Immune Correlates Analysis of a Single Ad26.COV2.S Dose in the ENSEMBLE COVID-19 Vaccine Efficacy Clinical Trial

Anti-spike IgG binding antibody, anti-receptor binding domain IgG antibody, and pseudovirus neutralizing antibody measurements four weeks post-vaccination were assessed as correlates of risk of moderate to severe-critical COVID-19 outcomes through 83 days post-vaccination and as correlates of protection following a single dose of Ad26.COV2.S COVID-19 vaccine in the placebo-controlled phase of ENSEMBLE, an international, randomized efficacy trial. Each marker had evidence as a correlate of risk and of protection, with strongest evidence for 50% inhibitory dilution (ID50) neutralizing antibody titer. The outcome hazard ratio was 0.49 (95% confidence interval 0.29, 0.81; p=0.006) per 10-fold increase in ID50; vaccine efficacy was 60% (43, 72%) at nonquantifiable ID50 (< 2.7 IU50/ml) and rose to 89% (78, 96%) at ID50 = 96.3 IU50/ml. Comparison of the vaccine efficacy by ID50 titer curves for ENSEMBLE-US, the COVE trial of the mRNA-1273 vaccine, and the COV002-UK trial of the AZD1222 vaccine supported consistency of the ID50 titer correlate of protection across trials and vaccine types.

Optimizing clinical dosing of combination broadly neutralizing antibodies for HIV prevention

Broadly neutralizing antibodies (bNAbs) are promising agents to prevent HIV infection and achieve HIV remission without antiretroviral therapy (ART). As with ART, bNAb combinations are likely needed to cover HIV's extensive diversity. Not all bNAbs are identical in terms of their breadth, potency, and in vivo longevity (half-life). Given these differences, it is important to optimally select the composition, or dose ratio, of combination bNAb therapies for future clinical studies. We developed a model that synthesizes 1) pharmacokinetics, 2) potency against a wide HIV diversity, 3) interaction models for how drugs work together, and 4) correlates that translate in vitro potency to clinical protection. We found optimization requires drug-specific balances between potency, longevity, and interaction type. As an example, tradeoffs between longevity and potency are shown by comparing a combination therapy to a bi-specific antibody (a single protein merging both bNAbs) that takes the better potency but the worse longevity of the two components. Then, we illustrate a realistic dose ratio optimization of a triple combination of VRC07, 3BNC117, and 10-1074 bNAbs. We apply protection estimates derived from both a non-human primate (NHP) challenge study meta-analysis and the human antibody mediated prevention (AMP) trials. In both cases, we find a 2:1:1 dose emphasizing VRC07 is nearly optimal. Our approach can be immediately applied to optimize the next generation of combination antibody prevention and cure studies.

Innovative vaccine approaches-a Keystone Symposia report

The rapid development of COVID-19 vaccines was the result of decades of research to establish flexible vaccine platforms and understand pathogens with pandemic potential, as well as several novel changes to the vaccine discovery and development processes that partnered industry and governments. And while vaccines offer the potential to drastically improve global health, low-and-middle-income countries around the world often experience reduced access to vaccines and reduced vaccine efficacy. Addressing these issues will require novel vaccine approaches and platforms, deeper insight how vaccines mediate protection, and innovative trial designs and models. On June 28-30, 2021, experts in vaccine research, development, manufacturing, and deployment met virtually for the Keystone eSymposium "Innovative Vaccine Approaches" to discuss advances in vaccine research and development.

Immune correlates analysis of the mRNA-1273 COVID-19 vaccine efficacy clinical trial

In the coronavirus efficacy (COVE) phase 3 clinical trial, vaccine recipients were assessed for neutralizing and binding antibodies as correlates of risk for COVID-19 disease and as correlates of protection. These immune markers were measured at the time of second vaccination and 4 weeks later, with values reported in standardized World Health Organization international units. All markers were inversely associated with COVID-19 risk and directly associated with vaccine efficacy. Vaccine recipients with postvaccination 50% neutralization titers 10, 100, and 1000 had estimated vaccine efficacies of 78% (95% confidence interval, 54 to 89%), 91% (87 to 94%), and 96% (94 to 98%), respectively. These results help define immune marker correlates of protection and may guide approval decisions for messenger RNA (mRNA) COVID-19 vaccines and other COVID-19 vaccines.

A general framework for inference on algorithm-agnostic variable importance

In many applications, it is of interest to assess the relative contribution of features (or subsets of features) toward the goal of predicting a response - in other words, to gauge the variable importance of features. Most recent work on variable importance assessment has focused on describing the importance of features within the confines of a given prediction algorithm. However, such assessment does not necessarily characterize the prediction potential of features, and may provide a misleading reflection of the intrinsic value of these features. To address this limitation, we propose a general framework for nonparametric inference on interpretable algorithm-agnostic variable importance. We define variable importance as a population-level contrast between the oracle predictiveness of all available features versus all features except those under consideration. We propose a nonparametric efficient estimation procedure that allows the construction of valid confidence intervals, even when machine learning techniques are used. We also outline a valid strategy for testing the null importance hypothesis. Through simulations, we show that our proposal has good operating characteristics, and we illustrate its use with data from a study of an antibody against HIV-1 infection.

Associations of human leukocyte antigen with neutralizing antibody titers in a tetravalent dengue vaccine phase 2 efficacy trial in Thailand

The recombinant, live, attenuated, tetravalent dengue vaccine CYD-TDV has shown efficacy against all four dengue serotypes. In this exploratory study (CYD59, NCT02827162), we evaluated potential associations of host human leukocyte antigen (HLA) alleles with dengue antibody responses, CYD-TDV vaccine efficacy, and virologically-confirmed dengue (VCD) cases. Children 4-11 years old, who previously completed a phase 2b efficacy study of CYD-TDV in a single center in Thailand, were included in the study. Genotyping of HLA class I and II loci was performed by next-generation sequencing from DNA obtained from 335 saliva samples. Dengue neutralizing antibody titers (NAb) were assessed as a correlate of risk and protection. Regression analyses were used to assess associations between HLA alleles and NAb responses, vaccine efficacy, and dengue outcomes. Month 13 NAb log geometric mean titers (GMTs) were associated with decreased risk of VCD. In the vaccine group, HLA-DRB1*11 was significantly associated with higher NAb log GMT levels (beta: 0.76; p = 0.002, q = 0.13). Additionally, in the absence of vaccination, HLA associations were observed between the presence of DPB1*03:01 and increased NAb log GMT levels (beta: 1.24; p = 0.005, q = 0.17), and between DPB1*05:01 and reduced NAb log GMT levels (beta: -1.1; p = 0.001, q = 0.07). This study suggests associations of HLA alleles with NAb titers in the context of dengue outcomes. This study was registered with clinicaltrials.gov: NCT02827162.

Simulation-Based Pharmacokinetics Sampling Design for Evaluating Correlates of Prevention Efficacy of Passive HIV Monoclonal Antibody Prophylaxis

We address sampling design of population pharmacokinetics (popPK) experiments in the context of two ongoing phase 2b efficacy trials that evaluate the efficacy of VRC01 (vs. placebo) in reducing the rate of HIV infection among 4625 participants. Blood samples are collected at up to 22 study visits from all participants for immediate HIV diagnosis as the primary trial outcome, and stored for future outcome-dependent marker measurements. A key secondary objective of the trials is to evaluate correlates of prevention efficacy among a sub-cohort of VRC01 recipients in terms of whether the current value of VRC01 serum concentration is associated with the instantaneous rate of HIV infection. To accomplish this, concentrations on a daily grid are estimated via non-linear mixed effects popPK modeling of observed 4-weekly concentrations. Given the impracticality of measuring concentrations in all stored blood samples, we devised a simulation-based sampling design framework to evaluate the impact of sub-cohort sample sizes (m) and sampling schemes of time-points on the accuracy and precision of the popPK model parameters. We accounted for specific study schedules and heterogeneity in participants' characteristics and study adherence patterns. We found that with m = 120, reasonably unbiased and consistent estimates of most fixed and random effect terms could be obtained without complete sampling of all 22 time-points, even under low study adherence (about half of the 4-weekly visits missing per participant). The described simulation framework is not only novel in its application to popPK sampling design for studying correlates of prevention efficacy in a subcohort of the parent trial, but also flexible in accommodating real-life study setup options, and can be generalized to other single- or multiple-dose PK sampling design settings.

Tracking SARS-CoV-2 Spike Protein Mutations in the United States (January 2020-March 2021) Using a Statistical Learning Strategy

The emergence and establishment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of interest (VOIs) and variants of concern (VOCs) highlight the importance of genomic surveillance. We propose a statistical learning strategy (SLS) for identifying and spatiotemporally tracking potentially relevant Spike protein mutations. We analyzed 167,893 Spike protein sequences from coronavirus disease 2019 (COVID-19) cases in the United States (excluding 21,391 sequences from VOI/VOC strains) deposited at GISAID from 19 January 2020 to 15 March 2021. Alignment against the reference Spike protein sequence led to the identification of viral residue variants (VRVs), i.e., residues harboring a substitution compared to the reference strain. Next, generalized additive models were applied to model VRV temporal dynamics and to identify VRVs with significant and substantial dynamics (false discovery rate q-value < 0.01; maximum VRV proportion >10% on at least one day). Unsupervised learning was then applied to hierarchically organize VRVs by spatiotemporal patterns and identify VRV-haplotypes. Finally, homology modeling was performed to gain insight into the potential impact of VRVs on Spike protein structure. We identified 90 VRVs, 71 of which had not previously been observed in a VOI/VOC, and 35 of which have emerged recently and are durably present. Our analysis identified 17 VRVs ~91 days earlier than their first corresponding VOI/VOC publication. Unsupervised learning revealed eight VRV-haplotypes of four VRVs or more, suggesting two emerging strains (B1.1.222 and B.1.234). Structural modeling supported a potential functional impact of the D1118H and L452R mutations. The SLS approach equally monitors all Spike residues over time, independently of existing phylogenic classifications, and is complementary to existing genomic surveillance methods.

Calibration of two validated SARS-CoV-2 pseudovirus neutralization assays for COVID-19 vaccine evaluation

Vaccine-induced neutralizing antibodies (nAbs) are key biomarkers considered to be associated with vaccine efficacy. In United States government-sponsored phase 3 efficacy trials of COVID-19 vaccines, nAbs are measured by two different validated pseudovirus-based SARS-CoV-2 neutralization assays, with each trial using one of the two assays. Here we describe and compare the nAb titers obtained in the two assays. We observe that one assay consistently yielded higher nAb titers than the other when both assays were performed on the World Health Organization's anti-SARS-CoV-2 immunoglobulin International Standard, COVID-19 convalescent sera, and mRNA-1273 vaccinee sera. To overcome the challenge this difference in readout poses in comparing/combining data from the two assays, we evaluate three calibration approaches and show that readouts from the two assays can be calibrated to a common scale. These results may aid decision-making based on data from these assays for the evaluation and licensure of new or adapted COVID-19 vaccines.

Efficient nonparametric inference on the effects of stochastic interventions under two-phase sampling, with applications to vaccine efficacy trials

The advent and subsequent widespread availability of preventive vaccines has altered the course of public health over the past century. Despite this success, effective vaccines to prevent many high-burden diseases, including human immunodeficiency virus (HIV), have been slow to develop. Vaccine development can be aided by the identification of immune response markers that serve as effective surrogates for clinically significant infection or disease endpoints. However, measuring immune response marker activity is often costly, which has motivated the usage of two-phase sampling for immune response evaluation in clinical trials of preventive vaccines. In such trials, the measurement of immunological markers is performed on a subset of trial participants, where enrollment in this second phase is potentially contingent on the observed study outcome and other participant-level information. We propose nonparametric methodology for efficiently estimating a counterfactual parameter that quantifies the impact of a given immune response marker on the subsequent probability of infection. Along the way, we fill in theoretical gaps pertaining to the asymptotic behavior of nonparametric efficient estimators in the context of two-phase sampling, including a multiple robustness property enjoyed by our estimators. Techniques for constructing confidence intervals and hypothesis tests are presented, and an open source software implementation of the methodology, the txshift R package, is introduced. We illustrate the proposed techniques using data from a recent preventive HIV vaccine efficacy trial.

Evaluating the Efficacy of Coronavirus Disease 2019 Vaccines

A large number of studies are being conducted to evaluate the efficacy and safety of candidate vaccines against coronavirus disease 2019 (COVID-19). Most phase 3 trials have adopted virologically confirmed symptomatic COVID-19 as the primary efficacy end point, although laboratory-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is also of interest. In addition, it is important to evaluate the effect of vaccination on disease severity. To provide a full picture of vaccine efficacy and make efficient use of available data, we propose using SARS-CoV-2 infection, symptomatic COVID-19, and severe COVID-19 as dual or triple primary end points. We demonstrate the advantages of this strategy through realistic simulation studies. Finally, we show how this approach can provide rigorous interim monitoring of the trials and efficient assessment of the durability of vaccine efficacy.

Mathematical Modeling of Vaccines That Prevent SARS-CoV-2 Transmission

SARS-CoV-2 vaccine clinical trials assess efficacy against disease (VEDIS), the ability to block symptomatic COVID-19. They only partially discriminate whether VEDIS is mediated by preventing infection completely, which is defined as detection of virus in the airways (VESUSC), or by preventing symptoms despite infection (VESYMP). Vaccine efficacy against transmissibility given infection (VEINF), the decrease in secondary transmissions from infected vaccine recipients, is also not measured. Using mathematical modeling of data from King County Washington, we demonstrate that if the Moderna (mRNA-1273QS) and Pfizer-BioNTech (BNT162b2) vaccines, which demonstrated VEDIS > 90% in clinical trials, mediate VEDIS by VESUSC, then a limited fourth epidemic wave of infections with the highly infectious B.1.1.7 variant would have been predicted in spring 2021 assuming rapid vaccine roll out. If high VEDIS is explained by VESYMP, then high VEINF would have also been necessary to limit the extent of this fourth wave. Vaccines which completely protect against infection or secondary transmission also substantially lower the number of people who must be vaccinated before the herd immunity threshold is reached. The limited extent of the fourth wave suggests that the vaccines have either high VESUSC or both high VESYMP and high VEINF against B.1.1.7. Finally, using a separate intra-host mathematical model of viral kinetics, we demonstrate that a 0.6 log vaccine-mediated reduction in average peak viral load might be sufficient to achieve 50% VEINF, which suggests that human challenge studies with a relatively low number of infected participants could be employed to estimate all three vaccine efficacy metrics.

RV144 vaccine imprinting constrained HIV-1 evolution following breakthrough infection

The scale of the HIV-1 epidemic underscores the need for a vaccine. The multitude of circulating HIV-1 strains together with HIV-1’s high evolvability hints that HIV-1 could adapt to a future vaccine. Here, we wanted to investigate the effect of vaccination on the evolution of the virus post-breakthrough infection. We analyzed 2,635 HIV-1 env sequences sampled up to a year post-diagnosis from 110 vaccine and placebo participants who became infected in the RV144 vaccine efficacy trial. We showed that the Env signature sites that were previously identified to distinguish vaccine and placebo participants were maintained over time. In addition, fewer sites were under diversifying selection in the vaccine group than in the placebo group. These results indicate that HIV-1 would possibly adapt to a vaccine upon its roll-out.

Calibration of Two Validated SARS-CoV-2 Pseudovirus Neutralization Assays for COVID-19 Vaccine Evaluation

Vaccine-induced neutralizing antibodies (nAbs) are key biomarkers considered to be associated with vaccine efficacy. In United States Government-sponsored phase 3 efficacy trials of COVID-19 vaccines, nAbs are measured by two different validated pseudovirus-based SARS-CoV-2 neutralization assays, with each trial using one of the two assays. Here we describe and compare the nAb titers obtained in the two assays. We observe that one assay consistently yielded higher nAb titers than the other when both assays were performed on the World Health Organization’s anti-SARS-CoV-2 immunoglobulin International Standard, COVID-19 convalescent sera, and mRNA-1273 vaccinee sera. To overcome the challenge this difference in readout poses in comparing/combining data from the two assays, we evaluate three calibration approaches and show that readouts from the two assays can be calibrated to a common scale. These results may aid decision-making based on data from these assays for the evaluation and licensure of new or adapted COVID-19 vaccines.

CMV viral load kinetics as surrogate endpoints after allogeneic transplantation

BACKGROUNDViral load (VL) surrogate endpoints transformed development of HIV and hepatitis C therapeutics. Surrogate endpoints for CMV-related morbidity and mortality could advance development of antiviral treatments. Although observational data support using CMV VL as a trial endpoint, randomized controlled trials (RCTs) demonstrating direct associations between virological markers and clinical endpoints are lacking.METHODSWe performed CMV DNA PCR on frozen serum samples from the only placebo-controlled RCT of ganciclovir for early treatment of CMV after hematopoietic cell transplantation (HCT). We used established criteria to assess VL kinetics as surrogates for CMV disease or death by weeks 8, 24, and 48 after randomization and quantified antiviral effects captured by each marker. We used ensemble-based machine learning to assess the predictive ability of VL kinetics and performed this analysis on a ganciclovir prophylaxis RCT for validation.RESULTSVL suppression with ganciclovir reduced cumulative incidence of CMV disease and death for 20 years after HCT. Mean VL, peak VL, and change in VL during the first 5 weeks of treatment fulfilled the Prentice definition for surrogacy, capturing more than 95% of ganciclovir's effect, and yielded highly sensitive and specific predictions by week 48. In the prophylaxis trial, the viral shedding rate satisfied the Prentice definition for CMV disease by week 24.CONCLUSIONSOur results support using CMV VL kinetics as surrogates for CMV disease, provide a framework for developing CMV preventative and therapeutic agents, and support reductions in VL as the mechanism through which antivirals reduce CMV disease.FUNDINGMerck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc.

Calibration of Two Validated SARS-CoV-2 Pseudovirus Neutralization Assays for COVID-19 Vaccine Evaluation

Vaccine-induced neutralizing antibodies (nAbs) are key biomarkers considered to be associated with vaccine efficacy. In United States Government-sponsored phase 3 efficacy trials of COVID-19 vaccines, nAbs are measured by two different validated pseudovirus-based SARS-CoV-2 neutralization assays, with each trial using one of the two assays. Here we describe and compare the nAb titers obtained in the two assays. We observe that one assay consistently yielded higher nAb titers than the other when both assays were performed on the World Health Organization’s anti-SARS-CoV-2 immunoglobulin International Standard, COVID-19 convalescent sera, and mRNA-1273 vaccinee sera. To overcome the challenge this difference in readout poses in comparing/combining data from the two assays, we evaluate three calibration approaches and show that readouts from the two assays can be calibrated to a common scale. These results may aid decision-making based on data from these assays for the evaluation and licensure of new or adapted COVID-19 vaccines.

Immune Correlates Analysis of the mRNA-1273 COVID-19 Vaccine Efficacy Trial

BACKGROUND

In the Coronavirus Efficacy (COVE) trial, estimated mRNA-1273 vaccine efficacy against coronavirus disease-19 (COVID-19) was 94%. SARS-CoV-2 antibody measurements were assessed as correlates of COVID-19 risk and as correlates of protection.

METHODS

Through case-cohort sampling, participants were selected for measurement of four serum antibody markers at Day 1 (first dose), Day 29 (second dose), and Day 57: IgG binding antibodies (bAbs) to Spike, bAbs to Spike receptor-binding domain (RBD), and 50% and 80% inhibitory dilution pseudovirus neutralizing antibody titers calibrated to the WHO International Standard (cID50 and cID80). Participants with no evidence of previous SARS-CoV-2 infection were included. Cox regression assessed in vaccine recipients the association of each Day 29 or 57 serologic marker with COVID-19 through 126 or 100 days of follow-up, respectively, adjusting for risk factors.

RESULTS

Day 57 Spike IgG, RBD IgG, cID50, and cID80 neutralization levels were each inversely correlated with risk of COVID-19: hazard ratios 0.66 (95% CI 0.50, 0.88; p=0.005); 0.57 (0.40, 0.82; p=0.002); 0.42 (0.27, 0.65; p<0.001); 0.35 (0.20, 0.61; p<0.001) per 10-fold increase in marker level, respectively, multiplicity adjusted P-values 0.003-0.010. Results were similar for Day 29 markers (multiplicity adjusted P-values <0.001-0.003). For vaccine recipients with Day 57 reciprocal cID50 neutralization titers that were undetectable (<2.42), 100, or 1000, respectively, cumulative incidence of COVID-19 through 100 days post Day 57 was 0.030 (0.010, 0.093), 0.0056 (0.0039, 0.0080), and 0.0023 (0.0013, 0.0036). For vaccine recipients at these titer levels, respectively, vaccine efficacy was 50.8% (-51.2, 83.0%), 90.7% (86.7, 93.6%), and 96.1% (94.0, 97.8%). Causal mediation analysis estimated that the proportion of vaccine efficacy mediated through Day 29 cID50 titer was 68.5% (58.5, 78.4%).

CONCLUSIONS

Binding and neutralizing antibodies correlated with COVID-19 risk and vaccine efficacy and likely have utility in predicting mRNA-1273 vaccine efficacy against COVID-19.

TRIAL REGISTRATION NUMBER

COVE ClinicalTrials.gov number, NCT04470427.

A Deferred-Vaccination Design to Assess Durability of COVID-19 Vaccine Effect After the Placebo Group Is Vaccinated

Multiple candidate vaccines to prevent COVID-19 have entered large-scale phase 3 placebo-controlled randomized clinical trials, and several have demonstrated substantial short-term efficacy. At some point after demonstration of substantial efficacy, placebo recipients should be offered the efficacious vaccine from their trial, which will occur before longer-term efficacy and safety are known. The absence of a placebo group could compromise assessment of longer-term vaccine effects. However, by continuing follow-up after vaccination of the placebo group, this study shows that placebo-controlled vaccine efficacy can be mathematically derived by assuming that the benefit of vaccination over time has the same profile for the original vaccine recipients and the original placebo recipients after their vaccination. Although this derivation provides less precise estimates than would be obtained by a standard trial where the placebo group remains unvaccinated, this proposed approach allows estimation of longer-term effect, including durability of vaccine efficacy and whether the vaccine eventually becomes harmful for some. Deferred vaccination, if done open-label, may lead to riskier behavior in the unblinded original vaccine group, confounding estimates of long-term vaccine efficacy. Hence, deferred vaccination via blinded crossover, where the vaccine group receives placebo and vice versa, would be the preferred way to assess vaccine durability and potential delayed harm. Deferred vaccination allows placebo recipients timely access to the vaccine when it would no longer be proper to maintain them on placebo, yet still allows important insights about immunologic and clinical effectiveness over time.

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 coronavirus disease 2019 (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 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection than against symptomatic COVID-19 because infection is not observed directly but rather is known to occur between 2 antibody or reverse-transcription polymerase chain reaction (RT-PCR) tests. Additional challenges arise as community transmission changes over time and as participants are vaccinated on different dates because of staggered enrollment of participants or crossover of placebo recipients to the vaccine arm 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 that mimic 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.

Immunobridging efficacy of a tetravalent dengue vaccine against dengue and against hospitalized dengue from children/adolescents to adults in highly endemic countries

BACKGROUND

The recombinant tetravalent live-attenuated dengue vaccine based on the YF 17D vaccine virus backbone (CYD-TDV) demonstrated vaccine efficacy (VE) against symptomatic, virologically confirmed dengue of any serotype from month 13 to month 25 (VCD-DENV-AnyM13→M25) in the CYD14 (2-14-y-olds) and CYD15 (9-16-y-olds) phase 3 trials. Fifty percent plaque reduction neutralization test (PRNT50) titers are a potential surrogate for immunobridging VE to adults.

METHODS

Using PRNT50 calibration datasets, we applied immunobridging approaches using baseline and/or M13 PRNT50 titers to estimate VE against VCD-DENV-AnyM0→M25 and against hospitalized VCD (HVCD)-DENV-AnyM0→M72 in hypothetical 18-45-y-old and 46-50-y-old CYD14 and CYD15 cohorts.

RESULTS

Baseline and M13 geometric mean PRNT50 titers were greater in 18-45-y-olds and in 46-50-y-olds vs 9-16-y-olds for most comparisons. Estimated VE (95% CIs against VCD-DENV-AnyM0→M25 ranged from 75.3% to 90.9% (52.5% to 100%) for 18-45-y-olds and 74.8% to 92.0% (53.4% to 100%) for 46-50-y-olds. Estimated VE (95% CIs) against HVCD-DENV-AnyM0→M72 ranged from 58.8% to 78.1% (40.9 to 98.9%) for 18-45-y-olds and 57.2% to 78.4% (40.5 to 97.6%) for 46-50-y-olds. Corresponding predictions among baseline-seropositive individuals yielded comparable or higher VE estimates.

CONCLUSIONS

VE M0→M25 against DENV-Any and VE against HVCD-DENV-AnyM0→M72 are both expected to be higher in 18-45 and 46-50-y-olds vs CYD14 and CYD15 9-16-y-olds.

Analysis of Neutralizing Antibodies as a Correlate of Instantaneous Risk of Hospitalized Dengue in Placebo Recipients of Dengue Vaccine Efficacy Trials

BACKGROUND

In the CYD14 (NCT01373281) and CYD15 (NCT01374516) dengue vaccine efficacy trials, Month 13 neutralizing antibody (nAb) titers correlated inversely with risk of symptomatic, virologically confirmed dengue (VCD) between Month 13 (one month post-final-dose) and Month 25. We assessed nAb titer as a correlate of instantaneous risk of hospitalized VCD (HVCD), for which participants were continually surveilled for 72 months.

METHODS

Using longitudinal nAb titers from the per-protocol immunogenicity subsets, we estimated hazard ratios (HRs) of HVCD by current nAb titer value for three correlate/endpoint pairs: average titer across all four serotypes/HVCD of any serotype (HVCD-Any), serotype-specific titer/homologous HVCD, and serotype-specific titer/heterologous HVCD.

RESULTS

Baseline-seropositive placebo recipients with higher average titer had lower instantaneous risk of HVCD-Any in 2-16-year-olds and in 9-16-year-olds (HR 0.26 or 0.15 per 10-fold increase in average titer by two methods, 95% CIs 0.14 to 0.45 and 0.07 to 0.34, respectively) pooled across both trials. Results were similar for homologous HVCD. There was evidence suggesting increased HVCD-Any risk in participants with low average titer (1:10 to 1:100) compared to seronegative participants (HR 1.85, 95% CI 0.93 to 3.68).

CONCLUSIONS

Natural infection-induced nAbs were inversely associated with hospitalized dengue, upon exceeding a relatively low threshold.

Tracking SARS-CoV-2 Spike Protein Mutations in the United States (2020/01 - 2021/03) Using a Statistical Learning Strategy

The emergence and establishment of SARS-CoV-2 variants of interest (VOI) and variants of concern (VOC) highlight the importance of genomic surveillance. We propose a statistical learning strategy (SLS) for identifying and spatiotemporally tracking potentially relevant Spike protein mutations. We analyzed 167,893 Spike protein sequences from US COVID-19 cases (excluding 21,391 sequences from VOI/VOC strains) deposited at GISAID from January 19, 2020 to March 15, 2021. Alignment against the reference Spike protein sequence led to the identification of viral residue variants (VRVs), i.e., residues harboring a substitution compared to the reference strain. Next, generalized additive models were applied to model VRV temporal dynamics, to identify VRVs with significant and substantial dynamics (false discovery rate q-value <0.01; maximum VRV proportion > 10% on at least one day). Unsupervised learning was then applied to hierarchically organize VRVs by spatiotemporal patterns and identify VRV-haplotypes. Finally, homology modelling was performed to gain insight into potential impact of VRVs on Spike protein structure. We identified 90 VRVs, 71 of which have not previously been observed in a VOI/VOC, and 35 of which have emerged recently and are durably present. Our analysis identifies 17 VRVs ∼91 days earlier than their first corresponding VOI/VOC publication. Unsupervised learning revealed eight VRV-haplotypes of 4 VRVs or more, suggesting two emerging strains (B1.1.222 and B.1.234). Structural modeling supported potential functional impact of the D1118H and L452R mutations. The SLS approach equally monitors all Spike residues over time, independently of existing phylogenic classifications, and is complementary to existing genomic surveillance methods.

Inference on treatment effect modification by biomarker response in a three-phase sampling design

An objective in randomized clinical trials is the evaluation of "principal surrogates," which consists of analyzing how the treatment effect on a clinical endpoint varies over principal strata subgroups defined by an intermediate response outcome under both or one of the treatment assignments. The latter effect modification estimand has been termed the marginal causal effect predictiveness (mCEP) curve. This objective was addressed in two randomized placebo-controlled Phase 3 dengue vaccine trials for an antibody response biomarker whose sampling design rendered previously developed inferential methods highly inefficient due to a three-phase sampling design. In this design, the biomarker was measured in a case-cohort sample and a key baseline auxiliary strongly associated with the biomarker (the "baseline surrogate measure") was only measured in a further sub-sample. We propose a novel approach to estimation of the mCEP curve in such three-phase sampling designs that avoids the restrictive "placebo structural risk" modeling assumption common to past methods and that further improves robustness by the use of non-parametric kernel smoothing for biomarker density estimation. Additionally, we develop bootstrap-based procedures for pointwise and simultaneous confidence intervals and testing of four relevant hypotheses about the mCEP curve. We investigate the finite-sample properties of the proposed methods and compare them to those of an alternative method making the placebo structural risk assumption. Finally, we apply the novel and alternative procedures to the two dengue vaccine trial data sets.

Semiparametric regression analysis of partly interval-censored failure time data with application to an AIDS clinical trial

Failure time data subject to various types of censoring commonly arise in epidemiological and biomedical studies. Motivated by an AIDS clinical trial, we consider regression analysis of failure time data that include exact and left-, interval-, and/or right-censored observations, which are often referred to as partly interval-censored failure time data. We study the effects of potentially time-dependent covariates on partly interval-censored failure time via a class of semiparametric transformation models that includes the widely used proportional hazards model and the proportional odds model as special cases. We propose an EM algorithm for the nonparametric maximum likelihood estimation and show that it unifies some existing approaches developed for traditional right-censored data or purely interval-censored data. In particular, the proposed method reduces to the partial likelihood approach in the case of right-censored data under the proportional hazards model. We establish that the resulting estimator is consistent and asymptotically normal. In addition, we investigate the proposed method via simulation studies and apply it to the motivating AIDS clinical trial.