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In randomized clinical trials, researchers are often interested in identifying an inexpensive intermediate study endpoint (typically a biomarker) that is a strong effect modifier of the treatment effect on a longer-term clinical endpoint of interest. Motivated by randomized placebo-controlled preventive vaccine efficacy trials, within the principal stratification framework a pseudo-score type estimator has been proposed to estimate disease risks conditional on the counter-factual biomarker of interest under each treatment assignment to vaccine or placebo, yielding an estimator of biomarker conditional vaccine efficacy. This method can be used for trial designs that use baseline predictors of the biomarker and/or designs that vaccinate disease-free placebo recipients at the end of the trial. In this article, we utilize the pseudo-score estimator to estimate the biomarker conditional vaccine efficacy adjusting for baseline covariates. We also propose a perturbation resampling method for making simultaneous inference on conditional vaccine efficacy over the values of the biomarker. We illustrate our method with datasets from two phase 3 dengue vaccine efficacy trials.

Despite the recent success of antiretrovirals for HIV prevention, additional, more effective, or more acceptable biomedical interventions will ultimately be needed to end the HIV epidemic. Designing clinical trials to evaluate the efficacy of new products that reduce HIV infection risk is challenging because of the existence of highly effective interventions to prevent HIV. However, the implementation of these interventions is uneven, and the fact that multiple HIV prevention efficacy trials are currently evaluating new products means the field confronts uncertainty in the emerging standard of prevention. In this Viewpoint, we take stock of the current state of HIV prevention, and subsequently discuss the key challenges in designing future trials to evaluate the next generation of HIV prevention products. We also highlight gaps in the knowledge base that need to be addressed to advance the design of research. Future trials are tenable, even in the context of existing and effective interventions, and should involve careful statistical approaches and multidisciplinary collaborative design., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

The CYD-TDV vaccine is licensed in multiple endemic countries based on vaccine efficacy (VE) against symptomatic, virologically confirmed dengue demonstrated in two phase 3 trials (CYD14, 2- to 14-year-olds, Asia; CYD15, 9- to 16-year-olds, Latin America). 50% plaque reduction neutralization test (PRNT 50 ) titers at baseline and month 13 (post-vaccination) were associated with VE and may enable bridging VE to adults. Two phase 2 trials of CYD-TDV measured baseline and month 13 PRNT 50 titers: CYD22 (9- to 45-year-olds, Vietnam) and CYD47 (18- to 45-year-olds, India). 50% plaque reduction neutralization test distributions were compared between age cohorts, and four versions of an epidemiological bridging method were used to estimate VE against any serotype (dengue virus [DENV]-Any) and against each serotype over 25 months post first vaccination in a hypothetical CYD14 + CYD15 18- to 45-year-old cohort (bridging population 1) and in the actual CYD47 18- to 45-year-old cohort (bridging population 2). Baseline and month 13 geometric mean PRNT 50 titers to each serotype were significantly greater in 18- to 45-year-olds than 9- to 16-year-olds for all comparisons. The four methods estimated VE against DENV-Any at 75.3-86.0% (95% CIs spanning 52.5-100%) for bridging population 1 and 68.4-77.5% (95% CIs spanning 42.3-88.5%) for bridging population 2. The vaccine efficacy against serotype 1, 2, 3, and 4 was estimated at 56.9-76.9%, 68.3-85.8%, 91.4-95.0%, and 93.2-100% (bridging population 1) and 44.5-66.9%, 53.2-69.2%, 79.8-92.0%, and 90.6-95.0% (bridging population 2), respectively; thus, CYD-TDV would likely confer improved efficacy in adults than 9- to 16-year-olds. Using the same methods, we predicted VE against hospitalized DENV-Any over 72 months of follow-up, with estimates 59.1-73.5% (95% CIs spanning 40.9-92.2%) for bridging population 1 and 50.9-65.9% (95% CIs spanning 38.1-82.1%) for bridging population 2.

An important objective in vaccine studies entails identifying an immune response which is predictive of disease risk. Nonparametric methods are developed for inference on immune response thresholds that are associated with specified levels of disease risk, including where the risk level is zero. This threshold is defined as the minimum immune response value above which disease risk is less than or equal to the desired level. The proposed nonparametric methods are compared to previously developed parametric methods in simulation studies. The methods are extended for use in studies that only measure the immune response in a subset of participants, such as case-cohort or case-control studies, and with right censored time to disease outcomes. Finally, these methods are used to estimate neutralizing antibody thresholds for virologically confirmed dengue risk using data from two recent dengue vaccine trials.

Background: High hemagglutination inhibition (HAI) and neuraminidase inhibition (NAI) titers are generally associated with reduced influenza risk. While repeated influenza vaccination reduces seroresponse, vaccine effectiveness is not always reduced., Methods: During the 2007-2008 influenza season, a randomized, placebo-controlled trial (FLUVACS) evaluated the efficacies of live-attenuated (LAIV) and inactivated influenza vaccines (IIV) among healthy adults aged 18-49 in Michigan; IIV vaccine efficacy (VE) and LAIV VE against influenza disease were estimated at 68% and 36%. Using the principal stratification/VE moderation framework, we analyzed data from this trial to assess how each VE varied by HAI or NAI responses to vaccination observed for vaccinated individuals and predicted counterfactually for placebo recipients. We also assessed how each VE varied with pre-vaccination/baseline variables including HAI titer, NAI titer, and vaccination history., Results: IIV VE appeared to increase with Day 30 post-vaccination HAI titer, albeit not significantly (p=0.20 and estimated VE 14.4%, 70.5%, and 85.5% at titer below the assay lower quantification limit, 512, and 4096 (maximum)). Moreover, IIV VE increased significantly with Day 30 post-vaccination NAI titer (p=0.040), with estimated VE zero at titer 10 and 92.2% at highest titer 640. There was no evidence that fold-change in post-vaccination HAI or NAI titer associated with IIV VE (p=0.76, 0.38). For LAIV, there was no evidence that VE associated with post-vaccination or fold-rise HAI or NAI titers (p-values >0.40). For IIV, VE increased with increasing baseline NAI titer in those previously vaccinated, but VE decreased with increasing baseline NAI titer in those previously unvaccinated. In contrast, for LAIV, VE did not depend on previous vaccination or baseline HAI or NAI titer., Conclusions: Future efficacy trials should measure baseline and post-vaccination antibody titers in both vaccine and control/placebo recipients, enabling analyses to better elucidate correlates of vaccine- and natural-protection., Trial Registration: ClinicalTrials.gov NCT00538512. October 1, 2007.

The broadly neutralizing antibody (bnAb) VRC01 is being evaluated for its efficacy to prevent HIV-1 infection in the Antibody Mediated Prevention (AMP) trials. A secondary objective of AMP utilizes sieve analysis to investigate how VRC01 prevention efficacy (PE) varies with HIV-1 envelope (Env) amino acid (AA) sequence features. An exhaustive analysis that tests how PE depends on every AA feature with sufficient variation would have low statistical power. To design an adequately powered primary sieve analysis for AMP, we modeled VRC01 neutralization as a function of Env AA sequence features of 611 HIV-1 gp160 pseudoviruses from the CATNAP database, with objectives: (1) to develop models that best predict the neutralization readouts; and (2) to rank AA features by their predictive importance with classification and regression methods. The dataset was split in half, and machine learning algorithms were applied to each half, each analyzed separately using cross-validation and hold-out validation. We selected Super Learner, a nonparametric ensemble-based cross-validated learning method, for advancement to the primary sieve analysis. This method predicted the dichotomous resistance outcome of whether the IC50 neutralization titer of VRC01 for a given Env pseudovirus is right-censored (indicating resistance) with an average validated AUC of 0.868 across the two hold-out datasets. Quantitative log IC50 was predicted with an average validated R2 of 0.355. Features predicting neutralization sensitivity or resistance included 26 surface-accessible residues in the VRC01 and CD4 binding footprints, the length of gp120, the length of Env, the number of cysteines in gp120, the number of cysteines in Env, and 4 potential N-linked glycosylation sites; the top features will be advanced to the primary sieve analysis. This modeling framework may also inform the study of VRC01 in the treatment of HIV-infected persons., Competing Interests: The authors have declared that no competing interests exist.

The RV144 vaccine trial showed reduced risk of HIV-1 acquisition by 31.2%, although mechanisms that led to protection remain poorly understood. Here we identify transcriptional correlates for reduced HIV-1 acquisition after vaccination. We assess the transcriptomic profile of blood collected from 223 participants and 40 placebo recipients. Pathway-level analysis of HIV-1 negative vaccinees reveals that type I interferons that activate the IRF7 antiviral program and type II interferon-stimulated genes implicated in antigen-presentation are both associated with a reduced risk of HIV-1 acquisition. In contrast, genes upstream and downstream of NF-κB, mTORC1 and host genes required for viral infection are associated with an increased risk of HIV-1 acquisition among vaccinees and placebo recipients, defining a vaccine independent association with HIV-1 acquisition. Our transcriptomic analysis of RV144 trial samples identifies IRF7 as a mediator of protection and the activation of mTORC1 as a correlate of the risk of HIV-1 acquisition.

This paper examines the accelerated failure time competing risks model with missing cause of failure using the monotone class rank-based estimating equations approach. We handle the non-smoothness of the rank-based estimating equations using a kernel smoothed estimation method, and estimate the unknown selection probability and the conditional expectation by non-parametric techniques. Under this setup, we propose three methods for estimating the unknown regression parameters based on 1) inverse probability weighting, 2) estimating equations imputation and 3) augmented inverse probability weighting. We also obtain the associated asymptotic theories of the proposed estimators and investigate the estimators' small sample behaviour in a simulation study. A direct plug-in method is suggested for estimating the asymptotic variances of the proposed estimators. A real data application based on a HIV vaccine efficacy trial study is considered.

When available, vaccines are an effective means of disease prevention. Unfortunately, efficacious vaccines have not yet been developed for several major infectious diseases, including HIV and malaria. Vaccine sieve analysis studies whether and how the efficacy of a vaccine varies with the genetics of the pathogen of interest, which can guide subsequent vaccine development and deployment. In sieve analyses, the effect of the vaccine on the cumulative incidence corresponding to each of several possible genotypes is often assessed within a competing risks framework. In the context of clinical trials, the estimators employed in these analyses generally do not account for covariates, even though the latter may be predictive of the study endpoint or censoring. Motivated by two recent preventive vaccine efficacy trials for HIV and malaria, we develop new methodology for vaccine sieve analysis. Our approach offers improved validity and efficiency relative to existing approaches by allowing covariate adjustment through ensemble machine learning. We derive results that indicate how to perform statistical inference using our estimators. Our analysis of the HIV and malaria trials shows markedly increased precision -- up to doubled efficiency in both trials -- under more plausible assumptions compared with standard methodology. Our findings provide greater evidence for vaccine sieve effects in both trials.

Four randomized placebo-controlled efficacy trials of a candidate vaccine or passively infused monoclonal antibody for prevention of HIV-1 infection are underway (HVTN 702 in South African men and women; HVTN 705 in sub-Saharan African women; HVTN 703/HPTN 081 in sub-Saharan African women; HVTN 704/HPTN 085 in U.S., Peruvian, Brazilian, and Swiss men or transgender persons who have sex with men). Several challenges are posed to the optimal design of the sequel efficacy trials, including: (1) how to account for the evolving mosaic of effective prevention interventions that may be part of the trial design or standard of prevention; (2) how to define viable and optimal sequel trial designs depending on the primary efficacy results and secondary "correlates of protection" results of each of the ongoing trials; and (3) how to define the primary objective of sequel efficacy trials if HIV-1 incidence is expected to be very low in all study arms such that a standard trial design has a steep opportunity cost. After summarizing the ongoing trials, I discuss statistical science considerations for sequel efficacy trial designs, both generally and specifically to each trial listed above. One conclusion is that the results of "correlates of protection" analyses, which ascertain how different host immunological markers and HIV-1 viral features impact HIV-1 risk and prevention efficacy, have an important influence on sequel trial design. This influence is especially relevant for the monoclonal antibody trials because of the focused pre-trial hypothesis that potency and coverage of serum neutralization constitutes a surrogate endpoint for HIV-1 infection. Another conclusion is that while assessing prevention efficacy against a counterfactual placebo group is fraught with risks for bias, such analysis is nonetheless important and study designs coupled with analysis methods should be developed to optimize such inferences. I draw a parallel with non-inferiority designs, which are fraught with risks given the necessity of making unverifiable assumptions for interpreting results, but nevertheless have been accepted when a superiority design is not possible and a rigorous/conservative non-inferiority margin is used. In a similar way, counterfactual placebo group efficacy analysis should use rigorous/conservative inference techniques that formally build in a rigorous/conservative margin to potential biases that could occur due to departures from unverifiable assumptions. Because reliability of this approach would require new techniques for verifying that the study cohort experienced substantial exposure to HIV-1, currently it may be appropriate as a secondary objective but not as a primary objective., Competing Interests: Conflict of interest statement: The author has no potential conflicts of interest to declare.

Objective: To evaluate the association of rainy season with overall dengue disease incidence and with the efficacy of the Sanofi Pasteur recombinant, live, attenuated, tetravalent vaccine (CYD-TDV) in two randomized, controlled multicenter phase III clinical trials in Asia and Latin America., Methods: Rainy seasons were defined for each study site using climatological information from the World Meteorological Organization. The dengue attack rate in the placebo group for each study month was calculated as the number of symptomatic, virologically-confirmed dengue events in a given month divided by the number of participants at risk in the same month. Time-dependent Cox proportional hazard models were used to test whether rainy season was associated with dengue disease and whether it modified vaccine efficacy in each of the two trials and in both of the trials combined., Findings: Rainy season, country, and age were all significantly associated with dengue disease in both studies. Vaccine efficacy did not change during the rainy season in any of the analyses., Conclusions: Although dengue transmission and exposure are expected to increase during the rainy season, our results indicate that CYD-TDV vaccine efficacy remains constant throughout the year in endemic regions., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests; ZM, MEH and PG were funded by contracts from Sanofi Pasteur. EL, RLO, MC, CF and LC are employees of Sanofi Pasteur. GC was employed as a Principal Investigator Coordinator by Fundacion Santa Fe de Bogotá who were contracted by Sanofi Pasteur to conduct the CYD15 study at five of the nine sites in Colombia. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

A common scientific problem is to determine a surrogate outcome for a long-term outcome so that future randomized studies can restrict themselves to only collecting the surrogate outcome. We consider the setting that we observe n independent and identically distributed observations of a random variable consisting of baseline covariates, a treatment, a vector of candidate surrogate outcomes at an intermediate time point, and the final outcome of interest at a final time point. We assume the treatment is randomized, conditional on the baseline covariates. The goal is to use these data to learn a most-promising surrogate for use in future trials for inference about a mean contrast treatment effect on the final outcome. We define an optimal surrogate for the current study as the function of the data generating distribution collected by the intermediate time point that satisfies the Prentice definition of a valid surrogate endpoint and that optimally predicts the final outcome: this optimal surrogate is an unknown parameter. We show that this optimal surrogate is a conditional mean and present super-learner and targeted super-learner based estimators, whose predicted outcomes are used as the surrogate in applications. We demonstrate a number of desirable properties of this optimal surrogate and its estimators, and study the methodology in simulations and an application to dengue vaccine efficacy trials., (© 2018 The Authors. Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.)

Using Super Learner, a machine learning statistical method, we assessed varicella zoster virus-specific glycoprotein-based enzyme-linked immunosorbent assay (gpELISA) antibody titer as an individual-level signature of herpes zoster (HZ) risk in the Zostavax Efficacy and Safety Trial. Gender and pre- and postvaccination gpELISA titers had moderate ability to predict whether a 50-59 year old experienced HZ over 1-2 years of follow-up, with equal classification accuracy (cross-validated area under the receiver operator curve = 0.65) for vaccine and placebo recipients. Previous analyses suggested that fold-rise gpELISA titer is a statistical correlate of protection and supported the hypothesis that it is not a mechanistic correlate of protection. Our results also support this hypothesis.

Two phase 3 placebo-controlled trials of the CYD-TDV vaccine, evaluated in children aged 2-14 y (CYD14) and 9-16 y (CYD15), demonstrated vaccine efficacy (VE) of 56.5% and 60.8%, respectively, against symptomatic virologically confirmed dengue (VCD). Sieve analyses were conducted to evaluate whether and how VE varied with amino acid sequence features of dengue viruses (DENVs). DENV premembrane/envelope amino acid sequences from VCD endpoint cases were aligned with the vaccine insert sequences, and extensions of the proportional hazards model were applied to assess variation in VE with amino acid mismatch proportion distances from vaccine strains, individual amino acid residues, and phylogenetic genotypes. In CYD14, VE against VCD of any serotype (DENV-Any) decreased significantly with increasing amino acid distance from the vaccine, whereas in CYD15, VE against DENV-Any was distance-invariant. Restricting to the common age range and amino acid distance range between the trials and accounting for differential VE by serotype, however, showed no evidence of VE variation with distance in either trial. In serotype-specific analyses, VE against DENV4 decreased significantly with increasing amino acid distance from the DENV4 vaccine insert and was significantly greater against residue-matched DENV4 at eight signature positions. These effects were restricted to 2- to 8-y-olds, potentially because greater seropositivity of older children at baseline might facilitate a broader protective immune response. The relevance of an antigenic match between vaccine strains and circulating DENVs was also supported by greater estimated VE against serotypes and genotypes for which the circulating DENVs had shorter amino acid sequence distances from the vaccine., Competing Interests: Conflict of interest statement: Y.G.-C., E.L., C.F., B.G., and N.J. are employees of Sanofi Pasteur. M.J., C.A.M., J.S., L.N.C., A.J.F.-G., P.T.E., and P.B.G. received a contract from Sanofi Pasteur to conduct the statistical analysis work. This work was supported by Sanofi Pasteur and the US National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services, under award number R37AI054165.

As oral tenofovir-based regimens for preexposure prophylaxis (PrEP) are adopted as standard of care for HIV prevention, their utilization in clinical trials among women in southern Africa will require an accurate estimate of oral PrEP efficacy in this population. This information is critical for women in choosing this prevention strategy, and in public health policy making. Estimates of the efficacy of oral PrEP regimens containing tenofovir have varied widely across trials that enrolled women, with some studies reporting high efficacy and others reporting no efficacy. Although poor adherence is strongly associated with lack of efficacy, other factors, such as mode of transmission (sexual vs. parenteral), predominant HIV subtype (C vs. non-C), intensity of exposure, and percentage of stable serodiscordant couples, may also contribute to the variation in efficacy estimates. In this article, we evaluate the evidence for PrEP efficacy in women and propose potential explanations for the observed differences in efficacy among studies. Our review emphasizes the need to continue to refine estimates of efficacy and effectiveness of tenofovir-based oral PrEP so as to best develop the next generation of HIV prevention tools, and to inform public policies directed toward HIV prevention.

Background: In efficacy trials of a tetravalent dengue vaccine (CYD-TDV), excess hospitalizations for dengue were observed among vaccine recipients 2 to 5 years of age. Precise risk estimates according to observed dengue serostatus could not be ascertained because of the limited numbers of samples collected at baseline. We developed a dengue anti-nonstructural protein 1 (NS1) IgG enzyme-linked immunosorbent assay and used samples from month 13 to infer serostatus for a post hoc analysis of safety and efficacy., Methods: In a case-cohort study, we reanalyzed data from three efficacy trials. For the principal analyses, we used baseline serostatus determined on the basis of measured (when baseline values were available) or imputed (when baseline values were missing) titers from a 50% plaque-reduction neutralization test (PRNT 50 ), with imputation conducted with the use of covariates that included the month 13 anti-NS1 assay results. The risk of hospitalization for virologically confirmed dengue (VCD), of severe VCD, and of symptomatic VCD according to dengue serostatus was estimated by weighted Cox regression and targeted minimum loss-based estimation., Results: Among dengue-seronegative participants 2 to 16 years of age, the cumulative 5-year incidence of hospitalization for VCD was 3.06% among vaccine recipients and 1.87% among controls, with a hazard ratio (vaccine vs. control) through data cutoff of 1.75 (95% confidence interval [CI], 1.14 to 2.70). Among dengue-seronegative participants 9 to 16 years of age, the cumulative incidence of hospitalization for VCD was 1.57% among vaccine recipients and 1.09% among controls, with a hazard ratio of 1.41 (95% CI, 0.74 to 2.68). Similar trends toward a higher risk among seronegative vaccine recipients than among seronegative controls were also found for severe VCD. Among dengue-seropositive participants 2 to 16 years of age and those 9 to 16 years of age, the cumulative incidence of hospitalization for VCD was 0.75% and 0.38%, respectively, among vaccine recipients and 2.47% and 1.88% among controls, with hazard ratios of 0.32 (95% CI, 0.23 to 0.45) and 0.21 (95% CI, 0.14 to 0.31). The risk of severe VCD was also lower among seropositive vaccine recipients than among seropositive controls., Conclusions: CYD-TDV protected against severe VCD and hospitalization for VCD for 5 years in persons who had exposure to dengue before vaccination, and there was evidence of a higher risk of these outcomes in vaccinated persons who had not been exposed to dengue. (Funded by Sanofi Pasteur; ClinicalTrials.gov numbers, NCT00842530 , NCT01983553 , NCT01373281 , and NCT01374516 .).

In HIV vaccine studies, a major research objective is to identify immune response biomarkers measured longitudinally that may be associated with risk of HIV infection. This objective can be assessed via joint modeling of longitudinal and survival data. Joint models for HIV vaccine data are complicated by the following issues: (i) left truncations of some longitudinal data due to lower limits of quantification; (ii) mixed types of longitudinal variables; (iii) measurement errors and missing values in longitudinal measurements; (iv) computational challenges associated with likelihood inference. In this article, we propose a joint model of complex longitudinal and survival data and a computationally efficient method for approximate likelihood inference to address the foregoing issues simultaneously. In particular, our model does not make unverifiable distributional assumptions for truncated values, which is different from methods commonly used in the literature. The parameters are estimated based on the h-likelihood method, which is computationally efficient and offers approximate likelihood inference. Moreover, we propose a new approach to estimate the standard errors of the h-likelihood based parameter estimates by using an adaptive Gauss-Hermite method. Simulation studies show that our methods perform well and are computationally efficient. A comprehensive data analysis is also presented.

Background: Modest efficacy was reported for the HIV vaccine tested in the RV144 trial, which comprised a canarypox vector (ALVAC) and envelope (env) glycoprotein (gp120). These vaccine components were adapted to express HIV-1 antigens from strains circulating in South Africa, and the adjuvant was changed to increase immunogenicity. Furthermore, 12-month immunisation was added to improve durability. In the HIV Vaccine Trials Network (HVTN) 100 trial, we aimed to assess this new regionally adapted regimen for advancement to efficacy testing., Methods: HVTN 100 is a phase 1/2, randomised controlled, double-blind trial at six community research sites in South Africa. We randomly allocated adults (aged 18-40 years) without HIV infection and at low risk of HIV infection to either the vaccine regimen (intramuscular injection of ALVAC-HIV vector [vCP2438] at 0, 1, 3, 6, and 12 months plus bivalent subtype C gp120 and MF59 adjuvant at 3, 6, and 12 months) or placebo, in a 5:1 ratio. Randomisation was done by computer-generated list. Participants, investigators, and those assessing outcomes were masked to random assignments. Primary outcomes included safety and immune responses associated with correlates of HIV risk in RV144, 2 weeks after vaccination at 6 months (month 6·5). We compared per-protocol participants (ie, those who completed the first four vaccinations and provided samples at month 6·5) from HVTN 100 with stored RV144 samples assayed contemporaneously. This trial is registered with the South African National Clinical Trials Registry (DOH-27-0215-4796) and ClinicalTrials.gov (NCT02404311)., Findings: Between Feb 9, 2015, and May 26, 2015, 252 participants were enrolled, of whom 210 were assigned vaccine and 42 placebo. 222 participants were included in the per-protocol analysis (185 vaccine and 37 placebo). 185 (100%) vaccine recipients developed IgG binding antibodies to all three vaccine-matched gp120 antigens with significantly higher titres (3·6-8·8 fold; all p<0·0001) than the corresponding vaccine-matched responses of RV144. The CD4+ T-cell response to the ZM96.C env protein in HVTN 100 was 56·4% (n=102 responders), compared with a response of 41·4% (n=79 responders) to 92TH023.AE in RV144 (p=0·0050). The IgG response to the 1086.C variable loops 1 and 2 (V1V2) env antigen in HVTN 100 was 70·5% (95% CI 63·5-76·6; n=129 responders), lower than the response to V1V2 in RV144 (99·0%, 95% CI 96·4-99·7; n=199 responders)., Interpretation: Although the IgG response to the HVTN 100 vaccine was lower than that reported in RV144, it exceeded the predicted 63% threshold needed for 50% vaccine efficacy using a V1V2 correlate of protection model. Thus, the subtype C HIV vaccine regimen qualified for phase 2b/3 efficacy testing, a critical next step of vaccine development., Funding: US National Institute of Allergy and Infectious Diseases (NIAID), and Bill & Melinda Gates Foundation., (Copyright © 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

The cumulative incidence function quantifies the probability of failure over time due to a specific cause for competing risks data. The generalized semiparametric regression models for the cumulative incidence functions with missing covariates are investigated. The effects of some covariates are modeled as non-parametric functions of time while others are modeled as parametric functions of time. Different link functions can be selected to add flexibility in modeling the cumulative incidence functions. The estimation procedures based on the direct binomial regression and the inverse probability weighting of complete cases are developed. This approach modifies the full data weighted least squares equations by weighting the contributions of observed members through the inverses of estimated sampling probabilities which depend on the censoring status and the event types among other subject characteristics. The asymptotic properties of the proposed estimators are established. The finite-sample performances of the proposed estimators and their relative efficiencies under different two-phase sampling designs are examined in simulations. The methods are applied to analyze data from the RV144 vaccine efficacy trial to investigate the associations of immune response biomarkers with the cumulative incidence of HIV-1 infection.

This article develops hypothesis testing procedures for the stratified mark-specific proportional hazards model with missing covariates where the baseline functions may vary with strata. The mark-specific proportional hazards model has been studied to evaluate mark-specific relative risks where the mark is the genetic distance of an infecting HIV sequence to an HIV sequence represented inside the vaccine. This research is motivated by analyzing the RV144 phase 3 HIV vaccine efficacy trial, to understand associations of immune response biomarkers on the mark-specific hazard of HIV infection, where the biomarkers are sampled via a two-phase sampling nested case-control design. We test whether the mark-specific relative risks are unity and how they change with the mark. The developed procedures enable assessment of whether risk of HIV infection with HIV variants close or far from the vaccine sequence are modified by immune responses induced by the HIV vaccine; this question is interesting because vaccine protection occurs through immune responses directed at specific HIV sequences. The test statistics are constructed based on augmented inverse probability weighted complete-case estimators. The asymptotic properties and finite-sample performances of the testing procedures are investigated, demonstrating double-robustness and effectiveness of the predictive auxiliaries to recover efficiency. The finite-sample performance of the proposed tests are examined through a comprehensive simulation study. The methods are applied to the RV144 trial., (© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Promising multi-dose HIV vaccine regimens are being tested in trials in South Africa. We estimated the potential epidemiological and economic impact of HIV vaccine campaigns compared to continuous vaccination, assuming that vaccine efficacy is transient and dependent on immune response. We used a dynamic economic mathematical model of HIV transmission calibrated to 2012 epidemiological data to simulate vaccination with anticipated antiretroviral treatment scale-up in South Africa. We estimate that biennial vaccination with a 70% efficacious vaccine reaching 20% of the sexually active population could prevent 480,000-650,000 HIV infections (13.8-15.3% of all infections) over 10 years. Assuming a launch price of $15 per dose, vaccination was found to be cost-effective, with an incremental cost-effectiveness ratio of $13,746 per quality-adjusted life-year as compared to no vaccination. Increasing vaccination coverage to 50% will prevent more infections but is less likely to achieve cost-effectiveness. Campaign vaccination is consistently more effective and costs less than continuous vaccination across scenarios. Results suggest that a partially effective HIV vaccine will have substantial impact on the HIV epidemic in South Africa and offer good value if priced less than $105 for a five-dose series. Vaccination campaigns every two years may offer greater value for money than continuous vaccination reaching the same coverage level.

Background: HVTN 505 was a human immunodeficiency virus type 1 (HIV-1) preventive vaccine efficacy trial of a DNA/recombinant adenovirus serotype 5 (rAd5) vaccine regimen. We assessed antibody responses measured 1 month after final vaccination (month 7) as correlates of HIV-1 acquisition risk., Methods: Binding antibody responses were quantified in serum samples from 25 primary endpoint vaccine cases (diagnosed with HIV-1 infection between month 7 and month 24) and 125 randomly sampled frequency-matched vaccine controls (HIV-1 negative at month 24). We prespecified for a primary analysis tier 6 antibody response biomarkers that measure immunoglobulin G (IgG) and immunoglobulin A (IgA) binding to Env proteins and 2 previously assessed T-cell response biomarkers., Results: Envelope-specific IgG responses were significantly correlated with decreased HIV-1 risk. Moreover, the interaction of IgG responses and Env-specific CD8+ T-cell polyfunctionality score had a highly significant association with HIV-1 risk after adjustment for multiple comparisons., Conclusions: Vaccinees with higher levels of Env IgG have significantly decreased HIV-1 risk when CD8+ T-cell responses are low. Moreover, vaccinees with high CD8+ T-cell responses generally have low risk, and those with low CD8+ T-cell and low Env antibody responses have high risk. These findings suggest the critical importance of inducing a robust IgG Env response when the CD8+ T-cell response is low.

Background: In the CYD14 and CYD15 Phase 3 trials of the CYD-TDV dengue vaccine, estimated vaccine efficacy (VE) against symptomatic, virologically confirmed dengue (VCD) occurring between months 13 and 25 was 56.5% and 60.8%, respectively., Methods: Neutralizing antibody titers to the 4 dengue serotypes in the CYD-TDV vaccine insert were measured at month 13 in a randomly sampled immunogenicity subcohort and in all VCD cases through month 25 (2848 vaccine, 1574 placebo) and studied for their association with VCD and with the level of VE to prevent VCD., Results: For each trial and serotype, vaccinees with higher month 13 titer to the serotype had significantly lower risk of VCD with that serotype (hazard ratios, 0.19-0.43 per 10-fold increase). Moreover, for each trial, vaccinees with higher month 13 average titer to the 4 serotypes had significantly higher VE against VCD of any serotype (P < .001)., Conclusions: Neutralizing antibody titers postdose 3 correlate with CYD-TDV VE to prevent dengue. High titers associate with high VE for all serotypes, baseline serostatus groups, age groups, and both trials. However, lowest titers do not fully correspond to zero VE, indicating that other factors influence VE., (© The Author(s) 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

Studying the incidence of rare events is both scientifically important and statistically challenging. When few events are observed, standard survival analysis estimators behave erratically, particularly if covariate adjustment is necessary. In these settings, it is possible to improve upon existing estimators by considering estimation in a bounded statistical model. This bounded model incorporates existing scientific knowledge about the incidence of an event in the population. Estimators that are guaranteed to agree with existing scientific knowledge on event incidence may exhibit superior behavior relative to estimators that ignore this knowledge. Focusing on the setting of competing risks, we propose estimators of cumulative incidence that are guaranteed to respect a bounded model and show that when few events are observed, the proposed estimators offer improvements over existing estimators in bias and variance. We illustrate the proposed estimators using data from a recent preventive HIV vaccine efficacy trial. Copyright © 2017 John Wiley & Sons, Ltd., (Copyright © 2017 John Wiley & Sons, Ltd.)

The Antibody Mediated Prevention trials are assessing whether intravenously-administered VRC01 (10 mg/kg or 30 mg/kg vs placebo) can prevent HIV infection. In a modeling exercise, we used two models to predict the overall prevention efficacy (PE) of each VRC01 dose in preventing HIV infection. For the first per-exposure PE model, parameters were estimated from studies where nonhuman primates (NHPs) were administered high-dose intra-rectal simian-human immunodeficiency virus challenge two days post-VRC01 infusion at various dosages ("NHP model"). To account for the fact that humans may require greater VRC01 concentration to achieve the same level of protection, we next assumed that a 5-fold greater VRC01 serum concentration would be needed to provide the same level of per-exposure PE as seen in the NHP data ("5-fold model"). For the 10 mg/kg regimen, the 5-fold and NHP models predict an overall PE of 37% and 64%, respectively; for the 30 mg/kg regimen, the two models predict an overall PE of 53% and 82%, respectively. Our results support that VRC01 may plausibly confer positive PE in the AMP trials. Given the lack of available knowledge and data to verify the assumptions undergirding our modeling framework, its quantitative predictions of overall PE are preliminary. Its current main applications are to supplement decisions to advance mAb regimens to efficacy trials, and to enable mAb regimen ranking by their potential for PE in humans.

Doubly robust estimators are widely used to draw inference about the average effect of a treatment. Such estimators are consistent for the effect of interest if either one of two nuisance parameters is consistently estimated. However, if flexible, data-adaptive estimators of these nuisance parameters are used, double robustness does not readily extend to inference. We present a general theoretical study of the behaviour of doubly robust estimators of an average treatment effect when one of the nuisance parameters is inconsistently estimated. We contrast different methods for constructing such estimators and investigate the extent to which they may be modified to also allow doubly robust inference. We find that while targeted minimum loss-based estimation can be used to solve this problem very naturally, common alternative frameworks appear to be inappropriate for this purpose. We provide a theoretical study and a numerical evaluation of the alternatives considered. Our simulations highlight the need for and usefulness of these approaches in practice, while our theoretical developments have broad implications for the construction of estimators that permit doubly robust inference in other problems.

Although the HVTN 505 DNA/recombinant adenovirus type 5 vector HIV-1 vaccine trial showed no overall efficacy, analysis of breakthrough HIV-1 sequences in participants can help determine whether vaccine-induced immune responses impacted viruses that caused infection. We analyzed 480 HIV-1 genomes sampled from 27 vaccine and 20 placebo recipients and found that intra-host HIV-1 diversity was significantly lower in vaccine recipients (P ≤ 0.04, Q-values ≤ 0.09) in Gag, Pol, Vif and envelope glycoprotein gp120 (Env-gp120). Furthermore, Env-gp120 sequences from vaccine recipients were significantly more distant from the subtype B vaccine insert than sequences from placebo recipients (P = 0.01, Q-value = 0.12). These vaccine effects were associated with signatures mapping to CD4 binding site and CD4-induced monoclonal antibody footprints. These results suggest either (i) no vaccine efficacy to block acquisition of any viral genotype but vaccine-accelerated Env evolution post-acquisition; or (ii) vaccine efficacy against HIV-1s with Env sequences closest to the vaccine insert combined with increased acquisition due to other factors, potentially including the vaccine vector.

The HIV Vaccine Trials Network (HVTN) 087 vaccine trial assessed the effect of increasing doses of pIL-12 (interleukin-12 delivered as plasmid DNA) adjuvant on the immunogenicity of an HIV-1 multiantigen (MAG) DNA vaccine delivered by electroporation and boosted with a vaccine comprising an attenuated vesicular stomatitis virus expressing HIV-1 Gag (VSV-Gag). We randomized 100 healthy adults to receive placebo or 3 mg HIV-MAG DNA vaccine (ProfectusVax HIV-1 gag / pol or ProfectusVax nef / tat / vif , env ) coadministered with pIL-12 at 0, 250, 1,000, or 1,500 μg intramuscularly by electroporation at 0, 1, and 3 months followed by intramuscular inoculation with 3.4 × 10 7 PFU VSV-Gag vaccine at 6 months. Immune responses were assessed after the prime and boost and 6 months after the last vaccination. High-dose pIL-12 increased the magnitude of CD8 + T-cell responses postboost compared to no pIL-12 ( P = 0.02), while CD4 + T-cell responses after the prime were higher in the absence of pIL-12 than with low- and medium-dose pIL-12 ( P ≤ 0.05). The VSV boost increased Gag-specific CD4 + and CD8 + T-cell responses in all groups ( P < 0.001 for CD4 + T cells), inducing a median of four Gag epitopes in responders. Six to 9 months after the boost, responses decreased in magnitude, but CD8 + T-cell response rates were maintained. The addition of a DNA prime dramatically improved responses to the VSV vaccine tested previously in the HVTN 090 trial, leading to broad epitope targeting and maintained CD8 + T-cell response rates at early memory. The addition of high-dose pIL-12 given with a DNA prime by electroporation and boosted with VSV-Gag increased the CD8 + T-cell responses but decreased the CD4 + responses. This approach may be advantageous in reshaping the T-cell responses to a variety of chronic infections or tumors. (This study has been registered at ClinicalTrials.gov under registration no. NCT01578889.)., (Copyright © 2017 American Society for Microbiology.)

Background: Threshold regression models are a diverse set of non-regular regression models that all depend on change points or thresholds. They provide a simple but elegant and interpretable way to model certain kinds of nonlinear relationships between the outcome and a predictor., Results: The R package chngpt provides both estimation and hypothesis testing functionalities for four common variants of threshold regression models. All allow for adjustment of additional covariates not subjected to thresholding. We demonstrate the consistency of the estimating procedures and the type 1 error rates of the testing procedures by Monte Carlo studies, and illustrate their practical uses using an example from the study of immune response biomarkers in the context of Mother-To-Child-Transmission of HIV-1 viruses., Conclusion: chngpt makes several unique contributions to the software for threshold regression models and will make these models more accessible to practitioners interested in modeling threshold effects.

Summary: Analysis of HIV-1 virions from participants infected in a randomized controlled preventive HIV-1 vaccine efficacy trial can help elucidate mechanisms of partial protection. By comparing the genetic sequence of viruses from vaccine and placebo recipients to the sequence of the vaccine itself, a technique called 'sieve analysis', one can identify functional specificities of vaccine-induced immune responses. We have created an interactive web-based visualization and data access tool for exploring the results of sieve analyses performed on four major preventive HIV-1 vaccine efficacy trials: (i) the HIV Vaccine Trial Network (HVTN) 502/Step trial, (ii) the RV144/Thai trial, (iii) the HVTN 503/Phambili trial and (iv) the HVTN 505 trial. The tool acts simultaneously as a platform for rapid reinterpretation of sieve effects and as a portal for organizing and sharing the viral sequence data. Access to these valuable datasets also enables the development of novel methodology for future sieve analyses., Availability and Implementation: Visualization: http://sieve.fredhutch.org/viz . Source code: https://github.com/nkullman/SIEVE . Data API: http://sieve.fredhutch.org/data ., Contact: agartlan@fredhutch.org., (© The Author(s) 2017. Published by Oxford University Press.)

Background: A phase 1 trial of a clade B HIV vaccine in HIV-uninfected adults evaluated the safety and immunogenicity of a DNA prime co-expressing GM-CSF (Dg) followed by different numbers and intervals of modified vaccinia Ankara Boosts (M). Both vaccines produce virus-like particles presenting membrane-bound Env., Methods: Four US sites randomized 48 participants to receiving 1/10th the DNA dose as DgDgMMM given at 0, 2, 4, 6 and 8 months, or full dose DgDgM&#95;M or DgDgMM&#95;M regimens, given at 0, 2, 4, and 8 months, and 0, 2, 4, 6, and 10 months, respectively. Peak immunogenicity was measured 2 weeks post-last vaccination., Results: All regimens were well tolerated and safe. Full dose DgDgM&#95;M and DgDgMM&#95;M regimens generated Env-specific IgG to HIV-1 Env in >90%, IgG3 in >80%, and IgA in <20% of participants. Responses to gp140 and gp41 targets were more common and of higher magnitude than to gp120 and V1V2. The gp41 antibody included reactivity to the conserved immunodominant region with specificities known to mediate virus capture and phagocytosis and did not cross-react with a panel of intestinal flora antigens. The 3rd dose of MVA increased the avidity of elicited antibody (7.5% to 39%), the ADCC response to Bal gp120 (14% to 64%), and the one-year durability of the IgG3 responses to gp41 by 4-fold (13% vs. 3.5% retention of peak response). The co-expressed GM-CSF did not enhance responses over those in trials testing this vaccine without GM-CSF., Conclusion: This DNA/MVA prime-boost regimen induced durable, functional humoral responses that included ADCC, high antibody avidity, and Env IgG1 and IgG3 binding responses to the immunodominant region of gp41. The third, spaced MVA boost improved the overall quality of the antibody response. These products without co-expressed GM-CSF but combined with protein boosts will be considered for efficacy evaluation., Trial Registration: ClinicalTrials.gov NCT01571960.

Under the case-cohort design introduced by Prentice (Biometrica 73:1-11, 1986), the covariate histories are ascertained only for the subjects who experience the event of interest (i.e., the cases) during the follow-up period and for a relatively small random sample from the original cohort (i.e., the subcohort). The case-cohort design has been widely used in clinical and epidemiological studies to assess the effects of covariates on failure times. Most statistical methods developed for the case-cohort design use the proportional hazards model, and few methods allow for time-varying regression coefficients. In addition, most methods disregard data from subjects outside of the subcohort, which can result in inefficient inference. Addressing these issues, this paper proposes an estimation procedure for the semiparametric additive hazards model with case-cohort/two-phase sampling data, allowing the covariates of interest to be missing for cases as well as for non-cases. A more flexible form of the additive model is considered that allows the effects of some covariates to be time varying while specifying the effects of others to be constant. An augmented inverse probability weighted estimation procedure is proposed. The proposed method allows utilizing the auxiliary information that correlates with the phase-two covariates to improve efficiency. The asymptotic properties of the proposed estimators are established. An extensive simulation study shows that the augmented inverse probability weighted estimation is more efficient than the widely adopted inverse probability weighted complete-case estimation method. The method is applied to analyze data from a preventive HIV vaccine efficacy trial.

The monoclonal antibody VRC01 targets the CD4 binding site of the human immunodeficiency virus (HIV)-1 envelope. In the clinical study HVTN 104 (NCT02165267), 84 HIV-uninfected adults received multiple-dose intravenous (IV) VRC01 (10, 20, 30 or 40 mg/kg) every 4 or 8 weeks or subcutaneous (SC) VRC01 (5 mg/kg) every 2 weeks, and were followed for 32 weeks. We conducted a population pharmacokinetics (popPK) analysis based on 1117 VRC01 serum concentrations using a 2-compartment PK model with first-order elimination; for SC VRC01 a depot compartment with a first-order absorption rate constant was also included. All PK parameters were estimated with acceptable precision. Estimated bioavailability of SC VRC01 was 74%, with peak concentrations occurring 2-3 d after administration. For both IV and SC VRC01, population mean estimates for clearance (CL), central volume of distribution (Vc), inter-compartmental distribution clearance (Q) and peripheral volume of distribution (Vp) were 0.40 L/day, 1.94 L, 0.84 L/day and 4.90 L, respectively; the estimated terminal half-life was 15 d and these were independent of VRC01 dose. Body weight significantly influenced CL (1.2% fold/kg), Vc (1.0% fold/kg), Q (0.69 log(L/day)/kg) and Vp (0.82 log(L)/kg). The developed popPK model, supporting weight-dependent dosing regimens, projected positive trough levels, 5.54 (95% prediction interval: 1.69, 14.5) mcg/mL and 15.9 (5.29, 46.63) mcg/mL, respectively, for the 10 mg/kg and 30 mg/kg 8-weekly regimens being evaluated in ongoing HIV prevention efficacy studies of IV VRC01. These results are critical for future dose-regimen selection and modeling research to identify VRC01 serum concentration levels sufficient for protection against HIV infection.

An objective of preventive HIV vaccine efficacy trials is to understand how vaccine-induced immune responses to specific protein sequences of HIV-1 associate with subsequent infection with specific sequences of HIV, where the immune response biomarkers are measured in vaccine recipients via a two-phase sampling design. Motivated by this objective, we investigate the stratified mark-specific proportional hazards model under two-phase biomarker sampling, where the mark is the genetic distance of an infecting HIV-1 sequence to an HIV-1 sequence represented inside the vaccine. Estimation and inference procedures based on inverse probability weighting of complete-cases and on augmented inverse probability weighting of complete-cases are developed. Asymptotic properties of the estimators are derived and their finite-sample performances are examined in simulation studies. The methods are shown to have satisfactory performance, and are applied to the RV144 vaccine trial to assess whether immune response correlates of HIV-1 infection are stronger for HIV-1 infecting sequences similar to the vaccine than for sequences distant from the vaccine. Augmented inverse probability weighting; auxiliary variables; case-cohort design; censored failure time; competing risks; HIV vaccine efficacy trial.

This article investigates a generalized semiparametric varying-coefficient model for longitudinal data that can flexibly model three types of covariate effects: time-constant effects, time-varying effects, and covariate-varying effects. Different link functions can be selected to provide a rich family of models for longitudinal data. The model assumes that the time-varying effects are unspecified functions of time and the covariate-varying effects are parametric functions of an exposure variable specified up to a finite number of unknown parameters. The estimation procedure is developed using local linear smoothing and profile weighted least squares estimation techniques. Hypothesis testing procedures are developed to test the parametric functions of the covariate-varying effects. The asymptotic distributions of the proposed estimators are established. A working formula for bandwidth selection is discussed and examined through simulations. Our simulation study shows that the proposed methods have satisfactory finite sample performance. The proposed methods are applied to the ACTG 244 clinical trial of HIV infected patients being treated with Zidovudine to examine the effects of antiretroviral treatment switching before and after HIV develops the T215Y/F drug resistance mutation. Our analysis shows benefits of treatment switching to the combination therapies as compared to continuing with ZDV monotherapy before and after developing the 215-mutation., (© 2016, The International Biometric Society.)

We study threshold regression models that allow the relationship between the outcome and a covariate of interest to change across a threshold value in the covariate. In particular, we focus on continuous threshold models, which experience no jump at the threshold. Continuous threshold regression functions can provide a useful summary of the association between outcome and the covariate of interest, because they offer a balance between flexibility and simplicity. Motivated by collaborative works in studying immune response biomarkers of transmission of infectious diseases, we study estimation of continuous threshold models in this article with particular attention to inference under model misspecification. We derive the limiting distribution of the maximum likelihood estimator, and propose both Wald and test-inversion confidence intervals. We evaluate finite sample performance of our methods, compare them with bootstrap confidence intervals, and provide guidelines for practitioners to choose the most appropriate method in real data analysis. We illustrate the application of our methods with examples from the HIV-1 immune correlates studies., (© 2016, The International Biometric Society.)

Background: In the HIV-1 vaccine trial RV144, ALVAC-HIV prime with an AIDSVAX® B/E boost reduced HIV-1 acquisition by 31% at 42 months post first vaccination. The bivalent AIDSVAX® B/E vaccine contains two gp120 envelope glycoproteins, one from the subtype B HIV-1 MN isolate and one from the subtype CRF01&#95;AE A244 isolate. Each envelope glycoprotein harbors a highly conserved 27-amino acid HSV-1 glycoprotein D (gD) tag sequence that shares 93% sequence identity with the HSV-2 gD sequence. We assessed whether vaccine-induced anti-gD antibodies protected females against HSV-2 acquisition in RV144., Methods: Of the women enrolled in RV144, 777 vaccine and 807 placebo recipients were eligible and randomly selected according to their pre-vaccination HSV-1 and HSV-2 serostatus for analysis. Immunoglobulin G (IgG) and IgA responses to gD were determined by a binding antibody multiplex assay and HSV-2 serostatus was determined by Western blot analysis. Ninety-three percent and 75% of the vaccine recipients had anti-gD IgG and IgA responses two weeks post last vaccination, respectively. There was no evidence of reduction in HSV-2 infection by vaccination compared to placebo recipients over 78 weeks of follow-up. The annual incidence of HSV-2 infection in individuals who were HSV-2 negative at baseline or HSV-1 positive and HSV-2 indeterminate at baseline were 4.38/100 person-years (py) and 3.28/100 py in the vaccine and placebo groups, respectively. Baseline HSV-1 status did not affect subsequent HSV-2 acquisition. Specifically, the estimated odds ratio of HSV-2 infection by Week 78 for female placebo recipients who were baseline HSV-1 positive (n = 422) vs. negative (n = 1120) was 1.14 [95% confidence interval 0.66 to 1.94, p = 0.64)]. No evidence of reduction in the incidence of HSV-2 infection by vaccination was detected., Conclusions: AIDSVAX® B/E containing gD did not confer protection from HSV-2 acquisition in HSV-2 seronegative women, despite eliciting anti-gD serum antibodies.

Background: It is important to identify vaccine-induced immune responses that predict the preventative efficacy of a human immunodeficiency virus (HIV)-1 vaccine. We assessed T-cell response markers as correlates of risk in the HIV Vaccine Trials Network (HVTN) 505 HIV-1 vaccine efficacy trial., Methods: 2504 participants were randomized to DNA/rAd5 vaccine or placebo, administered at weeks 0, 4, 8, and 24. Peripheral blood mononuclear cells were obtained at week 26 from all 25 primary endpoint vaccine cases and 125 matched vaccine controls, and stimulated with vaccine-insert-matched peptides. Primary variables were total HIV-1-specific CD4+ T-cell magnitude and Env-specific CD4+ polyfunctionality. Four secondary variables were also assessed. Immune responses were evaluated as predictors of HIV-1 infection among vaccinees using Cox proportional hazards models. Machine learning analyses identified immune response combinations best predicting HIV-1 infection., Results: We observed an unexpectedly strong inverse correlation between Env-specific CD8+ immune response magnitude and HIV-1 infection risk (hazard ratio [HR] = 0.18 per SD increment; P = .04) and between Env-specific CD8+ polyfunctionality and infection risk (HR = 0.34 per SD increment; P < .01)., Conclusions: Further research is needed to determine if these immune responses are predictors of vaccine efficacy or markers of natural resistance to HIV-1 infection., (© The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.)

Stepped wedge designs are increasingly commonplace and advantageous for cluster randomized trials when it is both unethical to assign placebo, and it is logistically difficult to allocate an intervention simultaneously to many clusters. We study marginal mean models fit with generalized estimating equations for assessing treatment effectiveness in stepped wedge cluster randomized trials. This approach has advantages over the more commonly used mixed models that (1) the population-average parameters have an important interpretation for public health applications and (2) they avoid untestable assumptions on latent variable distributions and avoid parametric assumptions about error distributions, therefore, providing more robust evidence on treatment effects. However, cluster randomized trials typically have a small number of clusters, rendering the standard generalized estimating equation sandwich variance estimator biased and highly variable and hence yielding incorrect inferences. We study the usual asymptotic generalized estimating equation inferences (i.e., using sandwich variance estimators and asymptotic normality) and four small-sample corrections to generalized estimating equation for stepped wedge cluster randomized trials and for parallel cluster randomized trials as a comparison. We show by simulation that the small-sample corrections provide improvement, with one correction appearing to provide at least nominal coverage even with only 10 clusters per group. These results demonstrate the viability of the marginal mean approach for both stepped wedge and parallel cluster randomized trials. We also study the comparative performance of the corrected methods for stepped wedge and parallel designs, and describe how the methods can accommodate interval censoring of individual failure times and incorporate semiparametric efficient estimators.

Biomarker endpoints measuring vaccine-induced immune responses are essential to HIV vaccine development because of their potential to predict the effect of a vaccine in preventing HIV infection. A vaccine's immune response profile observed in phase I immunogenicity studies is a key factor in determining whether it is advanced for further study in phase II and III efficacy trials. The multiplicity of immune variables and scientific uncertainty in their relative importance, however, pose great challenges to the development of formal algorithms for selecting vaccines to study further. Motivated by the practical need to identify a set of promising vaccines from a pool of candidate regimens for inclusion in an upcoming HIV vaccine efficacy trial, we propose a new statistical framework for the selection of vaccine regimens based on their immune response profile. In particular, we propose superiority and non-redundancy criteria to be achieved in down-selection, and develop novel statistical algorithms that integrate hypothesis testing and ranking for selecting vaccine regimens satisfying these criteria. Performance of the proposed selection algorithms are evaluated through extensive numerical studies. We demonstrate the application of the proposed methods through the comparison of immune responses between several HIV vaccine regimens. The methods are applicable to general down-selection applications in clinical trials., (© The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: The evaluation of durable immune responses is important in HIV vaccine research and development. The efficiency of such evaluation could be increased by incorporating predictors of the responses in the statistical analysis. In this paper, we investigated whether and how baseline demographic variables and immune responses measured two weeks after vaccination predicted durable immune responses measured six months later., Methods: We included data from seven preventive HIV vaccine regimens evaluated in three clinical trials: a Phase 1 study of four DNA, NYVAC and/or AIDSVAX vaccine regimens (HVTN096), a Phase 2 study of two DNA and/or MVA vaccine regimens (HVTN205), and a Phase 3 study of a single ALVAC/AIDSVAX regimen (RV144). Regularized random forests and linear regression models were used to identify and evaluate predictors of the positivity and magnitude of durable immune responses., Results: We analyzed 201 vaccine recipients with data from 10 to 127 immune response biomarkers, and 3-5 demographic variables. The best prediction of participants' durable response positivity based on two-week responses rendered up to close-to-perfect accuracy; the best prediction of participants' durable response magnitude rendered correlation coefficients between the observed and predicted responses ranging up to 0.91. Though prediction performances differed among biomarkers, durable immune responses were best predicted by the two-week response level of the same biomarker. Adding demographic information and two-week response levels of different biomarkers provided little or no improvement in the predictions., Conclusions: For some biomarkers and for the vaccines we studied, two-week post-vaccination responses can well predict durable responses six months later. Therefore, if immune response durability is only assessed in a sub-sample of vaccine recipients, statistical analyses of durable responses will have increased efficiency by incorporating two-week response data. Further research is needed to generalize the findings to other vaccine regimens and biomarkers. Clinicaltrials.gov identifiers: NCT01799954, NCT00820846, NCT00223080., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

The only evidence of vaccine-induced protection from HIV acquisition in humans was obtained in the RV144 HIV vaccine clinical trial. One immune correlate of risk in RV144 was observed to be higher titers of vaccine-induced antibodies (Abs) reacting with a 23-mer non-glycosylated peptide with the same amino acid sequence as a segment in the second variable (V2) loop of the MN strain of HIV. We used NMR to analyze the dynamic 3D structure of this peptide. Distance restraints between spatially proximate inter-residue protons were calculated from NOE cross peak intensities and used to constrain a thorough search of all possible conformations of the peptide. α-helical folding was strongly preferred by part of the peptide. A high-throughput structure prediction of this segment in all circulating HIV strains demonstrated that α-helical conformations are preferred by this segment almost universally across all subtypes. Notably, α-helical conformations of this segment of the V2 loop cluster cross-subtype-conserved amino acids on one face of the helix and the variable amino acid positions on the other in a semblance of an amphipathic α-helix. Accordingly, some Abs that protected against HIV in RV144 may have targeted a specific, conserved α-helical peptide epitope in the V2 loop of HIV's surface envelope glycoprotein., Competing Interests: The authors have declared that no competing interests exist.

Background: Anti-HIV-1 broadly neutralizing antibodies (bnAbs) have been developed as potential agents for prevention of HIV-1 infection. The HIV Vaccine Trials Network and the HIV Prevention Trials Network are conducting the Antibody Mediated Prevention (AMP) trials to assess whether, and how, intravenous infusion of the anti-CD4 binding site bnAb, VRC01, prevents HIV-1 infection. These are the first test-of-concept studies to assess HIV-1 bnAb prevention efficacy in humans., Methods: The AMP trials are two parallel phase 2b HIV-1 prevention efficacy trials conducted in two cohorts: 2700 HIV-uninfected men and transgender persons who have sex with men in the United States, Peru, Brazil, and Switzerland; and 1500 HIV-uninfected sexually active women in seven countries in sub-Saharan Africa. Participants are randomized 1:1:1 to receive an intravenous infusion of 10 mg/kg VRC01, 30 mg/kg VRC01, or a control preparation every 8 weeks for a total of 10 infusions. Each trial is designed (1) to assess overall prevention efficacy (PE) pooled over the two VRC01 dose groups vs. control and (2) to assess VRC01 dose and laboratory markers as correlates of protection (CoPs) against overall and genotype- and phenotype-specific infection., Results: Each AMP trial is designed to have 90% power to detect PE > 0% if PE is ≥ 60%. The AMP trials are also designed to identify VRC01 properties (i.e., concentration and effector functions) that correlate with protection and to provide insight into mechanistic CoPs. CoPs are assessed using data from breakthrough HIV-1 infections, including genetic sequences and sensitivities to VRC01-mediated neutralization and Fc effector functions., Conclusions: The AMP trials test whether VRC01 can prevent HIV-1 infection in two study populations. If affirmative, they will provide information for estimating the optimal dosage of VRC01 (or subsequent derivatives) and identify threshold levels of neutralization and Fc effector functions associated with high-level protection, setting a benchmark for future vaccine evaluation and constituting a bridge to other bnAb approaches for HIV-1 prevention., Competing Interests: Conflict of interest statement: All authors have no potential conflicts of interest to declare.

A common objective of cohort studies and clinical trials is to assess time-varying longitudinal continuous biomarkers as correlates of the instantaneous hazard of a study endpoint. We consider the setting where the biomarkers are measured in a designed sub-sample (i.e., case-cohort or two-phase sampling design), as is normative for prevention trials. We address this problem via joint models, with underlying biomarker trajectories characterized by a random effects model and their relationship with instantaneous risk characterized by a Cox model. For estimation and inference we extend the conditional score method of Tsiatis and Davidian (Biometrika 88(2):447-458, 2001) to accommodate the two-phase biomarker sampling design using augmented inverse probability weighting with nonparametric kernel regression. We present theoretical properties of the proposed estimators and finite-sample properties derived through simulations, and illustrate the methods with application to the AIDS Clinical Trials Group 175 antiretroviral therapy trial. We discuss how the methods are useful for evaluating a Prentice surrogate endpoint, mediation, and for generating hypotheses about biological mechanisms of treatment efficacy.

The World Health Organization has issued an early release revision to its antiretroviral guidelines in which PrEP (pre-exposure prophylaxis in the form of daily oral, fixed dose combination tenofovir disoproxil fumarate/emtricitabine) is recommended as a prevention option to all people at substantial risk of acquiring HIV. However, lack of effectiveness in 2 major women-only PrEP trials, VOICE and FEM-PrEP, continues to be a cause for concern about achieving effectiveness for women in Southern Africa. We conducted a series of meta-analyses of oral effectiveness of tenofovir disoproxil fumarate/emtricitabine in women including all 5 randomized placebo-controlled trials that included women. An adherence-based meta-analysis model showed that with high levels of adherence (75%), oral PrEP is estimated to be effective (relative risk = 0.39, 95% confidence interval: 0.25 to 0.60). Provided that these results apply to women in Southern Africa, future prevention trial designs in that region should account for potentially reduced HIV incidence when PrEP is available., Competing Interests: BH, HEJ, PDG, YH, ERB, YQC, SMH, PBG have nothing to disclose.

We develop a transport formula for predicting overall cumulative vaccine efficacy through time t ( VE ( t )) to prevent clinically significant infection with a genetically diverse pathogen (e.g., HIV infection) in a new setting for which a Phase III preventive vaccine efficacy trial that would directly estimate VE ( t ) has not yet been conducted. The formula integrates data from (1) a previous Phase III trial, (2) a Phase I/II immune response biomarker endpoint trial in the new setting where a follow-up Phase III trial is planned, (3) epidemiological data on background HIV infection incidence in the new setting; and (4) genomic epidemiological data on HIV sequence distributions in the previous and new settings. For (1), the randomized vaccine versus placebo Phase III trial yields estimates of vaccine efficacy to prevent particular genotypes of HIV in participant subgroups defined by baseline covariates X and immune responses to vaccination S (1) measured at a fixed time point τ (potential outcomes if assigned vaccine); often one or more immune responses to vaccination are available that modify genotype-specific vaccine efficacy. The formula focuses on subgroups defined by X and S (1) and being at-risk for HIV infection at τ under both the vaccine and placebo treatment assignments. For (2), the Phase I/II trial tests the same vaccine in a new setting, or a refined new vaccine in the same or new setting, and measures the same baseline covariates and immune responses as the original Phase III trial. For (3), epidemiological data in the new setting are used to project overall background HIV infection rates in the baseline covariate subgroups in the planned Phase III trial, hence re-calibrating for HIV incidence differences in the two settings; whereas for (4), data bases of HIV sequences measured from HIV infected individuals are used to re-calibrate for differences in the distributions of the circulating HIV genotypes in the two settings. The transport formula incorporates a user-specified bridging assumption function that measures differences in HIV genotype-specific conditional biological-susceptibility vaccine efficacies in the two settings, facilitating a sensitivity analysis. We illustrate the transport formula with application to HIV Vaccine Trials Network (HVTN) research. One application of the transport formula is to use predicted VE ( t ) as a rational criterion for ranking a set of candidate vaccines being studied in Phase I/II trials for their priority for down-selection into the follow-up Phase III trial.

Introduction: The Merck Adenovirus-5 Gag/Pol/Nef HIV-1 subtype-B vaccine evaluated in predominately subtype B epidemic regions (Step Study), while not preventing infection, exerted vaccine-induced immune pressure on HIV-1 breakthrough infections. Here we investigated if the same vaccine exerted immune pressure when tested in the Phambili Phase 2b study in a subtype C epidemic., Materials and Methods: A sieve analysis, which compares breakthrough viruses from placebo and vaccine arms, was performed on 277 near full-length genomes generated from 23 vaccine and 20 placebo recipients. Vaccine coverage was estimated by computing the percentage of 9-mers that were exact matches to the vaccine insert., Results: There was significantly greater protein distances from the vaccine immunogen sequence in Gag (p=0.045) and Nef (p=0.021) in viruses infecting vaccine recipients compared to placebo recipients. Twenty-seven putative sites of vaccine-induced pressure were identified (p<0.05) in Gag (n=10), Pol (n=7) and Nef (n=10), although they did not remain significant after adjustment for multiple comparisons. We found the epitope sieve effect in Step was driven by HLA A∗02:01; an allele which was found in low frequency in Phambili participants compared to Step participants. Furthermore, the coverage of the vaccine against subtype C Phambili viruses was 31%, 46% and 14% for Gag, Pol and Nef, respectively, compared to subtype B Step virus coverage of 56%, 61% and 26%, respectively., Discussion: This study presents evidence of sieve effects in Gag and Nef; however could not confirm effects on specific amino acid sites. We propose that this weaker signal of vaccine immune pressure detected in the Phambili study compared to the Step study may have been influenced by differences in host genetics (HLA allele frequency) and reduced impact of vaccine-induced immune responses due to mismatch between the viral subtype in the vaccine and infecting subtypes., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Purpose of Review: Models of implementation of known-effective interventions for HIV prevention indicate that an efficacious vaccine to prevent HIV infection would be critical for controlling the HIV pandemic. Key issues in the design of future HIV vaccine trials are: first, how to develop reliable immunological correlates of vaccine efficacy, second, how to down-select candidate vaccine regimens into efficacy trials, and third, how to learn about vaccine efficacy in the context of the evolving HIV prevention landscape., Recent Findings: Whereas in the past phase-I/-II HIV vaccine trials have addressed the first and second points using a small set of immunological assays and readouts, recently they have used a battery of assays with highly multivariate readouts. In addition, systems vaccinology studies of other pathogens measuring PBMC transcriptomics and other immunological features pre- and postfirst vaccination are demonstrating value, for example, providing discoveries that preimmunization and early postimmunization cell population markers can predict the influenza-specific antibody titer that is a correlate of vaccine protection. The HIV prevention landscape continues to evolve, and the design and analysis of vaccine trials is evolving alongside, to accommodate increasingly dynamic and regional standards of HIV prevention., Summary: Development of interpretable and robust functional assays, in addition to the associated bioinformatics and statistical analytic tools, is needed to improve the assessment of correlates of protection in efficacy trials and the down-selection of candidate vaccine regimens into efficacy trials. Moreover, high-priority trials should integrate systems vaccinology, including the analysis of prevaccination and early postvaccination markers.

An objective of randomized placebo-controlled preventive HIV vaccine efficacy (VE) trials is to assess the relationship between vaccine effects to prevent HIV acquisition and continuous genetic distances of the exposing HIVs to multiple HIV strains represented in the vaccine. The set of genetic distances, only observed in failures, is collectively termed the 'mark.' The objective has motivated a recent study of a multivariate mark-specific hazard ratio model in the competing risks failure time analysis framework. Marks of interest, however, are commonly subject to substantial missingness, largely due to rapid post-acquisition viral evolution. In this article, we investigate the mark-specific hazard ratio model with missing multivariate marks and develop two inferential procedures based on (i) inverse probability weighting (IPW) of the complete cases, and (ii) augmentation of the IPW estimating functions by leveraging auxiliary data predictive of the mark. Asymptotic properties and finite-sample performance of the inferential procedures are presented. This research also provides general inferential methods for semiparametric density ratio/biased sampling models with missing data. We apply the developed procedures to data from the HVTN 502 'Step' HIV VE trial.