The HPV type distribution is similar in HIV-positive and HIV-negative women. These results suggest that the HPV vaccines that are currently available could protect women from HPV infection independently of their HIV status.
The aim of this cross sectional study was to assess type distribution of human papillomavirus (HPV) among HIV positive and HIV negative women who underwent cervical cancer screening, and to examine the ability of visual inspection with acetic acid (VIA), the standard detection method in Tanzania, and HPV-testing to detect cytologically diagnosed high grade lesions or cancer (HSIL+). Women from different areas in Tanzania were invited by public announcement to cervical cancer screening organized by Ocean Road Cancer Institute (Dar-es-Salaam). A total of 3,767 women were enrolled. Women underwent gynecological examination with collection of cervical cells for conventional cytological examination, and swab for HPV-DNA detection (Hybrid-Capture2) and genotyping (LiPAv2 test). Subsequently VIA was performed. The participants were also tested for HIV. HPV16, HPV52 and HPV18 were the three most common HR HPV types among women with HSIL+ cytology with prevalences of 42.9, 35.7 and 28.6%, respectively, in HIV positive women which was higher than among HIV negative women (30.2, 21.9 and 16.7%). A total of 4.5% of the women were VIA positive, and VIA showed a low sensitivity compared to HPV-testing for detection of HSIL+. The sensitivity of VIA varied with staff VIA experience, HIV status and age. Vaccines including HPV16, HPV52 and HPV18 will likely reduce the number of HSIL+ cases independently of HIV status. The frequency of HSIL+ was high among HIV positive women, emphasizing the importance of establishing a screening program which also reaches HIV positive women. Our results highlight the importance of continuous training of staff performing VIA, and also point to the need for other screening methods such as HPV-testing at low cost.
From this prospective study a model based on preoperative symptoms was developed to predict postcholecystectomy pain. Since intrastudy reclassification may give too optimistic results, the model should be validated in future studies.
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