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There are now many options for doubly robust estimation; however, there is a concerning trend in the applied literature to believe that the combination of a propensity score and an adjusted outcome model automatically results in a doubly robust estimator and/or to misuse more complex established doubly robust estimators. A simple alternative, canonical link generalized linear models (GLM) fit via inverse probability of treatment (propensity score) weighted maximum likelihood estimation followed by standardization (the g$$ g $$‐formula) for the average causal effect, is a doubly robust estimation method. Our aim is for the reader not just to be able to use this method, which we refer to as IPTW GLM, for doubly robust estimation, but to fully understand why it has the doubly robust property. For this reason, we define clearly, and in multiple ways, all concepts needed to understand the method and why it is doubly robust. In addition, we want to make very clear that the mere combination of propensity score weighting and an adjusted outcome model does not generally result in a doubly robust estimator. Finally, we hope to dispel the misconception that one can adjust for residual confounding remaining after propensity score weighting by adjusting in the outcome model for what remains 'unbalanced' even when using doubly robust estimators. We provide R code for our simulations and real open‐source data examples that can be followed step‐by‐step to use and hopefully understand the IPTW GLM method. We also compare to a much better‐known but still simple doubly robust estimator. [ABSTRACT FROM AUTHOR]

Trial-level surrogates are useful tools for improving the speed and cost effectiveness of trials but surrogates that have not been properly evaluated can cause misleading results. The evaluation procedure is often contextual and depends on the type of trial setting. There have been many proposed methods for trial-level surrogate evaluation, but none, to our knowledge, for the specific setting of platform studies. As platform studies are becoming more popular, methods for surrogate evaluation using them are needed. These studies also offer a rich data resource for surrogate evaluation that would not normally be possible. However, they also offer a set of statistical issues including heterogeneity of the study population, treatments, implementation, and even potentially the quality of the surrogate. We propose the use of a hierarchical Bayesian semiparametric model for the evaluation of potential surrogates using nonparametric priors for the distribution of true effects based on Dirichlet process mixtures. The motivation for this approach is to flexibly model relationships between the treatment effect on the surrogate and the treatment effect on the outcome and also to identify potential clusters with differential surrogate value in a data-driven manner so that treatment effects on the surrogate can be used to reliably predict treatment effects on the clinical outcome. In simulations, we find that our proposed method is superior to a simple, but fairly standard, hierarchical Bayesian method. We demonstrate how our method can be used in a simulated illustrative example (based on the ProBio trial), in which we are able to identify clusters where the surrogate is, and is not useful. We plan to apply our method to the ProBio trial, once it is completed. [ABSTRACT FROM AUTHOR]

In randomized trials, once the total effect of the intervention has been estimated, it is often of interest to explore mechanistic effects through mediators along the causal pathway between the randomized treatment and the outcome. In the setting with two sequential mediators, there are a variety of decompositions of the total risk difference into mediation effects. We derive sharp and valid bounds for a number of mediation effects in the setting of two sequential mediators both with unmeasured confounding with the outcome. We provide five such bounds in the main text corresponding to two different decompositions of the total effect, as well as the controlled direct effect, with an additional 30 novel bounds provided in the corresponding to the terms of 24 four-way decompositions. We also show that, although it may seem that one can produce sharp bounds by adding or subtracting the limits of the sharp bounds for terms in a decomposition, this almost always produces valid, but not sharp bounds that can even be completely noninformative. We investigate the properties of the bounds by simulating random probability distributions under our causal model and illustrate how they are interpreted in a real data example. for this article are available online. [ABSTRACT FROM AUTHOR]

When multiple mediators are present, there are additional effects that may be of interest beyond the well-known natural (NDE) and controlled direct effects (CDE). These effects cross the type of control on the mediators, setting one to a constant level and one to its natural level, which differs across subjects. We introduce five such estimands for the cross-CDE and -NDE when two mediators are measured. We consider both the scenario where one mediator is influenced by the other, referred to as sequential mediators, and the scenario where the mediators do not influence each other. Such estimands may be of interest in immunology, as we discuss in relation to measured immunological responses to SARS-CoV-2 vaccination. We provide identifying expressions for the estimands in observational settings where there is no residual confounding, and where intervention, outcome, and mediators are of arbitrary type. We further provide tight symbolic bounds for the estimands in randomized settings where there may be residual confounding of the outcome and mediator relationship and all measured variables are binary. [ABSTRACT FROM AUTHOR]

Nonignorable missingness and noncompliance can occur even in well-designed randomized experiments, making the intervention effect that the experiment was designed to estimate nonidentifiable. Nonparametric causal bounds provide a way to narrow the range of possible values for a nonidentifiable causal effect with minimal assumptions. We derive novel bounds for the causal risk difference for a binary outcome and intervention in randomized experiments with nonignorable missingness that is caused by a variety of mechanisms, with both perfect and imperfect compliance. We show that the so-called worst-case imputation, whereby all missing subjects on the intervention arm are assumed to have events and all missing subjects on the control or placebo arm are assumed to be event-free, can be too pessimistic in blinded studies with perfect compliance, and is not bounding the correct estimand with imperfect compliance. We illustrate the use of the proposed bounds in our motivating data example of peanut consumption on the development of peanut allergies in infants. We find that, even accounting for potentially nonignorable missingness and noncompliance, our derived bounds confirm that regular exposure to peanuts reduces the risk of development of peanut allergies, making the results of this study much more compelling. [ABSTRACT FROM AUTHOR]

Outcome-dependent sampling designs are common in many different scientific fields including epidemiology, ecology, and economics. As with all observational studies, such designs often suffer from unmeasured confounding, which generally precludes the nonparametric identification of causal effects. Nonparametric bounds can provide a way to narrow the range of possible values for a nonidentifiable causal effect without making additional untestable assumptions. The nonparametric bounds literature has almost exclusively focused on settings with random sampling, and the bounds have often been derived with a particular linear programming method. We derive novel bounds for the causal risk difference, often referred to as the average treatment effect, in six settings with outcome-dependent sampling and unmeasured confounding for a binary outcome and exposure. Our derivations of the bounds illustrate two approaches that may be applicable in other settings where the bounding problem cannot be directly stated as a system of linear constraints. We illustrate our derived bounds in a real data example involving the effect of vitamin D concentration on mortality. for this article are available online. [ABSTRACT FROM AUTHOR]

There have been many strategies to adapt machine learning algorithms to account for right censored observations in survival data in order to build more accurate risk prediction models. These adaptions have included pre-processing steps such as pseudo-observation transformation of the survival outcome or inverse probability of censoring weighted (IPCW) bootstrapping of the observed binary indicator of an event prior to a time point of interest. These pre-processing steps allow existing or newly developed machine learning methods, which were not specifically developed with time-to-event data in mind, to be applied to right censored survival data for predicting the risk of experiencing an event. Stacking or ensemble methods can improve on risk predictions, but in general, the combination of pseudo-observation-based algorithms, IPCW bootstrapping, IPC weighting of the methods directly, and methods developed specifically for survival has not been considered in the same ensemble. In this paper, we propose an ensemble procedure based on the area under the pseudo-observation-based-time-dependent ROC curve to optimally stack predictions from any survival or survival adapted algorithm. The real application results show that our proposed method can improve on single survival based methods such as survival random forest or on other strategies that use a pre-processing step such as inverse probability of censoring weighted bagging or pseudo-observations alone. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to illustrate the use and interpretation of regression based on pseudo-observations for estimating risks of time-to-event outcomes in epidemiological studies.Methods: We use pseudo-observation based regression for estimation of contrasts in the relative and absolute risks at specific times. This relaxes the proportional hazards assumption and directly estimates relative and absolute risks without the need for secondary calculations or standardization. Statistical software is available to use this method, and we demonstrate its use in a reanalysis of the mortality risk in sarcoidosis patients in Sweden.Results: We report estimated adjusted mortality risk differences and risk ratios by age, and at different years of follow up. Compared to the hazard ratio of 1.62, which is assumed to be time constant, we find risk ratios ranging from 1.7 at 2 years of follow-up to 1.3 at 10 years.Conclusions: Pseudo-observation regression is a flexible and powerful tool for censored time-to-event data. The models are easy to run and interpret so they should be considered a standard tool alongside Cox regression and standardization. As with any statistical model, there are assumptions needed for valid inference, which should be assessed on a case-by-case basis. [ABSTRACT FROM AUTHOR]

Many infectious diseases are well prevented by proper vaccination. However, when a vaccine is not completely efficacious, there is great interest in determining how the vaccine effect differs in subgroups conditional on measured immune responses postvaccination and also according to the type of infecting agent (eg, strain of a virus). The former is often called correlate of protection (CoP) analysis, while the latter has been called sieve analysis. We propose a unified framework for simultaneously assessing CoP and sieve effects of a vaccine in a large Phase III randomized trial. We use flexible parametric models treating times to infection from different agents as competing risks and estimated maximum likelihood to fit the models. The parametric models under competing risks allow for estimation of both cumulative incidence‐based contrasts and instantaneous rates. We outline the assumptions with which we can link the observable data to the causal contrasts of interest, propose hypothesis testing procedures, and evaluate our proposed methods in an extensive simulation study. [ABSTRACT FROM AUTHOR]

Background: Social concerns about unintentional HIV status disclosure and HIV-related stigma are barriers to pregnant women's access to prevention of mother-to-child transmission of HIV (PMTCT) care. There is limited quantitative evidence of women's social and emotional barriers to PMTCT care and HIV disclosure. We aimed to investigate how social concerns related to participation in PMTCT care are associated with HIV status disclosure to partners and relatives among pregnant women living with HIV in western Kenya.Methods: A cross-sectional study, including 437 pregnant women living with HIV, was carried out at enrolment in a multicentre mobile phone intervention trial (WelTel PMTCT) in western Kenya. Women diagnosed with HIV on the day of enrolment were excluded. To investigate social concerns and their association with HIV disclosure we used multivariable-adjusted logistic regression, adjusted for sociodemographic and HIV-related characteristics, to estimate odds ratios (OR) and 95% confidence intervals (CI).Results: The majority (80%) had disclosed their HIV status to a current partner and 46% to a relative. Older women (35-44 years) had lower odds of disclosure to a partner (OR = 0.15; 95% CI: 0.05-0.44) compared to women 18-24 years. The most common social concern was involuntary HIV status disclosure (reported by 21%). Concern about isolation or lack of support from family or friends was reported by 9%, and was associated with lower odds of disclosure to partners (OR = 0.33; 95% CI: 0.12-0.85) and relatives (OR = 0.37; 95% CI: 0.16-0.85). Concern about separation (reported by 5%; OR = 0.17; 95% CI: 0.05-0.57), and concern about conflict with a partner (reported by 5%; OR = 0.18; 95% CI: 0.05-0.67), was associated with lower odds of disclosure to a partner.Conclusions: Compared to previous reports from Kenya, our estimated disclosure rate to a partner is higher, suggesting a possible improvement over time in disclosure. Younger pregnant women appear to be more likely to disclose, suggesting a possible decreased stigma and more openness about HIV among younger couples. Healthcare providers and future interventional studies seeking to increase partner disclosure should consider supporting women regarding their concerns about isolation, lack of support, separation, and conflict with a partner. PMTCT care should be organized to ensure women's privacy and confidentiality. [ABSTRACT FROM AUTHOR]

Surrogate evaluation is a difficult problem that is made more so by the presence of interference. Our proposed procedure can allow for relatively easy evaluation of surrogates for indirect or spill-over clinical effects at the cluster level. Our definition of surrogacy is based on the causal-association paradigm (Joffe and Greene, 2009. Related causal frameworks for surrogate outcomes. Biometrics65, 530-538), under which surrogates are evaluated by the strength of the association between a causal treatment effect on the clinical outcome and a causal treatment effect on the candidate surrogate. Hudgens and Halloran (2008, Toward causal inference with interference. Journal of the American Statistical Association103, 832-842) introduced estimators that can be used for many of the marginal causal estimands of interest in the presence of interference. We extend these to consider surrogates for not just direct effects, but indirect and total effects at the cluster level. We suggest existing estimators that can be used to evaluate biomarkers under our proposed definition of surrogacy. In our motivating setting of a transmission blocking malaria vaccine, there is expected to be no direct protection to those vaccinated and predictive surrogates are urgently needed. We use a set of simulated data examples based on the proposed Phase IIb/III trial design of transmission blocking malaria vaccine to demonstrate how our definition, proposed criteria and procedure can be used to identify biomarkers as predictive cluster level surrogates in the presence of interference on the clinical outcome. [ABSTRACT FROM AUTHOR]

We extend the method proposed in a recent work by the Authors for trial-level general surrogate evaluation to allow combinations of biomarkers and provide a procedure for finding the "best" combination of biomarkers based on the absolute prediction error summary of surrogate quality. We use a nonparametric Bayesian model that allows us to select an optimal subset of biomarkers without having to consider a large number of explicit model specifications for that subset. This dramatically reduces the number of model comparisons needed. Given the model's flexibility, complex nonlinear relationships can be fit when enough data are available. We evaluate the operating characteristics of our proposed method in simulations designed to be similar to our motivating example. We use our method to compare and evaluate combinations of biomarkers as trial-level general surrogates for the pentavalent rotavirus vaccine RotaTeq™ (RV5) (Merck & Co, Inc, Kenilworth, New Jersey, USA), finding that the same single biomarker identified in our previously published analysis is likely the optimal subset. [ABSTRACT FROM AUTHOR]

Strong untestable assumptions are almost universal in causal point estimation. In particular settings, bounds can be derived to narrow the possible range of a causal effect. Symbolic bounds apply to all settings that can be depicted using the same directed acyclic graph and for the same effect of interest. Although the core of the methodology for deriving symbolic bounds has been previously developed, the means of implementation and computation have been lacking. Our Rpackage causaloptim aims to solve this usability problem by providing the user with a graphical interface through Shiny. This interface takes input in a form that most researchers with an interest in causal inference will be familiar: a graph drawn in the user's web browser and a causal query written in text using common counterfactual notation. [ABSTRACT FROM AUTHOR]

An intermediate response measure that accurately predicts efficacy in a new setting at the individual level could be used both for prediction and personalized medical decisions. In this article, we define a predictive individual-level general surrogate (PIGS), which is an individual-level intermediate response that can be used to accurately predict individual efficacy in a new setting. While methods for evaluating trial-level general surrogates, which are predictors of trial-level efficacy, have been developed previously, few, if any, methods have been developed to evaluate individual-level general surrogates, and no methods have formalized the use of cross-validation to quantify the expected prediction error. Our proposed method uses existing methods of individual-level surrogate evaluation within a given clinical trial setting in combination with cross-validation over a set of clinical trials to evaluate surrogate quality and to estimate the absolute prediction error that is expected in a new trial setting when using a PIGS. Simulations show that our method performs well across a variety of scenarios. We use our method to evaluate and to compare candidate individual-level general surrogates over a set of multi-national trials of a pentavalent rotavirus vaccine. [ABSTRACT FROM AUTHOR]

Testing the equality of 2 proportions for a control group versus a treatment group is a well-researched statistical problem. In some settings, there may be strong historical data that allow one to reliably expect that the control proportion is one, or nearly so. While one-sample tests or comparisons to historical controls could be used, neither can rigorously control the type I error rate in the event the true control rate changes. In this work, we propose an unconditional exact test that exploits the historical information while controlling the type I error rate. We sequentially construct a rejection region by first maximizing the rejection region in the space where all controls have an event, subject to the constraint that our type I error rate does not exceed α for any true event rate; then with any remaining α we maximize the additional rejection region in the space where one control avoids the event, and so on. When the true control event rate is one, our test is the most powerful nonrandomized test for all points in the alternative space. When the true control event rate is nearly one, we demonstrate that our test has equal or higher mean power, averaging over the alternative space, than a variety of well-known tests. For the comparison of 4 controls and 4 treated subjects, our proposed test has higher power than all comparator tests. We demonstrate the properties of our proposed test by simulation and use our method to design a malaria vaccine trial. [ABSTRACT FROM AUTHOR]

Background: HIV and malaria geographically overlap. HIV protease inhibitors kill malaria parasites in vitro and in vivo, but further evaluation in clinical studies is needed. Methods: Thirty-one children from Malawi aged 4–62 months were followed every 3 months and at intercurrent illness visits for ≤47 months (September 2009-December 2011). We compared malaria parasite carriage by blood smear microscopy (BS) and confirmed clinical malaria incidence (CCM, or positive BS with malaria symptoms) in children initiated on HIV antiretroviral therapy (ART) with zidovudine, lamivudine, and either nevirapine (NVP), a non-nucleoside reverse transcriptase inhibitor, or lopinavir-ritonavir (LPV-rtv), a protease inhibitor. Results: We found an association between increased time to recurrent positive BS, but not CCM, when anti-malarial treatment and LPV-rtv based ART were used concurrently and when accounting for a LPV-rtv and antimalarial treatment interaction (adjusted HR 0.39; 95% CI (0.17,0.89); p = 0.03). Conclusions: LPV-rtv in combination with malaria treatment was associated with lower risk of recurrent positive BS, but not CCM, in HIV-infected children. Larger, randomized studies are needed to confirm these findings which may permit ART optimization for malaria-endemic settings. Trial Registration: ClinicalTrials.gov [ABSTRACT FROM AUTHOR]

An intermediate response measure that accurately predicts efficacy in a new setting can reduce trial cost and time to product licensure. In this article, we define a trial level general surrogate, which is an intermediate response that can be used to accurately predict efficacy in a new setting. Methods for evaluating general surrogates have been developed previously. Many methods in the literature use trial level intermediate responses for prediction. However, all existing methods focus on surrogate evaluation and prediction in new settings, rather than comparison of candidate general surrogates, and few formalize the use of cross validation to quantify the expected prediction error. Our proposed method uses Bayesian non-parametric modeling and cross-validation to estimate the absolute prediction error for use in evaluating and comparing candidate trial level general surrogates. Simulations show that our method performs well across a variety of scenarios. We use our method to evaluate and to compare candidate trial level general surrogates in several multi-national trials of a pentavalent rotavirus vaccine. We identify at least one immune measure that has potential value as a trial level general surrogate and use it to predict efficacy in a new trial where the clinical outcome was not measured. [ABSTRACT FROM AUTHOR]

Observation of counterfactual intermediate responses, and evaluation of them as candidate surrogates, is complicated in a standard randomized trial as half of the responses are systematically missing by design. Although some augmentation procedures exist for obtaining counterfactual responses, they are specific to vaccine trials. We outline extensions to the existing augmentations and suggest augmentations of three trial designs outside the setting of vaccines. We outline the assumptions needed to identify the causal estimands of interest under each augmented design, under which standard likelihood-based methods can be used to evaluate intermediate responses as principal surrogates. Two of these designs, crossover and individual stepped-wedge, allow for the observation of clinical endpoints under both treatment and control for some subset of subjects and can therefore improve efficiency over standard parallel trial designs. The third, the treatment run-in design, allows for the observation of a baseline measure that may be as useful a surrogate as the true counterfactual intermediate response. As the evaluation methods rely on several assumptions, we also outline a remediation analysis, which can be used to help overcome assumption violations. We illustrate our suggested methods in an example from a drug-resistant tuberculosis treatment trial. [ABSTRACT FROM AUTHOR]

In the article, the authors present their analysis of the Danish randomized trial on the effects of proposed masking protocols (DANMASK-19) against the serious acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from a causal inference perspective. Topics include the intent-to-treat effect in randomized experiments, how to avoid missing data in randomized experiments and the calculation of reported summary statistics.

Principal surrogate endpoints are useful as targets for phase I and II trials. In many recent trials, multiple post-randomization biomarkers are measured. However, few statistical methods exist for comparison of or combination of biomarkers as principal surrogates, and none of these methods to our knowledge utilize time-to-event clinical endpoint information. We propose a Weibull model extension of the semi-parametric estimated maximum likelihood method that allows for the inclusion of multiple biomarkers in the same risk model as multivariate candidate principal surrogates. We propose several methods for comparing candidate principal surrogates and evaluating multivariate principal surrogates. These include the time-dependent and surrogate-dependent true and false positive fraction, the time-dependent and the integrated standardized total gain, and the cumulative distribution function of the risk difference. We illustrate the operating characteristics of our proposed methods in simulations and outline how these statistics can be used to evaluate and compare candidate principal surrogates. We use these methods to investigate candidate surrogates in the Diabetes Control and Complications Trial. [ABSTRACT FROM AUTHOR]

Principal surrogate endpoints are useful as targets for phase I and II trials. In many recent trials, multiple post-randomization biomarkers are measured. However, few statistical methods exist for comparison of or combination of biomarkers as principal surrogates, and none of these methods to our knowledge utilize time-to-event clinical endpoint information. We propose a Weibull model extension of the semi-parametric estimated maximum likelihood method that allows for the inclusion of multiple biomarkers in the same risk model as multivariate candidate principal surrogates. We propose several methods for comparing candidate principal surrogates and evaluating multivariate principal surrogates. These include the time-dependent and surrogate-dependent true and false positive fraction, the time-dependent and the integrated standardized total gain, and the cumulative distribution function of the risk difference. We illustrate the operating characteristics of our proposed methods in simulations and outline how these statistics can be used to evaluate and compare candidate principal surrogates. We use these methods to investigate candidate surrogates in the Diabetes Control and Complications Trial. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Background. The phase III Zostavax Efficacy and Safety Trial of 1 dose of licensed zoster vaccine (ZV; Zostavax; Merck) in 50–59-year-olds showed approximately 70% vaccine efficacy (VE) to reduce the incidence of herpes zoster (HZ). An objective of the trial was to assess immune response biomarkers measuring antibodies to varicella zoster virus (VZV) by glycoprotein-based enzyme-linked immunosorbent assay as correlates of protection (CoPs) against HZ.Methods. The principal stratification vaccine efficacy curve framework for statistically evaluating immune response biomarkers as CoPs was applied. The VE curve describes how VE against the clinical end point (HZ) varies across participant subgroups defined by biomarker readout measuring vaccine-induced immune response. The VE curve was estimated using several subgroup definitions.Results. The fold rise in VZV antibody titers from the time before immunization to 6 weeks after immunization was an excellent CoP, with VE increasing sharply with fold rise: VE was estimated at 0% for the subgroup with no rise and at 90% for the subgroup with 5.26-fold rise. In contrast, VZV antibody titers measured 6 weeks after immunization did not predict VE, with similar estimated VEs across titer subgroups.Conclusions. The analysis illustrates the value of the VE curve framework for assessing immune response biomarkers as CoPs in vaccine efficacy trials.Clinical Trials Registration. NCT00534248. [ABSTRACT FROM AUTHOR]

Principal surrogate (PS) endpoints are relatively inexpensive and easy to measure study outcomes that can be used to reliably predict treatment effects on clinical endpoints of interest. Few statistical methods for assessing the validity of potential PSs utilize time-to-event clinical endpoint information and to our knowledge none allow for the characterization of time-varying treatment effects. We introduce the time-dependent and surrogate-dependent treatment efficacy curve, ${\mathrm {TE}}(t|s)$, and a new augmented trial design for assessing the quality of a biomarker as a PS. We propose a novel Weibull model and an estimated maximum likelihood method for estimation of the ${\mathrm {TE}}(t|s)$ curve. We describe the operating characteristics of our methods via simulations. We analyze data from the Diabetes Control and Complications Trial, in which we find evidence of a biomarker with value as a PS. [ABSTRACT FROM AUTHOR]

Background: Providing estimates of uncertainty for statistical quantities is important for statistical inference. When the statistical quantity of interest is a survival curve, which is a function over time, the appropriate type of uncertainty estimate is a confidence band constructed to account for the correlation between points on the curve, we will call this a simultaneous confidence band. This, however, is not the type of confidence band provided in standard software, which is constructed by joining the confidence intervals at given time points.Methods: We show that this type of band does not have desirable joint/simultaneous coverage properties in comparison to simultaneous bands.Results: There are different ways of constructing simultaneous confidence bands, and we find that bands based on the likelihood ratio appear to have the most desirable properties. Although there is no standard software available in the three major statistical packages to compute likelihood-based simultaneous bands, we summarise and give code to use available statistical software to construct other simultaneous forms of bands, which we illustrate using a study of colon cancer.Conclusions: There is a need for more user-friendly statistical software to compute simultaneous confidence bands using the available methods. [ABSTRACT FROM AUTHOR]

We determined whether polymorphisms in Fcy receptor (FCγR) IIa or FcγRllla genes were associated with outcomes in Vax004, a trial testing recombinant gp120 vaccination in preventing sexually ac-quired HIV infection. Male subjects (n = 1725), including infected and unin-fected vaccinees and placebo recipients, were genotyped. We observed no associa-tion between Fc-γRlla genotype and infec-tion rate in vaccinees or placebo recipi-ents. However, FcγRIIIa genotype was associated with infection rate among vac-cinees (P = .035). Exploratory analyses revealed that vaccinees homozygous for the Fc7Rllla V allele in the lowest behav-ioral risk group had a greater rate of infection than low risk vaccinees with at least 1 F allele (hazard ratio [HR] = 3.52; P = .002). No such association was seen among vaccinees with high-risk behav-iors or among placebo recipients in either risk stratum. Vaccinated low-risk VV sub-jects had a greater infection rate than low-risk VV placebo recipients (HR = 4.51; P=.17) or low-risk placebo recipientswith any genotype (HR = 4.72; P = .002). Moreover, low-risk VV vaccinees had in-fection rates similar to individuals with high behavioral risk, irrespective of geno-type. Our results generate the hypothesis that recombinant gp120 vaccine may have increased the likelihood of acquiring HIV infection in individuals with the VV geno-type (present in -- 10% of the population) at low behavioral risk of infection. [ABSTRACT FROM AUTHOR]

Abstract: Background: Immediate defibrillation is the traditional approach to resuscitation of cardiac arrest due to ventricular fibrillation or tachycardia (VF/VT). Delaying defibrillation to provide chest compressions may improve survival. We examined the effect of the duration of Emergency Medical Services (EMS) cardiopulmonary resuscitation (CPR) prior to first defibrillation on survival in patients with out-of-hospital VF/VT. Materials and methods: From a prospective multi-center observational registry of EMS-treated out-of-hospital cardiac arrest, we identified 1638 EMS-treated cardiac arrests with first recorded rhythm VF/VT or “shockable” and complete data for analysis. Survival to hospital discharge was determined as a function of EMS CPR duration prior to first shock. Results: Compared to the reference group of first EMS CPR duration ≤45s, the odds of survival was greater among patients who received between 46 and 195s of EMS CPR before first shock (46–75s odds ratio [OR] 1.15, 95% confidence interval [CI] 0.71–1.87; 76–105s, OR 1.37, 95% CI 0.80–2.35; 106–135s, OR 1.53, 95% CI 0.96–2.45; 136–165s, OR 1.24, 95% CI 0.71–2.15; 166–195s, OR 1.47, 95% CI 0.85–2.52). The benefit of EMS CPR before defibrillation was reduced when the duration of CPR exceeded 195s (196–225s, OR 0.95, 95% CI 0.47–1.81; 226–255s, OR 0.91, 95% CI 0.46–1.79; 256–285s, OR 0.46, 95% CI 0.17–1.29; 286–315s, OR 1.29, 95% CI 0.59–2.85). An optimal EMS CPR duration was not identified and no duration achieved statistical significance. Conclusion: In this observational analysis of VF/VT arrest, between 46 and 195s of EMS CPR prior to defibrillation was weakly associated with improved survival compared to ≤45s. Randomized trials are needed to confirm the optimal duration of EMS CPR prior to defibrillation and to assess the impact of first CPR duration on all initial rhythms. [Copyright &y& Elsevier]

Background: To improve future mobile health (mHealth) interventions in resource-limited settings, knowledge of participants' adherence to interactive interventions is needed, but previous studies are limited. We aimed to investigate how women in prevention of mother-to-child transmission of HIV (PMTCT) care in Kenya used, adhered to, and evaluated an interactive text-messaging intervention. Methods: We conducted a cohort study nested within the WelTel PMTCT trial among 299 pregnant women living with HIV aged ≥ 18 years. They received weekly text messages from their first antenatal care visit until 24 months postpartum asking "How are you?". They were instructed to text within 48 h stating that they were "okay" or had a "problem". Healthcare workers phoned non-responders and problem-responders to manage any issue. We used multivariable-adjusted logistic and negative binomial regression to estimate adjusted odds ratios (aORs), rate ratios (aRRs) and 95% confidence intervals (CIs) to assess associations between baseline characteristics and text responses. Perceptions of the intervention were evaluated through interviewer-administered follow-up questionnaires at 24 months postpartum. Results: The 299 participants sent 15,183 (48%) okay-responses and 438 (1%) problem-responses. There were 16,017 (51%) instances of non-response. The proportion of non-responses increased with time and exceeded 50% around 14 months from enrolment. Most reported problems were health related (84%). Having secondary education was associated with reporting a problem (aOR:1.88; 95%CI: 1.08–3.27) compared to having primary education or less. Younger age (18–24 years) was associated with responding to < 50% of messages (aOR:2.20; 95%CI: 1.03–4.72), compared to being 35–44 years. Women with higher than secondary education were less likely (aOR:0.28; 95%CI: 0.13–0.64), to respond to < 50% of messages compared to women with primary education or less. Women who had disclosed their HIV status had a lower rate of non-response (aRR:0.77; 95%CI: 0.60–0.97). In interviews with 176 women, 167 (95%) agreed or strongly agreed that the intervention had been helpful, mainly by improving access to and communication with their healthcare providers (43%). Conclusion: In this observational study, women of younger age, lower education, and who had not disclosed their HIV status were less likely to adhere to interactive text-messaging. The majority of those still enrolled at the end of the intervention reported that text-messaging had been helpful, mainly by improving access to healthcare providers. Future mHealth interventions aiming to improve PMTCT care need to be targeted to attract the attention of women with lower education and younger age. [ABSTRACT FROM AUTHOR]

Retention in prevention of mother-to-child transmission (PMTCT) care is critical to prevent vertical HIV transmission and reduce morbidity and mortality of mother-infant pairs. We investigated whether weekly, interactive text-messaging improved 18-month postpartum retention in PMTCT care. This randomised, two-armed, parallel trial was conducted at six PMTCT clinics in western Kenya. Pregnant women with HIV at least 18 years of age with access to a mobile phone, able to text-message, or had somebody who could text on their behalf, were eligible. Participants were randomly assigned at a 1:1 ratio in block sizes of four to the intervention or control group. The intervention group received weekly text messages asking "How are you?" ("Mambo?" in Swahili) and were requested to respond within 48 h. Healthcare workers called women who indicated a problem or did not respond. The intervention was administered up to 24 months after delivery. Both groups received standard care. The primary outcome was retention in care at 18 months postpartum (i.e., clinic attendance 16–24 months after delivery based on data from patient files, patient registers and Kenya's National AIDS and STI Control Programme database), which was analysed by intention-to-treat. Researchers and data collectors were masked to group assignment, while healthcare workers were not. Between June 25th, 2015, and July 5th, 2016, we randomly assigned 299 women to the intervention and 301 to standard care only. Follow-up concluded on July 26th, 2019. The proportion of women retained in PMTCT care at 18 months postpartum was not significantly different between the intervention (n = 210/299) and control groups (n = 207/301) (risk ratio 1.02, 95% confidence interval 0.92–1.14, p = 0.697). No adverse events related to the mobile phone intervention were reported. Weekly, interactive text-messaging was not associated with improved retention in PMTCT care at 18 months postpartum or linkage to care up to 30 months postpartum in this setting. (ISRCTN No. 98818734). [ABSTRACT FROM AUTHOR]

Long‐term register data offer unique opportunities to explore causal effects of treatments on time‐to‐event outcomes, in well‐characterized populations with minimum loss of follow‐up. However, the structure of the data may pose methodological challenges. Motivated by the Swedish Renal Registry and estimation of survival differences for renal replacement therapies, we focus on the particular case when an important confounder is not recorded in the early period of the register, so that the entry date to the register deterministically predicts confounder missingness. In addition, an evolving composition of the treatment arms populations, and suspected improved survival outcomes in later periods lead to informative administrative censoring, unless the entry date is appropriately accounted for. We investigate different consequences of these issues on causal effect estimation following multiple imputation of the missing covariate data. We analyse the performance of different combinations of imputation models and estimation methods for the population average survival. We further evaluate the sensitivity of our results to the nature of censoring and misspecification of fitted models. We find that an imputation model including the cumulative baseline hazard, event indicator, covariates and interactions between the cumulative baseline hazard and covariates, followed by regression standardization, leads to the best estimation results overall, in simulations. Standardization has two advantages over inverse probability of treatment weighting here: it can directly account for the informative censoring by including the entry date as a covariate in the outcome model, and allows for straightforward variance computation using readily available software. [ABSTRACT FROM AUTHOR]

A causal query will commonly not be identifiable from observed data, in which case no estimator of the query can be contrived without further assumptions or measured variables, regardless of the amount or precision of the measurements of observed variables. However, it may still be possible to derive symbolic bounds on the query in terms of the distribution of observed variables. Bounds, numeric or symbolic, can often be more valuable than a statistical estimator derived under implausible assumptions. Symbolic bounds, however, provide a measure of uncertainty and information loss due to the lack of an identifiable estimand even in the absence of data. We develop and describe a general approach for computation of symbolic bounds and characterize a class of settings in which our method is guaranteed to provide tight valid bounds. This expands the known settings in which tight causal bounds are solutions to linear programs. We also prove that our method can provide valid and possibly informative symbolic bounds that are not guaranteed to be tight in a larger class of problems. We illustrate the use and interpretation of our algorithms in three examples in which we derive novel symbolic bounds. for this article are available online. [ABSTRACT FROM AUTHOR]

Background: Medical advances in the treatment of cancer have allowed the development of multiple approved treatments and prognostic and predictive biomarkers for many types of cancer. Identifying improved treatment strategies among approved treatment options, the study of which is termed comparative effectiveness, using predictive biomarkers is becoming more common. RCTs that incorporate predictive biomarkers into the study design, called prediction-driven RCTs, are needed to rigorously evaluate these treatment strategies. Although researched extensively in the experimental treatment setting, literature is lacking in providing guidance about prediction-driven RCTs in the comparative effectiveness setting. Methods: Realistic simulations with time-to-event endpoints are used to compare contrasts of clinical utility and provide examples of simulated prediction-driven RCTs in the comparative effectiveness setting. Results: Our proposed contrast for clinical utility accurately estimates the true clinical utility in the comparative effectiveness setting while in some scenarios, the contrast used in current literature does not. Discussion: It is important to properly define contrasts of interest according to the treatment setting. Realistic simulations should be used to choose and evaluate the RCT design(s) able to directly estimate that contrast. In the comparative effectiveness setting, our proposed contrast for clinical utility should be used. [ABSTRACT FROM AUTHOR]

Shifting the malaria priorities from a paradigm of control and elimination to a goal of global eradication calls for renewed attention to the interruption of malaria transmission. Sustained progress toward eradication will require both improved understanding of infectious reservoirs and efficient development of novel transmission-blocking interventions, such as rapidly acting and highly efficacious therapeutics and vaccines. Here, we review the direct skin feeding assay (DSF), which has been proposed as a valuable tool for measuring the in natura transmission of malaria parasites from human hosts to mosquito vectors across heterogeneous populations. To capture the methodological breadth of this assay’s use, we first systematically review and qualitatively synthesize previously published investigations using DSFs to study malaria transmission in humans. Then, using a recent Phase 1 trial in Mali of the Pfs25H-EPA/Alhydrogel® vaccine candidate (NCT01867463) designed to interrupt Plasmodium falciparum transmission as a case study, we describe the potential opportunities and current limitations of utilizing the endpoints measured by DSF in making early clinical decisions for individually randomized transmission-interrupting intervention candidates. Using simulations based on the data collected in the clinical trial, we demonstrate that the capacity of the DSF to serve as an evaluative tool is limited by the statistical power constraints of the “effective sample size” (i.e. the number of subjects that are capable of transmitting at the time of feeding). Altogether, our findings suggest DSFs have great potential utility for assessing the public health impacts of emerging antimalarial tools, but additional research is needed to address issues of scalability and to establish correlation with community-wide clinical endpoints as well as complementary in vitro measures, such as standard membrane feeding assays. [ABSTRACT FROM AUTHOR]

Mother-to-child transmission of HIV remains a significant concern in Africa despite earlier progress. Early infant diagnosis (EID) of HIV is crucial to reduce mortality among infected infants through early treatment initiation. However, a large proportion of HIV-exposed infants are still not tested in Kenya. Our objective was to investigate whether weekly interactive text-messages improved prevention of mother-to-child transmission (PMTCT) of HIV care outcomes including EID HIV testing. This multicentre, parallel-group, randomised, open-label trial included six antenatal care clinics across western Kenya. Pregnant women living with HIV, aged 18 years or older, with mobile phone access, were randomised in a 1:1 ratio to weekly text messages that continued until 24 months postpartum, asking "How are you?" ("Mambo?") to which they were asked to respond within 48 h, or a control group. Healthcare workers contacted participants reporting problems and non-responders by phone. Participants in both groups received routine PMTCT care. The prespecified secondary outcome reported in this paper is EID HIV testing by eight weeks of age (blinded outcome assessment). Final 24-months trial results will be published separately. We estimated risk ratios using Poisson regression with robust standard errors. Between June 2015–July 2016, we screened 735 pregnant women, of whom 600 were enrolled: 299 were allocated to the intervention and 301 to the control group. By eight weeks of age, the uptake of EID HIV testing out of recorded live births was 85.5% in the intervention and 84.7% in the control group (71.2% vs. 71.8% of participants randomised, including miscarriages, stillbirths, etc.). The intention-to-treat risk ratio was 0.99; 95% CI: 0.90–1.10; p = 0.89. The proportion of infants diagnosed with HIV was 0.8% in the intervention and 1.2% in the control group. No adverse events were reported. We found no evidence to support that the WelTel intervention improved EID HIV testing. A higher uptake of EID testing than expected in both groups may be a result of lower barriers to EID testing and improved PMTCT care in western Kenya, including the broader standard use of mobile phone communication between healthcare workers and patients. (ISRCTN No. 98818734. Funded by the European-Developing Countries Clinical Trial Partnership and others). [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article on fold rise in antibody titers by measured by glycoprotein- based enzyme-linked immunosorbent assay being an excellent correlate of protection for herpes zoster vaccine by Gilbert P. B. in the 2014 issue. [ABSTRACT FROM AUTHOR]

The test-negative study design is often used to estimate vaccine effectiveness in influenza studies, but it has also been proposed in the context of other infectious diseases, such as cholera, dengue, or Ebola. It was introduced as a variation of the case-control design, in an attempt to reduce confounding bias due to health-care–seeking behavior, and has quickly gained popularity because of its logistic advantages. However, examination of the directed acyclic graphs that describe the test-negative design reveals that without strong assumptions, the estimated odds ratio derived under this sampling mechanism is not collapsible over the selection variable, such that the results obtained for the sampled individuals cannot be generalized to the whole population. In this paper, we show that adjustment for severity of disease can reduce this bias and, under certain assumptions, makes it possible to unbiasedly estimate a causal odds ratio. We support our findings with extensive simulations and discuss them in the context of recently published cholera test-negative studies of the effectiveness of cholera vaccines. [ABSTRACT FROM AUTHOR]

Chronic medical conditions often necessitate regular testing for proper treatment. Regular testing of all afflicted individuals may not be feasible due to limited resources, as is true with HIV monitoring in resource‐limited settings. Pooled testing methods have been developed in order to allow regular testing for all while reducing resource burden. However, the most commonly used methods do not make use of covariate information predictive of treatment failure, which could improve performance. We propose and evaluate four prediction‐driven pooled testing methods that incorporate covariate information to improve pooled testing performance. We then compare these methods in the HIV treatment management setting to current methods with respect to testing efficiency, sensitivity, and number of testing rounds using simulated data and data collected in Rakai, Uganda. Results show that the prediction‐driven methods increase efficiency by up to 20% compared with current methods while maintaining equivalent sensitivity and reducing number of testing rounds by up to 70%. When predictions were incorrect, the performance of prediction‐based matrix methods remained robust. The best performing method using our motivating data from Rakai was a prediction‐driven hybrid method, maintaining sensitivity over 96% and efficiency over 75% in likely scenarios. If these methods perform similarly in the field, they may contribute to improving mortality and reducing transmission in resource‐limited settings. Although we evaluate our proposed pooling methods in the HIV treatment setting, they can be applied to any setting that necessitates testing of a quantitative biomarker for a threshold‐based decision. [ABSTRACT FROM AUTHOR]

BACKGROUNDVaccines that block human-to-mosquito Plasmodium transmission are needed for malaria eradication, and clinical trials have targeted zygote antigen Pfs25 for decades. We reported that a Pfs25 protein-protein conjugate vaccine formulated in alum adjuvant induced serum functional activity in both US and Malian adults. However, antibody levels declined rapidly, and transmission-reducing activity required 4 vaccine doses. Functional immunogenicity and durability must be improved before advancing transmission-blocking vaccines further in clinical development. We hypothesized that the prefertilization protein Pfs230 alone or in combination with Pfs25 would improve functional activity.METHODSTransmission-blocking vaccine candidates based on gamete antigen Pfs230 or Pfs25 were conjugated with Exoprotein A, formulated in Alhydrogel, and administered to mice, rhesus macaques, and humans. Antibody levels were measured by ELISA and transmission-reducing activity was assessed by the standard membrane feeding assay.RESULTSPfs25-EPA/Alhydrogel and Pfs230D1-EPA/Alhydrogel induced similar serum functional activity in mice, but Pfs230D1-EPA induced significantly greater activity in rhesus monkeys that was enhanced by complement. In US adults, 2 vaccine doses induced complement-dependent activity in 4 of 5 Pfs230D1-EPA/Alhydrogel recipients but no significant activity in 5 Pfs25-EPA recipients, and combination with Pfs25-EPA did not increase activity over Pfs230D1-EPA alone.CONCLUSIONThe complement-dependent functional immunogenicity of Pfs230D1-EPA represents a significant improvement over Pfs25-EPA in this comparative study. The rhesus model is more predictive of the functional human immune response to Pfs230D1 than is the mouse model.TRIAL REGISTRATIONClinicalTrials.gov NCT02334462.FUNDINGIntramural Research Program of the National Institute of Allergy and Infectious Diseases, National Institutes of Health. [ABSTRACT FROM AUTHOR]

Personalized medicine asks if a new treatment will help a particular patient, rather than if it improves the average response in a population. Without a causal model to distinguish these questions, interpretational mistakes arise. These mistakes are seen in an article by Demidenko that recommends the "D-value," which is the probability that a randomly chosen person from the new-treatment group has a higher value for the outcome than a randomly chosen person from the control-treatment group. The abstract states "The D-value has a clear interpretation as the proportion of patients who get worse after the treatment" with similar assertions appearing later. We show these statements are incorrect because they require assumptions about the potential outcomes which are neither testable in randomized experiments nor plausible in general. The D-value will not equal the proportion of patients who get worse after treatment if (as expected) those outcomes are correlated. Independence of potential outcomes is unrealistic and eliminates any personalized treatment effects; with dependence, the D-value can even imply treatment is better than control even though most patients are harmed by the treatment. Thus, D-values are misleading for personalized medicine. To prevent misunderstandings, we advise incorporating causal models into basic statistics education. [ABSTRACT FROM AUTHOR]

Background: Multiple therapies exist for patients with metastatic castration-resistant prostate cancer (mCRPC). However, their improvement on progression-free survival (PFS) remains modest, potentially explained by tumor molecular heterogeneity. Several prognostic molecular biomarkers have been identified for mCRPC that may have predictive potential to guide treatment selection and prolong PFS. We designed a platform trial to test this hypothesis.Methods: The Prostate-Biomarker (ProBio) study is a multi-center, outcome-adaptive, multi-arm, biomarker-driven platform trial for tailoring treatment decisions for men with mCRPC. Treatment decisions in the experimental arms are based on biomarker signatures defined as mutations in certain genes/pathways suggested in the scientific literature to be important for treatment response in mCRPC. The biomarker signatures are determined by targeted sequencing of circulating tumor and germline DNA using a panel specifically designed for mCRPC.Discussion: Patients are stratified based on the sequencing results and randomized to either current clinical practice (control), where the treating physician decides treatment, or to molecularly driven treatment selection based on the biomarker profile. Outcome-adaptive randomization is implemented to early identify promising treatments for a biomarker signature. Biomarker signature-treatment combinations graduate from the platform when they demonstrate 85% probability of improving PFS compared to the control arm. Graduated combinations are further evaluated in a seamless confirmatory trial with fixed randomization. The platform design allows for new drugs and biomarkers to be introduced in the study.Conclusions: The ProBio design allows promising treatment-biomarker combinations to quickly graduate from the platform and be confirmed for rapid implementation in clinical care.Trial Registration: ClinicalTrials.gov Identifier NCT03903835. Date of registration: April 4, 2019. Status: Recruiting. [ABSTRACT FROM AUTHOR]

Although the P value from a Wilcoxon-Mann-Whitney test is used often with randomized experiments, it is rarely accompanied with a causal effect estimate and its confidence interval. The natural parameter for the Wilcoxon-Mann-Whitney test is the Mann-Whitney parameter, ϕ, which measures the probability that a randomly selected individual in the treatment arm will have a larger response than a randomly selected individual in the control arm (plus an adjustment for ties). We show that the Mann-Whitney parameter may be framed as a causal parameter and show that it is not equal to a closely related and nonidentifiable causal effect, ψ, the probability that a randomly selected individual will have a larger response under treatment than under control (plus an adjustment for ties). We review the paradox, first expressed by Hand, that the ψ parameter may imply that the treatment is worse (or better) than control, while the Mann-Whitney parameter shows the opposite. Unlike the Mann-Whitney parameter, ψ is nonidentifiable from a randomized experiment. We review some nonparametric assumptions that rule out Hand's paradox through bounds on ψ and use bootstrap methods to make inferences on those bounds. We explore the relationship of the proportional odds parameter to Hand's paradox, showing that the paradox may occur for proportional odds parameters between 1/9 and 9. Thus, large effects are needed to ensure that if treatment appears better by the Mann-Whitney parameter, then treatment improves responses in most individuals. We demonstrate these issues using a vaccine trial. [ABSTRACT FROM AUTHOR]

Background: Pfs25H-EPA is a protein-protein conjugate transmission-blocking vaccine against Plasmodium falciparum that is safe and induces functional antibodies in malaria-naive individuals. In this field trial, we assessed Pfs25H-EPA/Alhydrogel for safety and functional immunogenicity in Malian adults.Methods: This double-blind, randomised, comparator-controlled, dose-escalation trial in Bancoumana, Mali, was done in two staggered phases, an initial pilot safety assessment and a subsequent main phase. Healthy village residents aged 18-45 years were eligible if they had normal laboratory results (including HIV, hepatitis B, hepatitis C tests) and had not received a previous malaria vaccine or recent immunosuppressive drugs, vaccines, or blood products. Participants in the pilot safety cohort and the main cohort were assigned (1:1) by block randomisation to a study vaccine group. Participants in the pilot safety cohort received two doses of Pfs25H-EPA/Alhydrogel 16 μg or Euvax B (comparator vaccine), and participants in the main cohort received Pfs25H-EPA/Alhydrogel 47 μg or comparator vaccine (Euvax B for the first, second, and third vaccinations and Menactra for the fourth vaccination). Participants and investigators were masked to group assignment, and randomisation codes in sealed envelopes held by a site pharmacist. Vials with study drug for injection were covered by opaque tape and labelled with a study identification number. Group assignments were unmasked at final study visit. The primary outcomes were safety and tolerability for all vaccinees. The secondary outcome measure was immunogenicity 14 days after vaccination in the per-protocol population, as confirmed by the presence of antibodies against Pfs25H measured by ELISA IgG and antibody functionality assessed by standard membrane feeding assays and by direct skin feeding assays. This trial is registered with ClinicalTrials.gov, number NCT01867463.Findings: Between May 15, and Jun 16, 2013, 230 individuals were screened for eligibility. 20 individuals were enrolled in the pilot safety cohort; ten participants were assigned to receive Pfs25H-EPA/Alhydrogel 16 μg, and ten participants were assigned to receive comparator vaccine. 100 individuals were enrolled in the main cohort; 50 participants were assigned to receive Pfs25H-EPA/Alhydrogel 47 μg, and 50 participants were assigned to receive comparator vaccine. Compared with comparator vaccinees, Pfs25H vaccinees had more solicited adverse events (137 events vs 86 events; p=0·022) and treatment-related adverse events (191 events vs 126 events, p=0·034), but the number of other adverse events did not differ between study vaccine groups (792 vs 683). Pfs25H antibody titres increased with each dose, with a peak geometric mean of 422·3 ELISA units (95% CI 290-615) after the fourth dose, but decreased relatively rapidly thereafter, with a half-life of 42 days for anti-Pfs25H and 59 days for anti-EPA (median ratio of titres at day 600 to peak, 0·19 for anti-Pfs25H vs 0·29 for anti-EPA; p=0·009). Serum transmission-reducing activity was greater for Pfs25H than for comparator vaccine after the fourth vaccine dose (p<0·001) but not after the third dose (p=0·09). Repeated direct skin feeds were well tolerated, but the number of participants who infected at least one mosquito did not differ between Pfs25H and comparator vaccinees after the fourth dose (p=1, conditional exact).Interpretation: Pfs25H-EPA/Alhydrogel was well tolerated and induced significant serum activity by standard membrane feeding assays but transmission blocking activity was not confirmed by weekly direct skin feed. This activity required four doses, and titres decreased rapidly after the fourth dose. Alternative antigens or combinations should be assessed to improve activity.Funding: Division of Intramural Research, National Institute of Allergy and Infectious Diseases. [ABSTRACT FROM AUTHOR]

Background: Plasmodium falciparum sporozite (PfSPZ) Vaccine is a metabolically active, non-replicating, whole malaria sporozoite vaccine that has been reported to be safe and protective against P falciparum controlled human malaria infection in malaria-naive individuals. We aimed to assess the safety and protective efficacy of PfSPZ Vaccine against naturally acquired P falciparum in malaria-experienced adults in Mali.Methods: After an open-label dose-escalation study in a pilot safety cohort, we did a double-blind, randomised, placebo-controlled trial based in Donéguébougou and surrounding villages in Mali. We recruited 18-35-year-old healthy adults who were randomly assigned (1:1) in a double-blind manner, with stratification by village and block randomisation, to receive either five doses of 2·7 × 105 PfSPZ or normal saline at days 0, 28, 56, 84, and 140 during the dry season (January to July inclusive). Participants and investigators were masked to group assignments, which were unmasked at the final study visit, 6 months after receipt of the last vaccination. Participants received combined artemether and lumefantrine (four tablets, each containing 20 mg artemether and 120 mg lumefantrine, given twice per day over 3 days for a total of six doses) to eliminate P falciparum before the first and last vaccinations. We collected blood smears every 2 weeks and during any illness for 24 weeks after the fifth vaccination. The primary outcome was the safety and tolerability of the vaccine, assessed as local and systemic reactogenicity and adverse events. The sample size was calculated for the exploratory efficacy endpoint of time to first P falciparum infection beginning 28 days after the fifth vaccination. The safety analysis included all participants who received at least one dose of investigational product, whereas the efficacy analyses included only participants who received all five vaccinations. This trial is registered at ClinicalTrials.gov, number NCT01988636.Findings: Between Jan 18 and Feb 24, 2014, we enrolled 93 participants into the main study cohort with 46 participants assigned PfSPZ Vaccine and 47 assigned placebo, all of whom were evaluable for safety. We detected no significant differences in local or systemic adverse events or laboratory abnormalities between the PfSPZ Vaccine and placebo groups, and only grade 1 (mild) local or systemic adverse events occurred in both groups. The most common solicited systemic adverse event in the vaccine and placebo groups was headache (three [7%] people in the vaccine group vs four [9%] in the placebo group) followed by fatigue (one [2%] person in the placebo group), fever (one [2%] person in the placebo group), and myalgia (one [2%] person in each group). The exploratory efficacy analysis included 41 participants from the vaccine group and 40 from the placebo group. Of these participants, 37 (93%) from the placebo group and 27 (66%) from the vaccine group developed P falciparum infection. The hazard ratio for vaccine efficacy was 0·517 (95% CI 0·313-0·856) by time-to-infection analysis (log-rank p=0·01), and 0·712 (0·528-0·918) by proportional analysis (p=0·006).Interpretation: PfSPZ Vaccine was well tolerated and safe. PfSPZ Vaccine showed significant protection in African adults against P falciparum infection throughout an entire malaria season.Funding: US National Institutes of Health Intramural Research Program, Sanaria. [ABSTRACT FROM AUTHOR]

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

A successful HIV vaccine will likely induce both humoral and cell-mediated immunity, however, the enormous diversity of HIV has hampered the development of a vaccine that effectively elicits both arms of the adaptive immune response. To tackle the problem of viral diversity, T cell-based vaccine approaches have focused on two main strategies (i) increasing the breadth of vaccine-induced responses or (ii) increasing vaccine-induced responses targeting only conserved regions of the virus. The relative extent to which set-point viremia is impacted by epitope-conservation of CD8+ T cell responses elicited during early HIV-infection is unknown but has important implications for vaccine design. To address this question, we comprehensively mapped HIV-1 CD8+ T cell epitope-specificities in 23 ART-naïve individuals during early infection and computed their conservation score (CS) by three different methods (prevalence, entropy and conseq) on clade-B and group-M sequence alignments. The majority of CD8+ T cell responses were directed against variable epitopes (p<0.01). Interestingly, increasing breadth of CD8+ T cell responses specifically recognizing conserved epitopes was associated with lower set-point viremia (r = - 0.65, p = 0.009). Moreover, subjects possessing CD8+ T cells recognizing at least one conserved epitope had 1.4 log10 lower set-point viremia compared to those recognizing only variable epitopes (p = 0.021). The association between viral control and the breadth of conserved CD8+ T cell responses may be influenced by the method of CS definition and sequences used to determine conservation levels. Strikingly, targeting variable versus conserved epitopes was independent of HLA type (p = 0.215). The associations with viral control were independent of functional avidity of CD8+ T cell responses elicited during early infection. Taken together, these data suggest that the next-generation of T-cell based HIV-1 vaccines should focus on strategies that can elicit CD8+ T cell responses to multiple conserved epitopes of HIV-1. [ABSTRACT FROM AUTHOR]