The possibility of safe discontinuation of therapy with nucleos(t)ide analogues (NAs) remains one of the most controversial topics in the management of chronic hepatitis B. Therefore, we systematically reviewed the existing data on NA discontinuation in this setting and tried to identify factors affecting the probability of posttherapy remission. A literature search was performed in order to identify all published studies including patients who discontinued NAs in virological remission (VR) and were followed for 12 months thereafter. Twenty-five studies with 1716 patients were included. The pooled rates of durable VR remission were 51.4%, 39.3%, and 38.2% at 12, 24, and 36 months, respectively, after NA discontinuation, being relatively higher in initially hepatitis B e antigen (HBeAg)-positive patients (62.5%, 53.4%, 51.5%) than HBeAg-negative patients (43.7%, 31.3%, 30.1%) (P 5 0.064). The weighted probability of durable biochemical remission was 65.4%, being numerically higher in HBeAg-positive than HBeAg-negative patients (76.2% versus 56.7%, P 5 0.130). The weighted probability of hepatitis B surface antigen loss was 2.0%. The rates of durable VR did not significantly differ according to the VR definition (hepatitis B virus DNA <200, < 2000, < 20,000 IU/mL) or duration of on-therapy VR in HBeAg-positive patients, but they were significantly higher in studies with HBeAg-negative patients and on-therapy VR > 24 than £ 24 months (VR at 12 months off-NAs: 75.0% versus 35.6%, P 5 0.005). The weighted probability of durable HBeAg seroconversion was 91.9% and 88.0% at 12 and 24 months, respectively, after NA discontinuation without being affected by the duration of on-therapy VR or consolidation therapy (>6 months in all studies). Conclusion: Durable VR seems to be feasible in a substantial proportion of patients who discontinue long-term NA therapy; on-therapy VR > 24 months offers higher chances of off-NA VR in patients with HBeAg-negative chronic hepatitis B. (HEPATOLOGY 2016;63:1481-1492 T reatment against hepatitis B virus (HBV) has dramatically improved over the last 15 years, but HBV eradication remains a rarely attainable target. (1-3) Pegylated interferon-alfa therapy given for a finite duration of usually 48 weeks can achieve sustained off-therapy responses, with almost half of the responders clearing hepatitis B surface antigen (HBsAg) in the long term. However, only 20%-30% of patients with hepatitis B e antigen (HBeAg)-positive or HBeAg-negative chronic hepatitis B (CHB) may achieve sustained off-therapy responses after a course of pegylated interferon-alfa. (1)(2)(3) Many patients are reluctant to start treatment with this agent because interferon-alfa may have severe side effects as well as an unfavorable safety profile. Thus, oral antiviral agents, nucleos(t)ide analogues (NAs), represent the main therapeutic option for the majority of CHB patients. (4) Abbreviations: ALT, alanine aminotransferase; BR, biochemical remission; CHB, chronic hepatitis B; CI, confidence interval; HBeAg, hepatitis B e a...

Objective: We aimed to estimate the proportion of post-migration HIV acquisition among HIVpositive migrants in Europe. Design:To reach HIV positive migrants we designed a cross sectional study performed in HIV clinics. Methods:The study was conducted from July 2013-July 2015 in 57 clinics (9 European countries, targeting individuals over 18 years diagnosed in the preceding 5 years and born abroad.Electronic questionnaires supplemented with clinical data were completed in any of 15 languages.Post-migration HIV acquisition was estimated through Bayesian approaches combining extensive information on migration and patients' characteristics. CD4 counts and HIV-RNA trajectories from seroconversion were estimated by bivariate linear mixed models fitted to natural history data. Post-migration acquisition risk factors were investigated with weighted logistic regression. Median time in host countries was 8 years. Post-migration HIV acquisition was 63% (95% CI: 57%-67%); 72% among MSM, 58% and 51% in heterosexual men and women, respectively. Post-migration HIV acquisition was 71% for LAC migrants and 45% for people from SSA. ResultsFactors associated with post-migration HIV acquisition among heterosexual women and MSM were age at migration, length of stay in host country and HIV diagnosis year and among heterosexual men, length of stay in host country, and HIV diagnosis year. Conclusions:A substantial proportion of HIV-positive migrants living in Europe acquired HIV post-migration. This has important implications for European public health policies.

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.

Missing data are common in longitudinal studies. Likelihood-based methods ignoring the missingness mechanism are unbiased provided missingness is at random (MAR);under not-at-random missingness (MNAR), joint modeling is commonly used, often as part of sensitivity analyses. In our motivating example of modeling CD4 count trajectories during untreated HIV infection, CD4 counts are mainly censored due to treatment initiation, with the nature of this mechanism remaining debatable. Here, we evaluate the bias in the disease progression marker's change over time (slope) of a specific class of joint models, termed shared-random-effects-models (SREMs), under MAR drop-out and propose an alternative SREM model. Our proposed model relates drop-out to both the observed marker's data and the corresponding random effects, in contrast to most SREMs, which assume that the marker and the drop-out processes are independent given the random effects. We analytically calculate the asymptotic bias in two SREMs under specific MAR drop-out mechanisms, showing that the bias in marker's slope increases as the drop-out probability increases. The performance of the proposed model, and other commonly used SREMs, is evaluated under specific MAR and MNAR scenarios through simulation studies. Under MAR, the proposed model yields nearly unbiased slope estimates, whereas the other SREMs yield seriously biased estimates. Under MNAR, the proposed model estimates are approximately unbiased, whereas those from the other SREMs are moderately to heavily biased, depending on the parameterization used. The examined models are also fitted to real data and results are compared/discussed in the light of our analytical and simulation-based findings.

Despite data inconsistency and clinical heterogeneity, this systematic review and meta-analysis showed that patients with PMD are at a two-fold higher risk, both during lifetime and in acute phase, of committing a suicidal attempt than patients with non-PMD.

BackgroundIt remains unclear whether psychotic features increase the risk of completed suicides in unipolar depression. The present systematic review coupled with a meta-analysis attempts to elucidate whether unipolar psychotic major depression (PMD) compared to non-PMD presents higher rates of suicides.MethodsA systematic search was conducted in Scopus, PubMed, and “gray literature” for all studies providing data on completed suicides in PMD compared to non-PMD, and the findings were then subjected to meta-analysis. All articles were independently extracted by two authors using predefined data fields.ResultsNine studies with 33,873 patients, among them 828 suicides, met our inclusion criteria. PMD compared to non-PMD presented a higher lifetime risk of completed suicides with fixed-effect pooled OR 1.21 (95% CI 1.04–1.40). In a sub-analysis excluding a very large study (weight = 86.62%), and comparing 681 PMD to 2106 non-PMD patients, an even higher pooled OR was found [fixed-effect OR 1.69 (95% CI 1.16–2.45)]. Our meta-analysis may provide evidence that the presence of psychosis increases the risk of suicide in patients suffering from severe depression. The data are inconclusive on the contribution of age, mood congruence, comorbidity, and suicide method on PMD’s suicide risk. The lack of accurate diagnosis at the time of suicide, PMD’s diagnostic instability, and the use of ICD-10 criteria constitute the main study limitations.ConclusionsThe presence of psychosis in major depression should alert clinicians for the increased risk of completed suicide. Thus, the implementation of an effective treatment both for psychotic depression and patients’ suicidality constitutes a supreme priority.Electronic supplementary materialThe online version of this article (10.1186/s12991-018-0207-1) contains supplementary material, which is available to authorized users.

Misspecification of the covariance structure in a linear mixed model (LMM) can lead to biased population parameters' estimates under MAR drop‐out. In our motivating example of modeling CD4 cell counts during untreated HIV infection, random intercept and slope LMMs are frequently used. In this article, we evaluate the performance of LMMs with specific covariance structures, in terms of bias in the fixed effects estimates, under specific MAR drop‐out mechanisms, and adopt a Bayesian model comparison criterion to discriminate between the examined approaches in real‐data applications. We analytically show that using a random intercept and slope structure when the true one is more complex can lead to seriously biased estimates, with the degree of bias depending on the magnitude of the MAR drop‐out. Under misspecified covariance structure, we compare in terms of induced bias the approach of adding a fractional Brownian motion (BM) process on top of random intercepts and slopes with the approach of using splines for the random effects. In general, the performance of both approaches was satisfactory, with the BM model leading to smaller bias in most cases. A simulation study is carried out to evaluate the performance of the proposed Bayesian criterion in identifying the model with the correct covariance structure. Overall, the proposed method performs better than the AIC and BIC criteria under our specific simulation setting. The models under consideration are applied to real data from the CASCADE study; the most plausible model is identified by all examined criteria.

Introduction: We aimed to assess alterations in glucose, blood pressure and temperature in acute ischaemic stroke and investigate their association with early all-cause mortality and functional outcome. Patients and methods: We studied all consecutive acute ischaemic stroke patients admitted in 2001-2010 to the Acute Stroke Unit, at Alexandra University Hospital, in Athens. Serial measurements were performed in the first seven days post-stroke and different parameters have been estimated: mean daily values, variability, subject-specific baseline levels and rate of change in serial measurements. Cox-proportional-hazards-model analysis and logistic-regression analysis were applied to investigate the association between these parameters and all-cause mortality and functional outcome after adjustment for known confounders of stroke outcome. Results: In 1271 patients (mean age 72.3 AE 11.2 years), after adjusting for confounders, baseline glucose levels (HR: 1.005, 95%CI: 1.001-1.01; p ¼ 0.017), variability of systolic BP (SBP) as estimated by standard deviation (HR: 1.028, 95% CI: 1.01-1.048; p ¼ 0.005), the baseline temperature (HR: 2.758, 95%CI: 2.067-3.68; p < 0.001) and the rate of temperature change (HR: 1.841, 95%CI: 1.616-2.908; p < 0.001) were independently associated with all-cause mortality within three months. Poor functional outcome was associated with subject-specific baseline values of temperature (OR: 1.743; 95%CI: 1.076-2.825; p ¼ 0.024), the rate of SBP (OR: 1.159; 95% CI: 1.047-1.280; p ¼ 0.004) and temperature change (OR: 1.402; 95% CI: 1.061-1.853; p ¼ 0.018). Discussion: The main strength of our study is that we analysed simultaneously three parameters and we used four different variables for each parameter of interest. Conclusion: Baseline glucose levels, variability of SBP and baseline temperature and its rate of change are independent predictors of all-cause mortality. Baseline values of temperature and the rate of changes in SBP and temperature are independent predictors of poor functional outcome.