Omicron COVID-19 Immune Correlates Analysis of a Third Dose of mRNA-1273 in the COVE Trial (preprint)

In the coronavirus efficacy (COVE) phase 3 efficacy trial of the mRNA-1273 vaccine, IgG binding antibody (bAb) concentration against Spike (BA.1 strain) and neutralizing antibody (nAb) titer against Spike (BA.1 strain) pseudovirus were assessed as correlates of risk of Omicron COVID-19 and as correlates of relative boost efficacy in per-protocol recipients of a third (booster) dose. Markers were measured on the day of the boost (BD1) and 28 days later (BD29). For SARS-CoV-2 naive individuals, BD29 Spike IgG-BA.1 strain bAbs and BD29 BA.1-strain nAbs inversely correlated with Omicron COVID-19: hazard ratio (HR) per 10-fold marker increase [95% confidence interval (CI)] = 0.16 (0.03, 0.79); P=0.024 and 0.31 (0.10, 0.96); P = 0.042, respectively. These markers also inversely correlated with Omicron COVID-19 in non-naive individuals: HR = 0.15 (0.04, 0.63); P = 0.009 and 0.28 (0.07, 1.08); P = 0.06, trend. Fold-rise in markers from BD1 to BD29 had similarly strong inverse correlations. For SARS-CoV-2 naive individuals, overall booster relative (three-dose vs two-dose) efficacy was 46% (95% CI: 20%, 64%) and correlated with BA.1 strain nAb titer at exposure. At 56, 251, and 891 arbitrary units (AU)/ml (10th, 50th, and 90th percentile), the booster relative efficacies were -8% (95% CI: -126%, 48%), 50% (25%, 67%), and 74% (49%, 87%), respectively. Similar relationships were observed for Spike IgG-BA.1 strain bAbs and for the markers measured at BD29. The performance of bAb and nAb markers as correlates of protection against Omicron COVID-19 supports their continued use as surrogate endpoints for mRNA vaccination against Omicron COVID-19.

Semiparametric inference for relative heterogeneous vaccine efficacy between strains in observational case-only studies (preprint)

The aim of this manuscript is to explore semiparametric methods for inferring subgroup-specific relative vaccine efficacy in a partially vaccinated population against multiple strains of a virus. We consider methods for observational case-only studies with informative missingness in viral strain type due to vaccination status, pre-vaccination variables, and also post-vaccination factors such as viral load. We establish general causal conditions under which the relative conditional vaccine efficacy between strains can be identified nonparametrically from the observed data-generating distribution. Assuming that the relative strain-specific conditional vaccine efficacy has a known parametric form, we propose semiparametric asymptotically linear estimators of the parameters based on targeted (debiased) machine learning estimators for partially linear logistic regression models. Finally, we apply our methods to estimate the relative strain-specific conditional vaccine efficacy in the ENSEMBLE COVID-19 vaccine trial.

Immune Correlates Analysis of the PREVENT-19 COVID-19 Vaccine Efficacy Clinical Trial (preprint)

In the randomized, placebo-controlled PREVENT-19 phase 3 trial conducted in the U.S. and Mexico of the NVX-CoV2373 adjuvanted, recombinant spike protein nanoparticle vaccine, anti-spike binding IgG concentration (spike IgG) and pseudovirus 50% neutralizing antibody titer (nAb ID50) measured two weeks after two doses were assessed as correlates of risk and as correlates of protection against PCR-confirmed symptomatic SARS-CoV-2 infection (COVID-19). These immune correlates analyses were conducted in the U.S. cohort of baseline SARS-CoV-2 negative per-protocol participants using a case-cohort design that measured the antibody markers from all 12 vaccine recipient breakthrough COVID-19 cases starting 7 days post antibody measurement and from 639 vaccine recipient non-cases (Mexico was excluded due to zero breakthrough cases with the efficacy data cut-off date April 19, 2021). In vaccine recipients, the baseline risk factor-adjusted hazard ratio of COVID-19 was 0.36 (95% CI: 0.20, 0.63), p<0.001 (adjusted p-0.005) per 10-fold increase in IgG spike concentration and 0.39 (0.19, 0.82), p=0.013 (adjusted p=0.030) per 10-fold increase in nAb ID50 titer. At spike IgG concentration 100, 1000, and 6934 binding antibody units/ml (100 is the 3rd percentile, 6934 is the 97.5th percentile), vaccine efficacy to reduce the probability of acquiring COVID-19 at 59 days post marker measurement was 65.5% (95% CI: 23.0%, 90.8%), 87.7% (77.7%, 94.4%), and 94.8% (88.0%, 97.9%), respectively. At nAb ID50 titers of 50, 100, 1000, and 7230 IU50/ml (50 is the 5th percentile, 7230 the 97.5th percentile), these estimates were 75.7% (49.8%, 93.2%), 81.7% (66.3%, 93.2%), 92.8% (85.1%, 97.4%) and 96.8% (88.3%, 99.3%). The same two antibody markers were assessed as immune correlates via the same study design and statistical analysis in the mRNA-1273 phase 3 COVE trial (except in COVE the markers were measured four weeks post dose two). Spike IgG levels were slightly lower and nAb ID50 titers slightly higher after NVX-CoV2373 than after mRNA-1273 vaccination. The strength of the nAb ID50 correlate was similar between the trials, whereas the spike IgG antibodies appeared to correlate more strongly with NVX-CoV2373 in PREVENT-19, as quantified by the hazard ratio and the degree of change in vaccine efficacy across antibody levels. However, the relatively few breakthrough cases in PREVENT-19 limited the ability to infer a stronger correlate. The conclusion is that both markers were consistent correlates of protection for the two vaccines, supporting potential cross-vaccine platform applications of these markers for guiding decisions about vaccine approval and use.

Correlates of protection, thresholds of protection, and immunobridging in SARS-CoV-2 infection (preprint)

Several studies show neutralizing antibody levels are an important correlate of immune protection from COVID-19 and have estimated the relationship between neutralizing antibodies and protection. However, a number of these studies appear to yield quite different estimates of the level of neutralizing antibodies required for protection. Here we show that after normalization of antibody titers current studies converge on a consistent relationship between antibody levels and protection from COVID-19.

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

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.

Estimation and Hypothesis Testing of Strain-Specific Vaccine Efficacy with Missing Strain Types, with Applications to a COVID-19 Vaccine Trial (preprint)

Statistical methods are developed for analysis of clinical and virus genetics data from phase 3 randomized, placebo-controlled trials of vaccines against novel coronavirus COVID-19. Vaccine efficacy (VE) of a vaccine to prevent COVID-19 caused by one of finitely many genetic strains of SARS-CoV-2 may vary by strain. The problem of assessing differential VE by viral genetics can be formulated under a competing risks model where the endpoint is virologically confirmed COVID-19 and the cause-of-failure is the infecting SARS-CoV-2 genotype. Strain-specific VE is defined as one minus the cause-specific hazard ratio (vaccine/placebo). For the COVID-19 VE trials, the time to COVID-19 is right-censored, and a substantial percentage of failure cases are missing the infecting virus genotype. We develop estimation and hypothesis testing procedures for strain-specific VE when the failure time is subject to right censoring and the cause-of-failure is subject to missingness, focusing on $J \ge 2$ discrete categorical unordered or ordered virus genotypes. The stratified Cox proportional hazards model is used to relate the cause-specific outcomes to explanatory variables. The inverse probability weighted complete-case (IPW) estimator and the augmented inverse probability weighted complete-case (AIPW) estimator are investigated. Hypothesis tests are developed to assess whether the vaccine provides at least a specified level of efficacy against some viral genotypes and whether VE varies across genotypes, adjusting for covariates. The finite-sample properties of the proposed tests are studied through simulations and are shown to have good performances. In preparation for the real data analyses, the developed methods are applied to a pseudo dataset mimicking the Moderna COVE trial.

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

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 Organizations 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 (preprint)

BackgroundIn 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. MethodsThrough 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. ResultsDay 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%). ConclusionsBinding 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 numberCOVE ClinicalTrials.gov number, NCT04470427

Evidence for antibody as a protective correlate for COVID-19 vaccines (preprint)

Though eleven novel COVID-19 vaccines have demonstrated efficacy, additional affordable, scalable, and deliverable vaccines are needed to meet unprecedented global demand. With placebo-controlled efficacy trials becoming infeasible due to the roll out of licensed vaccines, a correlate of protection is urgently needed to provide a path for regulatory approval of novel vaccines. To assess whether antibody titers may reasonably predict efficacy, 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 ({rho}= 0.79) and binding antibody titer and efficacy ({rho} = 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. This correlation is strengthened by substituting post-hoc analyses for efficacy against the ancestral strain (D614G), where available. Together with an accumulating body of 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.

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

BackgroundSeveral 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. MethodsFollowing 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. ResultsPost-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. ConclusionsWe 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.

Vaccines that prevent SARS-CoV-2 transmission may prevent or dampen a spring wave of COVID-19 cases and deaths in 2021 (preprint)

Ongoing SARS-CoV-2 vaccine trials assess vaccine efficacy against disease (VEDIS), the ability of a vaccine to block symptomatic COVID-19. They will only partially discriminate whether VEDIS is mediated by preventing infection as defined by the detection of virus in the airways (vaccine efficacy against infection defined as VESUSC), or by preventing symptoms despite breakthrough infection (vaccine efficacy against symptoms or VESYMP). Vaccine efficacy against infectiousness (VEINF), defined as the decrease in secondary transmissions from infected vaccine recipients versus from infected placebo recipients, is also not being measured. Using mathematical modeling of data from King County Washington, we demonstrate that if the Moderna and Pfizer vaccines, which have observed VEDIS>90%, mediate VEDIS predominately by complete protection against infection, then prevention of a fourth epidemic wave in the spring of 2021, and associated reduction of subsequent cases and deaths by 60%, is likely to occur assuming rapid enough vaccine roll out. If high VEDIS is explained primarily by reduction in symptoms, then VEINF>50% will be necessary to prevent or limit the extent of this fourth epidemic wave. The potential added benefits of high VEINF would be evident regardless of vaccine allocation strategy and would be enhanced if vaccine roll out rate is low or if available vaccines demonstrate waning immunity. Finally, we demonstrate that a 1.0 log vaccine-mediated reduction in average peak viral load might be sufficient to achieve VEINF=60% and that human challenge studies with 104 infected participants, or clinical trials in a university student population could estimate VESUSC, VESYMP and VEINF using viral load metrics.

Evaluating the Efficacy of COVID-19 Vaccines (preprint)

A large number of studies are being conducted to evaluate the efficacy and safety of candidate vaccines against novel coronavirus disease-2019 (COVID-19). Most Phase 3 trials have adopted virologically confirmed symptomatic COVID-19 disease as the primary efficacy endpoint, although laboratory-confirmed 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, COVID-19, and severe COVID-19 as dual or triple primary endpoints. 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.