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- Pantazis, N, et al.
(author)
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Determining the likely place of HIV acquisition for migrants in Europe combining subject-specific information and biomarkers data
- 2019
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In: Statistical methods in medical research. - : SAGE Publications. - 1477-0334 .- 0962-2802. ; 28:7, s. 1979-1997
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Journal article (peer-reviewed)abstract
- In most HIV-positive individuals, infection time is only known to lie between the time an individual started being at risk for HIV and diagnosis time. However, a more accurate estimate of infection time is very important in certain cases. For example, one of the objectives of the Advancing Migrant Access to Health Services in Europe (aMASE) study was to determine if HIV-positive migrants, diagnosed in Europe, were infected pre- or post-migration. We propose a method to derive subject-specific estimates of unknown infection times using information from HIV biomarkers’ measurements, demographic, clinical, and behavioral data. We assume that CD4 cell count (CD4) and HIV-RNA viral load trends after HIV infection follow a bivariate linear mixed model. Using post-diagnosis CD4 and viral load measurements and applying the Bayes’ rule, we derived the posterior distribution of the HIV infection time, whereas the prior distribution was informed by AIDS status at diagnosis and behavioral data. Parameters of the CD4–viral load and time-to-AIDS models were estimated using data from a large study of individuals with known HIV infection times (CASCADE). Simulations showed substantial predictive ability (e.g. 84% of the infections were correctly classified as pre- or post-migration). Application to the aMASE study ( n = 2009) showed that 47% of African migrants and 67% to 72% of migrants from other regions were most likely infected post-migration. Applying a Bayesian method based on bivariate modeling of CD4 and viral load, and subject-specific information, we found that the majority of HIV-positive migrants in aMASE were most likely infected after their migration to Europe.
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- Klug, Stefanie J, et al.
(author)
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TP53 codon 72 polymorphism and cervical cancer : a pooled analysis of individual data from 49 studies
- 2009
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In: The Lancet Oncology. - 1470-2045 .- 1474-5488. ; 10:8, s. 772-784
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Journal article (peer-reviewed)abstract
- BACKGROUND: Cervical cancer is caused primarily by human papillomaviruses (HPV). The polymorphism rs1042522 at codon 72 of the TP53 tumour-suppressor gene has been investigated as a genetic cofactor. More than 80 studies were done between 1998 and 2006, after it was initially reported that women who are homozygous for the arginine allele had a risk for cervical cancer seven times higher than women who were heterozygous for the allele. However, results have been inconsistent. Here we analyse pooled data from 49 studies to determine whether there is an association between TP53 codon 72 polymorphism and cervical cancer. METHODS: Individual data on 7946 cases and 7888 controls from 49 different studies worldwide were reanalysed. Odds ratios (OR) were estimated using logistic regression, stratifying by study and ethnic origin. Subgroup analyses were done for infection with HPV, ethnic origin, Hardy-Weinberg equilibrium, study quality, and the material used to determine TP53 genotype. FINDINGS: The pooled estimates (OR) for invasive cervical cancer were 1.22 (95% CI 1.08-1.39) for arginine homozygotes compared with heterozygotes, and 1.13 (0.94-1.35) for arginine homozygotes versus proline homozygotes. Subgroup analyses showed significant excess risks only in studies where controls were not in Hardy-Weinberg equilibrium (1.71 [1.21-2.42] for arginine homozygotes compared with heterozygotes), in non-epidemiological studies (1.35 [1.15-1.58] for arginine homozygotes compared with heterozygotes), and in studies where TP53 genotype was determined from tumour tissue (1.39 [1.13-1.73] for arginine homozygotes compared with heterozygotes). Null results were noted in studies with sound epidemiological design and conduct (1.06 [0.87-1.29] for arginine homozygotes compared with heterozygotes), and studies in which TP53 genotype was determined from white blood cells (1.06 [0.87-1.29] for arginine homozygotes compared with heterozygotes). INTERPRETATION: Subgroup analyses indicated that excess risks were most likely not due to clinical or biological factors, but to errors in study methods. No association was found between cervical cancer and TP53 codon 72 polymorphism when the analysis was restricted to methodologically sound studies.
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