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      Cervical cancer risk factors among HIV-infected Nigerian women

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          Cervical cancer is the third most common cancer among women worldwide, and in Nigeria it is the second most common female cancer. Cervical cancer is an AIDS-defining cancer; however, HIV only marginally increases the risk of cervical pre-cancer and cancer. In this study, we examine the risk factors for cervical pre-cancer and cancer among HIV-positive women screened for cervical cancer at two medical institutions in Abuja, Nigeria.


          A total of 2,501 HIV-positive women participating in the cervical cancer screen-and-treat program in Abuja, Nigeria consented to this study and provided socio-demographic and clinical information. Log-binomial models were used to calculate relative risk (RR) and 95% confidence intervals (95%CI) for the risk factors of cervical pre-cancer and cancer.


          There was a 6% prevalence of cervical pre-cancer and cancer in the study population of HIV-positive women. The risk of screening positivity or invasive cancer diagnosis reduced with increasing age, with women aged 40 years and older having the lowest risk (RR=0.4; 95%CI=0.2–0.7). Women with a CD4 count of 650 per mm 3 or more also had lower risk of screening positivity or invasive cancer diagnosis (RR=0.3, 95%CI=0.2–0.6). Other factors such as having had 5 or more abortions (RR=1.8, 95%CI=1.0–3.6) and the presence of other vaginal wall abnormalities (RR=1.9, 95%CI=1.3–2.8) were associated with screening positivity or invasive cancer diagnosis.


          The prevalence of screening positive lesions or cervical cancer was lower than most previous reports from Africa. HIV-positive Nigerian women were at a marginally increased risk of cervical pre-cancer and cancer. These findings highlight the need for more epidemiological studies of cervical cancer and pre-cancerous lesions among HIV-positive women in Africa and an improved understanding of incidence and risk factors.

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          In the absence of prior knowledge about population relations, investigators frequently employ a strategy that uses the data to help them decide whether to adjust for a variable. The authors compared the performance of several such strategies for fitting multiplicative Poisson regression models to cohort data: 1) the "change-in-estimate" strategy, in which a variable is controlled if the adjusted and unadjusted estimates differ by some important amount; 2) the "significance-test-of-the-covariate" strategy, in which a variable is controlled if its coefficient is significantly different from zero at some predetermined significance level; 3) the "significance-test-of-the-difference" strategy, which tests the difference between the adjusted and unadjusted exposure coefficients; 4) the "equivalence-test-of-the-difference" strategy, which significance-tests the equivalence of the adjusted and unadjusted exposure coefficients; and 5) a hybrid strategy that takes a weighted average of adjusted and unadjusted estimates. Data were generated from 8,100 population structures at each of several sample sizes. The performance of the different strategies was evaluated by computing bias, mean squared error, and coverage rates of confidence intervals. At least one variation of each strategy that was examined performed acceptably. The change-in-estimate and equivalence-test-of-the-difference strategies performed best when the cut-point for deciding whether crude and adjusted estimates differed by an important amount was set to a low value (10%). The significance test strategies performed best when the alpha level was set to much higher than conventional levels (0.20).
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                Author and article information

                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central
                14 June 2013
                : 13
                : 582
                [1 ]Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
                [2 ]Office of Research and Training, Institute of Human Virology, Abuja, Nigeria
                [3 ]National Hospital, Abuja, Nigeria
                [4 ]University of Abuja Teaching Hospital, Gwagwalada, Nigeria
                [5 ]Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA
                [6 ]Department of Epidemiology and Public Health, Institute of Human Virology and Greenebaum Cancer Centre, University of Maryland School of Medicine, Baltimore, MD 21201, USA
                Copyright © 2013 Ononogbu et al.; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Research Article

                Public health

                via/vili, cervical cancer, screen and treat, hiv


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