Improved estimation of the cumulative incidence of rare outcomes

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.

Population pharmacokinetics analysis of VRC01, an HIV-1 broadly neutralizing monoclonal antibody, in healthy adults

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.

Analysis of two-phase sampling data with semiparametric additive hazards models

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.

Antibody to HSV gD peptide induced by vaccination does not protect against HSV-2 infection in HSV-2 seronegative women

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_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.

Higher T-Cell Responses Induced by DNA/rAd5 HIV-1 Preventive Vaccine Are Associated With Lower HIV-1 Infection Risk in an Efficacy Trial

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.

Predictors of durable immune responses six months after the last vaccination in preventive HIV vaccine trials

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.

Peptide Targeted by Human Antibodies Associated with HIV Vaccine-Associated Protection Assumes a Dynamic α-Helical Structure

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.

Joint modeling of longitudinal and survival data with the Cox model and two-phase sampling

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.

Basis and Statistical Design of the Passive HIV-1 Antibody Mediated Prevention (AMP) Test-of-Concept Efficacy Trials

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.

Generalized semiparametric varying-coefficient model for longitudinal data with applications to adaptive treatment randomizations

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.

Model-robust inference for continuous threshold regression models

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.

Mark-specific hazard ratio model with missing multivariate marks

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.

Sequential Immunization with gp140 Boosts Immune Responses Primed by Modified Vaccinia Ankara or DNA in HIV-Uninfected South African Participants

BACKGROUND

The safety and immunogenicity of SAAVI DNA-C2 (4 mg IM), SAAVI MVA-C (2.9 x 109 pfu IM) and Novartis V2-deleted subtype C gp140 (100 mcg) with MF59 adjuvant in various vaccination regimens was evaluated in HIV-uninfected adults in South Africa.

METHODS

Participants at three South African sites were randomized (1:1:1:1) to one of four vaccine regimens: MVA prime, sequential gp140 protein boost (M/M/P/P); concurrent MVA/gp140 (MP/MP); DNA prime, sequential MVA boost (D/D/M/M); DNA prime, concurrent MVA/gp140 boost (D/D/MP/MP) or placebo. Peak HIV specific humoral and cellular responses were measured.

RESULTS

184 participants were enrolled: 52% were female, all were Black/African, median age was 23 years (range, 18-42 years) and 79% completed all vaccinations. 159 participants reported at least one adverse event, 92.5% were mild or moderate. Five, unrelated, serious adverse events were reported. The M/M/P/P and D/D/MP/MP regimens induced the strongest peak neutralizing and binding antibody responses and the greatest CD4+ T-cell responses to Env. All peak neutralizing and binding antibody responses decayed with time. The MVA, but not DNA, prime contributed to the humoral and cellular immune responses. The D/D/M/M regimen was poorly immunogenic overall but did induce modest CD4+ T-cell responses to Gag and Pol. CD8+ T-cell responses to any antigen were low for all regimens.

CONCLUSIONS

The SAAVI DNA-C2, SAAVI MVA-C and Novartis gp140 with MF59 adjuvant in various combinations were safe and induced neutralizing and binding antibodies and cellular immune responses. Sequential immunization with gp140 boosted immune responses primed by MVA or DNA. The best overall immune responses were seen with the M/M/P/P regimen.

TRIAL REGISTRATION

ClinicalTrials.gov NCT01418235.

HLA class II genes modulate vaccine-induced antibody responses to affect HIV-1 acquisition

In the RV144 vaccine trial, two antibody responses were found to correlate with HIV-1 acquisition. Because human leukocyte antigen (HLA) class II-restricted CD4(+) T cells are involved in antibody production, we tested whether HLA class II genotypes affected HIV-1-specific antibody levels and HIV-1 acquisition in 760 individuals. Indeed, antibody responses correlated with acquisition only in the presence of single host HLA alleles. Envelope (Env)-specific immunoglobulin A (IgA) antibodies were associated with increased risk of acquisition specifically in individuals with DQB1*06. IgG antibody responses to Env amino acid positions 120 to 204 were higher and were associated with decreased risk of acquisition and increased vaccine efficacy only in the presence of DPB1*13. Screening IgG responses to overlapping peptides spanning Env 120-204 and viral sequence analysis of infected individuals defined differences in vaccine response that were associated with the presence of DPB1*13 and could be responsible for the protection observed. Overall, the underlying genetic findings indicate that HLA class II modulated the quantity, quality, and efficacy of antibody responses in the RV144 trial.

Power/sample size calculations for assessing correlates of risk in clinical efficacy trials

In a randomized controlled clinical trial that assesses treatment efficacy, a common objective is to assess the association of a measured biomarker response endpoint with the primary study endpoint in the active treatment group, using a case-cohort, case-control, or two-phase sampling design. Methods for power and sample size calculations for such biomarker association analyses typically do not account for the level of treatment efficacy, precluding interpretation of the biomarker association results in terms of biomarker effect modification of treatment efficacy, with detriment that the power calculations may tacitly and inadvertently assume that the treatment harms some study participants. We develop power and sample size methods accounting for this issue, and the methods also account for inter-individual variability of the biomarker that is not biologically relevant (e.g., due to technical measurement error). We focus on a binary study endpoint and on a biomarker subject to measurement error that is normally distributed or categorical with two or three levels. We illustrate the methods with preventive HIV vaccine efficacy trials and include an R package implementing the methods. Copyright © 2016 John Wiley & Sons, Ltd.

FCGR2C Polymorphisms Associated with HIV-1 Vaccine Protection Are Linked to Altered Gene Expression of Fc-γ Receptors in Human B Cells

The phase III Thai RV144 vaccine trial showed an estimated vaccine efficacy (VE) to prevent HIV-1 infection of 31.2%, which has motivated the search for immune correlates of vaccine protection. In a recent report, several single nucleotide polymorphisms (SNPs) in FCGR2C were identified to associate with the level of VE in the RV144 trial. To investigate the functional significance of these SNPs, we utilized a large scale B cell RNA sequencing database of 462 individuals from the 1000 Genomes Project to examine associations between FCGR2C SNPs and gene expression. We found that the FCGR2C SNPs that associated with vaccine efficacy in RV144 also strongly associated with the expression of FCGR2A/C and one of them also associated with the expression of Fc receptor-like A (FCRLA), another Fc-γ receptor (FcγR) gene that was not examined in the previous report. These results suggest that the expression of FcγR genes is influenced by these SNPs either directly or in linkage with other causal variants. More importantly, these results motivate further investigations into the potential for a causal association of expression and alternative splicing of FCGR2C and other FcγR genes with the HIV-1 vaccine protection in the RV144 trial and other similar studies.

Pooled-Peptide Epitope Mapping Strategies Are Efficient and Highly Sensitive: An Evaluation of Methods for Identifying Human T Cell Epitope Specificities in Large-Scale HIV Vaccine Efficacy Trials

The interferon gamma, enzyme-linked immunospot (IFN-γ ELISpot) assay is widely used to identify viral antigen-specific T cells is frequently employed to quantify T cell responses in HIV vaccine studies. It can be used to define T cell epitope specificities using panels of peptide antigens, but with sample and cost constraints there is a critical need to improve the efficiency of epitope mapping for large and variable pathogens. We evaluated two epitope mapping strategies, based on group testing, for their ability to identify vaccine-induced T-cells from participants in the Step HIV-1 vaccine efficacy trial, and compared the findings to an approach of assaying each peptide individually. The group testing strategies reduced the number of assays required by >7-fold without significantly altering the accuracy of T-cell breadth estimates. Assays of small pools containing 7–30 peptides were highly sensitive and effective at detecting single positive peptides as well as summating responses to multiple peptides. Also, assays with a single 15-mer peptide, containing an identified epitope, did not always elicit a response providing validation that 15-mer peptides are not optimal antigens for detecting CD8+ T cells. Our findings further validate pooling-based epitope mapping strategies, which are critical for characterizing vaccine-induced T-cell responses and more broadly for informing iterative vaccine design. We also show ways to improve their application with computational peptide:MHC binding predictors that can accurately identify the optimal epitope within a 15-mer peptide and within a pool of 15-mer peptides.

Selection of HIV vaccine candidates for concurrent testing in an efficacy trial

Phase IIb or III HIV-1 vaccine efficacy trials are generally large and operationally challenging. To mitigate this challenge, the HIV Vaccine Trials Network is designing a Phase IIb efficacy trial accommodating the evaluation of multiple vaccine regimens concurrently. As this efficacy trial would evaluate a limited number of vaccine regimens, there is a need to develop a framework for optimizing the strategic selection of regimens from the large number of vaccine candidates tested in Phase I/IIa trials. In this paper we describe the approaches for the selection process, including the choice of immune response endpoints and the statistical criteria and algorithms. We illustrate the selection approaches using data from HIV-1 vaccine trials.

Predicting Overall Vaccine Efficacy in a New Setting by Re-Calibrating Baseline Covariate and Intermediate Response Endpoint Effect Modifiers of Type-Specific Vaccine Efficacy

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.

Goodness-of-fit test of the stratified mark-specific proportional hazards model with continuous mark

Motivated by the need to assess HIV vaccine efficacy, previous studies proposed an extension of the discrete competing risks proportional hazards model, in which the cause of failure is replaced by a continuous mark only observed at the failure time. However the model assumptions may fail in several ways, and no diagnostic testing procedure for this situation has been proposed. A goodness-of-fit test procedure for the stratified mark-specific proportional hazards model in which the regression parameters depend nonparametrically on the mark and the baseline hazards depends nonparametrically on both time and the mark is proposed. The test statistics are constructed based on the weighted cumulative mark-specific martingale residuals. The critical values of the proposed test statistics are approximated using the Gaussian multiplier method. The performance of the proposed tests are examined extensively in simulations for a variety of the models under the null hypothesis and under different types of alternative models. An analysis of the 'Step' HIV vaccine efficacy trial using the proposed method is presented. The analysis suggests that the HIV vaccine candidate may increase susceptibility to HIV acquisition.

Genetic Diversity and Protective Efficacy of the RTS,S/AS01 Malaria Vaccine

BACKGROUND

The RTS,S/AS01 vaccine targets the circumsporozoite protein of Plasmodium falciparum and has partial protective efficacy against clinical and severe malaria disease in infants and children. We investigated whether the vaccine efficacy was specific to certain parasite genotypes at the circumsporozoite protein locus.

METHODS

We used polymerase chain reaction-based next-generation sequencing of DNA extracted from samples from 4985 participants to survey circumsporozoite protein polymorphisms. We evaluated the effect that polymorphic positions and haplotypic regions within the circumsporozoite protein had on vaccine efficacy against first episodes of clinical malaria within 1 year after vaccination.

RESULTS

In the per-protocol group of 4577 RTS,S/AS01-vaccinated participants and 2335 control-vaccinated participants who were 5 to 17 months of age, the 1-year cumulative vaccine efficacy was 50.3% (95% confidence interval [CI], 34.6 to 62.3) against clinical malaria in which parasites matched the vaccine in the entire circumsporozoite protein C-terminal (139 infections), as compared with 33.4% (95% CI, 29.3 to 37.2) against mismatched malaria (1951 infections) (P=0.04 for differential vaccine efficacy). The vaccine efficacy based on the hazard ratio was 62.7% (95% CI, 51.6 to 71.3) against matched infections versus 54.2% (95% CI, 49.9 to 58.1) against mismatched infections (P=0.06). In the group of infants 6 to 12 weeks of age, there was no evidence of differential allele-specific vaccine efficacy.

CONCLUSIONS

These results suggest that among children 5 to 17 months of age, the RTS,S vaccine has greater activity against malaria parasites with the matched circumsporozoite protein allele than against mismatched malaria. The overall vaccine efficacy in this age category will depend on the proportion of matched alleles in the local parasite population; in this trial, less than 10% of parasites had matched alleles. (Funded by the National Institutes of Health and others.).

Immune correlates of vaccine protection against HIV-1 acquisition

The partial efficacy reported in the RV144 HIV vaccine trial in 2009 has driven the HIV vaccine field to define correlates of risk associated with HIV-1 acquisition and connect these functionally to preventing HIV infection. Immunological correlates, mainly including CD4(+) T cell responses to the HIV envelope and Fc-mediated antibody effector function, have been connected to reduced acquisition. These immunological correlates place immunological and genetic pressure on the virus. Indeed, antibodies directed at conserved regions of the V1V2 loop and antibodies that mediate antibody-dependent cellular cytotoxicity to HIV envelope in the absence of inhibiting serum immunoglobulin A antibodies correlated with decreased HIV risk. More recently, researchers have expanded their search with nonhuman primate studies using vaccine regimens that differ from that used in RV144; these studies indicate that non-neutralizing antibodies are associated with protection from experimental lentivirus challenge as well. These immunological correlates have provided the basis for the design of a next generation of vaccine regimens to improve upon the qualitative and quantitative degree of magnitude of these immune responses on HIV acquisition.

Continued Follow-Up of Phambili Phase 2b Randomized HIV-1 Vaccine Trial Participants Supports Increased HIV-1 Acquisition among Vaccinated Men

Background

The Phase 2b double-blinded, randomized Phambili/HVTN 503 trial evaluated safety and efficacy of the MRK Ad5 gag/pol/nef subtype B HIV-1 preventive vaccine vs placebo in sexually active HIV-1 seronegative participants in South Africa. Enrollment and vaccinations stopped and participants were unblinded but continued follow-up when the Step study evaluating the same vaccine in the Americas, Caribbean, and Australia was unblinded for non-efficacy. Final Phambili analyses found more HIV-1 infections amongst vaccine than placebo recipients, impelling the HVTN 503-S recall study.

Methods

HVTN 503-S sought to enroll all 695 HIV-1 uninfected Phambili participants, provide HIV testing, risk reduction counseling, physical examination, risk behavior assessment and treatment assignment recall. After adding HVTN 503-S data, HIV-1 infection hazard ratios (HR vaccine vs. placebo) were estimated by Cox models.

Results

Of the 695 eligible, 465 (67%) enrolled with 230 from the vaccine group and 235 from the placebo group. 38% of the 184 Phambili dropouts were enrolled. Enrollment did not differ by treatment group, gender, or baseline HSV-2. With the additional 1286 person years of 503-S follow-up, the estimated HR over Phambili and HVTN 503-S follow-up was 1.52 (95% CI 1.08–2.15, p = 0.02, 82 vaccine/54 placebo infections). The HR was significant for men (HR = 2.75, 95% CI 1.49, 5.06, p = 0.001) but not for women (HR = 1.12, 95% CI 0.73, 1.72, p = 0.62).

Conclusion

The additional follow-up from HVTN 503-S supported the Phambili finding of increased HIV-1 acquisition among vaccinated men and strengthened the evidence of lack of vaccine effect among women.

Trial Registration

clinicaltrials.gov NCT00413725

SA National Health Research Database DOH-27-0207-1539