On nonparametric maximum likelihood estimation with double truncation.

Doubly truncated survival data arise if failure times are observed only within certain time intervals. The nonparametric maximum likelihood estimator is widely used to estimate the underlying failure time distribution. Using a directed graph representation of the data suggested by Vardi (1985), a certain graphical condition holds if and only if the nonparametric maximum likelihood estimate exists and is unique. If this condition does not hold, then such an estimate may exist but need not be unique, so another graphical condition is proposed to check whether such an estimate exists. The conditions are simple to check using existing graphical software. Reanalysis of an AIDS incubation time dataset shows that a nonparametric maximum likelihood estimate does not exist for these data.

Timing and predictors of severe rotavirus gastroenteritis among unvaccinated infants in low- and middle-income countries.

Delays in rotavirus vaccine schedule could improve performance in low- and middle-income countries (LMICs). However, delaying the first dose could be detrimental if infants experience severe rotavirus gastroenteritis (RVGE) early in life. Our objective was to describe the timing and predictors of severe RVGE in unvaccinated children in LMICs. We analysed the placebo arms from two clinical trials (cohort 1: NCT00241644; cohort 2: NCT00362648). We estimated the rate, cumulative incidence (per 1000 infants) and age distribution of severe RVGE episodes. Cox proportional hazards models were used to estimate hazard ratios and 95% confidence intervals (CI) for the association between baseline factors and severe RVGE. Cumulative incidence at 6 months of age was 23/1000 (95% CI 15-30) in cohort 1 and 6/1000 (95% CI 3-8) in cohort 2. Early antibiotic use (compared with no use) was associated with 2.03 (95% CI 1.18-3.48) and 1.41 (95% CI 0.80-2.51) times the rate of severe RVGE in cohorts 1 and 2, respectively. The cumulative incidence of severe RVGE was low at 6 months of age, suggesting that a 4-week delay in the vaccination schedule may not result in a large number of severe RVGE episodes prior to vaccine receipt.

Increased risk of influenza among vaccinated adults who are obese.

BACKGROUND: Influenza infects 5-15% of the global population each year, and obesity has been shown to be an independent risk factor for increased influenza-related complications including hospitalization and death. However, the risk of developing influenza or influenza-like illness (ILI) in a vaccinated obese adult population has not been addressed. OBJECTIVE: This study evaluated whether obesity was associated with increased risk of influenza and ILI among vaccinated adults. SUBJECTS AND METHODS: During the 2013-2014 and 2014-2015 influenza seasons, we recruited 1042 subjects to a prospective observational study of trivalent inactivated influenza vaccine (IIV3) in adults. A total of 1022 subjects completed the study. Assessments of relative risk for laboratory confirmed influenza and ILI were determined based on body mass index. Seroconversion and seroprotection rates were determined using prevaccination and 26-35 days post vaccination serum samples. Recruitment criteria for this study were adults 18 years of age and older receiving the seasonal trivalent inactivated influenza vaccine (IIV3) for the years 2013-2014 and 2014-2015. Exclusion criteria were immunosuppressive diseases, use of immunomodulatory or immunosuppressive drugs, acute febrile illness, history of Guillain-Barre syndrome, use of theophylline preparations or use of warfarin. RESULTS: Among obese, 9.8% had either confirmed influenza or influenza-like-illness compared with 5.1% of healthy weight participants. Compared with vaccinated healthy weight, obese participants had double the risk of developing influenza or ILI (relative risk=2.01, 95% CI 1.12, 3.60, P=0.020). Seroconversion or seroprotection rates were not different between healthy weight and obese adults with influenza or ILI. CONCLUSIONS: Despite robust serological responses, vaccinated obese adults are twice as likely to develop influenza and ILI compared with healthy weight adults. This finding challenges the current standard for correlates of protection, suggesting use of antibody titers to determine vaccine effectiveness in an obese population may provide misleading information.

The differential short- and long-term effects of HIV-1 latency-reversing agents on T cell function.

Despite the extraordinary success of HIV-1 antiretroviral therapy in prolonging life, infected individuals face lifelong therapy because of a reservoir of latently-infected cells that harbor replication competent virus. Recently, compounds have been identified that can reverse HIV-1 latency in vivo. These latency- reversing agents (LRAs) could make latently-infected cells vulnerable to clearance by immune cells, including cytolytic CD8+ T cells. We investigated the effects of two leading LRA classes on CD8+ T cell phenotype and function: the histone deacetylase inhibitors (HDACis) and protein kinase C modulators (PKCms). We observed that relative to HDACis, the PKCms induced much stronger T cell activation coupled with non-specific cytokine production and T cell proliferation. When examining antigen-specific CD8+ T cell function, all the LRAs except the HDACi Vorinostat reduced, but did not abolish, one or more measurements of CD8+ T cell function. Importantly, the extent and timing of these effects differed between LRAs. Panobinostat had detrimental effects within 10 hours of drug treatment, whereas the effects of the other LRAs were observed between 48 hours and 5 days. These observations suggest that scheduling of LRA and CD8+ T cell immunotherapy regimens may be critical for optimal clearance of the HIV-1 reservoir.

On inverse probability-weighted estimators in the presence of interference.

We consider inference about the causal effect of a treatment or exposure in the presence of interference, i.e., when one individual's treatment affects the outcome of another individual. In the observational setting where the treatment assignment mechanism is not known, inverse probability-weighted estimators have been proposed when individuals can be partitioned into groups such that there is no interference between individuals in different groups. Unfortunately this assumption, which is sometimes referred to as partial interference, may not hold, and moreover existing weighted estimators may have large variances. In this paper we consider weighted estimators that could be employed when interference is present. We first propose a generalized inverse probability-weighted estimator and two Hájek-type stabilized weighted estimators that allow any form of interference. We derive their asymptotic distributions and propose consistent variance estimators assuming partial interference. Empirical results show that one of the Hájek estimators can have substantially smaller finite-sample variance than the other estimators. The different estimators are illustrated using data on the effects of rotavirus vaccination in Nicaragua.

Administration of vorinostat disrupts HIV-1 latency in patients on antiretroviral therapy.

Despite antiretroviral therapy, proviral latency of human immunodeficiency virus type 1 (HIV-1) remains a principal obstacle to curing the infection. Inducing the expression of latent genomes within resting CD4(+) T cells is the primary strategy to clear this reservoir. Although histone deacetylase inhibitors such as suberoylanilide hydroxamic acid (also known as vorinostat, VOR) can disrupt HIV-1 latency in vitro, the utility of this approach has never been directly proven in a translational clinical study of HIV-infected patients. Here we isolated the circulating resting CD4(+) T cells of patients in whom viraemia was fully suppressed by antiretroviral therapy, and directly studied the effect of VOR on this latent reservoir. In each of eight patients, a single dose of VOR increased both biomarkers of cellular acetylation, and simultaneously induced an increase in HIV RNA expression in resting CD4(+) cells (mean increase, 4.8-fold). This demonstrates that a molecular mechanism known to enforce HIV latency can be therapeutically targeted in humans, provides proof-of-concept for histone deacetylase inhibitors as a therapeutic class, and defines a precise approach to test novel strategies to attack and eradicate latent HIV infection directly.

Obesity is associated with impaired immune response to influenza vaccination in humans.

BACKGROUND: Obesity is an independent risk factor for morbidity and mortality from pandemic influenza H1N1. Influenza is a significant public health threat, killing an estimated 250,000-500,000 people worldwide each year. More than one in ten of the world's adult population is obese and more than two-thirds of the US adult population is overweight or obese. No studies have compared humoral or cellular immune responses to influenza vaccination in healthy weight, overweight and obese populations despite clear public health importance. OBJECTIVE: The study employed a convenience sample to determine the antibody response to the 2009-2010 inactivated trivalent influenza vaccine (TIV) in healthy weight, overweight and obese participants at 1 and 12 months post vaccination. In addition, activation of CD8⁺ T cells and expression of interferon-γ and granzyme B were measured in influenza-stimulated peripheral blood mononuclear cell (PBMC) cultures. RESULTS: Body mass index (BMI) correlated positively with higher initial fold increase in IgG antibodies detected by enzyme-linked immunosorbent assay to TIV, confirmed by HAI antibody in a subset study. However, 12 months post vaccination, higher BMI was associated with a greater decline in influenza antibody titers. PBMCs challenged ex vivo with vaccine strain virus, demonstrated that obese individuals had decreased CD8⁺ T-cell activation and decreased expression of functional proteins compared with healthy weight individuals. CONCLUSION: These results suggest obesity may impair the ability to mount a protective immune response to influenza virus.

Discrete-time semi-Markov modeling of human papillomavirus persistence.

Multi-state modeling is often employed to describe the progression of a disease process. In epidemiological studies of certain diseases, the disease state is typically only observed at periodic clinical visits, producing incomplete longitudinal data. In this paper we consider fitting semi-Markov models to estimate the persistence of human papillomavirus (HPV) type-specific infection in studies where the status of HPV type(s) is assessed periodically. Simulation study results are presented indicating that the semi-Markov estimator is more accurate than an estimator currently used in the HPV literature. The methods are illustrated using data from the HIV Epidemiology Research Study.

Nonparametric inference for competing risks current status data with continuous, discrete or grouped observation times.

New methods and theory have recently been developed to nonparametrically estimate cumulative incidence functions for competing risks survival data subject to current status censoring. In particular, the limiting distribution of the nonparametric maximum likelihood estimator and a simplified naive estimator have been established under certain smoothness conditions. In this paper, we establish the large-sample behaviour of these estimators in two additional models, namely when the observation time distribution has discrete support and when the observation times are grouped. These asymptotic results are applied to the construction of confidence intervals in the three different models. The methods are illustrated on two datasets regarding the cumulative incidence of different types of menopause from a cross-sectional sample of women in the United States and subtype-specific HIV infection from a sero-prevalence study in injecting drug users in Thailand.

Nonparametric maximum likelihood estimation for competing risks survival data subject to interval censoring and truncation.

We derive the nonparametric maximum likelihood estimate (NPMLE) of the cumulative incidence functions for competing risks survival data subject to interval censoring and truncation. Since the cumulative incidence function NPMLEs give rise to an estimate of the survival distribution which can be undefined over a potentially larger set of regions than the NPMLE of the survival function obtained ignoring failure type, we consider an alternative pseudolikelihood estimator. The methods are then applied to data from a cohort of injecting drug users in Thailand susceptible to infection from HIV-1 subtypes B and E.

A Markov model for measuring vaccine efficacy for both susceptibility to infection and reduction in infectiousness for prophylactic HIV vaccines.

We use a discrete-time non-homogeneous Markov chain to model data from augmented human immunodeficiency virus (HIV) vaccine trials. For this design, the study population consists of primary participants some of whom have steady sexual partners who are also enrolled to augment the trial. The state space consists of the infection status of primary participants without steady partners and the infection status of both persons in the steady partnerships. The transition probabilities are functions of the two parameters: vaccine efficacy for susceptibility (VES) and infectiousness (VEI). We use likelihood methods to estimate VES and VEI from time-to-event data. We then use stochastic simulations to explore the bias and precision of the estimators under various plausible conditions for HIV vaccine trials. We show that both the VES and VEI are estimable with reasonable precision for the conditions that may exist for planned HIV vaccine trials. We show that exams conducted every six months will likely provide sufficient information to estimate the VE parameters accurately, and that there is little gain in precision for more frequent exams. Finally, we show that joint estimation of the VES and VEI will likely be feasible in a currently planned HIV vaccine trial among injecting drug users in Bangkok, Thailand, if one augments the information about the primary participants in the trial with information about their steady sexual partners.