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Previous studies have reported an increased risk for certain types of cancer in the HIV-infected population. The aim of this study was to assess the risk for cancer in people with AIDS (PWA) in comparison with the general population in São Paulo (Brazil), between 1997 and 2012. A population-based registry linkage study was carried out to assess the risk for cancer, using a standardized incidence ratio (SIR) approach. A total of 480 102 person-years, of which 337 941 (70.4%) person-years were men, were included in the analysis. Around 2074 cancer cases were diagnosed among PWA, of which 51.0% were non-AIDS-defining cancers (NADC). The risk for AIDS-defining cancers and NADC in the male population with AIDS was significantly higher than that in the general population (SIR=27.74 and 1.87, respectively), as it was in the female population with AIDS compared with the general population (SIR=8.71 and 1.44, respectively). Most virus-related NADC occurred at elevated rates among PWA: anal cancer (SIR=33.02 in men and 11.21 in women), liver (SIR=4.35 in men and 4.84 in women), vulva and vagina (SIR=6.78 in women) and Hodgkin lymphoma (SIR=5.84 in men and 2.71 in women). Lung (SIR=2.24 in men and 2.60 in women) and central nervous system (SIR=1.92 in men and 3.48 in women) cancers also occurred at increased rates. Cancer burden among PWA in São Paulo was similar to that described in high-income countries such as the USA and Italy following the introduction of the highly active antiretroviral therapy. As coinfection with oncogenic viruses disproportionally affects this population, virus-related cancers accounted for a great share of excessive cases.

Background: Both CD4 count and viral load in HIV-infected persons are measured with error. There is no clear guidance on how to deal with this measurement error in the presence of missing data., Methods: We used multiple overimputation, a method recently developed in the political sciences, to account for both measurement error and missing data in CD4 count and viral load measurements from four South African cohorts of a Southern African HIV cohort collaboration. Our knowledge about the measurement error of ln CD4 and log10 viral load is part of an imputation model that imputes both missing and mismeasured data. In an illustrative example, we estimate the association of CD4 count and viral load with the hazard of death among patients on highly active antiretroviral therapy by means of a Cox model. Simulation studies evaluate the extent to which multiple overimputation is able to reduce bias in survival analyses., Results: Multiple overimputation emphasizes more strongly the influence of having high baseline CD4 counts compared to both a complete case analysis and multiple imputation (hazard ratio for >200 cells/mm vs. <25 cells/mm: 0.21 [95% confidence interval: 0.18, 0.24] vs. 0.38 [0.29, 0.48], and 0.29 [0.25, 0.34], respectively). Similar results are obtained when varying assumptions about measurement error, when using p-splines, and when evaluating time-updated CD4 count in a longitudinal analysis. The estimates of the association with viral load are slightly more attenuated when using multiple imputation instead of multiple overimputation. Our simulation studies suggest that multiple overimputation is able to reduce bias and mean squared error in survival analyses., Conclusions: Multiple overimputation, which can be used with existing software, offers a convenient approach to account for both missing and mismeasured data in HIV research.