Timing and predictors of severe rotavirus gastroenteritis among unvaccinated infants in low- and middle-income countries

Delays in rotavirus vaccine schedule could improve performance in low- and middle-income countries (LMICs). However, delaying the first dose could be detrimental if infants experience severe rotavirus gastroenteritis (RVGE) early in life. Our objective was to describe the timing and predictors of severe RVGE in unvaccinated children in LMICs. We analysed the placebo arms from two clinical trials (cohort 1: NCT00241644; cohort 2: NCT00362648). We estimated the rate, cumulative incidence (per 1000 infants) and age distribution of severe RVGE episodes. Cox proportional hazards models were used to estimate hazard ratios and 95% confidence intervals (CI) for the association between baseline factors and severe RVGE. Cumulative incidence at 6 months of age was 23/1000 (95% CI 15-30) in cohort 1 and 6/1000 (95% CI 3-8) in cohort 2. Early antibiotic use (compared with no use) was associated with 2.03 (95% CI 1.18-3.48) and 1.41 (95% CI 0.80-2.51) times the rate of severe RVGE in cohorts 1 and 2, respectively. The cumulative incidence of severe RVGE was low at 6 months of age, suggesting that a 4-week delay in the vaccination schedule may not result in a large number of severe RVGE episodes prior to vaccine receipt. Copyright © Cambridge University Press 2018

Generalizing Evidence from Randomized Trials using Inverse Probability of Sampling Weights

Results obtained in randomized trials may not easily generalize to target populations. Whereas in randomized trials the treatment assignment mechanism is known, the sampling mechanism by which individuals are selected to participate in the trial is typically not known and assuming random sampling from the target population is often dubious. We consider an inverse probability of sampling weighted (IPSW) estimator for generalizing trial results to a target population. The IPSW estimator is shown to be consistent and asymptotically normal. A consistent sandwich-type variance estimator is derived and simulation results are presented comparing the IPSW estimator to a previously proposed stratified estimator. The methods are then utilized to generalize results from two randomized trials of HIV treatment to all people living with HIV in the US

Chemical Kinetic Insights into the Octane Number and Octane Sensitivity of Gasoline Surrogate Mixtures

Gasoline octane number is a significant empirical parameter for the optimization and development of internal combustion engines capable of resisting knock. Although extensive databases and blending rules to estimate the octane numbers of mixtures have been developed and the effects of molecular structure on autoignition properties are somewhat understood, a comprehensive theoretical chemistry-based foundation for blending effects of fuels on engine operations is still to be developed. In this study, we present models that correlate the research octane number (RON) and motor octane number (MON) with simulated homogeneous gas-phase ignition delay times of stoichiometric fuel/air mixtures. These correlations attempt to bridge the gap between the fundamental autoignition behavior of the fuel (e.g., its chemistry and how reactivity changes with temperature and pressure) and engine properties such as its knocking behavior in a cooperative fuels research (CFR) engine. The study encompasses a total of 79 hydrocarbon gasoline surrogate mixtures including 11 primary reference fuels (PRF), 43 toluene primary reference fuels (TPRF), and 19 multicomponent (MC) surrogate mixtures. In addition to TPRF mixture components of iso-octane/n-heptane/toluene, MC mixtures, including n-heptane, iso-octane, toluene, 1-hexene, and 1,2,4-trimethylbenzene, were blended and tested to mimic real gasoline sensitivity. ASTM testing protocols D-2699 and D-2700 were used to measure the RON and MON of the MC mixtures in a CFR engine, while the PRF and TPRF mixtures' octane ratings were obtained from the literature. The mixtures cover a RON range of 0-100, with the majority being in the 70-100 range. A parametric simulation study across a temperature range of 650-950 K and pressure range of 15-50 bar was carried out in a constant-volume homogeneous batch reactor to calculate chemical kinetic ignition delay times. Regression tools were utilized to find the conditions at which RON and MON best correlate with simulated ignition delay times. Furthermore, temperature and pressure dependences were investigated for fuels with varying octane sensitivity. This analysis led to the formulation of correlations useful to the definition of surrogates for modeling purposes and allowed one to identify conditions for a more in-depth understanding of the chemical phenomena controlling the antiknock behavior of the fuels

Inference with interference between units in an fMRI experiment of motor inhibition

An experimental unit is an opportunity to randomly apply or withhold a treatment. There is interference between units if the application of the treatment to one unit may also affect other units. In cognitive neuroscience, a common form of experiment presents a sequence of stimuli or requests for cognitive activity at random to each experimental subject and measures biological aspects of brain activity that follow these requests. Each subject is then many experimental units, and interference between units within an experimental subject is likely, in part because the stimuli follow one another quickly and in part because human subjects learn or become experienced or primed or bored as the experiment proceeds. We use a recent fMRI experiment concerned with the inhibition of motor activity to illustrate and further develop recently proposed methodology for inference in the presence of interference. A simulation evaluates the power of competing procedures.Comment: Published by Journal of the American Statistical Association at http://www.tandfonline.com/doi/full/10.1080/01621459.2012.655954 . R package cin (Causal Inference for Neuroscience) implementing the proposed method is freely available on CRAN at https://CRAN.R-project.org/package=ci

Patterns of use of recombinant zoster vaccine among commercially-insured immunocompetent and immunocompromised adults 50–64 years old in the United States

Purpose: The Centers for Disease Control and Prevention (CDC) recommends recombinant zoster vaccination (RZV) for adults ≥ 50 years to prevent herpes zoster (HZ) and its sequelae. Initially, no distinct recommendation was made for immunocompromised adults, who experience higher HZ rates and more severe outcomes. We characterized receipt of first RZV dose (initiation) and both doses (completion) over time, and the impact of immune function on RZV uptake among adults aged 50–64 years in the United States. Methods: We identified RZV claims from the IBM MarketScan database between 1/1/2018 and 12/31/2019. We characterized immunocompromised enrollees as having malignancy, HIV, solid organ transplant, primary immunosuppression, or medication-induced immunosuppression using inpatient, outpatient, and prescription claims in the 6 months prior to study start. We evaluated patterns of vaccine uptake by demographic and healthcare access characteristics and immune status. Results: The cumulative incidence of RZV initiation during the study period was 10.0%. Incidence increased with age and number of medical office visits, and was higher among women, urban residents, high-deductible insurance beneficiaries, and those who were immunocompromised compared to immunocompetent. Among immunocompromised adults, RZV initiation was highest among those with HIV and primary immunodeficiencies. Of those who initiated RZV, 89.5% received both doses. RZV completion was highest among those who received the first dose at a pharmacy. Most enrollees (88.6%) who completed RZV vaccination did so within the recommended dosing schedule. Conclusions: RZV uptake was low in the two years since the CDC recommendation, and differed by demographic, healthcare access, and clinical characteristics. Initiation rates were higher among immunocompromised adults compared to immunocompetent adults, despite no CDC recommendation for vaccination in these groups during the study period. The CDC has since recommended RZV for immunocompromised individuals, and our findings may inform efforts to increase RZV uptake in individuals at higher risk of severe disease

Use of Patient-Reported Outcomes to Understand & Measure the Patient Experience of Novel Cell and Gene Therapies

Patient reported outcomes (PROs) are the gold standard for assessing patients’ experience of treatment in oncology, defined in the 21st Century Cures Act as information about patients’ experiences with a disease or condition, including the impact of a disease or condition, or a related therapy or clinical investigation on patients’ lives; and patient preferences with respect to treatment of their disease or condition [1]. PROs provide a comprehensive assessment of the benefits and risks of new medical products, as well as essential data to inform real-world use. Although RCTs are the ultimate source for information for evaluating products in development, they are not always feasible for rare diseases with few or no effective treatment options available. Thus, it is important to consider other measures that can help to improve the strength of evidence for cell and gene therapies targeting rare indications. While collection of PROs and other patient experience endpoints does not resolve the difficulty of conducting trials in small populations, doing so contributes empirical evidence that informs both product development and patient access. Additionally, including routine collection of PROs in registries may provide supplemental data to further characterize the benefit:risk profile of cell and gene therapies at follow-up times that would be infeasible to operationalize in a clinical trial setting

Discrete-time semi-Markov modeling of human papillomavirus persistence

Multi-state modeling is often employed to describe the progression of a disease process. In epidemiological studies of certain diseases, the disease state is typically only observed at periodic clinical visits, producing incomplete longitudinal data. In this paper we consider fitting semi-Markov models to estimate the persistence of human papillomavirus (HPV) type-specific infection in studies where the status of HPV type(s) is assessed periodically. Simulation study results are presented indicating the semi-Markov estimator is more accurate than an estimator currently used in the HPV literature. The methods are illustrated using data from the HIV Epidemiology Research Study (HERS)