Extensive observational data suggest that herpes simplex virus type 2 (HSV-2) infection may facilitate HIV acquisition, increase HIV viral load, and accelerate HIV progression and onward transmission. To explore these relationships, we examined the impact of preexisting HSV-2 infection in an international HIV vaccine trial.
The use of surrogate variables has been proposed as a means to capture, for a given observed set of data, sources driving the dependency structure among high-dimensional sets of features and remove the effects of those sources and their potential negative impact on simultaneous inference. In this article we illustrate the potential effects of latent variables on testing dependence and the resulting impact on multiple inference, we briefly review the method of surrogate variable analysis proposed by Leek and Storey (PNAS 2008; 105:18718-18723), and assess that method via simulations intended to mimic the complexity of feature dependence observed in real-world microarray data. The method is also assessed via application to a recent Merck microarray data set. Both simulation and case study results indicate that surrogate variable analysis can offer a viable strategy for tackling the multiple testing dependence problem when the features follow a potentially complex correlation structure, yielding improvements in the variability of false positive rates and increases in power.
Abstract The safety and immunogenicity of the MRK adenovirus type 5 (Ad5) HIV-1 clade B gag vaccine was assessed in an international Phase I trial. Three-hundred and sixty healthy HIV-uninfected adults were enrolled on five continents. Subjects received placebo or 1?×?10(9) or 1?×?10(10) viral particles (vp) per dose of the MRKAd5 HIV-1 gag vaccine at day 1, week 4, and week 26. Immunogenicity was evaluated using an IFN-? ELISPOT gag 15-mer assay with positive responses defined as ?55 SFC/10(6) PBMCs and ?4-fold over mock control. The vaccine was well tolerated. The most common adverse events were injection site reactions, headache, pyrexia, diarrhea, fatigue, and myalgia. At week 30, geometric mean ELISPOT responses were 24, 114, and 226 SFC/10(6) PBMCs in the placebo, 1?×?10(9) vp/dose, and 1?×?10(10) vp/dose groups, respectively. Overall, responses to 1?×?10(10) vp were 85% and 68% in subjects with low (?200) and high (>200) baseline Ad5 titers, respectively. The MRKAd5 HIV-1 gag vaccine was immunogenic in diverse geographic regions. Gag ELISPOT responses were greater in the 1?×?10(10) vp/dose groups than in the 1?×?10(9) vp/dose groups. Data from this first international study indicate that adenovirus-vectored vaccines are well tolerated and may be immunogenic in subjects from regions with high prevalence of preexisting Ad5 immunity.
Following the disappointing outcome of the phase IIb test-of-concept step study in which Mercks adenovirus type 5 (Ad5) HIV-1 clade B gag/pol/nef vaccine failed to demonstrate efficacy in HIV high-risk individuals, an extensive review of the trial and preclinical studies which supported the trial is ongoing. One point of interest is how well preclinical nonhuman primate immunogenicity studies predicted what was observed in humans. Here we compare the HIV-1-specific cellular immune responses elicited in nonhuman primates and human clinical trial subjects to several HIV-1 vaccine candidates. We find that although rhesus macaques are immunologically more responsive to vaccination than humans, the hierarchy in potency of single-modality prime-boost regimens using several vector approaches (adenovirus, DNA, and pox vectors) was well predicted. Vaccine approaches using complex formulations such as novel adjuvants (DNA+CRL1005) or mixed-modality prime-boost (DNA/Ad5; Ad5/ALVAC) did not correlate as well between rhesus macaques and humans. Although the immunogenicity of the vaccines and vaccine regimens evaluated were not all accurately predicted, testing in rhesus macaques generally offers an indispensable tool for ranking the immunological potential of HIV-1 vaccine candidates.
Human immunodeficiency virus type 1 (HIV-1)-specific cellular immunity contributes to the control of HIV-1 replication. HIV-1-infected volunteers who were receiving antiretroviral therapy were given a replication-defective adenovirus type 5 HIV-1 gag vaccine in a randomized, blinded therapeutic vaccination study.
In randomized clinical trials, a pre-treatment measurement is often taken at baseline, and post-treatment effects are measured at several time points post-baseline, say t=1, ..., T. At the end of the trial, it is of interest to assess the treatment effect based on the mean change from baseline at the last time point T. We consider statistical methods for (i) a point estimate and 95 per cent confidence interval for the mean change from baseline at time T for each treatment group, and (ii) a p-value and 95 per cent confidence interval for the between-group difference in the mean change from baseline. The manner in which the baseline responses are used in the analysis influences both the accuracy and the efficiency of items (i) and (ii). In this paper, we will consider the ANCOVA approach with change from baseline as a dependent variable and compare that with a constrained longitudinal data analysis (cLDA) model proposed by Liang and Zeger (Sankhya: Indian J. Stat. (Ser B) 2000; 62:134-148), in which the baseline is modeled as a dependent variable in conjunction with the constraint of a common baseline mean across the treatment groups. Some drawbacks of the ANCOVA model and potential advantages of the cLDA approach are discussed and illustrated using numerical simulations.
Preexisting immunity to adenovirus serotype 5 (Ad5) diminishes immune responses to vaccines using Ad5 as a vector. Alternate Ad serotypes as vaccine vectors might overcome Ad5-specific neutralizing antibodies and enhance immune responses in populations with a high prevalence of Ad5 immunity. To test this hypothesis, healthy human immunodeficiency virus (HIV)-seronegative adults were enrolled in a blinded, randomized, dose-escalating, placebo-controlled study. In part A, subjects with baseline Ad6 titers of < or = 18 received the Merck Ad6 (MRKAd6) HIV type 1 (HIV-1) trigene vaccine at weeks 0, 4, and 26. In part B, subjects stratified by Ad5 titers (< or = 200 or >200) and Ad6 titers (< or = 18 or >18) received the MRKAd5-plus-MRKAd6 (MRKAd5+6) HIV-1 trigene vaccine at weeks 0, 4, and 26. Immunogenicity was assessed by an enzyme-linked immunospot (ELISPOT) assay at week 30. No serious adverse events occurred. MRKAd6 trigene vaccine recipients responded more often to Nef than to Gag or Pol. In part A, ELISPOT response rates to > or = 2 vaccine antigens were 14%, 63%, and 71% at 10(9), 10(10), and 10(11) viral genomes (vg)/dose, respectively. All responders had positive Nef-specific ELISPOT results. In part B, Nef-ELISPOT response rates at 10(10) vg/dose of the MRKAd5+6 trigene vaccine were 50% in the low-Ad5/low-Ad6 stratum (n = 8), 78% in the low-Ad5/high-Ad6 stratum (n = 9), 75% in the high-Ad5/low-Ad6 stratum (n = 8), and 44% in the high-Ad5/high-Ad6 stratum (n = 9). The MRKAd6 and MRKAd5+6 trigene vaccines elicited dose-dependent responses predominantly to Nef and were generally well tolerated, indicating that Ad6 should be considered a candidate vector for future vaccines. Although small sample sizes limit the conclusions that can be drawn from this exploratory study, combining two Ad vectors may be a useful vaccine strategy for circumventing isolated immunity to a single Ad serotype.
The longitudinal data analysis model proposed by Liang and Zeger (Sankhy?: Indian J. Stat. Ser. B 2000; 62:134-148) uses the baseline as well as postbaseline values as the dependent variables, and the baseline mean responses are constrained to be the same across treatment groups due to randomization. Compared with the conventional longitudinal analysis of covariance, this approach can correctly estimate the variance of within-group mean changes and achieve the specified coverage probabilities. General results on the sample size and power calculations for this model in the presence of missing data are obtained. The sample size relationship between the constrained and unconstrained longitudinal data analysis is established. Simple expressions for sample size calculation are obtained for the compound symmetry and first-order autoregressive correlation structures. The sensitivity of the sample size requirement to the configuration of correlation structure and retention pattern is assessed. The performance of several ad hoc approximations for longitudinal data analysis sample size calculation is evaluated. Simulation studies are conducted to assess the validity of the proposed sample size formulas with deviation from normality. The sample size formulas are also illustrated in detail using real clinical trial data.
In randomized clinical trials designed to compare the magnitude of vaccine-induced immune responses between vaccination regimens, the statistical method used for the analysis typically does not account for baseline participant characteristics. This article shows that incorporating baseline variables predictive of the immunogenicity study endpoint can provide large gains in precision and power for estimation and testing of the group mean difference (requiring fewer subjects for the same scientific output) compared to conventional methods, and recommends the "semiparametric efficient" method described in Tsiatis et al. [Tsiatis AA, Davidian M, Zhang M, Lu X. Covariate adjustment for two-sample treatment comparisons in randomized clinical trials: a principled yet flexible approach. Stat Med 2007. doi:10.1002/sim.3113] for practical use. As such, vaccine clinical trial programs can be improved (1) by investigating baseline predictors (e.g., readouts from laboratory assays) of vaccine-induced immune responses, and (2) by implementing the proposed semiparametric efficient method in trials where baseline predictors are available.
Immunotherapy against infectious agents and malignant tumors requires efficient priming of effector cells through direct expression and/or efficient cross-presentation of antigens by antigen-presenting cells. Electroporation is a new procedure aimed at transiently increasing cell membrane permeability and direct delivery of antigen or antigen-encoding nucleic acids inside targeted cells. We evaluated the tolerability including compliance with repeated electroporation treatments using MedPulser DDS in 24 healthy adults. Pain severity was evaluated at time of electroporation treatment, and at 1, 5, 10, and 20 minutes, and 24 hours thereafter, using two clinically validated questionnaires: McGill Pain Questionnaire (MPQ) (Present Pain Intensity) and Brief Pain Inventory (BPI). Electroporation treatments were generally well tolerated. Twenty-two out of 24 subjects returned for the second electroporation treatment 14 days after first treatment. Only two subjects reported a treatment-related systemic adverse experience following either electroporation application. For both pain assessment tools, maximum pain and/or discomfort were mostly reported immediately (within 5 minutes) after electroporation; Furthermore, no difference was observed when comparing peak-pain scores after first and second electroporation treatments. This study supports the clinical application of MedPulser DDS for the improvement of antigen-induced immune responses for prophylactic or therapeutic vaccines, especially in gene-based therapies for cancer.
Vaccines inducing pathogen-specific cell-mediated immunity are being developed using attenuated adenoviral (Ad) vectors. We report the results of two independent Phase I trials of similar replication-deficient Ad5 vaccines containing a near-consensus HIV-1 clade B gag transgene. Healthy HIV-uninfected adults were enrolled in two separate, multicenter, dose-escalating, blinded, placebo-controlled studies to assess the safety and immunogenicity of a three-dose homologous regimen of Ad5 and MRKAd5 HIV-1 gag vaccines given on day 1, week 4, and week 26. Adverse events were collected for 29 days following each intradeltoid injection. The primary immunogenicity endpoint was the proportion of subjects with a positive unfractionated Gag-specific IFN-gamma ELISPOT response measured 4 weeks after the last dose (week 30). Analyses were performed after combining data for each dose group from both protocols, stratifying by baseline Ad5 titers. Overall, 252 subjects were randomized to receive either vaccine or placebo, including 229 subjects (91%) who completed the study through week 30. Tolerability and immunogenicity did not appear to differ between the Ad5 and MRKAd5 vaccines. The frequency of injection-site reactions was dose dependent. Systemic adverse events were also dose dependent and more frequent in subjects with baseline Ad5 titers <200 versus > or =200, especially after the first dose. The percent of ELISPOT responders and the ELISPOT geometric means overall were significantly higher for all four vaccine doses studied compared to placebo, and were generally higher in vaccine recipients with baseline Ad5 titers <200 versus > or = 200. Ad5 titers increased after vaccination in a dose-dependent fashion. Both Ad5-vectored HIV-1 vaccines were generally well tolerated and induced cell-mediated immune responses against HIV Gag-peptides in the majority of healthy adults with baseline Ad5 titers <200. Preexistent and/or vaccine-induced immunity to the Ad5 vector may dampen the CMI response to HIV Gag.
In a typical randomized clinical trial, a continuous variable of interest (e.g., bone density) is measured at baseline and fixed postbaseline time points. The resulting longitudinal data, often incomplete due to dropouts and other reasons, are commonly analyzed using parametric likelihood-based methods that assume multivariate normality of the response vector. If the normality assumption is deemed untenable, then semiparametric methods such as (weighted) generalized estimating equations are considered. We propose an alternate approach in which the missing data problem is tackled using multiple imputation, and each imputed dataset is analyzed using robust regression (M-estimation; Huber, 1973, Annals of Statistics 1, 799-821.) to protect against potential non-normality/outliers in the original or imputed dataset. The robust analysis results from each imputed dataset are combined for overall estimation and inference using either the simple Rubin (1987, Multiple Imputation for Nonresponse in Surveys, New York: Wiley) method, or the more complex but potentially more accurate Robins and Wang (2000, Biometrika 87, 113-124.) method. We use simulations to show that our proposed approach performs at least as well as the standard methods under normality, but is notably better under both elliptically symmetric and asymmetric non-normal distributions. A clinical trial example is used for illustration.
Consider a typical two-treatment randomized clinical trial involving a time-to-event endpoint, with randomization stratified by a categorical prognostic factor (for example gender). At the design stage, it is often assumed that the treatment hazard ratio (HR) is constant across the strata, and the data are commonly analyzed using the stratified Cox proportional hazards model. We caution that this ubiquitous approach is needlessly risky because departures from the assumption of the HR being the same for all the strata can result in a notably biased and/or less powerful analysis. An alternative approach is proposed in which first the [log] HR is estimated separately for each stratum using an unstratified Cox model, and then the stratum-specific estimates are combined for overall inference using either sample size or minimum risk stratum weights. The advantages of the proposed two-step analysis versus the common one-step stratified Cox model analysis are illustrated using simulations that were conducted to support the design of a vaccine clinical trial.
Comparative analyses of safety/tolerability data from a typical phase III randomized clinical trial generate multiple p-values associated with adverse experiences (AEs) across several body systems. A common approach is to flag any AE with a p-value less than or equal to 0.05, ignoring the multiplicity problem. Despite the fact that this approach can result in excessive false discoveries (false positives), many researchers avoid a multiplicity adjustment to curtail the risk of missing true safety signals. We propose a new flagging mechanism that significantly lowers the false discovery rate (FDR) without materially compromising the power for detecting true signals, relative to the common no-adjustment approach. Our simple two-step procedure is an enhancement of the Mehrotra-Heyse-Tukey approach that leverages the natural grouping of AEs by body systems. We use simulations to show that, on the basis of FDR and power, our procedure is an attractive alternative to the following: (i) the no-adjustment approach; (ii) a one-step FDR approach that ignores the grouping of AEs by body systems; and (iii) a recently proposed two-step FDR approach for much larger-scale settings such as genome-wide association studies. We use three clinical trial examples for illustration.
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