013; 41:347–353.
80. Masiá M, Padilla S, Robledano C, Ramos JM, Gutiérrez F. Evaluation of endothelial function and subclinical atherosclerosis in association with hepatitis C virus in HIV-infected patients: a cross-sectional study. BMC Infect Dis 2011; 11:265.
81. Overton ET, Patel P, Mondy K, Bush T, Conley L, Rhame F, et al. Cystatin C and baseline renal function among HIV-infected persons in the SUN Study. AIDS Res Hum Retroviruses 2012; 28:148–155.
82. Pombo M, Olalla J, Del Arco A, De La Torre J, Urdiales D, Aguilar A, et al. Left ventricular hypertrophy detected by echocardiography in HIV-infected patients. Eur J Intern Med 2013; 24:558–561.
83. Quezada M, Martin-Carbonero L, Soriano V, Vispo E, Valencia E, Moreno V, et al. Prevalence and risk factors associated with pulmonary hypertension in HIV-infected patients on regular follow-up. AIDS 2012; 26:1387–1392.
84. Roca B, Bennasar M, Ferrero JA, del Monte MC, Resino E. Hepatitis C virus co-infection and sexual risk behaviour are associated with a high homocysteine serum level in HIV-infected patients. Swiss Med Wkly 2012; 141:w13323.
85. Shacham E, Lian M, Önen NF, Donovan M, Overton ET. Are neighborhood conditions associated with HIV management?. HIV Med 2013; 14:624–632.
86. Shirley DK, Kesari RK, Glesby MJ. Factors associated with smoking in HIV-infected patients and potential barriers to cessation. AIDS Patient Care STDS 2013; 27:604–612.
87. Stewart DW, Jones GN, Minor KS. Smoking, depression, and gender in low-income African Americans with HIV/AIDS. Behav Med 2011; 37:77–80.
88. Vassallo M, Dunais B, Durant J, Carsenti-Dellamonica H, Harvey-Langton A, Cottalorda J, et al. Relevance of lipopolysaccharide levels in HIV-associated neurocognitive impairment: the Neuradapt study. J Neurovirol 2013; 19:376–382.
89. Yin MT, Kendall MA, Wu X, Tassiopoulos K, Hochberg M, Huang JS, et al. Fractures after antiretroviral initiation. AIDS 2012; 26:2175–2184.
90. Young B, Dao CN, Buchacz K, Baker R, Brooks JT. HIV Outpatient Study (HOPS) Investigators. Increased rates of bone fracture among HIV-infected persons in the HIV Outpatient Study (HOPS) compared with the US general population, 2000–2006. Clin Infect Dis 2011; 52:1061–1068.
91. Beachler DC, Weber KM, Margolick JB, Strickler HD, Cranston RD, Burk RD, et al. Risk factors for oral HPV infection among a high prevalence population of HIV-positive and at-risk HIV-negative adults. Cancer Epidemiol Biomarkers Prev 2012; 21:122–133.
92. Kojic EM, Cu-Uvin S, Conley L, Bush T, Onyekwuluje J, Swan DC, et al. Human papillomavirus infection and cytologic abnormalities of the anus and cervix among HIV-infected women in the Study to Understand the Natural History of HIV/AIDS in the Era of Effective Therapy (the SUN Study). Sex Transm Dis 2011; 38:253–259.
93. Konopnicki D, Manigart Y, Gilles C, Barlow P, de Marchin J, Feoli F, et al. Sustained viral suppression and higher CD4+ T-cell count reduces the risk of persistent cervical high-risk human papillomavirus infection in HIV-positive women. J Infect Dis 2013; 207:1723–1729.
94. Siemieniuk RA, Krentz HB, Miller P, Woodman K, Ko K, Gill MJ. The clinical implications of high rates of intimate partner violence against HIV-positive women. J Acquir Immune Defic Syndr 2013; 64:32–38.
95. Stuardo V, Agustí C, Godinez JM, Montoliu A, Torné A, Tarrats A, et al. Human papillomavirus infection in HIV-1 infected women in Catalonia (Spain): implications for prevention of cervical cancer. PLoS One 2012; 7:e47755.
96. Videla S, Darwich L, Canadas MP, Coll J, Pinol M, García-Cuyás F, et al. Natural history of human papillomavirus infections involving anal, penile, and oral sites among HIV-positive men. Sex Transm Dis 2013; 40:3–10.
97. Schwartz LM, Castle PE, Follansbee S, Borgonovo S, Fetterman B, Tokugawa D, et al. Risk factors for anal HPV infection and anal precancer in HIV-infected men who have sex with men. J Infect Dis 2013; 208:1768–1775.
98. van der Snoek EM, van der Ende ME, den Hollander JC, Schutten M, Neumann HAM, van Doornum GJJ. Use of highly active antiretroviral therapy is associated with lower prevalence of anal intraepithelial neoplastic lesions and lower prevalence of human papillomavirus in HIV-infected men who have sex with men. Sex Transm Dis 2012; 39:495–500.
99. Wieland U, Silling S, Scola N, Potthoff A, Gambichler T, Brockmeyer NH, et al. Merkel cell polyomavirus infection in HIV-positive men. Arch Dermatol 2011; 147:401–406.
100. Marshall MM, Kirk GD, Caporaso NE, McCormack MC, Merlo CA, Hague JC, et al. Tobacco use and nicotine dependence among HIV-infected and uninfected injection drug users. Addict Behav 2011; 36:61–67.
101. Buchacz K, Baker RK, Palella FJ Jr, Shaw L, Patel P, Lichtenstein KA, et al. Disparities in prevalence of key chronic diseases by gender and race/ethnicity among antiretroviral-treated HIV-infected adults in the US. Antivir Ther 2013; 18:65–75.
102. Esposito V, Chiodini P, Viglietti R, Parrella R, Parrella G, Maddaloni A, et al. Safety of fosamprenavir in a cohort of HIV-1-infected patients with co-morbidities. In Vivo 2011; 25:813–819.
103. Fong R, Cheng AC, Vujovic O, Hoy JF. Factors associated with virological failure in a cohort of combination antiretroviral therapy-treated patients managed at a tertiary referral centre. Sex Health 2013; 10:442–447.
104. Kim DJ, Westfall AO, Chamot E, Willig AL, Mugavero MJ, Ritchie C, et al. Multimorbidity patterns in HIV-infected patients: the role of obesity in chronic disease clustering. J Acquir Immune Defic Syndr 2012; 61:600–605.
105. Krishnan S, Schouten JT, Atkinson B, Brown T, Wohl D, McComsey GA, et al. Metabolic syndrome before and after initiation of antiretroviral therapy in treatment-naive HIV-infected individuals. J Acquir Immune Defic Syndr 2012; 61:381–389.
106. Winnock M, Bani-Sadr F, Pambrun E, Loko MA, Lascoux-Combe C, Garipuy D, et al. Prevalence of immunity to hepatitis viruses A and B in a large cohort of HIV/HCV-coinfected patients, and factors associated with HAV and HBV vaccination. Vaccine 2011; 29:8656–8660.
107. Sharma A, Cohen HW, Freeman R, Santoro N, Schoenbaum EE. Prospective evaluation of bone mineral density among middle-aged HIV-infected and uninfected women: association between methadone use and bone loss. Maturitas 2011; 70:295–301.
108. Chitsaz E, Meyer JP, Krishnan A, Springer SA, Marcus R, Zaller N, et al. Contribution of substance use disorders on HIV treatment outcomes and antiretroviral medication adherence among HIV-infected persons entering jail. AIDS Behav 2013; 17 (Suppl 2):S118–S127.
109. Devlin KN, Gongvatana A, Clark US, Chasman JD, Westbrook ML, Tashima KT, et al. Neurocognitive effects of HIV, hepatitis C, and substance use history. J Int Neuropsychol Soc 2012; 18:68–78.
110. Frontini M, Chotalia J, Spizale L, Onya W, Ruiz M, Clark RA. Sex and race effects on risk for selected outcomes among elderly HIV-infected patients. J Int Assoc Physicians AIDS Care 2012; 11:12–15.
111. Hutton HE, McCaul ME, Chander G, Jenckes MW, Nollen C, Sharp VL, et al. Alcohol use, anal sex, and other risky sexual behaviors among HIV-infected women and men. AIDS Behav 2013; 17:1694–1704.
112. Korthuis PT, Saha S, Chander G, McCarty D, Moore RD, Cohn JA, et al. Substance use and the quality of patient-provider communication in HIV clinics. AIDS Behav 2011; 15:832–841.
113. Martinez DA, Goggin K, Catley D, Gerkovich MM, Williams K, Wright J, et al. Do coping styles mediate the relationship between substance use and educational attainment and antiretroviral adherence?. AIDS Behav 2012; 16:2319–2329.
114. Morano JP, Gibson BA, Altice FL. The burgeoning HIV/HCV syndemic in the urban Northeast: HCV, HIV, and HIV/HCV coinfection in an urban setting. PLoS One 2013; 8:e64321.
115. Roux P, Cohen J, Lascoux-Combe C, Sogni P, Winnock M, Salmon-Ceron D, et al. Determinants of the underreporting of alcohol consumption by HIV/HCV co-infected patients during face-to-face medical interviews: the role of the physician. Drug Alcohol Depend 2011; 116:228–232.
116. Shacham E, Agbebi A, Stamm K, Overton ET. Alcohol consumption is associated with poor health in HIV clinic patient population: a behavioral surveillance study. AIDS Behav 2011; 15:209–213.
117. Surah S, Kieran J, O’Dea S, Shiel C, Raffee S, Mulcahy F, et al. Use of the Alcohol Use Disorders Identification Test (AUDIT) to determine the prevalence of alcohol misuse among HIV-infected individuals. Int J STD AIDS 2013; 24:517–521.
118. Yoon JC, Crane PK, Ciechanowski PS, Harrington RD, Kitahata MM, Crane HM. Somatic symptoms and the association between hepatitis C infection and depression in HIV-infected patients. AIDS Care 2011; 23:1208–1218.
119. Crystal H, Kleyman I, Anastos K, Lazar J, Cohen M, Liu C, et al. Effects of hepatitis C and HIV on cognition in women: data from the Women's Interagency HIV Study. J Acquir Immune Defic Syndr 2012; 59:149–154.
120. McGinnis KA, Justice AC, Kraemer KL, Saitz R, Bryant KJ, Fiellin DA. Comparing alcohol screening measures among HIV-infected and -uninfected men. Alcohol Clin Exp Res 2013; 37:435–442.
121. Skeer MR, Mimiaga MJ, Mayer KH, O’Cleirigh C, Covahey C, Safren SA. Patterns of substance use among a large urban cohort of HIV-infected men who have sex with men in primary care. AIDS Behav 2012; 16:676–689.
122. Gangcuangco LM, Chow DC, Liang CY, Nakamoto BK, Umaki TM, Kallianpur KJ, et al. Predictors of 25-hydroxyvitamin D levels in HIV-infected patients in Hawai‘i. Hawaii J Med Public Health 2013; 72:197–201.
123. Patel N, Veve M, Kwon S, McNutt LA, Fish D, Miller CD. Frequency of electrocardiogram testing among HIV-infected patients at risk for medication-induced QTc prolongation. HIV Med 2013; 14:463–471.
124. Bauer LO. Interactive effects of HIV/AIDS, body mass, and substance abuse on the frontal brain: a P300 study. Psychiatry Res 2011; 185:232–237.
125. Chung RT, Umbleja T, Chen JY, Andersen JW, Butt AA, Sherman KE, et al. Extended therapy with pegylated interferon and weight-based ribavirin for HCV-HIV coinfected patients. HIV Clin Trials 2012; 13:70–82.
126. Blashill AJ, Mayer KH, Crane HM, Grasso C, Safren SA. Body mass index, immune status, and virological control in HIV-infected men who have sex with men. J Int Assoc Provid AIDS Care 2013; 12:319–324.
127. Salter ML, Lau B, Mehta SH, Go VF, Leng S, Kirk GD. Correlates of elevated interleukin-6 and C-reactive protein in persons with or at high risk for HCV and HIV infections. J Acquir Immune Defic Syndr 2013; 64:488–495.
128. Garbuglia AR, Piselli P, Lapa D, Sias C, Del Nonno F, Baiocchini A, et al. Frequency and multiplicity of human papillomavirus infection in HIV-1 positive women in Italy. J Clin Virol 2012; 54:141–146.
129. Kang M, Cu-Uvin S. Association of HIV viral load and CD4 cell count with human papillomavirus detection and clearance in HIV-infected women initiating highly active antiretroviral therapy. HIV Med 2012; 13:372–378.
130. Beachler DC, D'Souza G, Sugar EA, Xiao W, Gillison ML. Natural history of anal vs oral HPV infection in HIV-infected men and women. J Infect Dis 2013; 208:330–339.
131. Del Mistro A, Baboci L, Frayle-Salamanca H, Trevisan R, Bergamo E, Lignitto L, et al. Oral human papillomavirus and human herpesvirus-8 infections among human immunodeficiency virus type 1-infected men and women in Italy. Sex Transm Dis 2012; 39:894–898.
132. Steinau M, Reddy D, Sumbry A, Reznik D, Gunthel CJ, Del Rio C, et al. Oral sampling and human papillomavirus genotyping in HIV-infected patients. J Oral Pathol Med 2012; 41:288–291.
133. Parisi SG, Cruciani M, Scaggiante R, Boldrin C, Andreis S, Dal Bello F, et al. Anal and oral human papillomavirus (HPV) infection in HIV-infected subjects in northern Italy: a longitudinal cohort study among men who have sex with men. BMC Infect Dis 2011; 11:150.
134. Read TR, Hocking JS, Vodstrcil LA, Tabrizi SN, McCullough MJ, Grulich AE, et al. Oral human papillomavirus in men having sex with men: risk-factors and sampling. PLoS One 2012; 7:e49324.
135. Cranston RD, Murphy R, Weiss RE, Da Costa M, Palefsky J, Shoptaw S, et al. Anal human papillomavirus infection in a street-based sample of drug using HIV-positive men. Int J STD AIDS 2012; 23:195–200.
136. Sahasrabuddhe VV, Castle PE, Follansbee S, Borgonovo S, Tokugawa D, Schwartz LM, et al. Human papillomavirus genotype attribution and estimation of preventable fraction of anal intraepithelial neoplasia cases among HIV-infected men who have sex with men. J Infect Dis 2013; 207:392–401.
137. Torres M, González C, del Romero J, Viciana P, Ocampo A, Rodríguez-Fortúnez P, et al. Anal human papillomavirus genotype distribution in HIV-infected men who have sex with men by geographical origin, age, and cytological status in a Spanish cohort. J Clin Microbiol 2013; 51:3512–3520.
138. Goldstone SE, Lowe B, Rothmann T, Nazarenko I. Evaluation of the hybrid capture 2 assay for detecting anal high-grade dysplasia. Int J Cancer 2012; 131:1641–1648.
139. Swedish KA, Lee EQ, Goldstone SE. The changing picture of high-grade anal intraepithelial neoplasia in men who have sex with men: the effects of 10 years of experience performing high-resolution anoscopy. Dis Colon Rectum 2011; 54:1003–1007.
140. Angeli E, Mainini A, Meraviglia P, Schiavini M, Ricci E, Giorgi R, et al. Eligibility and feasibility of the treatment of chronic hepatitis C in a cohort of Italian HIV-positive patients at a single HIV reference center. AIDS Patient Care STDS 2011; 25:295–301.
141. Bickel M, Marben W, Betz C, Khaykin P, Stephan C, Gute P, et al. End-stage renal disease and dialysis in HIV-positive patients: observations from a long-term cohort study with a follow-up of 22 years. HIV Med 2013; 14:127–135.
142. Branch AD, Van Natta ML, Vachon ML, Dieterich DT, Meinert CL, Jabs DA, et al. Mortality in hepatitis C virus-infected patients with a diagnosis of AIDS in the era of combination antiretroviral therapy. Clin Infect Dis 2012; 55:137–144.
143. Di Biagio A, Rosso R, Vitale F, Cardinale F, Sormani MP, Secondo G, et al. Risk factors for chronic kidney disease among human immunodeficiency virus-infected patients: a European case control study. Clin Nephrol 2011; 75:518–523.
144. Di Lello FA, Macías J, Cifuentes CC, Vargas J, Palomares JC, Pineda JA. Low prevalence of occult HBV infection among HIV-infected patients in Southern Spain. Enferm Infecc Microbiol Clin 2012; 30:312–314.
145. Grebely J, Raffa JD, Lai C, Kerr T, Fischer B, Krajden M, et al. Impact of hepatitis C virus infection on all-cause and liver-related mortality in a large community-based cohort of inner city residents. J Viral Hepat 2011; 18:32–41.
146. Jernigan TL, Archibald SL, Fennema-Notestine C, Taylor MJ, Theilmann RJ, Julaton MD, et al. Clinical factors related to brain structure in HIV: the CHARTER study. J Neurovirol 2011; 17:248–257.
147. Kim JH, Psevdos G Jr, Sharp V. Five-year review of HIV-hepatitis B virus (HBV) co-infected patients in a New York City AIDS center. J Korean Med Sci 2012; 27:830–833.
148. Linas BP, Wang B, Smurzynski M, Losina E, Bosch RJ, Schackman BR, et al. The impact of HIV/HCV co-infection on health care utilization and disability: results of the ACTG Longitudinal Linked Randomized Trials (ALLRT) Cohort. J Viral Hepat 2011; 18:506–512.
149. Marcellin F, Lacombe K, Fugon L, Molina JM, Bonnard P, Miailhes P, et al. Correlates of poor perceived health among individuals living with HIV and HBV chronic infections: a longitudinal assessment. AIDS Care 2011; 23:501–507.
150. Pensieroso S, Galli L, Nozza S, Ruffin N, Castagna A, Tambussi G, et al. B-cell subset alterations and correlated factors in HIV-1 infection. AIDS 2013; 27:1209–1217.
151. Pérez Cachafeiro S, Caro-Murillo AM, Berenguer J, Segura F, Gutiérrez F, Vidal F, et al. Association of patients’ geographic origins with viral hepatitis co-infection patterns, Spain. Emerg Infect Dis 2011; 17:1116–1119.
152. Raboud J, Anema A, Su D, Klein MB, Zakaryan A, Swan T, et al. Relationship of chronic hepatitis C infection to rates of AIDS-defining illnesses in a Canadian cohort of HIV seropositive individuals receiving highly active antiretroviral therapy. HIV Clin Trials 2012; 13:90–102.
153. Reiberger T, Obermeier M, Payer BA, Baumgarten A, Weitner L, Moll A, et al. Considerable under-treatment of chronic HCV infection in HIV patients despite acceptable sustained virological response rates in a real-life setting. Antivir Ther 2011; 16:815–824.
154. Reuter S, Oette M, Wilhelm FC, Beggel B, Kaiser R, Balduin M, et al. Prevalence and characteristics of hepatitis B and C virus infections in treatment-naive HIV-infected patients. Med Microbiol Immunol 2011; 200:39–49.
155. Sassoon SA, Rosenbloom MJ, Fama R, Sullivan EV, Pfefferbaum A. Selective neurocognitive deficits and poor life functioning are associated with significant depressive symptoms in alcoholism-HIV infection comorbidity. Psychiatry Res 2012; 199:102–110.
156. Speers S, Klevens RM, Vonderwahl C, Bryant T, Daniloff E, Capizzi J, et al. Electronic matching of HIV/AIDS and hepatitis C surveillance registries in three states. Public Health Rep 2011; 126:344–348.
157. Weimer LE, Fragola V, Floridia M, Guaraldi G, Ladisa N, Francisci D, et al. Response to raltegravir-based salvage therapy in HIV-infected patients with hepatitis C virus or hepatitis B virus coinfection. J Antimicrob Chemother 2013; 68:193–199.
158. Witteck A, Schmid P, Hensel-Koch K, Thurnheer MC, Bruggmann P, Vernazza P, et al. Management of hepatitis C virus (HCV) infection in drug substitution programs. Swiss Med Wkly 2011; 141:w13193.
159. Floridia M, Mastroiacovo P, Tamburrini E, Tibaldi C, Todros T, Crepaldi A, et al. Birth defects in a national cohort of pregnant women with HIV infection in Italy, 2001–2011. BJOG 2013; 120:1466–1475.
160. Barfod TS, Omland LH, Katzenstein TL. Incidence and characteristics of sexually transmitted acute hepatitis C virus infection among HIV-positive men who have sex with men in Copenhagen, Denmark during four years (2006–2009): a retrospective cohort study. Scand J Infect Dis 2011; 43:145–148.
161. Gamage DG, Read TR, Bradshaw CS, Hocking JS, Howley K, Chen MY, et al. Incidence of hepatitis-C among HIV infected men who have sex with men (MSM) attending a sexual health service: a cohort study. BMC Infect Dis 2011; 11:39.
162. Hoover KW, Butler M, Workowski KA, Follansbee S, Gratzer B, Hare CB, et al. Low rates of hepatitis screening and vaccination of HIV-infected MSM in HIV clinics. Sex Transm Dis 2012; 39:349–353.
163. Matser A, Vanhommerig J, Schim van der Loeff MF, Geskus RB, de Vries HJC, Prins JM, et al. HIV-infected men who have sex with men who identify themselves as belonging to subcultures are at increased risk for hepatitis C infection. PLoS One 2013; 8:e57740.
164. van der Helm JJ, Prins M, del Amo J, Bucher HC, Chêne G, Dorrucci M, et al. The hepatitis C epidemic among HIV-positive MSM: incidence estimates from 1990 to 2007. AIDS 2011; 25:1083–1091.
165. Bayón C, Ribera E, Cabrero E, Griffa L, Burgos A. Prevalence of depressive and other central nervous system symptoms in HIV-infected patients treated with HAART in Spain. J Int Assoc Physicians AIDS Care 2012; 11:321–328.
166. Guaraldi G, Lonardo A, Ballestri S, Zona S, Stentarelli C, Orlando G, et al. Human immunodeficiency virus is the major determinant of steatosis and hepatitis C virus of insulin resistance in virus-associated fatty liver disease. Arch Med Res 2011; 42:690–697.
167. Labarga P, Soriano V, Caruz A, Poveda E, Di Lello FA, Hernandez-Quero J, et al. Association between IL28B gene polymorphisms and plasma HCV-RNA levels in HIV/HCV-co-infected patients. AIDS 2011; 25:761–766.
168. Rabkin JG, McElhiney MC, Rabkin R. Modafinil and armodafinil treatment for fatigue for HIV-positive patients with and without chronic hepatitis C. Int J STD AIDS 2011; 22:95–101.
169. Suárez-Zarracina T, Valle-Garay E, Collazos J, Montes AH, Cárcaba V, Carton JA, et al. Didanosine (ddI) associates with increased liver fibrosis in adult HIV-HCV coinfected patients. J Viral Hepat 2012; 19:685–693.
170. Treviño A, Soriano V, Rodríguez C, Arredondo M, Rivas P, Herrero-Mendoza D, et al. Changing rate of non-B subtypes and coinfection with hepatitis B/C viruses in newly diagnosed HIV type 1 individuals in Spain. AIDS Res Hum Retroviruses 2011; 27:633–638.
171. Tsui JI, Cheng DM, Libman H, Bridden C, Samet J. Hepatitis C virus infection is associated with painful symptoms in HIV-infected adults. AIDS Care 2012; 24:820–827.
172. Vermehren J, Vermehren A, Mueller A, Carlebach A, Lutz T, Gute P, et al. Assessment of liver fibrosis and associated risk factors in HIV-infected individuals using transient elastography and serum biomarkers. BMC Gastroenterol 2012; 12:27.
173. Raymond HF, Chu P, Nieves-Rivera I, Louie B, McFarland W, Pandori M. Hepatitis C infection among men who have sex with men, San Francisco, 2011. Sex Transm Dis 2012; 39:985–986.
174. Chun HM, Roediger MP, Hullsiek KH, Thio CL, Agan BK, Bradley WP, et al. Hepatitis B virus coinfection negatively impacts HIV outcomes in HIV seroconverters. J Infect Dis 2012; 205:185–193.
175. Coffin CS, Osiowy C, Myers RP, Gill MJ. Virology and clinical sequelae of long-term antiviral therapy in a North American cohort of hepatitis B virus (HBV)/human immunodeficiency virus type 1 (HIV-1) co-infected patients. J Clin Virol 2013; 57:103–108.
176. Clifford GM, Gonçalves MA, Franceschi S. HPV and HIV Study Group. Human papillomavirus types among women infected with HIV: a meta-analysis. AIDS 2006; 20:2337–2344.
177. Shiels MS, Pfeiffer RM, Gail MH, Hall HI, Li J, Chaturvedi AK, et al. Cancer burden in the HIV-infected population in the United States. J Natl Cancer Inst 2011; 103:753–762.
178. Torian L, Chen M, Rhodes P, Hall HI. HIV surveillance--United States, 1981–2008. MMWR Morb Mortal Wkly Rep 2011; 60:689–693.
179. Boodram B, Plankey MW, Cox C, Tien PC, Cohen MH, Anastos K, et al. Prevalence and correlates of elevated body mass index among HIV-positive and HIV-negative women in the Women's Interagency HIV Study. AIDS Patient Care STDS 2009; 23:1009–1016.
180. Crum-Cianflone N, Tejidor R, Medina S, Barahona I, Ganesan A. Obesity among patients with HIV: the latest epidemic. AIDS Patient Care STDS 2008; 22:925–930.
181. Palefsky J. Biology of HPV in HIV infection. Adv Dent Res 2006; 19:99–105.
182. Lakey W, Yang LY, Yancy W, Chow SC, Hicks C. Short communication: from wasting to obesity: initial antiretroviral therapy and weight gain in HIV-infected persons. AIDS Res Hum Retroviruses 2013; 29:435–440.
183. Drach L, Holbert T, Maher J, Fox V, Schubert S, Saddler LC. Integrating smoking cessation into HIV care. AIDS Patient Care STDS 2010; 24:139–140.
184. Lifson AR, Lando HA. Smoking and HIV: prevalence, health risks, and cessation strategies. Curr HIV/AIDS Rep 2012; 9:223–230.
185. Toft L, Storgaard M, Müller M, Sehr P, Bonde J, Tolstrup M, et al. Comparison of the immunogenicity and reactogenicity of Cervarix and Gardasil human papillomavirus vaccines in HIV-infected adults: a randomized, double-blind clinical trial. J Infect Dis 2014; 209:1165–1173.
186. Kojic EM, Kang M, Cespedes MS, Umbleja T, Godfrey C, Allen RT, et al. Immunogenicity and safety of the quadrivalent human papillomavirus vaccine in HIV-1-infected women. Clin Infect Dis 2014; 59:127–135.
187. Wilkin T, Lee JY, Lensing SY, Stier EA, Goldstone SE, Berry JM, et al. Safety and immunogenicity of the quadrivalent human papillomavirus vaccine in HIV-1-infected men. J Infect Dis 2010; 202:1246–1253.
188. Kahn JA, Xu J, Kapogiannis BG, Rudy B, Gonin R, Liu N, et al. Immunogenicity and safety of the human papillomavirus 6, 11, 16, 18 vaccine in HIV-infected young women. Clin Infect Dis 2013; 57:735–744.
189. Kaplan JE, Benson C, Holmes KK, Brooks JT, Pau A, Masur H, et al. Guidelines for prevention and treatment of opportunistic infections in HIV-infected adults and adolescents: recommendations from CDC, the National Institutes of Health, and the HIV Medicine Association of the Infectious Diseases Society of America. MMWR Recomm Rep 2009; 58:1–207.
190. Whitaker JA, Rouphael NG, Edupuganti S, Lai L, Mulligan MJ. Strategies to increase responsiveness to hepatitis B vaccination in adults with HIV-1. Lancet Infect Dis 2012; 12:966–976.
191. Osinusi A, Townsend K, Kohli A, Nelson A, Seamon C, Meissner EG, et al. Virologic response following combined ledipasvir and sofosbuvir administration in patients with HCV genotype 1 and HIV co-infection. JAMA 2015; 313:1232–1239.
192. Sulkowski MS, Eron JJ, Wyles D, Trinh R, Lalezari J, Wang C, et al. Ombitasvir, paritaprevir co-dosed with ritonavir, dasabuvir, and ribavirin for hepatitis C in patients co-infected with HIV-1: a randomized trial. JAMA 2015; 313:1223–1231.
193. Panel on Antiretroviral Guidelines for Adults and Adolescents. Guidelines for the use of antiretroviral agents in HIV-1-infected adults and adolescents. Department of Health and Human Services, 2014. [Accessed 25 February 2015]
194. Cui Q, Robinson L, Elston D, Smaill F, Cohen J, Quan C, et al. Safety and tolerability of varenicline tartrate (Champix ®/Chantix ®) for smoking cessation in HIV-infected subjects: a pilot open-label study. AIDS Patient Care STDS 2012; 26:12–19.
195. Park J, Vousden M, Brittain C, McConn DJ, Iavarone L, Ascher J, et al. Dose-related reduction in bupropion plasma concentrations by ritonavir. J Clin Pharmacol 2010; 50:1180–1187.
196. American Association for the Study of Liver Diseases, Infectious Diseases Society of America, International Antiviral Society. Recommendations for testing, managing, and treating hepatitis C, 2014. [Accessed 25 February 2015]
197. Firnhaber C, Wilkin T. Human papillomavirus vaccines: where do they fit in HIV-infected individuals?. Curr HIV/AIDS Rep 2012; 9:278–286.
198. Heard I. Human papillomavirus, cancer and vaccination. Curr Opin HIV AIDS 2011; 6:297–302.
199. Widdice LE, Bernstein DI, Leonard AC, Marsolo KA, Kahn JA. Adherence to the HPV vaccine dosing intervals and factors associated with completion of 3 doses. Pediatrics 2011; 127:77–84.

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