Methods for estimating the AIDS incubation time distribution when date of seroconversion is censored

Two biases in incubation time estimation related to exposure

BACKGROUND

Estimation of the SARS-CoV-2 incubation time distribution is hampered by incomplete data about infection. We discuss two biases that may result from incorrect handling of such data. Notified cases may recall recent exposures more precisely (differential recall). This creates bias if the analysis is restricted to observations with well-defined exposures, as longer incubation times are more likely to be excluded. Another bias occurred in the initial estimates based on data concerning travellers from Wuhan. Only individuals who developed symptoms after their departure were included, leading to under-representation of cases with shorter incubation times (left truncation). This issue was not addressed in the analyses performed in the literature.

METHODS

We performed simulations and provide a literature review to investigate the amount of bias in estimated percentiles of the SARS-CoV-2 incubation time distribution.

RESULTS

Depending on the rate of differential recall, restricting the analysis to a subset of narrow exposure windows resulted in underestimation in the median and even more in the 95th percentile. Failing to account for left truncation led to an overestimation of multiple days in both the median and the 95th percentile.

CONCLUSION

We examined two overlooked sources of bias concerning exposure information that the researcher engaged in incubation time estimation needs to be aware of.

Towards robust and accurate estimates of the incubation time distribution, with focus on upper tail probabilities and SARS-CoV-2 infection

Quarantine length for individuals who have been at risk for infection with SARS-CoV-2 has been based on estimates of the incubation time distribution. The time of infection is often not known exactly, yielding data with an interval censored time origin. We give a detailed account of the data structure, likelihood formulation and assumptions usually made in the literature: (i) the risk of infection is assumed constant on the exposure window and (ii) the incubation time follows a specific parametric distribution. The impact of these assumptions remains unclear, especially for the right tail of the distribution which informs quarantine policy. We quantified bias in percentiles by means of simulation studies that mimic reality as close as possible. If assumption (i) is not correct, then median and upper percentiles are affected similarly, whereas misspecification of the parametric approach (ii) mainly affects upper percentiles. The latter may yield considerable bias. We suggest a semiparametric method that provides more robust estimates without the need of a parametric choice. Additionally, we used a simulation study to evaluate a method that has been suggested if all infection times are left censored. It assumes that the width of the interval from infection to latest possible exposure follows a uniform distribution. This assumption gave biased results in the exponential phase of an outbreak. Our application to open source data suggests that focus should be on the level of information in the observations, as expressed by the width of exposure windows, rather than the number of observations.

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.

Restricted mean survival time for interval-censored data

Restricted mean survival time (RMST) evaluates the mean event-free survival time up to a prespecified time point. It has been used as an alternative measure of treatment effect owing to its model-free structure and clinically meaningful interpretation of treatment benefit for right-censored data. In clinical trials, another type of censoring called interval censoring may occur if subjects are examined at several discrete time points and the survival time falls into an interval rather than being exactly observed. The missingness of exact observations under interval-censored cases makes the nonparametric measure of treatment effect more challenging. Employing the linear smoothing technique to overcome the ambiguity, we propose a new model-free measure for the interval-censored RMST. As an alternative to the commonly used log-rank test, we further construct a hypothesis testing procedure to assess the survival difference between two groups. Simulation studies show that the bias of our proposed interval-censored RMST estimator is negligible and the testing procedure delivers promising performance in detecting between-group difference with regard to size and power under various configurations of survival curves. The proposed method is illustrated by reanalyzing two real datasets containing interval-censored observations.

Determining the Most Likely Source of Infection: An Application to Neisseria Gonorrhoeae Among Men Who Have Sex with Men

BACKGROUND

The source of an infection is often unknown. To inform directed prevention measures, it is useful to know the location and partner type with the highest transmission risk. We developed a method to estimate infection risk of Neisseria gonorrhoeae per meeting location among men who have sex with men (MSM).

METHODS

In 2008-2009, we collected information from 2,438 MSM attending the sexually transmitted infections clinic of Amsterdam. For up to four partners per participant (8,028 in total), we asked for details on meeting location, partner, and partnership characteristics. We used logistic regression to relate these to the participant's infection risk, accounting for unobserved transmission information in the likelihood. Based on the model estimates, we predicted the probability of a partner having N. gonorrhoeae. The probability that a partner was the source was proportional to his predicted infection risk. Each source was linked to the meeting location. We used a Bayesian method.

RESULTS

Rectal N. gonorrhoeae was diagnosed in 157 MSM who reported data on 422 possible source partners, urethral N. gonorrhoeae in 126 reporting 285 possible sources, and pharyngeal N. gonorrhoeae in 162 reporting 451 possible sources. We estimated that most infections were acquired from long-lasting steady partners (21%; 95% CI = 17, 24). Partners met in an Amsterdam street with gay venues posed the highest transmission risk (13%; 95% CI = 7.9, 18).

CONCLUSIONS

The presented method estimates the source of infection when there are multiple possible sources and enables the summation over various kinds of epidemiologic characteristics (here, meeting locations) that are relevant for prevention.

A real-world observational cohort of patients with primary biliary cholangitis: TARGET-primary biliary cholangitis study design and rationale

Primary biliary cholangitis (PBC) is a rare chronic cholestatic liver disease that may progress to biliary cirrhosis if left untreated. The first‐line therapy for PBC is ursodeoxycholic acid (UDCA). Unfortunately, 1 of 3 patients does not respond to UDCA. These patients are at risk for developing clinical events, including cirrhosis, complications of portal hypertension, hepatocellular carcinoma, liver transplant, or death. Recently, the U.S. Food and Drug Administration approved obeticholic acid to be used in certain patients with PBC. Off‐label therapies are also used, and several other therapies are currently under evaluation. Real‐world effectiveness of newly approved and off‐label therapies remains unknown. TARGET‐PBC is a 5‐year, longitudinal, observational study of patients with PBC that will evaluate the effectiveness of clinical practice interventions and provide practical information unobtainable in registration trials. Enrollment will take place at both academic and community sites. In addition to consenting to medical records review, participants will be asked to provide an annual blood sample and complete patient reported outcome surveys at predetermined intervals. Any available liver biopsies will be digitally preserved. Conclusion: Key study outcomes will be the evaluation of the safety and effectiveness of PBC interventions and the assessment of disease progression under real‐world conditions. (Hepatology Communications 2018;2:484‐491)

Time from HIV infection to virological suppression: dramatic fall from 2007 to 2016

AIM

Time from HIV infection to virological suppression: dramatic fall from 2007 to 2016.

OBJECTIVES

We examined the time from HIV infection to virological suppression in MSM who were first diagnosed at Melbourne Sexual Health Centre between 2007 and 2016.

DESIGN

Retrospective cohort.

METHODS

Date of infection was imputed from the testing history or serological evidence of recent infection (negative or indeterminate western blot) or baseline CD4 cell count. Date of virological suppression was determined using clinical viral load data. We analysed predictors of diagnosis with serological evidence of recent infection (logistic regression) and time from diagnosis to suppression and from infection to suppression (Cox regression) using demographic, clinical, and behavioral covariates.

RESULTS

Between 2007 and 2016, the median time from HIV infection to diagnosis fell from 6.8 to 4.3 months (P = 0.001), from diagnosis to suppression fell from 22.7 to 3.2 months (P < 0.0001), and from infection to suppression fell from 49.0 to 9.6 months (P < 0.0001). Serological evidence of recent infection increased from 15.6 to 34.3% (P < 0.0001) of diagnoses. In the multivariate analyses, age, being recently arrived from a non-English speaking country, history of IDU, other sexually transmitted infections, and sexual risk were not associated with any of these measures.

CONCLUSION

The duration of infectiousness in MSM diagnosed with HIV infection at Melbourne Sexual Health Centre in Victoria has fallen dramatically between 2007 and 2016 and the proportion diagnosed with serological evidence of recent infection has increased. This effect is observed across all population subgroups and marks a positive milestone for the treatment as prevention paradigm.

Design and rationale for a real-world observational cohort of patients with nonalcoholic fatty liver disease: The TARGET-NASH study

Nonalcoholic fatty liver disease (NAFLD) is highly prevalent and can lead to cirrhosis, hepatocellular carcinoma, and end-stage liver disease. NAFLD comprises the spectrum from simple steatosis (nonalcoholic fatty liver, NAFL), to steatosis with inflammation (nonalcoholic steatohepatitis, NASH). Current primary therapy recommended for NAFLD is weight loss induced by lifestyle modification. The difficulty in achieving this has led to robust pharmacological therapy development. While new drugs may show efficacy in selected phase II/III clinical trial populations, their real-world effectiveness is unknown. TARGET-NASH is a 5-year, longitudinal, observational study of patients with NAFLD designed to evaluate the effectiveness of clinical practice interventions and provide practical information unobtainable in registration trials. A biological specimen repository is included in TARGET-NASH for translational studies of genomics and biomarkers of disease activity. Patients are enrolling at adult and pediatric sites representing multiple specialties. All patients being managed for NAFLD are eligible, whereas those in other NASH registries or clinical trials will be excluded. Enrolled patients range in age from 6 and up and will have 3years of clinical data reviewed. Patient comorbidities, concomitant medications, disease progression and off-label interventions will be assessed, and adverse outcomes, monitored. Confirming the use, safety and effectiveness of NAFLD interventions in children and adults and establishing pragmatic methods of assessing disease progression under real-world conditions are key study outcomes. Ultimately, TARGET-NASH will establish a large, diverse registry of NAFLD patients at academic and community practices to be leveraged to improve health and reduce development of cirrhosis and hepatocellular carcinoma.

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.

Increasing risk behaviour can outweigh the benefits of antiretroviral drug treatment on the HIV incidence among men-having-sex-with-men in Amsterdam

Background

The transmission through contacts among MSM (men who have sex with men) is one of the dominating contributors to HIV prevalence in industrialized countries. In Amsterdam, the capital of the Netherlands, the MSM risk group has been traced for decades. This has motivated studies which provide detailed information about MSM's risk behavior statistically, psychologically and sociologically. Despite the era of potent antiretroviral therapy, the incidence of HIV among MSM increases. In the long term the contradictory effects of risk behavior and effective therapy are still poorly understood.

Methods

Using a previously presented Complex Agent Network model, we describe steady and casual partnerships to predict the HIV spreading among MSM. Behavior-related parameters and values, inferred from studies on Amsterdam MSM, are fed into the model; we validate the model using historical yearly incidence data. Subsequently, we study scenarios to assess the contradictory effects of risk behavior and effective therapy, by varying corresponding values of parameters. Finally, we conduct quantitative analysis based on the resulting incidence data.

Results

The simulated incidence reproduces the ACS historical incidence well and helps to predict the HIV epidemic among MSM in Amsterdam. Our results show that in the long run the positive influence of effective therapy can be outweighed by an increase in risk behavior of at least 30% for MSM.

Conclusion

We recommend, based on the model predictions, that lowering risk behavior is the prominent control mechanism of HIV incidence even in the presence of effective therapy.

A simple G-computation algorithm to quantify the causal effect of a secondary illness on the progression of a chronic disease

Progression of a chronic disease can lead to the development of secondary illnesses. An example is the development of active tuberculosis (TB) in HIV-infected individuals. HIV disease progression, as indicated by declining CD4 + T-cell count (CD4), increases both the risk of TB and the risk of AIDS-related mortality. This means that CD4 is a time-dependent confounder for the effect of TB on AIDS-related mortality. Part of the effect of TB on AIDS-related mortality may be indirect by causing a drop in CD4. Estimating the total causal effect of TB on AIDS-related mortality using standard statistical techniques, conditioning on CD4 to adjust for confounding, then gives an underestimate of the true effect. Marginal structural models (MSMs) can be used to obtain an unbiased estimate. We describe an easily implemented algorithm that uses G-computation to fit an MSM, as an alternative to inverse probability weighting (IPW). Our algorithm is simplified by utilizing individual baseline parameters that describe CD4 development. Simulation confirms that the algorithm can produce an unbiased estimate of the effect of a secondary illness, when a marker for primary disease progression is both a confounder and intermediary for the effect of the secondary illness. We used the algorithm to estimate the total causal effect of TB on AIDS-related mortality in HIV-infected individuals, and found a hazard ratio of 3.5 (95 per cent confidence interval 1.2-9.1).

Imputation methods for doubly censored HIV data

In medical research, it is common to have doubly censored survival data: origin time and event time are both subject to censoring. In this paper, we review simple and probability-based methods that are used to impute interval censored origin time and compare the performance of these methods through extensive simulations in the one-sample problem, two-sample problem and Cox regression model problem. The use of a bootstrap procedure for inference is demonstrated.

[Cohort studies and their contribution to the study of HIV infection: main characteristics and limitations]

In this paper, we provide a definition of cohort studies and reviews the main types of cohort studies used in the context of HIV infection. We discuss how the main sources of selection biases in cohort studies are those derived from the lack of observation of the event that determines the origin and/or of the event of interest due to losses to follow-up or development of a competing event, and how this bias must be appropriately taken into account following specific epidemiological methods. Although cohort studies play an essential role in the study of HIV infection, they are logistically complex and require considerable resources. Therefore, strategic planning on the quality and quantity of the information collected must always be accompanied by a resource allocation plan.

In vitro whole-genome analysis identifies a susceptibility locus for HIV-1

Advances in large-scale analysis of human genomic variability provide unprecedented opportunities to study the genetic basis of susceptibility to infectious agents. We report here the use of an in vitro system for the identification of a locus on HSA8q24.3 associated with cellular susceptibility to HIV-1. This locus was mapped through quantitative linkage analysis using cell lines from multigeneration families, validated in vitro, and followed up by two independent association studies in HIV-positive individuals. Single nucleotide polymorphism rs2572886, which is associated with cellular susceptibility to HIV-1 in lymphoblastoid B cells and in primary T cells, was also associated with accelerated disease progression in one of two cohorts of HIV-1-infected patients. Biological analysis suggests a role of the rs2572886 region in the regulation of the LY6 family of glycosyl-phosphatidyl-inositol (GPI)-anchored proteins. Genetic analysis of in vitro cellular phenotypes provides an attractive approach for the discovery of susceptibility loci to infectious agents.

HIV prevalence and incidence in rural Tanzania: results from 10 years of follow-up in an open-cohort study

BACKGROUND

Tanzanian antenatal clinic surveillance data suggest stabilizing HIV levels. Data from an open cohort in northern Tanzania provide robust estimates of prevalence and incidence.

METHODS

Between 1994 and 2004, 19 rounds of household-based demographic surveillance and 4 rounds of individually linked HIV serologic surveys were conducted. Longitudinal knowledge of individuals' testing histories is used to allow for effects of selective participation on prevalence estimates; multiple imputation procedures allow for interval censoring effects on incidence.

RESULTS

A total of 16,820 adults donated blood for HIV testing in at least 1 of 4 serologic surveys. HIV prevalence increased steadily from 6.0% in 1994/1995 to 8.3% in 2000/2001, leveling out thereafter. HIV incidence increased sharply from 0.8% in 1994 to 1997 to 1.2% per thousand in 1997 to 2000, remaining high (1.1%) in 2000 to 2003. In roadside areas, incidence fell in the last interval, especially among women, but in remote rural areas, incidence rose slightly.

CONCLUSIONS

HIV spread is continuing in rural areas, suggesting a need for more intensive HIV prevention efforts and antiretroviral interventions. The leveling off in prevalence is attributable to a combination of high mortality among HIV-infected persons and a slight decrease in incidence in roadside villages.

A comparison of imputation techniques for handling missing predictor values in a risk model with a binary outcome

Risk models that aim to predict the future course and outcome of disease processes are increasingly used in health research, and it is important that they are accurate and reliable. Most of these risk models are fitted using routinely collected data in hospitals or general practices. Clinical outcomes such as short-term mortality will be near-complete, but many of the predictors may have missing values. A common approach to dealing with this is to perform a complete-case analysis. However, this may lead to overfitted models and biased estimates if entire patient subgroups are excluded. The aim of this paper is to investigate a number of methods for imputing missing data to evaluate their effect on risk model estimation and the reliability of the predictions. Multiple imputation methods, including hotdecking and multiple imputation by chained equations (MICE), were investigated along with several single imputation methods. A large national cardiac surgery database was used to create simulated yet realistic datasets. The results suggest that complete case analysis may produce unreliable risk predictions and should be avoided. Conditional mean imputation performed well in our scenario, but may not be appropriate if using variable selection methods. MICE was amongst the best performing multiple imputation methods with regards to the quality of the predictions. Additionally, it produced the least biased estimates, with good coverage, and hence is recommended for use in practice.

Do HIV Disease Progression and HAART Response Vary among Injecting Drug Users in Europe?

Prior to HAART availability, there was no evidence of a geographical variation in HIV disease progression among injecting drug users (IDU) from different European regions. Nowadays, factors of importance regarding HIV disease progression in the face of HAART availability, such as HAART access, adherence, and the organization of care for IDU may differ across Europe. Therefore we studied HIV disease progression in a European study of IDU with known dates of HIV-seroconversion. Results show that with ongoing HAART availability, the risk of HIV disease progression has continued to decrease. When accounting for pre-AIDS death (in AIDS analyses) and non-natural deaths (suicide, overdose, accidents and homicide, in analyses of death) which are common among IDU, the risk of AIDS and death has decreased by as much as 65% and 75%, respectively, in 2000/2001. Results show little geographic variation in progression to AIDS. All-cause mortality was higher in IDU from Glasgow than elsewhere, while in the Valencian region (Spain) IDU were at a significantly lower risk of non-natural deaths. The timing of HAART initiation by treatment-naïve IDU likewise differed across Europe: IDU in Amsterdam, Innsbruck, and Edinburgh started at significantly lower CD4 counts than IDU in Paris, Geneva, Glasgow, and the Valencian region, but the subsequent short-term immune response was similar. In conclusion, the risk in progression to AIDS or natural death is similar across western Europe although IDU across Europe differ in other factors, such as the risk of non-natural death and the timing of HAART initiation.

HIV-1 subtype E progression among northern Thai couples: traditional and non-traditional predictors of survival

BACKGROUND

In the continuing effort to introduce antiretroviral therapy in resource-limited settings, there is a need to understand differences between natural history of HIV in different populations and to identify feasible clinical measures predictive of survival.

METHODS

We examined predictors of survival among 836 heterosexuals who were infected with HIV subtype CRF01_AE in Thailand.

RESULTS

From 1993 to 1999, 269 (49.4%) men and 65 (25.7%) women died. The median time from the estimated seroconversion to death was 7.8 years (95% confidence interval 7.0-9.1). Men and women with enrolment CD4 counts <200 cells/microl had about 2 and 11 times greater risk of death than those with CD4 counts of 200-500 and >500, respectively. Measurements available in resource-limited settings, including total lymphocyte count (TLC), anaemia, and low body mass index (BMI), also predicted survival. Men with two or more of these predictors had a median survival of 0.8 (0.5-1.8) years, compared with 2.7 (1.9-3.3) years for one predictor and 4.9 (4.1-5.2) years for no predictors.

CONCLUSIONS

The time from HIV infection to death appears shorter among this Thai population than among antiretroviral naive Western populations. CD4 count and viral load (VL) were strong, independent predictors of survival. When CD4 count and VL are unavailable, individuals at high risk for shortened HIV survival may be identified by a combination of low TLC, anaemia, and low BMI. This combination of accessible clinical measures of the disease stage may be useful for medical management in resource-limited settings.

Pre-seroconversion immune status predicts the rate of CD4 T cell decline following HIV infection

OBJECTIVE

To study whether immune status prior to HIV seroconversion predicts CD4 T cell decline during HIV infection.

DESIGN

Prospective cohort study including 51 injecting drug users (IDU) who were HIV negative at study entry and seroconverted for HIV during follow-up.

METHODS

Cryopreserved peripheral blood mononuclear cells obtained before HIV seroconversion were used to measure naive (CD45RO-CD27+), memory (CD45RO+CD27+), and total CD4 T cell numbers, the fraction of dividing Ki67+CD4+ T cells, and CD4 T cell receptor excision circles (TREC). The effect of pre-seroconversion immune status, as defined by these markers, on the rate of CD4 T cell decline during HIV infection was assessed using linear regression for repeated measurements.

RESULTS

IDU with low pre-seroconversion CD4 T cell TREC contents lost CD4 T cells at a significantly faster rate during HIV infection than those with a high CD4 T cell TREC content. IDU with higher pre-seroconversion CD4 T cell numbers had a significantly steeper CD4 T cell decline in the first 3 months of HIV infection, but their CD4 T cell counts remained higher throughout HIV infection. Intermediate levels of pre-seroconversion dividing Ki67+CD4+ T cells were associated with a significantly steeper CD4 cell decline than high levels. IDU with the highest pre-seroconversion drug-injecting frequencies showed slower CD4 T cell decline than those who injected less. No correlation was present between pre-seroconversion immune markers and the pre-seroconversion duration or intensity of drug use.

CONCLUSION

Among IDU, immune status prior to HIV infection as measured by TREC content affects the disease course after HIV seroconversion.

[Imputation of the date of HIV seroconversion in cohorts of haemophiliacs]

OBJECTIVES

To describe the methods used to impute HIV seroconversion date in the haemophiliac cohorts from GEMES project and to validate its use.

METHOD

632 haemophiliacs coming from three hemophilia units identified as HIV+ and 1.092 individuals coming from 5 project GEMES cohorts with a seroconversion window (time among test HIV and HIV+) less than 3 years where mid point (PM) was assumed as seroconversion date. For both groups, seroconversion date was imputed after estimating the probability distribution of seroconversion by means of the EM algorithm. Two imputation methods are used: one obtained from the expected value and the other from the geometric mean of 5 random samples. from the estimated distribution. Imputations have been validated in the non haemophiliacs cohorts comparing with the PM seroconversion date. Also AIDS free time and survival from the different seroconversion imputed dates were compared.

RESULTS

Median seroconversion date is located in May of 1993 for the non haemophiliacs and in 1982 for the haemophiliacs. Not big differences are observed among the imputed seroconversion dates and the mid-point seroconversion date in the non-haemophiliac cohorts. Similar results are found for the haemophiliac cohorts. Also no differences are observed in the estimated AIDS-free time for both groups of cohorts.

CONCLUSIONS

Geometric mean imputation from several random samples provides a good estimate of the HIV seroconversion date that can be used to estimate AIDS-free time and survival in haemophiliac cohorts where seroconversion date is ignored.

A parametric survival model with an interval-censored covariate

We present a parametric survival model whose particularity consists in the inclusion of an interval-censored covariate. The methodology is motivated by a study on injecting drug users in Badalona (Spain), most of whom suffered HIV infection as a result of their drug addiction. The study aims to examine the possible association between the elapsed time from first injecting drug use until HIV infection and the subsequent AIDS incubation period. Whereas the moment of HIV infection cannot be observed exactly and is therefore interval-censored, time until AIDS onset is doubly-censored. For the maximization of the resulting likelihood function, we use a numerical solver. Maximization is carried out by means of the mathematical programming language AMPL.

Tuberculosis risk varies with the duration of HIV infection: a prospective study of European drug users with known date of HIV seroconversion

BACKGROUND

It is not known whether the risk of active tuberculosis disease varies with the length of time that individuals are infected with HIV.

OBJECTIVE

To study how, independently of CD4 T cell count, the risk of tuberculosis varies with the duration of HIV infection.

METHODS

Using Poisson regression analysis, the incidence of and risk factors for tuberculosis were studied in 683 injecting drug users (IDU) with a documented date of HIV seroconversion followed in seven cohorts in six European countries until 1998.

RESULTS

Overall incidence was 11.5/1000 person-years. Adjusted for CD4 T cell count and geographic region, the risk ratio (RR) for tuberculosis (both pulmonary and extrapulmonary), compared with the first 3 years of HIV infection, was 2.8 for years 4 to 6 of HIV infection [95% confidence interval (CI), 1.3-6.3], 1.2 for year 7 to 9 (95% CI, 0.3-4.2) and 4.6 after 9 years (95% CI, 1.4-15.0). The adjusted RR for geographic region was 13.1 (95% CI, 4.3-40.0) for Amsterdam and 15.8 (95% CI, 4.8-52.0) for the Valencian region of Spain compared with all other sites combined.

CONCLUSION

The risk of tuberculosis is increased relatively early in HIV infection (year 4 to 6) and also later (after year 9) with possibly a relatively silent period between. As expected, IDU in Southern Europe have a substantially higher risk of tuberculosis than IDU in Northern and Central Europe. Amsterdam forms an exception for Northern Europe, with very high incidence rates.

The contribution of steady and casual partnerships to the incidence of HIV infection among homosexual men in Amsterdam

OBJECTIVE

To assess the relative contribution of steady and casual partnerships to the incidence of HIV infection among homosexual men in Amsterdam, and to determine the effect of increasing sexually risky behaviours among both types of partners in the era of highly active antiretroviral therapy (HAART).

METHODS

A mathematical model was developed for the spread of HIV infection among young homosexual men in Amsterdam after the introduction of HAART. The model describes the formation of both steady and casual partnerships. Behavioural parameters were estimated separately for steady and casual partners from the Amsterdam Cohort Study among young homosexual men. HIV incidence and the fraction of new infections attributed to casual contacts were calculated from the model, allowing for uncertainty in the increases in risky behaviour, the effect of HAART, and levels of HIV testing and HAART administration.

RESULTS

Currently, 86% (range 74-90%) of new HIV infections occur within steady partnerships. A reduction of 75-99% in infectivity caused by HAART will be counterbalanced by increases of 50% (range 30-80%) in risky behaviour with steady partners, but not by increases of up to 100% with casual partners. If HIV testing is increased from 42 to 80% and HAART administration from 70 to 85%, then even an increase of 100% in risk-taking with steady partners will not outweigh the effect of HAART.

CONCLUSION

Most new HIV infections among homosexual men in Amsterdam occur within steady relationships. Prevention measures should address risky behaviour, specifically with steady partners, and the promotion of HIV testing.

Prediction of residual time to AIDS and death based on markers and cofactors

A model was constructed that estimates the probability of an HIV-infected individual developing AIDS or dying within a certain time span if left untreated, based on the most recent CD4 lymphocyte count, HIV-1 RNA load, and HIV-1 phenotype, together with age, time since seroconversion, and two genetic cofactors. The model helps clinicians in deciding when to start highly active antiretroviral treatment (HAART). Data from the Amsterdam Cohort Study among homosexual men restricted to individuals with an estimated date of seroconversion (N = 280) were used. Individual predictions based on several combinations of marker and cofactor values were obtained, and their accuracy was measured using two indices of predictive value. CD4 lymphocyte count and HIV RNA load have the highest predictive value and act independently. The predictive value of the HIV phenotype is only slightly lower and greatly enhances predictions at high CD4 counts. The CCR5-Delta32 and CCR2-64I alleles have no additional predictive value. Some predictive value is lost by not knowing time since seroconversion, and some effect of calendar period is present. In summary, for prognosis, the markers CD4 count, HIV-1 RNA load, and HIV-1 phenotype (at a high CD4 count) are equally important, and the genetic cofactors considered are of no use.

Seasonal influences on immunological parameters in HIV-infected homosexual men: searching for the immunomodulating effects of sunlight

In view of the capacity of ultraviolet radiation (UVR) to induce suppression of various immunological parameters and to enhance the viral replication of HIV, we investigated whether seasonal influences on immunological parameters that are relevant for HIV infection could be identified. As the sunny season is associated with high levels of ambient UVR, a decline of immunological parameters and an increase of the HIV viral load during the summer months might ensue. We analysed the immunological data of the HIV-infected homosexual men who participated in the Amsterdam Cohort Study on HIV infection and AIDS (1984-1996; n = 556). The effect of season on the individual development of various immunological parameters in time was examined by means of a random effects model for repeated measurements. Lower levels in the mean number of CD4+ T cells and the mean CD4+/CD8+ ratio were found during summer and spring, respectively (P = 0.0001/0.0001). For the CD8+ T cells, high mean values were observed both in April and September (P = 0.0001). The highest T-cell reactivity values were found during the summer (P = 0.0001). No effect of season on the viral load was established. The seasonal effect on CD4+ T cells seemed to be more pronounced at a more advanced stage of the HIV infection. It is concluded that the lower CD4+ T-cell counts during summer support the notion that solar UVR may have a suppressive effect on the cellular immunity of HIV-infected persons. However, whether this observation can be attributed to the effect of ambient UVR solely is questionable, as the other immunological parameters follow different seasonal courses and other reports suggest that both internal and environmental factors influence immunological parameters.

Higher viral loads and other risk factors associated with HIV-1 seroconversion during a period of high incidence among injection drug users in Bangkok

We analyzed data from a prospective cohort study of injection drug users (IDUs) attending methadone treatment clinics in Bangkok, Thailand, during 1995-1998 to characterize factors associated with a period of high incidence (PHI) from July 1996 through January 1997 compared with periods of lower incidence. Sociobehavioral characteristics were similar for all participants during and outside the PHI except for the following: there was more reported drug injection while IDUs were incarcerated during the PHI (odds ratio, 1.67; p =.02) and significantly higher proportions of persons reported heroin injection (91% vs. 75%, respectively; p =.02) and higher frequencies of daily injection and sharing of injection equipment (40% vs. 25%, respectively; p =.05) during the PHI than outside the PHI. Through most of the first year after seroconversion, plasma HIV-1 loads were significantly higher in persons who seroconverted during the PHI than in those who seroconverted outside the PHI. Higher viral loads may potentially contribute to faster disease progression and increased infectiousness or transmissibility to subsequent contacts. Our findings suggest that prevention efforts to reduce the effective size and turnover within IDU sharing networks may have a significant impact on the epidemic by disrupting the rapid transmission of HIV-1 from recently infected, highly infectious individuals.