Evidence for antibody as a protective correlate for COVID-19 vaccines

A correlate of protection (CoP) is urgently needed to expedite development of additional COVID-19 vaccines to meet unprecedented global demand. To assess whether antibody titers may reasonably predict efficacy and serve as the basis of a CoP, we evaluated the relationship between efficacy and in vitro neutralizing and binding antibodies of 7 vaccines for which sufficient data have been generated. Once calibrated to titers of human convalescent sera reported in each study, a robust correlation was seen between neutralizing titer and efficacy (ρ = 0.79) and binding antibody titer and efficacy (ρ = 0.93), despite geographically diverse study populations subject to different forces of infection and circulating variants, and use of different endpoints, assays, convalescent sera panels and manufacturing platforms. Together with evidence from natural history studies and animal models, these results support the use of post-immunization antibody titers as the basis for establishing a correlate of protection for COVID-19 vaccines.

Super LeArner Prediction of NAb Panels (SLAPNAP): A Contain-erized Tool for Predicting Combination Monoclonal Broadly Neu-tralizing Antibody Sensitivity

MOTIVATION

A single monoclonal broadly neutralizing antibody (bnAb) regimen was recently evaluated in two randomized trials for prevention efficacy against HIV-1 infection. Subsequent trials will evaluate combination bnAb regimens (e.g., cocktails, multi-specific antibodies), which demonstrate higher potency and breadth in vitro compared to single bnAbs. Given the large number of potential regimens, methods for down-selecting these regimens into efficacy trials are of great interest.

RESULTS

We developed Super LeArner Prediction of NAb Panels (SLAPNAP), a software tool for training and evaluating machine learning models that predict in vitro neutralization sensitivity of HIV Envelope (Env) pseudoviruses to a given single or combination bnAb regimen, based on Env amino acid sequence features. SLAPNAP also provides measures of variable importance of sequence features. By predicting bnAb coverage of circulating sequences, SLAPNAP can improve ranking of bnAb regimens by their potential prevention efficacy. In addition, SLAPNAP can improve sieve analysis by defining sequence features that impact bnAb prevention efficacy.

AVAILABILITY

SLAPNAP is a freely available docker image that can be downloaded from DockerHub (https://hub.docker.com/r/slapnap/slapnap). Source code and documentation are available at GitHub (respectively, https://github.com/benkeser/slapnap and https://benkeser.github.io/slapnap/).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Feasibility and Successful Enrollment in a Proof-of-Concept HIV Prevention Trial of VRC01, a Broadly Neutralizing HIV-1 Monoclonal Antibody

BACKGROUND

The Antibody-Mediated Prevention trials (HVTN 704/HPTN 085 and HVTN 703/HPTN 081) are the first efficacy trials to evaluate whether VRC01, a broadly neutralizing monoclonal antibody targeting the CD4-binding site of the HIV envelope protein, prevents sexual transmission of HIV-1. HVTN 704/HPTN 085 enrolled 2701 cisgender men and transgender (TG) individuals who have sex with men at 26 sites in Brazil, Peru, Switzerland, and the United States.

METHODS

Participants were recruited and retained through early, extensive community engagement. Eligible participants were randomized 1:1:1 to 10 mg/kg or 30 mg/kg of VRC01 or saline placebo. Visits occurred monthly, with intravenous (IV) infusions every 8 weeks over 2 years, for a total of 10 infusions. Participants were followed for 104 weeks after first infusion.

RESULTS

The median HVTN 704/HPTN 085 participant age was 28 years; 99% were assigned male sex; 90% identified as cisgender men, 5% as TG women and the remaining as other genders. Thirty-two percent were White, 15% Black, and 57% Hispanic/Latinx. Twenty-eight percent had a sexually transmitted infection at enrollment. More than 23,000 infusions were administered with no serious IV administration complications. Overall, retention and adherence to the study schedule exceeded 90%, and the dropout rate was below 10% annually (7.3 per 100 person-years) through week 80, the last visit for the primary end point.

CONCLUSIONS

HVTN 704/HPTN 085 exceeded accrual and retention expectations. With exceptional safety of IV administration and operational feasibility, it paves the way for future large-scale monoclonal antibody trials for HIV prevention and/or treatment.

Evaluating Vaccine Efficacy Against SARS-CoV-2 Infection

Although interim results from several large placebo-controlled phase 3 trials demonstrated high vaccine efficacy (VE) against symptomatic COVID-19, it is unknown how effective the vaccines are in preventing people from becoming asymptomatically infected and potentially spreading the virus unwittingly. It is more difficult to evaluate VE against SARS-CoV-2 infection than against symptomatic COVID-19 because infection is not observed directly but rather is known to occur between two antibody or RT-PCR tests. Additional challenges arise as community transmission changes over time and as participants are vaccinated on different dates because of staggered enrollment or crossover before the end of the study. Here, we provide valid and efficient statistical methods for estimating potentially waning VE against SARS-CoV-2 infection with blood or nasal samples under time-varying community transmission, staggered enrollment, and blinded or unblinded crossover. We demonstrate the usefulness of the proposed methods through numerical studies mimicking the BNT162b2 phase 3 trial and the Prevent COVID U study. In addition, we assess how crossover and the frequency of diagnostic tests affect the precision of VE estimates.

SUMMARY

We show how to estimate potentially waning efficacy of COVID-19 vaccines against SARS-CoV-2 infection using blood or nasal samples collected periodically from clinical trials with staggered enrollment of participants and crossover of placebo recipients.

Meta-analysis of HIV-1 vaccine elicited mucosal antibodies in humans

We studied mucosal immune responses in six HIV-1 vaccine trials investigating different envelope (Env)-containing immunogens. Regimens were classified into four categories: DNA/vector, DNA/vector plus protein, protein alone, and vector alone. We measured HIV-1-specific IgG and IgA in secretions from cervical (n = 111) and rectal swabs (n = 154), saliva (n = 141), and seminal plasma (n = 124) and compared to corresponding blood levels. Protein-containing regimens had up to 100% response rates and the highest Env-specific IgG response rates. DNA/vector groups elicited mucosal Env-specific IgG response rates of up to 67% that varied across specimen types. Little to no mucosal IgA responses were observed. Overall, gp41- and gp140-specific antibodies dominated gp120 mucosal responses. In one trial, prior vaccination with a protein-containing immunogen maintained durability of cervical and rectal IgG for up to 17 years. Mucosal IgG responses were boosted after revaccination. These findings highlight a role for protein immunization in eliciting HIV-1-specific mucosal antibodies and the ability of HIV-1 vaccines to elicit durable HIV-1-specific mucosal IgG.

Vaccine Efficacy of ALVAC-HIV and Bivalent Subtype C gp120-MF59 in Adults

BACKGROUND

A safe, effective vaccine is essential to eradicating human immunodeficiency virus (HIV) infection. A canarypox-protein HIV vaccine regimen (ALVAC-HIV plus AIDSVAX B/E) showed modest efficacy in reducing infection in Thailand. An analogous regimen using HIV-1 subtype C virus showed potent humoral and cellular responses in a phase 1-2a trial in South Africa. Efficacy data and additional safety data were needed for this regimen in a larger population in South Africa.

METHODS

In this phase 2b-3 trial, we randomly assigned 5404 adults without HIV-1 infection to receive the vaccine (2704 participants) or placebo (2700 participants). The vaccine regimen consisted of injections of ALVAC-HIV at months 0 and 1, followed by four booster injections of ALVAC-HIV plus bivalent subtype C gp120-MF59 adjuvant at months 3, 6, 12, and 18. The primary efficacy outcome was the occurrence of HIV-1 infection from randomization to 24 months.

RESULTS

In January 2020, prespecified criteria for nonefficacy were met at an interim analysis; further vaccinations were subsequently halted. The median age of the trial participants was 24 years; 70% of the participants were women. The incidence of adverse events was similar in the vaccine and placebo groups. During the 24-month follow-up, HIV-1 infection was diagnosed in 138 participants in the vaccine group and in 133 in the placebo group (hazard ratio, 1.02; 95% confidence interval, 0.81 to 1.30; P = 0.84).

CONCLUSIONS

The ALVAC-gp120 regimen did not prevent HIV-1 infection among participants in South Africa despite previous evidence of immunogenicity. (HVTN 702 ClinicalTrials.gov number, NCT02968849.).

Two Randomized Trials of Neutralizing Antibodies to Prevent HIV-1 Acquisition

BACKGROUND

Whether a broadly neutralizing antibody (bnAb) can be used to prevent human immunodeficiency virus type 1 (HIV-1) acquisition is unclear.

METHODS

We enrolled at-risk cisgender men and transgender persons in the Americas and Europe in the HVTN 704/HPTN 085 trial and at-risk women in sub-Saharan Africa in the HVTN 703/HPTN 081 trial. Participants were randomly assigned to receive, every 8 weeks, infusions of a bnAb (VRC01) at a dose of either 10 or 30 mg per kilogram (low-dose group and high-dose group, respectively) or placebo, for 10 infusions in total. HIV-1 testing was performed every 4 weeks. The VRC01 80% inhibitory concentration (IC80) of acquired isolates was measured with the TZM-bl assay.

RESULTS

Adverse events were similar in number and severity among the treatment groups within each trial. Among the 2699 participants in HVTN 704/HPTN 085, HIV-1 infection occurred in 32 in the low-dose group, 28 in the high-dose group, and 38 in the placebo group. Among the 1924 participants in HVTN 703/HPTN 081, infection occurred in 28 in the low-dose group, 19 in the high-dose group, and 29 in the placebo group. The incidence of HIV-1 infection per 100 person-years in HVTN 704/HPTN 085 was 2.35 in the pooled VRC01 groups and 2.98 in the placebo group (estimated prevention efficacy, 26.6%; 95% confidence interval [CI], -11.7 to 51.8; P = 0.15), and the incidence per 100 person-years in HVTN 703/HPTN 081 was 2.49 in the pooled VRC01 groups and 3.10 in the placebo group (estimated prevention efficacy, 8.8%; 95% CI, -45.1 to 42.6; P = 0.70). In prespecified analyses pooling data across the trials, the incidence of infection with VRC01-sensitive isolates (IC80 <1 μg per milliliter) per 100 person-years was 0.20 among VRC01 recipients and 0.86 among placebo recipients (estimated prevention efficacy, 75.4%; 95% CI, 45.5 to 88.9). The prevention efficacy against sensitive isolates was similar for each VRC01 dose and trial; VRC01 did not prevent acquisition of other HIV-1 isolates.

CONCLUSIONS

VRC01 did not prevent overall HIV-1 acquisition more effectively than placebo, but analyses of VRC01-sensitive HIV-1 isolates provided proof-of-concept that bnAb prophylaxis can be effective. (Supported by the National Institute of Allergy and Infectious Diseases; HVTN 704/HPTN 085 and HVTN 703/HPTN 081 ClinicalTrials.gov numbers, NCT02716675 and NCT02568215.).

Evaluating the Long-Term Efficacy of COVID-19 Vaccines

Large-scale deployment of safe and durably effective vaccines can curtail the coronavirus disease-2019 (COVID-19) pandemic. However, the high vaccine efficacy (VE) reported by ongoing phase 3 placebo-controlled clinical trials is based on a median follow-up time of only about 2 months, and thus does not pertain to long-term efficacy. To evaluate the duration of protection while allowing trial participants timely access to efficacious vaccine, investigators can sequentially cross participants over from the placebo arm to the vaccine arm. Here, we show how to estimate potentially time-varying placebo-controlled VE in this type of staggered vaccination of participants. In addition, we compare the performance of blinded and unblinded crossover designs in estimating long-term VE.

Evaluating the Long-Term Efficacy of COVID-19 Vaccines

Large-scale deployment of safe and durably effective vaccines can curtail the COVID-19 pandemic. ^1-3 However, the high vaccine efficacy (VE) reported by ongoing phase 3 placebo-controlled clinical trials is based on a median follow-up time of only about two months ^4-5 and thus does not pertain to long-term efficacy. To evaluate the duration of protection while allowing trial participants timely access to efficacious vaccine, investigators can sequentially cross participants over from the placebo arm to the vaccine arm according to priority groups. Here, we show how to estimate potentially time-varying placebo-controlled VE in this type of staggered vaccination of participants. In addition, we compare the performance of blinded and unblinded crossover designs in estimating long-term VE.

Authors’ Information

Dan-Yu Lin, Ph.D., is Dennis Gillings Distinguished Professor of Biostatistics, and Donglin Zeng, Ph.D., is Professor of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599-7420, USA. Peter B. Gilbert, Ph.D., is Member, Vaccine and Infectious Disease Division, Fred Hutch, Seattle, WA 98109-1024, USA.

Summary

We show how to estimate the potentially waning long-term efficacy of COVID-19 vaccines using data from randomized, placebo-controlled clinical trials with staggered enrollment of participants and sequential crossover of placebo recipients.

Nonparametric variable importance assessment using machine learning techniques

In a regression setting, it is often of interest to quantify the importance of various features in predicting the response. Commonly, the variable importance measure used is determined by the regression technique employed. For this reason, practitioners often only resort to one of a few regression techniques for which a variable importance measure is naturally defined. Unfortunately, these regression techniques are often suboptimal for predicting the response. Additionally, because the variable importance measures native to different regression techniques generally have a different interpretation, comparisons across techniques can be difficult. In this work, we study a variable importance measure that can be used with any regression technique, and whose interpretation is agnostic to the technique used. This measure is a property of the true data-generating mechanism. Specifically, we discuss a generalization of the analysis of variance variable importance measure and discuss how it facilitates the use of machine learning techniques to flexibly estimate the variable importance of a single feature or group of features. The importance of each feature or group of features in the data can then be described individually, using this measure. We describe how to construct an efficient estimator of this measure as well as a valid confidence interval. Through simulations, we show that our proposal has good practical operating characteristics, and we illustrate its use with data from a study of risk factors for cardiovascular disease in South Africa.

Clinical Endpoints for Evaluating Efficacy in COVID-19 Vaccine Trials

Several vaccine candidates to protect against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or coronavirus disease 2019 (COVID-19) have entered or will soon enter large-scale, phase 3, placebo-controlled randomized clinical trials. To facilitate harmonized evaluation and comparison of the efficacy of these vaccines, a general set of clinical endpoints is proposed, along with considerations to guide the selection of the primary endpoints on the basis of clinical and statistical reasoning. The plausibility that vaccine protection against symptomatic COVID-19 could be accompanied by a shift toward more SARS-CoV-2 infections that are asymptomatic is highlighted, as well as the potential implications of such a shift.

Assessing Durability of Vaccine Effect Following Blinded Crossover in COVID-19 Vaccine Efficacy Trials

BACKGROUND

Several candidate vaccines to prevent COVID-19 disease have entered large-scale phase 3 placebo-controlled randomized clinical trials and some have demonstrated substantial short-term efficacy. Efficacious vaccines should, at some point, be offered to placebo participants, which will occur before long-term efficacy and safety are known.

METHODS

Following vaccination of the placebo group, we show that placebo-controlled vaccine efficacy can be derived by assuming the benefit of vaccination over time has the same profile for the original vaccine recipients and the placebo crossovers. This reconstruction allows estimation of both vaccine durability and potential vaccine-associated enhanced disease.

RESULTS

Post-crossover estimates of vaccine efficacy can provide insights about durability, identify waning efficacy, and identify late enhancement of disease, but are less reliable estimates than those obtained by a standard trial where the placebo cohort is maintained. As vaccine efficacy estimates for post-crossover periods depend on prior vaccine efficacy estimates, longer pre-crossover periods with higher case counts provide better estimates of late vaccine efficacy. Further, open-label crossover may lead to riskier behavior in the immediate crossover period for the unblinded vaccine arm, confounding vaccine efficacy estimates for all post-crossover periods.

CONCLUSIONS

We advocate blinded crossover and continued follow-up of trial participants to best assess vaccine durability and potential delayed enhancement of disease. This approach allows placebo recipients timely access to the vaccine when it would no longer be proper to maintain participants on placebo, yet still allows important insights about immunological and clinical effectiveness over time.

A Hybrid Approach for the Stratified Mark-Specific Proportional Hazards Model with Missing Covariates and Missing Marks, with Application to Vaccine Efficacy Trials

Deployment of the recently licensed CYD-TDV dengue vaccine requires understanding of how the risk of dengue disease in vaccine recipients depends jointly on a host biomarker measured after vaccination (neutralization titer - NAb) and on a "mark" feature of the dengue disease failure event (the amino acid sequence distance of the dengue virus to the dengue sequence represented in the vaccine). The CYD14 phase 3 trial of CYD-TDV measured NAb via case-cohort sampling and the mark in dengue disease failure events, with about a third missing marks. We addressed the question of interest by developing inferential procedures for the stratified mark-specific proportional hazards model with missing covariates and missing marks. Two hybrid approaches are investigated that leverage both augmented inverse probability weighting and nearest neighborhood hot deck multiple imputation. The two approaches differ in how the imputed marks are pooled in estimation. Our investigation shows that NNHD imputation can lead to biased estimation without properly selected neighborhood. Simulations show that the developed hybrid methods perform well with unbiased NNHD imputations from proper neighborhood selection. The new methods applied to CYD14 show that NAb is strongly inversely associated with risk of dengue disease in vaccine recipients, more strongly against dengue viruses with shorter distances.

Prospects for a safe COVID-19 vaccine

Rapid development of an efficacious vaccine against the viral pathogen severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the cause of the coronavirus disease 2019 (COVID-19) pandemic, is essential, but rigorous studies are required to determine the safety of candidate vaccines. Here, on behalf of the Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) Working Group, we evaluate research on the potential risk of immune enhancement of disease by vaccines and viral infections, including coronavirus infections, together with emerging data about COVID-19 disease. Vaccine-associated enhanced disease has been rarely encountered with existing vaccines or viral infections. Although animal models of SARS-CoV-2 infection may elucidate mechanisms of immune protection, we need observations of enhanced disease in people receiving candidate COVID-19 vaccines to understand the risk of immune enhancement of disease. Neither principles of immunity nor preclinical studies provide a basis for prioritizing among the COVID-19 vaccine candidates with respect to safety at this time. Rigorous clinical trial design and postlicensure surveillance should provide a reliable strategy to identify adverse events, including the potential for enhanced severity of COVID-19 disease, after vaccination.

Analysis of the time-varying Cox model for the cause-specific hazard functions with missing causes

This paper studies the Cox model with time-varying coefficients for cause-specific hazard functions when the causes of failure are subject to missingness. Inverse probability weighted and augmented inverse probability weighted estimators are investigated. The latter is considered as a two-stage estimator by directly utilizing the inverse probability weighted estimator and through modeling available auxiliary variables to improve efficiency. The asymptotic properties of the two estimators are investigated. Hypothesis testing procedures are developed to test the null hypotheses that the covariate effects are zero and that the covariate effects are constant. We conduct simulation studies to examine the finite sample properties of the proposed estimation and hypothesis testing procedures under various settings of the auxiliary variables and the percentages of the failure causes that are missing. These simulation results demonstrate that the augmented inverse probability weighted estimators are more efficient than the inverse probability weighted estimators and that the proposed testing procedures have the expected satisfactory results in sizes and powers. The proposed methods are illustrated using the Mashi clinical trial data for investigating the effect of randomization to formula-feeding versus breastfeeding plus extended infant zidovudine prophylaxis on death due to mother-to-child HIV transmission in Botswana.

Evaluation of treatment effect modification by biomarkers measured pre- and post-randomization in the presence of non-monotone missingness

In vaccine studies, an important research question is to study effect modification of clinical treatment efficacy by intermediate biomarker-based principal strata. In settings where participants entering a trial may have prior exposure and therefore variable baseline biomarker values, clinical treatment efficacy may further depend jointly on a biomarker measured at baseline and measured at a fixed time after vaccination. This makes it important to conduct a bivariate effect modification analysis by both the intermediate biomarker-based principal strata and the baseline biomarker values. Existing research allows this assessment if the sampling of baseline and intermediate biomarkers follows a monotone pattern, i.e., if participants who have the biomarker measured post-randomization would also have the biomarker measured at baseline. However, additional complications in study design could happen in practice. For example, in a dengue correlates study, baseline biomarker values were only available from a fraction of participants who have biomarkers measured post-randomization. How to conduct the bivariate effect modification analysis in these studies remains an open research question. In this article, we propose approaches for bivariate effect modification analysis in the complicated sampling design based on an estimated likelihood framework. We demonstrate advantages of the proposed method over existing methods through numerical studies and illustrate our method with data sets from two phase 3 dengue vaccine efficacy trials.

Antigenic competition in CD4+ T cell responses in a randomized, multicenter, double-blind clinical HIV vaccine trial

T cell responses have been implicated in reduced risk of HIV acquisition in uninfected persons and control of viral replication in HIV-infected individuals. HIV Gag-specific T cells have been predominantly associated with post-infection control, whereas Env antigens are the target for protective antibodies; therefore, inclusion of both antigens is common in HIV vaccine design. However, inclusion of multiple antigens may provoke antigenic competition, reducing the potential effectiveness of the vaccine. HVTN 084 was a randomized, multicenter, double-blind phase 1 trial to investigate whether adding Env to a Gag/Pol vaccine decreases the magnitude or breadth of Gag/Pol-specific T cell responses. Fifty volunteers each received one intramuscular injection of 1 × 10¹⁰ particle units (PU) of rAd5 Gag/Pol and EnvA/B/C (3:1:1:1 mixture) or 5 × 10⁹ PU of rAd5 Gag/Pol. CD4⁺ T cell responses to Gag/Pol measured 4 weeks after vaccination by cytokine expression were significantly higher in the group vaccinated without Env, whereas CD8⁺ T cell responses did not differ significantly between the two groups. Mapping of individual epitopes revealed greater breadth of the Gag/Pol-specific T cell response in the absence of Env compared to Env coimmunization. Addition of an Env component to a Gag/Pol vaccine led to reduced Gag/Pol CD4⁺ T cell response rate and magnitude as well as reduced epitope breadth, confirming the presence of antigenic competition. Therefore, T cell-based vaccine strategies should aim at choosing a minimalist set of antigens to reduce interference of individual vaccine components with the induction of the maximally achievable immune response.

Brief Report: Prediction of Serum HIV-1 Neutralization Titers After Passive Administration of VRC01

BACKGROUND

VRC01 is a human IgG1 broadly neutralizing antibody (bnAb) that binds to the HIV-1 envelope glycoprotein. It is being evaluated in two ongoing Phase 2b trials, the first efficacy assessment of a passively-administered bnAb for HIV-1 prevention. HVTN 104 was a phase 1 trial of VRC01.

SETTING

We measured serum concentrations and serum neutralization of VRC01 in 1079 longitudinal samples collected after passive administration of VRC01 in 84 HVTN 104 participants. As assays for measuring VRC01 serum neutralization titers are resource-intensive, we investigated approaches to predicting such titers.

METHODS

Serum concentration was measured using an anti-idiotypic ELISA assay. Serum neutralization ID50 titers and in vitro neutralization potency IC50 of the VRC01 clinical lot were measured against Env-pseudoviruses. Three approaches were used to predict serum neutralization ID50 titers based on (1) observed serum concentration divided by IC50, (2) pharmacokinetics model-predicted serum concentration divided by IC50, and (3) joint modeling of the longitudinal serum concentrations and ID50 titers.

RESULTS

All 3 approaches yielded satisfactory prediction of neutralization titers against viruses of varied sensitivities; the median fold differences (FDs) of observed-over-predicted ID50 titers were between 0.95 and 1.37. Approach 3 generally performed the best with fold differences between 0.95 and 0.99 and <82% mean squared prediction error relative to approach 1. Similar results were obtained for ID80 titers.

CONCLUSION

VRC01 serum neutralization could be accurately predicted, especially when using pharmacokinetics models. The proposed prediction approaches could potentially save significant resources for the characterization of serum neutralization of VRC01, including for other bnAbs and bnAb combinations.

Designing a Study of Correlates of Risk for Ebola Vaccination

The recombinant vesicular stomatitis virus (rVSV) Ebola vaccine was shown to be very efficacious in a novel ring vaccination trial in Guinea. However, no correlates of vaccine protection have been established for Ebola vaccines. Several Ebola vaccine candidates are available, but conducting randomized trials of additional candidates in outbreaks is difficult. Establishing correlates of vaccine protection is essential. Here we explore power and sample-size calculations to evaluate potential correlates of risk during an Ebola vaccination campaign in an outbreak. The method requires that a blood draw be made at a predetermined time after vaccination. The statistical analysis estimates the relative risk of the Ebola endpoint occurring from after the blood draw through to the end of follow-up, contrasting vaccine recipients with different values of the immune response marker. The analysis can be done assuming a trichotomous or continuous marker. Under certain assumptions, at an overall vaccine efficacy of 75%, 50 Ebola endpoints in the vaccinees provided good power. At an overall vaccine efficacy of 90%, 20 Ebola endpoints gave good power. Power was highest when more vaccinees were in the high- and low-responder groups versus the middle group and when vaccine efficacy differed the most between the high- and low-responder groups.

Post-randomization Biomarker Effect Modification Analysis in an HIV Vaccine Clinical Trial

While the HVTN 505 trial showed no overall efficacy of the tested vaccine to prevent HIV infection over placebo, markers measuring immune response to vaccination were strongly correlated with infection. This finding generated the hypothesis that some marker-defined vaccinated subgroups were partially protected whereas others had their risk increased. This hypothesis can be assessed using the principal stratification framework (Frangakis and Rubin, 2002) for studying treatment effect modification by an intermediate response variable, using methods in the sub-field of principal surrogate (PS) analysis that studies multiple principal strata. Unfortunately, available methods for PS analysis require an augmented study design not available in HVTN 505, and make untestable structural risk assumptions, motivating a need for more robust PS methods. Fortunately, another sub-field of principal stratification, survivor average causal effect (SACE) analysis (Rubin, 2006) - which studies effects in a single principal stratum - provides many methods not requiring an augmented design and making fewer assumptions. We show how, for a binary intermediate response variable, methods developed for SACE analysis can be adapted to PS analysis, providing new and more robust PS methods. Application to HVTN 505 supports that the vaccine partially protected individuals with vaccine-induced T-cells expressing certain combinations of functions.

Assessing trends in vaccine efficacy by pathogen genetic distance

Preventive vaccines are an effective public health intervention for reducing the burden of infectious diseases, but have yet to be developed for several major infectious diseases. Vaccine sieve analysis studies whether and how the efficacy of a vaccine varies with the genetics of the infectious pathogen, which may help guide future vaccine development and deployment. A standard statistical approach to sieve analysis compares the effect of the vaccine to prevent infection and disease caused by pathogen types defined dichotomously as genetically near or far from a reference pathogen strain inside the vaccine construct. For example, near may be defined by amino acid identity at all amino acid positions considered in a multiple alignment and far defined by at least one amino acid difference. An alternative approach is to study the efficacy of the vaccine as a function of genetic distance from a pathogen to a reference vaccine strain where the distance cumulates over the set of amino acid positions. We propose a nonparametric method for estimating and testing the trend in the effect of a vaccine across genetic distance. We illustrate the operating characteristics of the estimator via simulation and apply the method to a recent preventive malaria vaccine efficacy trial.

General regression model for the subdistribution of a competing risk under left-truncation and right-censoring

Left-truncation poses extra challenges for the analysis of complex time-to-event data. We propose a general semiparametric regression model for left-truncated and right-censored competing risks data that is based on a novel weighted conditional likelihood function. Targeting the subdistribution hazard, our parameter estimates are directly interpretable with regard to the cumulative incidence function. We compare different weights from recent literature and develop a heuristic interpretation from a cure model perspective that is based on pseudo risk sets. Our approach accommodates external time-dependent covariate effects on the subdistribution hazard. We establish consistency and asymptotic normality of the estimators and propose a sandwich estimator of the variance. In comprehensive simulation studies we demonstrate solid performance of the proposed method. Comparing the sandwich estimator with the inverse Fisher information matrix, we observe a bias for the inverse Fisher information matrix and diminished coverage probabilities in settings with a higher percentage of left-truncation. To illustrate the practical utility of the proposed method, we study its application to a large HIV vaccine efficacy trial dataset.

Microneutralization assay titer correlates analysis in two phase 3 trials of the CYD-TDV tetravalent dengue vaccine in Asia and Latin America

We previously showed that Month 13 50% plaque reduction neutralization test (PRNT50) neutralizing antibody (nAb) titers against dengue virus (DENV) correlated with vaccine efficacy (VE) of CYD-TDV against symptomatic, virologically-confirmed dengue (VCD) in the CYD14 and CYD15 Phase 3 trials. While PRNT is the gold standard nAb assay, it is time-consuming and costly. We developed a next-generation high-throughput microneutralization (MN) assay and assessed its suitability for immune-correlates analyses and immuno-bridging applications. We analyzed MN and PRNT50 titers measured at baseline and Month 13 in a randomly sampled immunogenicity subset, and at Month 13 in nearly all VCD cases through Month 25. For each serotype, MN and PRNT50 titers showed high correlations, at both baseline and Month 13, with MN yielding a higher frequency of baseline-seronegatives. For both assays, Month 13 titer correlated inversely with VCD risk. Like PRNT50, high Month 13 MN titers were associated with high VE, and estimated VE increased with average Month 13 MN titer. We also studied each assay as a valid surrogate endpoint based on the Prentice criteria, which supported each assay as a valid surrogate for DENV-1 but only partially valid for DENV-2, -3, and -4. In addition, we applied Super-Learner to assess how well demographic, Month 13 MN, and/or Month 13 PRNT50 titers could predict Month 13-25 VCD outcome status; prediction was best when using demographic, MN, and PRNT50 information. We conclude that Month 13 MN titer performs comparably to Month 13 PRNT50 titer as a correlate of risk, correlate of vaccine efficacy, and surrogate endpoint. The MN assay could potentially be used to assess nAb titers in immunogenicity studies, immune-correlates studies, and immuno-bridging applications. Additional research would be needed for assessing the utility of MN titer in correlates analyses of other DENV endpoints and over longer follow-up periods.