A joint back calculation model for the imputation of the date of HIV infection in a prevalent cohort

Cohort profile: the South African HIV Cancer Match (SAM) Study, a national population-based cohort

PURPOSE

The South African HIV Cancer Match (SAM) Study is a national cohort of people living with HIV (PLWH). It was created using probabilistic record linkages of routine laboratory records of PLWH retrieved by National Health Laboratory Services (NHLS) and cancer data from the National Cancer Registry. The SAM Study aims to assess the spectrum and risk of cancer in PLWH in the context of the evolving South African HIV epidemic. The SAM Study's overarching goal is to inform cancer prevention and control programmes in PLWH in the era of antiretroviral treatment in South Africa.

PARTICIPANTS

PLWH (both adults and children) who accessed HIV care in public sector facilities and had HIV diagnostic or monitoring laboratory tests from NHLS.

FINDINGS TO DATE

The SAM cohort currently includes 5 248 648 PLWH for the period 2004 to 2014; 69% of these are women. The median age at cohort entry was 33.0 years (IQR: 26.2-40.9). The overall cancer incidence in males and females was 235.9 (95% CI: 231.5 to 240.5) and 183.7 (181.2-186.2) per 100 000 person-years, respectively.Using data from the SAM Study, we examined national cancer incidence in PLWH and the association of different cancers with immunodeficiency. Cancers with the highest incidence rates were Kaposi sarcoma, cervix, breast, non-Hodgkin's lymphoma and eye cancer.

FUTURE PLANS

The SAM Study is a unique, evolving resource for research and surveillance of malignancies in PLWH. The SAM Study will be regularly updated. We plan to enrich the SAM Study through record linkages with other laboratory data within the NHLS (eg, tuberculosis, diabetes and lipid profile data), mortality data and socioeconomic data to facilitate comprehensive epidemiological research of comorbidities among PLWH.

Time-to-Event Analysis with Unknown Time Origins via Longitudinal Biomarker Registration

In observational studies, the time origin of interest for time-to-event analysis is often unknown, such as the time of disease onset. Existing approaches to estimating the time origins are commonly built on extrapolating a parametric longitudinal model, which rely on rigid assumptions that can lead to biased inferences. In this paper, we introduce a flexible semiparametric curve registration model. It assumes the longitudinal trajectories follow a flexible common shape function with person-specific disease progression pattern characterized by a random curve registration function, which is further used to model the unknown time origin as a random start time. This random time is used as a link to jointly model the longitudinal and survival data where the unknown time origins are integrated out in the joint likelihood function, which facilitates unbiased and consistent estimation. Since the disease progression pattern naturally predicts time-to-event, we further propose a new functional survival model using the registration function as a predictor of the time-to-event. The asymptotic consistency and semiparametric efficiency of the proposed models are proved. Simulation studies and two real data applications demonstrate the effectiveness of this new approach.

HIV genetic diversity informs stage of HIV-1 infection among patients receiving antiretroviral therapy in Botswana

Background

Human immunodeficiency virus (HIV)-1 genetic diversity increases during infection and can help infer the time elapsed since infection. However, the effect of antiretroviral treatment (ART) on the inference remains unknown.

Methods

Participants with estimated duration of HIV-1 infection based on repeated testing were sourced from cohorts in Botswana (n = 1944). Full-length HIV genome sequencing was performed from proviral deoxyribonucleic acid. We optimized a machine learning model to classify infections as < or >1 year based on viral genetic diversity, demographic, and clinical data.

Results

The best predictive model included variables for genetic diversity of HIV-1 gag, pol, and env, viral load, age, sex, and ART status. Most participants were on ART. Balanced accuracy was 90.6% (95% confidence interval, 86.7%–94.1%). We tested the algorithm among newly diagnosed participants with or without documented negative HIV tests. Among those without records, those who self-reported a negative HIV test within <1 year were more frequently classified as recent than those who reported a test >1 year previously. There was no difference in classification between those self-reporting a negative HIV test <1 year, whether or not they had a record.

Conclusions

These results indicate that recency of HIV-1 infection can be inferred from viral sequence diversity even among patients on suppressive ART.

Spatial modeling of individual-level infectious disease transmission: Tuberculosis data in Manitoba, Canada

Geographically dependent individual level models (GD-ILMs) are a class of statistical models that can be used to study the spread of infectious disease through a population in discrete-time in which covariates can be measured both at individual and area levels. The typical ILMs to illustrate spatial data are based on the distance between susceptible and infectious individuals. A key feature of GD-ILMs is that they take into account the spatial location of the individuals in addition to the distance between susceptible and infectious individuals. As a motivation of this article, we consider tuberculosis (TB) data which is an infectious disease which can be transmitted through individuals. It is also known that certain areas/demographics/communities have higher prevalent of TB (see Section 4 for more details). It is also of interest of policy makers to identify those areas with higher infectivity rate of TB for possible preventions. Therefore, we need to analyze this data properly to address those concerns. In this article, the expectation conditional maximization algorithm is proposed for estimating the parameters of GD-ILMs to be able to predict the areas with the highest average infectivity rates of TB. We also evaluate the performance of our proposed approach through some simulations. Our simulation results indicate that the proposed method provides reliable estimates of parameters which confirms accuracy of the infectivity rates.

Heritability of the HIV-1 reservoir size and decay under long-term suppressive ART

The HIV-1 reservoir is the major hurdle to curing HIV-1. However, the impact of the viral genome on the HIV-1 reservoir, i.e. its heritability, remains unknown. We investigate the heritability of the HIV-1 reservoir size and its long-term decay by analyzing the distribution of those traits on viral phylogenies from both partial-pol and viral near full-length genome sequences. We use a unique nationwide cohort of 610 well-characterized HIV-1 subtype-B infected individuals on suppressive ART for a median of 5.4 years. We find that a moderate but significant fraction of the HIV-1 reservoir size 1.5 years after the initiation of ART is explained by genetic factors. At the same time, we find more tentative evidence for the heritability of the long-term HIV-1 reservoir decay. Our findings indicate that viral genetic factors contribute to the HIV-1 reservoir size and hence the infecting HIV-1 strain may affect individual patients’ hurdle towards a cure.

The HIV reservoir is a major hurdle for a cure of HIV, but the factors determining its size and dynamics remain unclear. Here the authors show in a large cohort of 610 HIV-1 infected individuals, who are on suppressive ART for a median of 5.4 years, that viral genetic factors contribute substantially to the HIV-1 reservoir size.

Bayesian reconstruction of transmission trees from genetic sequences and uncertain infection times

Genetic sequence data of pathogens are increasingly used to investigate transmission dynamics in both endemic diseases and disease outbreaks. Such research can aid in the development of appropriate interventions and in the design of studies to evaluate them. Several computational methods have been proposed to infer transmission chains from sequence data; however, existing methods do not generally reliably reconstruct transmission trees because genetic sequence data or inferred phylogenetic trees from such data contain insufficient information for accurate estimation of transmission chains. Here, we show by simulation studies that incorporating infection times, even when they are uncertain, can greatly improve the accuracy of reconstruction of transmission trees. To achieve this improvement, we propose a Bayesian inference methods using Markov chain Monte Carlo that directly draws samples from the space of transmission trees under the assumption of complete sampling of the outbreak. The likelihood of each transmission tree is computed by a phylogenetic model by treating its internal nodes as transmission events. By a simulation study, we demonstrate that accuracy of the reconstructed transmission trees depends mainly on the amount of information available on times of infection; we show superiority of the proposed method to two alternative approaches when infection times are known up to specified degrees of certainty. In addition, we illustrate the use of a multiple imputation framework to study features of epidemic dynamics, such as the relationship between characteristics of nodes and average number of outbound edges or inbound edges, signifying possible transmission events from and to nodes. We apply the proposed method to a transmission cluster in San Diego and to a dataset from the 2014 Sierra Leone Ebola virus outbreak and investigate the impact of biological, behavioral, and demographic factors.

IL-4 polymorphism influences susceptibility to Pneumocystis jirovecii pneumonia in HIV-positive patients

OBJECTIVES

Pneumocystis jirovecii pneumonia (PJP) is an important cause of morbidity and mortality in HIV-positive patients. Polymorphisms in immune genes are increasingly reported to influence susceptibility to fungal infections. We analysed the role of 21 single nucleotide polymorphisms from 19 candidate genes on PJP development in patients from the Swiss HIV Cohort Study.

DESIGN AND METHODS

The analysis included patients with a nadir CD4 T-cell count less than 200 cells/μl, divided into a discovery (N = 1645) and a replication (N = 1861) cohort. The associations were analysed by using cumulative incidence curves as well as competing risk regression over 18 years, starting from the estimated date of HIV infection, considering death a competing risk, with censoring at lost follow-up, and assuming the dominant mode of inheritance.

RESULTS

The minor allele of rs2243250 in IL-4 was associated with the risk of PJP in the discovery cohort (cumulative incidence 0.18 versus 0.12, P = 0.002). This association was replicated in the validation cohort (0.16 versus 0.12, P = 0.02). It was still significant in multivariate models, adjusted for HIV transmission mode, viral load, CD4 T cells slope, age, antiretroviral therapy, tobacco smoking, hepatitis C virus coinfection, year of cohort entry and PJP prophylaxis (global subhazard ratio 1.42, 95% confidence interval 1.17-1.73, P = 0.0004).

CONCLUSION

Our data suggest rs2243250, a single nucleotide polymorphism known to influence IL-4 production, is associated with susceptibility to PJP in HIV-positive patients.

Determinants of HIV-1 reservoir size and long-term dynamics during suppressive ART

The HIV-1 reservoir is the major hurdle to a cure. We here evaluate viral and host characteristics associated with reservoir size and long-term dynamics in 1,057 individuals on suppressive antiretroviral therapy for a median of 5.4 years. At the population level, the reservoir decreases with diminishing differences over time, but increases in 26.6% of individuals. Viral blips and low-level viremia are significantly associated with slower reservoir decay. Initiation of ART within the first year of infection, pretreatment viral load, and ethnicity affect reservoir size, but less so long-term dynamics. Viral blips and low-level viremia are thus relevant for reservoir and cure studies.

Here, Bachmann et al. provide data on long-term dynamics of the HIV-1 reservoir in 1,057 individuals on suppressive antiretroviral therapy and show that in 26.6% of individuals the reservoir increases. Viral blips and low-level viremia are significantly associated with a slower reservoir decay.

Random effects models for estimation of the probability and time to progression of a continuous biomarker

Biomarkers play a key role in the monitoring of disease progression. The time taken for an individual to reach a biomarker exceeding or lower than a meaningful threshold is often of interest. Due to the inherent variability of biomarkers, persistence criteria are sometimes included in the definitions of progression, such that only two consecutive measurements above or below the relevant threshold signal that "true" progression has occurred. In previous work, a novel approach was developed, which allowed estimation of the time to threshold using the parameters from a linear mixed model where the residual variance was assumed to be pure measurement error. In this paper, we extend this methodology so that serial correlation can be accommodated. Assuming that the Markov property holds and applying the chain rule of probabilities, we found that the probability of progression at each timepoint can be expressed simply as the product of conditional probabilities. The methodology is applied to a cohort of HIV positive individuals, where the time to reach a CD4 count threshold is estimated. The second application we present is based on a study on abdominal aortic aneurysms, where the time taken for an individual to reach a diameter exceeding 55 mm is studied. We observed that erroneously ignoring the residual correlation when it is strong may result in substantial overestimation of the time to threshold. The estimated probability of the biomarker reaching a threshold of interest, expected time to threshold, and confidence intervals are presented for selected patients in both applications.

Interferon lambda 3/4 polymorphisms are associated with AIDS-related Kaposi's sarcoma

BACKGROUND

Kaposi's sarcoma, the most common AIDS-related cancer, represents a major public concern in resource-limited countries. Single nucleotide polymorphisms within the Interferon lambda 3/4 region (IFNL3/4) determine the expression, function of IFNL4, and influence the clinical course of an increasing number of viral infections.

OBJECTIVES

To analyze whether IFNL3/4 variants are associated with susceptibility to AIDS-related Kaposi's sarcoma among MSM enrolled in the Swiss HIV Cohort Study (SHCS).

METHODS

The risk of developing Kaposi's sarcoma according to the carriage of IFNL3/4 SNPs rs8099917 and rs12980275 and their haplotypic combinations was assessed by using cumulative incidence curves and Cox regression models, accounting for relevant covariables.

RESULTS

Kaposi's sarcoma was diagnosed in 221 of 2558 MSM Caucasian SHCS participants. Both rs12980275 and rs8099917 were associated with an increased risk of Kaposi's sarcoma (cumulative incidence 15 versus 10%, P = 0.01 and 16 versus 10%, P = 0.009, respectively). Diplotypes predicted to produce the active P70 form (cumulative incidence 16 versus 10%, P = 0.01) but not the less active S70 (cumulative incidence 11 versus 10%, P = 0.7) form of IFNL4 were associated with an increased risk of Kaposi's sarcoma, compared with those predicted not to produce IFNL4. The associations remained significant in a multivariate Cox regression model after adjustment for age at infection, combination antiretroviral therapy, median CD4+ T-cell count nadir and CD4+ slopes (hazard ratio 1.42, 95% confidence interval 1.06-1.89, P = 0.02 for IFLN P70 versus no IFNL4).

CONCLUSION

This study reports for the first time an association between IFNL3/4 polymorphisms and susceptibility to AIDS-related Kaposi's sarcoma.

HIV-1 Viral Loads Are Not Elevated in Individuals Co-infected With Schistosoma spp. After Adjustment for Duration of HIV-1 Infection

Studies of the role of Schistosoma co-infections on plasma HIV-1 RNA (HIV-1 viral load) have yielded incongruent results. The role of duration of HIV-1 infection on the link between Schistosoma and HIV-1 viral load has not been previously investigated. We aimed to assess the impact of HIV-1/Schistosoma co-infections on viral load in Antiretroviral Treatment (ART)-naïve HIV-1 infected people taking into account the duration of HIV-1 infection. We describe 79 HIV-infected outpatients greater than 18 years of age who had never used ART in Mwanza, Tanzania. Schistosomiasis testing was done by urine and stool microscopy and by serum Schistosoma circulating anodic antigen (CAA) testing. Schistosoma positivity was defined as having either test positive. We conducted univariable and multivariable linear regressions to assess the relationship between Schistosoma infection and the log₁₀ of viral load. Duration of HIV infection was calculated using the first measured CD4⁺ T-cell (CD4) count as a function of normal CD4 count decay per calendar year in drug naïve individuals. An active Schistosoma infection was demonstrated in 46.8% of the patients. The median log₁₀ viral load was 4.5[3.4–4.9] log₁₀ copies/mL in Schistosoma uninfected patients and 4.3[3.7–4.6] log₁₀ copies/mL in Schistosoma infected patients. Schistosoma co-infection was negatively associated with the log₁₀ of viral load after adjustment for Schistosoma intensity as measured by CAA, CD4 counts at time of testing, and duration of HIV-1 infection (β = −0.7[−1.3;−0.1], p = 0.022). Schistosoma co-infection was not associated with viral load in univariable analysis. There was also no interaction between Schistosoma positivity and duration of HIV-1 infection. Our study is the first, to our knowledge, to report adjustment for duration of HIV-1 infection when analyzing the relationship between HIV-1 viral load and Schistosoma spp. We found that time infected with HIV-1 has a major effect on the relationship between HIV-1 viral load and Schistosoma infection and may be a critical explanatory factor in the disparate findings of studies on HIV-1 viral load and schistosomiasis. The log₁₀ viral load difference found indicates that Schistosoma co-infection does not make HIV progression worse, and could possibly lead to slower HIV disease progression.

Modelling disease progression in relapsing-remitting onset multiple sclerosis using multilevel models applied to longitudinal data from two natural history cohorts and one treated cohort

BACKGROUND

The ability to better predict disease progression represents a major unmet need in multiple sclerosis (MS), and would help to inform therapeutic and management choices.

OBJECTIVES

To develop multilevel models using longitudinal data on disease progression in patients with relapsing-remitting MS (RRMS) or secondary-progressive MS (SPMS); and to use these models to estimate the association of disease-modifying therapy (DMT) with progression.

DESIGN

Secondary analysis of three MS cohorts.

SETTING

Two natural history cohorts: University of Wales Multiple Sclerosis (UoWMS) cohort, UK, and British Columbia Multiple Sclerosis (BCMS) cohort, Canada. One observational DMT-treated cohort: UK MS risk-sharing scheme (RSS).

PARTICIPANTS

The UoWMS database has > 2000 MS patients and the BCMS database (as of 2009) has > 5900 MS patients. All participants who had definite MS (RRMS/SPMS), who reached the criteria set out by the Association of British Neurologists (ABN) for eligibility for DMT [i.e. age ≥ 18 years, Expanded Disability Status Scale (EDSS) score of ≤ 6.5, occurrence of two or more relapses in the previous 2 years] and who had at least two repeated outcome measures were included: 404 patients for the UoWMS cohort and 978 patients for the BCMS cohort. Through the UK MS RSS scheme, 5583 DMT-treated patients were recruited, with the analysis sample being the 4137 who had RRMS and were eligible and treated at baseline, with at least one valid EDSS score post baseline.

MAIN OUTCOME MEASURES

EDSS score observations post ABN eligibility.

METHODS

We used multilevel models in the development cohort (UoWMS) to develop a model for EDSS score with time since ABN eligibility, allowing for covariates and appropriate transformation of outcome and/or time. These methods were then applied to the BCMS cohort to obtain a 'natural history' model for changes in the EDSS score with time. We then used this natural history model to predict the trajectories of EDSS score in treated patients in the UK MS RSS database. Differences between the progression predicted by the natural history model and the progression observed at 6 years' follow-up for the UK MS RSS cohort were used as indicators of the effectiveness of the DMTs. Previously developed utility scores were assigned to each EDSS score, and differences in utility also examined.

RESULTS

The model best fitting the UoWMS data showed a non-linear increase in EDSS score over time since ABN eligibility. This model fitted the BCMS cohort data well, with similar coefficients, and the BCMS model predicted EDSS score in UoWMS data with little evidence of bias. Using the natural history model predicts EDSS score in a treated cohort (UK MS RSS) higher than that observed [by 0.59 points (95% confidence interval 0.54 to 0.64 points)] at 6 years post treatment.

LIMITATIONS

Only two natural history cohorts were compared, limiting generalisability. The comparison of a treated cohort with untreated cohorts is observational, thus limiting conclusions about causality.

CONCLUSIONS

EDSS score progression in two natural history cohorts of MS patients showed a similar pattern. Progression in the natural history cohorts was slightly faster than EDSS score progression in the DMT-treated cohort, up to 6 years post treatment.

FUTURE WORK

Long-term follow-up of randomised controlled trials is needed to replicate these findings and examine duration of any treatment effect.

FUNDING DETAILS

The National Institute for Health Research Health Technology Assessment programme.

Assessing the danger of self-sustained HIV epidemics in heterosexuals by population based phylogenetic cluster analysis

Assessing the danger of transition of HIV transmission from a concentrated to a generalized epidemic is of major importance for public health. In this study, we develop a phylogeny-based statistical approach to address this question. As a case study, we use this to investigate the trends and determinants of HIV transmission among Swiss heterosexuals. We extract the corresponding transmission clusters from a phylogenetic tree. To capture the incomplete sampling, the delayed introduction of imported infections to Switzerland, and potential factors associated with basic reproductive number R0, we extend the branching process model to infer transmission parameters. Overall, the R0 is estimated to be 0.44 (95%-confidence interval 0.42—0.46) and it is decreasing by 11% per 10 years (4%—17%). Our findings indicate rather diminishing HIV transmission among Swiss heterosexuals far below the epidemic threshold. Generally, our approach allows to assess the danger of self-sustained epidemics from any viral sequence data.

In epidemiology, the “basic reproductive number” describes how efficiently a disease is transmitted, and represents the average number of new infections that an infected individual causes. If this number is less than one, many people do not infect anybody and hence the transmission chains die out. On the other hand, if the basic reproductive number is larger than one, an infected person infects on average more than one new individual, which leads to the virus or bacteria spreading in a self-sustained way.

Turk et al. have now developed a method to estimate the basic reproductive number using the genetic sequences of the virus or bacteria, and have used it to investigate how efficiently HIV spreads among Swiss heterosexuals. The results show that the basic reproductive number of HIV in this group is far below the critical value of one and that over the last years this number has been decreasing. Furthermore, the basic reproductive number differs for different subtypes of the HIV virus, indicating that the geographical region where the infection was acquired may play a role in transmission. Turk et al. also found that people who are diagnosed later or who often have sex with occasional partners spread the virus more efficiently.

These findings might be helpful for policy makers as they indicate that the risk of self-sustained transmission in this group in Switzerland is small. Furthermore the method allows HIV epidemics to be monitored at high resolution using sequence data, assesses the success of currently implemented preventive measures, and helps to target subgroups who are at higher risk of an infection – for instance, by supporting frequent HIV testing of these people. The method developed by Turk et al. could also prove useful for assessing the danger of other epidemics.

Impact of screening and antiretroviral therapy on anal cancer incidence in HIV-positive MSM

BACKGROUND

The incidence of anal cancer is high in HIV-positive MSM. We modeled the impact of screening strategies and combination antiretroviral therapy (cART) coverage on anal cancer incidence in Switzerland.

METHODS

Individual-based, dynamic simulation model parameterized with Swiss HIV Cohort Study and literature data. We assumed all men to be human papillomavirus infected. CD4 cell count trajectories were the main predictors of anal cancer. From 2016 we modeled cART coverage either as below 100% (corresponding to 2010-2015) or as 100%, and the following four screening strategies: no screening, yearly anal cytology (Papanicolaou smears), yearly anoscopy and targeted anoscopy 5 years after CD4 count dropped below 200 cells/μl.

RESULTS

Median nadir CD4 cell count of 6411 MSM increased from 229 cells/μl during 1980-1989 to 394 cells/μl during 2010-2015; cART coverage increased from 0 to 83.4%. Modeled anal cancer incidence peaked at 81.7/100 000 in 2009, plateaued 2010-2015 and will decrease to 58.7 by 2030 with stable cART coverage, and to 52.0 with 100% cART coverage. With yearly cytology, incidence declined to 38.2/100 000 by 2030, with yearly anoscopy to 32.8 and with CD4 cell count guided anoscopy to 51.3. The numbers needed to screen over 15 years to prevent one anal cancer case were 384 for yearly cytology, 313 for yearly anoscopy and 242 for CD4 cell count-dependent screening.

CONCLUSION

Yearly screening of HIV-positive MSM may reduce anal cancer incidence substantially, with a number needed to screen that is comparable with other screening interventions to prevent cancer.

CD4/CD8 ratio and CD8 counts predict CD4 response in HIV-1-infected drug naive and in patients on cART

Plasma HIV viral load is related to declining CD4 lymphocytes. The extent to which CD8 cells, in addition to RNA viral load, predict the depletion of CD4 cells is not well characterized so far. We examine if CD8 cell count is a prognostic factor for CD4 cell counts during an HIV infection.A longitudinal analysis is conducted using data from the Swiss HIV cohort study collected between January 2000 and October 2014. Linear mixed regression models were applied to observations from HIV-1-infected treatment naive patients (NAIVE) and cART-treated patients to predict the short-term evolution of CD4 cell counts. For each subgroup, it was quantified to which extent CD8 cell counts or CD4/CD8 ratios are prognostic factors for disease progression.In both subgroups, 2500 NAIVE and 8902 cART patients, past CD4 cells are positively (P < 0.0001) and past viral load is negatively (P < 0.0001) associated with the outcome. Including additionally past CD8 cell counts improves the fit significantly (P < 0.0001) and increases the marginal explained variation 31.7% to 40.7% for the NAIVE and from 44.1% to 50.7% for the cART group. The past CD4/CD8 ratio (instead of the past CD8 level) is positively associated with the outcome, increasing the explained variation further to 41.8% for NAIVE and 51.9% for cART.

Determinants of HIV-1 broadly neutralizing antibody induction

Broadly neutralizing antibodies (bnAbs) are a focal component of HIV-1 vaccine design, yet basic aspects of their induction remain poorly understood. Here we report on viral, host and disease factors that steer bnAb evolution using the results of a systematic survey in 4,484 HIV-1-infected individuals that identified 239 bnAb inducers. We show that three parameters that reflect the exposure to antigen-viral load, length of untreated infection and viral diversity-independently drive bnAb evolution. Notably, black participants showed significantly (P = 0.0086-0.038) higher rates of bnAb induction than white participants. Neutralization fingerprint analysis, which was used to delineate plasma specificity, identified strong virus subtype dependencies, with higher frequencies of CD4-binding-site bnAbs in infection with subtype B viruses (P = 0.02) and higher frequencies of V2-glycan-specific bnAbs in infection with non-subtype B viruses (P = 1 × 10^-5). Thus, key host, disease and viral determinants, including subtype-specific envelope features that determine bnAb specificity, remain to be unraveled and harnessed for bnAb-based vaccine design.

A novel approach to estimation of the time to biomarker threshold: applications to HIV

In longitudinal studies of biomarkers, an outcome of interest is the time at which a biomarker reaches a particular threshold. The CD4 count is a widely used marker of human immunodeficiency virus progression. Because of the inherent variability of this marker, a single CD4 count below a relevant threshold should be interpreted with caution. Several studies have applied persistence criteria, designating the outcome as the time to the occurrence of two consecutive measurements less than the threshold. In this paper, we propose a method to estimate the time to attainment of two consecutive CD4 counts less than a meaningful threshold, which takes into account the patient-specific trajectory and measurement error. An expression for the expected time to threshold is presented, which is a function of the fixed effects, random effects and residual variance. We present an application to human immunodeficiency virus-positive individuals from a seroprevalent cohort in Durban, South Africa. Two thresholds are examined, and 95% bootstrap confidence intervals are presented for the estimated time to threshold. Sensitivity analysis revealed that results are robust to truncation of the series and variation in the number of visits considered for most patients. Caution should be exercised when interpreting the estimated times for patients who exhibit very slow rates of decline and patients who have less than three measurements. We also discuss the relevance of the methodology to the study of other diseases and present such applications. We demonstrate that the method proposed is computationally efficient and offers more flexibility than existing frameworks. Copyright © 2016 John Wiley & Sons, Ltd.

Estimation of the Undiagnosed Intervals of HIV-Infected Individuals by a Modified Back-Calculation Method for Reconstructing the Epidemic Curves

Background

Undiagnosed infections accounted for the hidden proportion of HIV cases that have escaped from public health surveillance. To assess the population risk of HIV transmission, we estimated the undiagnosed interval of each known infection for constructing the HIV incidence curves.

Methods

We used modified back-calculation methods to estimate the seroconversion year for each diagnosed patient attending any one of the 3 HIV specialist clinics in Hong Kong. Three approaches were used, depending on the adequacy of CD4 data: (A) estimating one’s pre-treatment CD4 depletion rate in multilevel model;(B) projecting one’s seroconversion year by referencing seroconverters’ CD4 depletion rate; or (C) projecting from the distribution of estimated undiagnosed intervals in (B). Factors associated with long undiagnosed interval (>2 years) were examined in univariate analyses. Epidemic curves constructed from estimated seroconversion data were evaluated by modes of transmission.

Results

Between 1991 and 2010, a total of 3695 adult HIV patients were diagnosed. The undiagnosed intervals were derived from method (A) (28%), (B) (61%) and (C) (11%) respectively. The intervals ranged from 0 to 10 years, and were shortened from 2001. Heterosexual infection, female, Chinese and age >64 at diagnosis were associated with long undiagnosed interval. Overall, the peaks of the new incidence curves were reached 4–6 years ahead of reported diagnoses, while their contours varied by mode of transmission. Characteristically, the epidemic growth of heterosexual male and female declined after 1998 with slight rebound in 2004–2006, but that of MSM continued to rise after 1998.

Conclusions

By determining the time of seroconversion, HIV epidemic curves could be reconstructed from clinical data to better illustrate the trends of new infections. With the increasing coverage of antiretroviral therapy, the undiagnosed interval can add to the measures for assessing HIV transmission risk in the population.

A Bayesian hierarchical model with novel prior specifications for estimating HIV testing rates

Human immunodeficiency virus (HIV) infection is a severe infectious disease actively spreading globally, and acquired immunodeficiency syndrome (AIDS) is an advanced stage of HIV infection. The HIV testing rate, that is, the probability that an AIDS-free HIV infected person seeks a test for HIV during a particular time interval, given no previous positive test has been obtained prior to the start of the time, is an important parameter for public health. In this paper, we propose a Bayesian hierarchical model with two levels of hierarchy to estimate the HIV testing rate using annual AIDS and AIDS-free HIV diagnoses data. At level one, we model the latent number of HIV infections for each year using a Poisson distribution with the intensity parameter representing the HIV incidence rate. At level two, the annual numbers of AIDS and AIDS-free HIV diagnosed cases and all undiagnosed cases stratified by the HIV infections at different years are modeled using a multinomial distribution with parameters including the HIV testing rate. We propose a new class of priors for the HIV incidence rate and HIV testing rate taking into account the temporal dependence of these parameters to improve the estimation accuracy. We develop an efficient posterior computation algorithm based on the adaptive rejection metropolis sampling technique. We demonstrate our model using simulation studies and the analysis of the national HIV surveillance data in the USA.

Correlating HIV tropism with immunological response under combination antiretroviral therapy

OBJECTIVES

A significant percentage of patients infected with HIV-1 experience only suboptimal CD4 cell recovery while treated with combination therapy (cART). It is still unclear whether viral properties such as cell tropism play a major role in this incomplete immune response. This study therefore intended to follow the tropism evolution of the HIV-1 envelope during periods of suppressive cART.

METHODS

Viruses from two distinct patient groups, one with good and another one with poor CD4 recovery after 5 years of suppressive cART, were genotypically analysed for viral tropism at baseline and at the end of the study period.

RESULTS

Patients with CCR5-tropic CC-motif chemokine receptor 5 viruses at baseline tended to maintain this tropism to the study end. Patients who had a CXCR4-tropic CXC-motif chemokine receptor 4 virus at baseline were overrepresented in the poor CD4 recovery group. Overall, however, the majority of patients presented with CCR5-tropic viruses at follow-up.

CONCLUSIONS

Our data lend support to the hypothesis that tropism determination can be used as a parameter for disease progression even if analysed long before the establishment of a poorer immune response. Moreover, the lasting predominating CCR5-tropism during periods of full viral control suggests the involvement of cellular mechanisms that preferentially reduce CXCR4-tropic viruses during cART.

The impact of vaccination on the breadth and magnitude of the antibody response to influenza A viruses in HIV-infected individuals

OBJECTIVE

HIV-positive individuals have lower antibody titers to influenza viruses than HIV-negative individuals, and the benefits of the annual vaccinations are controversially discussed. Also, there is no information about the breadth of the antibody response in HIV-infected individuals.

DESIGN

The binding and neutralizing antibody titers to various human and nonhuman influenza A virus strain were determined in sera from 146 HIV-infected volunteers: They were compared with those found in 305 randomly selected HIV-negative donors, and put in relation to HIV-specific parameters. Univariable and multivariable regression was used to identify HIV-specific parameters associated with the measured binding and neutralizing activity.

METHODS

Enzyme-linked immunosorbent assays and in-vitro neutralization assays were used to determine the binding and neutralizing antibodiy titers to homo and heterosubtypic influenza A subtypes.

RESULTS

We found that both homo and heterosubtypic antibody titers are lower in HIV-positive individuals. Vaccination promoted higher binding and neutralizing antibody titers to human but not to nonhuman isolates. HIV-induced immune damage (high viral load, low CD4 T-cell counts, and long untreated disease progression) is associated with impaired homosubtypic responses, but can have beneficial effects on the development of heterosubtypic antibodies, and an improved ratio of binding to neutralizing antibody titers to homosubtypic isolates.

CONCLUSIONS

Our results indicate that repetitive vaccinations in HIV-positive individuals enhance antibody titers to human isolates. Interestingly, development of antibody titers to conserved heterosubtypic epitopes paradoxically appeared to profit from HIV-induced immune damage, as did the ratio of binding to neutralizing antibodies.

Incorporation of Estimated Community Viral Load Before HIV Diagnosis for Enhancing Epidemiologic Investigations: A Comparison Between Men Who Have Sex With Men and Heterosexual Men in Hong Kong

Currently, no studies have specifically incorporated population-level viral load measures for analyzing temporal trends of HIV infection in the Asia Pacific. With the use of longitudinal data from 950 HIV-infected heterosexual male and 1331 men who have sex with men managed at a major HIV clinic in Hong Kong between 1985 and 2012, viral load changes at population levels were compared. We back-calculated seroconversion year of each diagnosed patient and estimated the population-level viral load under the framework recommended by the Centers for Disease Control and Prevention. Full community viral load, a newly designed measure incorporating diagnosed and undiagnosed HIV-infected patients, was 3 to 8 times higher than community viral load derived from diagnosed patients only. The growth curve of full community viral load was 5 years ahead of other viral load measures, the shape of which lent support to the phenomenon of local transmission of men who have sex with men but not among heterosexual male in the predominantly Chinese HIV community in Hong Kong.

Limited clinical benefit of minority K103N and Y181C-variant detection in addition to routine genotypic resistance testing in antiretroviral therapy-naive patients

OBJECTIVE

The presence of minority nonnucleoside reverse transcriptase inhibitor (NNRTI)-resistant HIV-1 variants prior to antiretroviral therapy (ART) has been linked to virologic failure in treatment-naive patients.

DESIGN

We performed a large retrospective study to determine the number of treatment failures that could have been prevented by implementing minority drug-resistant HIV-1 variant analyses in ART-naïve patients in whom no NNRTI resistance mutations were detected by routine resistance testing.

METHODS

Of 1608 patients in the Swiss HIV Cohort Study, who have initiated first-line ART with two nucleoside reverse transcriptase inhibitors (NRTIs) and one NNRTI before July 2008, 519 patients were eligible by means of HIV-1 subtype, viral load and sample availability. Key NNRTI drug resistance mutations K103N and Y181C were measured by allele-specific PCR in 208 of 519 randomly chosen patients.

RESULTS

Minority K103N and Y181C drug resistance mutations were detected in five out of 190 (2.6%) and 10 out of 201 (5%) patients, respectively. Focusing on 183 patients for whom virologic success or failure could be examined, virologic failure occurred in seven out of 183 (3.8%) patients; minority K103N and/or Y181C variants were present prior to ART initiation in only two of those patients. The NNRTI-containing, first-line ART was effective in 10 patients with preexisting minority NNRTI-resistant HIV-1 variant.

CONCLUSION

As revealed in settings of case-control studies, minority NNRTI-resistant HIV-1 variants can have an impact on ART. However, the implementation of minority NNRTI-resistant HIV-1 variant analysis in addition to genotypic resistance testing (GRT) cannot be recommended in routine clinical settings. Additional associated risk factors need to be discovered.

The IFNL3/4 ΔG variant increases susceptibility to cytomegalovirus retinitis among HIV-infected patients

BACKGROUND

Cytomegalovirus (CMV) retinitis is a major cause of visual impairment and blindness among patients with uncontrolled HIV infections. Whereas polymorphisms in interferon-lambda 3 (IFNL3, previously named IL28B) strongly influence the clinical course of hepatitis C, few studies examined the role of such polymorphisms in infections due to viruses other than hepatitis C virus.

OBJECTIVES

To analyze the association of newly identified IFNL3/4 variant rs368234815 with susceptibility to CMV-associated retinitis in a cohort of HIV-infected patients.

DESIGN AND METHODS

This retrospective longitudinal study included 4884 white patients from the Swiss HIV Cohort Study, among whom 1134 were at risk to develop CMV retinitis (CD4 nadir < 00 /μl and positive CMV serology). The association of CMV-associated retinitis with rs368234815 was assessed by cumulative incidence curves and multivariate Cox regression models, using the estimated date of HIV infection as a starting point, with censoring at death and/or lost follow-up.

RESULTS

A total of 40 individuals among 1134 patients at risk developed CMV retinitis. The minor allele of rs368234815 was associated with a higher risk of CMV retinitis (log-rank test P = 0.007, recessive mode of inheritance). The association was still significant in a multivariate Cox regression model (hazard ratio 2.31, 95% confidence interval 1.09-4.92, P = 0.03), after adjustment for CD4 nadir and slope, HAART and HIV-risk groups.

CONCLUSION

We reported for the first time an association between an IFNL3/4 polymorphism and susceptibility to AIDS-related CMV retinitis. IFNL3/4 may influence immunity against viruses other than HCV.

Treatment-naive individuals are the major source of transmitted HIV-1 drug resistance in men who have sex with men in the Swiss HIV Cohort Study

BACKGROUND

Human immunodeficiency virus type 1 (HIV-1) transmitted drug resistance (TDR) can compromise antiretroviral therapy (ART) and thus represents an important public health concern. Typically, sources of TDR remain unknown, but they can be characterized with molecular epidemiologic approaches. We used the highly representative Swiss HIV Cohort Study (SHCS) and linked drug resistance database (SHCS-DRDB) to analyze sources of TDR.

METHODS

ART-naive men who have sex with men with infection date estimates between 1996 and 2009 were chosen for surveillance of TDR in HIV-1 subtype B (N = 1674), as the SHCS-DRDB contains pre-ART genotypic resistance tests for >69% of this surveillance population. A phylogeny was inferred using pol sequences from surveillance patients and all subtype B sequences from the SHCS-DRDB (6934 additional patients). Potential sources of TDR were identified based on phylogenetic clustering, shared resistance mutations, genetic distance, and estimated infection dates.

RESULTS

One hundred forty of 1674 (8.4%) surveillance patients carried virus with TDR; 86 of 140 (61.4%) were assigned to clusters. Potential sources of TDR were found for 50 of 86 (58.1%) of these patients. ART-naive patients constitute 56 of 66 (84.8%) potential sources and were significantly overrepresented among sources (odds ratio, 6.43 [95% confidence interval, 3.22-12.82]; P < .001). Particularly large transmission clusters were observed for the L90M mutation, and the spread of L90M continued even after the near cessation of antiretroviral use selecting for that mutation. Three clusters showed evidence of reversion of K103N or T215Y/F.

CONCLUSIONS

Many individuals harboring viral TDR belonged to transmission clusters with other Swiss patients, indicating substantial domestic transmission of TDR in Switzerland. Most TDR in clusters could be linked to sources, indicating good surveillance of TDR in the SHCS-DRDB. Most TDR sources were ART naive. This, and the presence of long TDR transmission chains, suggests that resistance mutations are frequently transmitted among untreated individuals, highlighting the importance of early diagnosis and treatment.

Correcting for exposure misclassification using survival analysis with a time-varying exposure

PURPOSE

Survival analysis is increasingly being used in perinatal epidemiology to assess time-varying risk factors for various pregnancy outcomes. Here we show how quantitative correction for exposure misclassification can be applied to a Cox regression model with a time-varying dichotomous exposure.

METHODS

We evaluated influenza vaccination during pregnancy in relation to preterm birth among 2267 non-malformed infants whose mothers were interviewed as part of the Slone Birth Defects Study during 2006 through 2011. The hazard of preterm birth was modeled using a time-varying exposure Cox regression model with gestational age as the time-scale. The effect of exposure misclassification was then modeled using a probabilistic bias analysis that incorporated vaccination date assignment. The parameters for the bias analysis were derived from both internal and external validation data.

RESULTS

Correction for misclassification of prenatal influenza vaccination resulted in an adjusted hazard ratio (AHR) slightly higher and less precise than the conventional analysis: Bias-corrected AHR 1.04 (95% simulation interval, 0.70-1.52); conventional AHR, 1.00 (95% confidence interval, 0.71-1.41).

CONCLUSIONS

Probabilistic bias analysis allows epidemiologists to assess quantitatively the possible confounder-adjusted effect of misclassification of a time-varying exposure, in contrast with a speculative approach to understanding information bias.

Is back-projection methodology still relevant for estimating HIV incidence from national surveillance data?

Accurate estimates of HIV incidence are crucial to understand the extent of transmission of the infection, evaluate intervention strategies and effectively plan new public health control measures. HIV/AIDS surveillance systems in numerous industrialised countries record the number of known new HIV and/or AIDS diagnoses, which are often used as a surrogate marker for HIV incidence. HIV/AIDS diagnosis data have been used to reconstruct historical HIV incidence trends using modified back-projection methods. Estimates of HIV incidence are most robust when reliable data on the number of incident infections, a subset of all diagnoses, is widely available, and surveillance systems should prioritise the collection of these data. Back-projection alone provides reliable estimates of HIV incidence in the past, but is not useful when estimating current or future HIV incidence. However, back-projection methodology should be used in conjunction with other corroborative methods to estimate current HIV incidence, and methods to combine the various techniques should be investigated.

Simple epidemiological dynamics explain phylogenetic clustering of HIV from patients with recent infection

Phylogenies of highly genetically variable viruses such as HIV-1 are potentially informative of epidemiological dynamics. Several studies have demonstrated the presence of clusters of highly related HIV-1 sequences, particularly among recently HIV-infected individuals, which have been used to argue for a high transmission rate during acute infection. Using a large set of HIV-1 subtype B pol sequences collected from men who have sex with men, we demonstrate that virus from recent infections tend to be phylogenetically clustered at a greater rate than virus from patients with chronic infection ('excess clustering') and also tend to cluster with other recent HIV infections rather than chronic, established infections ('excess co-clustering'), consistent with previous reports. To determine the role that a higher infectivity during acute infection may play in excess clustering and co-clustering, we developed a simple model of HIV infection that incorporates an early period of intensified transmission, and explicitly considers the dynamics of phylogenetic clusters alongside the dynamics of acute and chronic infected cases. We explored the potential for clustering statistics to be used for inference of acute stage transmission rates and found that no single statistic explains very much variance in parameters controlling acute stage transmission rates. We demonstrate that high transmission rates during the acute stage is not the main cause of excess clustering of virus from patients with early/acute infection compared to chronic infection, which may simply reflect the shorter time since transmission in acute infection. Higher transmission during acute infection can result in excess co-clustering of sequences, while the extent of clustering observed is most sensitive to the fraction of infections sampled.

Role of retroviral restriction factors in the interferon-α-mediated suppression of HIV-1 in vivo

The antiviral potency of the cytokine IFN-α has been long appreciated but remains poorly understood. A number of studies have suggested that induction of the apolipoprotein B mRNA editing enzyme, catalytic polypeptide 3 (APOBEC3) and bone marrow stromal cell antigen 2 (BST-2/tetherin/CD317) retroviral restriction factors underlies the IFN-α-mediated suppression of HIV-1 replication in vitro. We sought to characterize the as-yet-undefined relationship between IFN-α treatment, retroviral restriction factors, and HIV-1 in vivo. APOBEC3G, APOBEC3F, and BST-2 expression levels were measured in HIV/hepatitis C virus (HCV)-coinfected, antiretroviral therapy-naïve individuals before, during, and after pegylated IFN-α/ribavirin (IFN-α/riba) combination therapy. IFN-α/riba therapy decreased HIV-1 viral load by -0.921 (±0.858) log(10) copies/mL in HIV/HCV-coinfected patients. APOBEC3G/3F and BST-2 mRNA expression was significantly elevated during IFN-α/riba treatment in patient-derived CD4+ T cells (P < 0.04 and P < 0.008, paired Wilcoxon), and extent of BST-2 induction was correlated with reduction in HIV-1 viral load during treatment (P < 0.05, Pearson's r). APOBEC3 induction during treatment was correlated with degree of viral hypermutation (P < 0.03, Spearman's ρ), and evolution of the HIV-1 accessory protein viral protein U (Vpu) during IFN-α/riba treatment was suggestive of increased BST-2-mediated selection pressure. These data suggest that host restriction factors play a critical role in the antiretroviral capacity of IFN-α in vivo, and warrant investigation into therapeutic strategies that specifically enhance the expression of these intrinsic immune factors in HIV-1-infected individuals.

Dates of HIV infection can be estimated for seroprevalent patients by coalescent analysis of serial next-generation sequencing data

OBJECTIVE

To reconstruct dates of HIV infection by the coalescent analysis of longitudinal next-generation sequencing (NGS) data.

DESIGN

The coalescent predicts the time that has elapsed since the most recent common ancestor (MRCA) of a population. Because HIV tends to undergo severe bottlenecks upon transmission, the MRCA may be a good predictor of the time of infection. NGS provides an efficient means for performing large-scale clonal sequencing of HIV populations within patients, and the ideal raw material for coalescent analysis.

METHODS

Baseline and follow-up plasma samples were obtained from 19 individuals enrolled into the Montréal Primary HIV Infection cohort. Dates of infection were initially estimated at baseline from nongenetic data (clinical and serological markers and patient questionnaires). HIV RNA was extracted and seven regions of the genome were amplified, subjected to parallel-tagged 454 pyrosequencing, and analyzed using the software package BEAST.

RESULTS

Mean estimates of the time to the MRCA per patient were significantly correlated with nongenetic estimates (Spearman's ρ = 0.65, P = 4.4 × 10(-3)). The median absolute difference between coalescent and nongenetic date estimates was smallest (median 29.4 days) for highly variable regions of the HIV genome such as env V3, and greater (median 114.9 days) for more conserved regions such as pol.

CONCLUSION

This application of NGS represents an important advancement, not only because accurate estimates of dates of infection can be derived retrospectively from archived specimens, but also because each analysis is patient-specific and, therefore, robust to variation in rates of HIV evolution.

Imputation of the Date of HIV Seroconversion in a Cohort of Seroprevalent Subjects: Implications for Analysis of Late HIV Diagnosis

Objectives. Since subjects may have been diagnosed before cohort entry, analysis of late HIV diagnosis (LD) is usually restricted to the newly diagnosed. We estimate the magnitude and risk factors of LD in a cohort of seroprevalent individuals by imputing seroconversion dates. Methods. Multicenter cohort of HIV-positive subjects who were treatment naive at entry, in Spain, 2004–2008. Multiple-imputation techniques were used. Subjects with times to HIV diagnosis longer than 4.19 years were considered LD. Results. Median time to HIV diagnosis was 2.8 years in the whole cohort of 3,667 subjects. Factors significantly associated with LD were: male sex; Sub-Saharan African, Latin-American origin compared to Spaniards; and older age. In 2,928 newly diagnosed subjects, median time to diagnosis was 3.3 years, and LD was more common in injecting drug users. Conclusions. Estimates of the magnitude and risk factors of LD for the whole cohort differ from those obtained for new HIV diagnoses.

Morbidity and aging in HIV-infected persons: the Swiss HIV cohort study

BACKGROUND

Patterns of morbidity and mortality among human immunodeficiency virus (HIV)-infected individuals taking antiretroviral therapy are changing as a result of immune reconstitution and improved survival. We studied the influence of aging on the epidemiology of non-AIDS diseases in the Swiss HIV Cohort Study.

METHODS

The Swiss HIV Cohort Study is a prospective observational cohort established in 1988 with continuous enrollment. We determined the incidence of clinical events (per 1000 person-years) from January 2008 (when a new questionnaire on non-AIDS-related morbidity was introduced) through December 2010. Differences across age groups were analyzed using Cox regression, adjusted for CD4 cell count, viral load, sex, injection drug use, smoking, and years of HIV infection.

RESULTS

Overall, 8444 (96%) of 8848 participants contributed data from 40,720 semiannual visits; 2233 individuals (26.4%) were aged 50-64 years, and 450 (5.3%) were aged ≥65 years. The median duration of HIV infection was 15.4 years (95% confidence interval [CI], 9.59-22.0 years); 23.2% had prior clinical AIDS. We observed 994 incident non-AIDS events in the reference period: 201 cases of bacterial pneumonia, 55 myocardial infarctions, 39 strokes, 70 cases of diabetes mellitus, 123 trauma-associated fractures, 37 fractures without adequate trauma, and 115 non-AIDS malignancies. Multivariable hazard ratios for stroke (17.7; CI, 7.06-44.5), myocardial infarction (5.89; 95% CI, 2.17-16.0), diabetes mellitus (3.75; 95% CI, 1.80-7.85), bone fractures without adequate trauma (10.5; 95% CI, 3.58-30.5), osteoporosis (9.13; 95% CI, 4.10-20.3), and non-AIDS-defining malignancies (6.88; 95% CI, 3.89-12.2) were elevated for persons aged ≥65 years.

CONCLUSIONS

Comorbidity and multimorbidity because of non-AIDS diseases, particularly diabetes mellitus, cardiovascular disease, non-AIDS-defining malignancies, and osteoporosis, become more important in care of HIV-infected persons and increase with older age.

Development and validation of decision rules to guide frequency of monitoring CD4 cell count in HIV-1 infection before starting antiretroviral therapy

Background

Although CD4 cell count monitoring is used to decide when to start antiretroviral therapy in patients with HIV-1 infection, there are no evidence-based recommendations regarding its optimal frequency. It is common practice to monitor every 3 to 6 months, often coupled with viral load monitoring. We developed rules to guide frequency of CD4 cell count monitoring in HIV infection before starting antiretroviral therapy, which we validated retrospectively in patients from the Swiss HIV Cohort Study.

Methodology/Principal Findings

We built up two prediction rules (“Snap-shot rule” for a single sample and “Track-shot rule” for multiple determinations) based on a systematic review of published longitudinal analyses of CD4 cell count trajectories. We applied the rules in 2608 untreated patients to classify their 18 061 CD4 counts as either justifiable or superfluous, according to their prior ≥5% or <5% chance of meeting predetermined thresholds for starting treatment. The percentage of measurements that both rules falsely deemed superfluous never exceeded 5%. Superfluous CD4 determinations represented 4%, 11%, and 39% of all actual determinations for treatment thresholds of 500, 350, and 200×10⁶/L, respectively. The Track-shot rule was only marginally superior to the Snap-shot rule. Both rules lose usefulness for CD4 counts coming near to treatment threshold.

Conclusions/Significance

Frequent CD4 count monitoring of patients with CD4 counts well above the threshold for initiating therapy is unlikely to identify patients who require therapy. It appears sufficient to measure CD4 cell count 1 year after a count >650 for a threshold of 200, >900 for 350, or >1150 for 500×10⁶/L, respectively. When CD4 counts fall below these limits, increased monitoring frequency becomes advisable. These rules offer guidance for efficient CD4 monitoring, particularly in resource-limited settings.

Ambiguous nucleotide calls from population-based sequencing of HIV-1 are a marker for viral diversity and the age of infection

The fraction of ambiguous nucleotide calls in bulk sequencing of human immunodeficiency virus type 1 (HIV-1) carries important information on viral diversity and the age of infection. In particular, a fraction of ambiguous nucleotides of >.5% provides evidence against a recent infection event <1 year ago.

Background. The time passed since the infection of a human immunodeficiency virus (HIV)–infected individual (the age of infection) is an important but often only poorly known quantity. We assessed whether the fraction of ambiguous nucleotides obtained from bulk sequencing as done for genotypic resistance testing can serve as a proxy of this parameter.

Methods. We correlated the age of infection and the fraction of ambiguous nucleotides in partial pol sequences of HIV-1 sampled before initiation of antiretroviral therapy (ART). Three groups of Swiss HIV Cohort Study participants were analyzed, for whom the age of infection was estimated on the basis of Bayesian back calculation (n = 3,307), seroconversion (n = 366), or diagnoses of primary HIV infection (n = 130). In addition, we studied 124 patients for whom longitudinal genotypic resistance testing was performed while they were still ART-naïve.

Results. We found that the fraction of ambiguous nucleotides increased with the age of infection with a rate of .2% per year within the first 8 years but thereafter with a decreasing rate. We show that this pattern is consistent with population-genetic models for realistic parameters. Finally, we show that, in this highly representative population, a fraction of ambiguous nucleotides of >.5% provides strong evidence against a recent infection event <1 year prior to sampling (negative predictive value, 98.7%).

Conclusions. These findings show that the fraction of ambiguous nucleotides is a useful marker for the age of infection.

Low postseroconversion CD4 count and rapid decrease of CD4 density identify HIV+ fast progressors

CD4 expression in HIV replication is paradoxical: HIV entry requires high cell-surface CD4 densities, but replication requires CD4 down-modulation. However, is CD4 density in HIV+ patients affected over time? Do changes in CD4 density correlate with disease progression? Here, we examined the role of CD4 density for HIV disease progression by longitudinally quantifying CD4 densities on CD4+ T cells and monocytes of ART-naive HIV+ patients with different disease progression rates. This was a retrospective study. We defined three groups of HIV+ patients by their rate of CD4+ T cell loss, calculated by the time between infection and reaching a CD4 level of 200 cells/microl: fast (<7.5 years), intermediate (7.5-12 years), and slow progressors (>12 years). Mathematical modeling permitted us to determine the maximum CD4+ T cell count after HIV seroconversion (defined as "postseroconversion CD4 count") and longitudinal profiles of CD4 count and density. CD4 densities were quantified on CD4+ T cells and monocytes from these patients and from healthy individuals by flow cytometry. Fast progressors had significantly lower postseroconversion CD4 counts than other progressors. CD4 density on T cells was lower in HIV+ patients than in healthy individuals and decreased more rapidly in fast than in slow progressors. Antiretroviral therapy (ART) did not normalize CD4 density. Thus, postseroconversion CD4 counts define individual HIV disease progression rates that may help to identify patients who might benefit most from early ART. Early discrimination of slow and fast progressors suggests that critical events during primary infection define long-term outcome. A more rapid CD4 density decrease in fast progressors might contribute to progressive functional impairments of the immune response in advanced HIV infection. The lack of an effect of ART on CD4 density implies a persistent dysfunctional immune response by uncontrolled HIV infection.

The effect of transmitted HIV-1 drug resistance on pre-therapy viral load

BACKGROUND

Reduced replication capacity of viruses expressing drug resistant mutations implies that patients with transmitted drug resistance (TDR) could have lower HIV RNA viral load than those infected with wild-type virus.

METHODS

We performed analysis using data from the UK HIV Drug Resistance Database and the UK CHIC study. Eligible patients had a resistance test performed between 1997 and 2007 while naive to antiretroviral therapy, were 16 years or older, and had a viral load and CD4 cell count measurement within 6 months of this test. Models were adjusted for CD4 cell count, viral subtype, ethnicity, risk group, sex, age, calendar year, clinical centre, and viral load assay.

RESULTS

Of a total of 7994 patients included, 709 (9%) had TDR: 604 (85%) had resistance to one drug class only [350 nucleos(t)ide reverse transcriptase inhibitors (NRTIs), 164 non-nucleos(t)ide reverse transcriptase inhibitors (NNRTIs), 90 protease inhibitors (PIs)], 77 (11%) to two classes (42 NRTIs/NNRTIs, 31 NRTIs/PIs, 4 NNRTIs/PIs), and 28 (4%) had resistance to all three classes. The overall mean (SD) viral load at the time of resistance testing was 4.60 (0.82) log(10) copies/ml, and did not differ by class of TDR. However, patients harbouring M184V/I (n = 61) had a significantly lower viral load [adjusted mean difference -0.33 log10 copies/ml (95% CI -0.54 to -0.11), 53% lower (95% CI 22 to 71%), P = 0.002] compared to wild-type virus.

DISCUSSION

Our study provides clear evidence of an in-vivo fitness cost associated with the M184V/I mutation independent of drug effects which select for this mutation. This was not observed for any other mutation, but true effects may have been obscured by reversion of initially resistant viruses to wild-type.

CD4(+) T cell count decreases by ethnicity among untreated patients with HIV infection in South Africa and Switzerland

BACKGROUND

Estimates of the decrease in CD4(+) cell counts in untreated patients with human immunodeficiency virus (HIV) infection are important for patient care and public health. We analyzed CD4(+) cell count decreases in the Cape Town AIDS Cohort and the Swiss HIV Cohort Study.

METHODS

We used mixed-effects models and joint models that allowed for the correlation between CD4(+) cell count decreases and survival and stratified analyses by the initial cell count (50-199, 200-349, 350-499, and 500-750 cells/microL). Results are presented as the mean decrease in CD4(+) cell count with 95% confidence intervals (CIs) during the first year after the initial CD4(+) cell count.

RESULTS

A total of 784 South African (629 nonwhite) and 2030 Swiss (218 nonwhite) patients with HIV infection contributed 13,388 CD4(+) cell counts. Decreases in CD4(+) cell count were steeper in white patients, patients with higher initial CD4(+) cell counts, and older patients. Decreases ranged from a mean of 38 cells/microL (95% CI, 24-54 cells/microL) in nonwhite patients from the Swiss HIV Cohort Study 15-39 years of age with an initial CD4(+) cell count of 200-349 cells/microL to a mean of 210 cells/microL (95% CI, 143-268 cells/microL) in white patients in the Cape Town AIDS Cohort > or =40 years of age with an initial CD4(+) cell count of 500-750 cells/microL.

CONCLUSIONS

Among both patients from Switzerland and patients from South Africa, CD4(+) cell count decreases were greater in white patients with HIV infection than they were in nonwhite patients with HIV infection.

Long-term outcome of peripartum cardiomyopathy in a population with high seropositivity for human immunodeficiency virus

BACKGROUND

Peripartum cardiomyopathy (PPCM) is a rare cardiomyopathy with a high risk of mortality. The present study assessed clinical outcome and mortality over a 2-year period in an African cohort of 80 PPCM patients.

METHODS

A prospective study over a 2-year period at a tertiary center, where 80 consecutive women presenting with PPCM were enrolled on first diagnosis. Patients obtained standard heart failure therapy. Detailed assessments included echocardiography, NYHA functional class, left ventricular ejection fraction (LVEF), mortality and serum levels for hemoglobin, CRP, IL-6, TNF-alpha, Fas/Apo-1, and T-cell count at each 6-month intervals for 24 months.

RESULTS

Baseline mean age was 30 ± 7 years; 38% were primigravidas and 34% were co-infected with HIV. NYHA functional class III-IV was present in 89% patients with a mean LVEF of 30 ± 9%. Four patients were lost to follow-up, 9 moved to remote areas, 7 were excluded due to subsequent pregnancy. The 2-year mortality rate was 28%. Eight of 80 (10%) died by 6 months. Mean LVEF of surviving patients was: 44 ± 11% at 6-months, 46 ± 13% at 12-months and 50 ± 14% at 24-months follow-up. Of the 69 patients still enrolled at 6 months 14 (20%) died over the remaining 18-month period, despite functional recovery. No statistically significant difference in LVEF and mortality was observed between PPCM patients with or without HIV co-infection.

CONCLUSION

The novel finding of this study is the continuous high mortality of PPCM patients occurring beyond 6 months independent of HIV infection and subsequent pregnancy. This finding strongly encourages the need for long-term clinical follow-up and management of women with PPCM.