Triple challenges - Small sample size in both exposure and control groups to scan rare maternal outcomes in a signal identification approach: A simulation study.

There is a dearth of safety data on maternal outcomes after perinatal medication exposure. Data-mining for unexpected adverse event occurrence in existing datasets is a potentially useful approach. One method, the Poisson tree-based scan statistic (TBSS), assumes that the expected outcome counts, based on incidence of outcomes in the control group, are estimated without error. This assumption may be difficult to satisfy with a small control group. Our simulation study evaluated the effect of imprecise incidence proportions from the control group on TBSS' ability to identify maternal outcomes in pregnancy research. We simulated base case analyses with "true" expected incidence proportions and compared these to imprecise incidence proportions derived from sparse control samples. We varied parameters impacting Type I error and statistical power (exposure group size, outcome's incidence proportion, and effect size). We found that imprecise incidence proportions generated by a small control group resulted in inaccurate alerting, inflation of Type I error, and removal of very rare outcomes for TBSS analysis due to "zero" background counts. Ideally, the control size should be at least several times larger than the exposure size to limit the number of false positive alerts and retain statistical power for true alerts.

Statistical methods to control for confounders in rare disease settings that use external control.

In the drug development for rare disease, the number of treated subjects in the clinical trial is often very small, whereas the number of external controls can be relatively large. There is no clear guidance on choosing an appropriate statistical method to control baseline confounding in this situation. To fill this gap, we conduct extensive simulations to evaluate the performance of commonly used matching and weighting methods as well as the more recently developed targeted maximum likelihood estimation (TMLE) and cardinality matching in small sample settings, mimicking the motivating data from a pediatric rare disease. Among the methods examined, the performance of coarsened exact matching (CEM) and TMLE are relatively robust under various model specifications. CEM is only feasible when the number of controls far exceeds the number of treated, whereas TMLE has better performance with less extreme treatment allocation ratios. Our simulations suggest bootstrap is useful for variance estimation in small samples after matching.

Retrieved-Dropout-Based multiple imputation for time-to-event data in cardiovascular outcome trials.

Recently, retrieved-dropout-based multiple imputation has been used in some therapeutic areas to address the treatment policy estimand, mostly for continuous endpoints. In this approach, data from subjects who discontinued study treatment but remained in study were used to construct a model for multiple imputation for the missing data of subjects in the same treatment arm who discontinued study. We extend this approach to time-to-event endpoints and provide a practical guide for its implementation. We use a cardiovascular outcome trial dataset to illustrate the method and compare the results with those from Cox proportional hazard and reference-based multiple imputation methods.

Statistical methods for handling missing data to align with treatment policy strategy.

The International Council for Harmonization (ICH) E9(R1) addendum recommends choosing an appropriate estimand based on the study objectives in advance of trial design. One defining attribute of an estimand is the intercurrent event, specifically what is considered an intercurrent event and how it should be handled. The primary objective of a clinical study is usually to assess a product's effectiveness and safety based on the planned treatment regimen instead of the actual treatment received. The estimand using the treatment policy strategy, which collects and analyzes data regardless of the occurrence of intercurrent events, is usually utilized. In this article, we explain how missing data can be handled using the treatment policy strategy from the authors' viewpoint in connection with antihyperglycemic product development programs. The article discusses five statistical methods to impute missing data occurring after intercurrent events. All five methods are applied within the framework of the treatment policy strategy. The article compares the five methods via Markov Chain Monte Carlo simulations and showcases how three of these five methods have been applied to estimate the treatment effects published in the labels for three antihyperglycemic agents currently on the market.

Regression calibration to correct correlated errors in outcome and exposure.

Measurement error arises through a variety of mechanisms. A rich literature exists on the bias introduced by covariate measurement error and on methods of analysis to address this bias. By comparison, less attention has been given to errors in outcome assessment and nonclassical covariate measurement error. We consider an extension of the regression calibration method to settings with errors in a continuous outcome, where the errors may be correlated with prognostic covariates or with covariate measurement error. This method adjusts for the measurement error in the data and can be applied with either a validation subset, on which the true data are also observed (eg, a study audit), or a reliability subset, where a second observation of error prone measurements are available. For each case, we provide conditions under which the proposed method is identifiable and leads to consistent estimates of the regression parameter. When the second measurement on the reliability subset has no error or classical unbiased measurement error, the proposed method is consistent even when the primary outcome and exposures of interest are subject to both systematic and random error. We examine the performance of the method with simulations for a variety of measurement error scenarios and sizes of the reliability subset. We illustrate the method's application using data from the Women's Health Initiative Dietary Modification Trial.

Resampling-based stepwise multiple testing procedures with applications to clinical trial data.

Endpoints in clinical trials are often highly correlated. However, the commonly used multiple testing procedures in clinical trials either do not take into consideration the correlations among test statistics or can only exploit known correlations. Westfall and Young constructed a resampling-based stepdown method that implicitly utilizes the correlation structure of test statistics in situations with unknown correlations. However, their method requires a "subset pivotality" assumption. Romano and Wolf proposed a more general stepdown method, which does not require such an assumption. There is at present little experience with the application of such methods in analyzing clinical trial data. We advocate the application of resampling-based multiple testing procedures to clinical trials data when appropriate. We have conjectured that the resampling-based stepdown methods can be extended to a stepup procedure under appropriate assumptions and examined the performance of both stepdown and stepup methods under a variety of correlation structures and distribution types. Results from our simulation studies support the use of the resampling-based methods under various scenarios, including binary data and small samples, with strong control of Family wise type I error rate (FWER). Under positive dependence and for binary data even under independence, the resampling-based methods are more powerful than the Holm and Hochberg methods. Last, we illustrate the advantage of the resampling-based stepwise methods with two clinical trial data examples: a cardiovascular outcome trial and an oncology trial.

Perturbation of Brain Oscillations after Ischemic Stroke: A Potential Biomarker for Post-Stroke Function and Therapy.

Brain waves resonate from the generators of electrical current and propagate across brain regions with oscillation frequencies ranging from 0.05 to 500 Hz. The commonly observed oscillatory waves recorded by an electroencephalogram (EEG) in normal adult humans can be grouped into five main categories according to the frequency and amplitude, namely δ (1-4 Hz, 20-200 µV), θ (4-8 Hz, 10 µV), α (8-12 Hz, 20-200 µV), ß (12-30 Hz, 5-10 µV), and γ (30-80 Hz, low amplitude). Emerging evidence from experimental and human studies suggests that groups of function and behavior seem to be specifically associated with the presence of each oscillation band, although the complex relationship between oscillation frequency and function, as well as the interaction between brain oscillations, are far from clear. Changes of brain oscillation patterns have long been implicated in the diseases of the central nervous system including ischemic stroke, in which the reduction of cerebral blood flow as well as the progression of tissue damage have direct spatiotemporal effects on the power of several oscillatory bands and their interactions. This review summarizes the current knowledge in behavior and function associated with each brain oscillation, and also in the specific changes in brain electrical activities that correspond to the molecular events and functional alterations observed after experimental and human stroke. We provide the basis of the generations of brain oscillations and potential cellular and molecular mechanisms underlying stroke-induced perturbation. We will also discuss the implications of using brain oscillation patterns as biomarkers for the prediction of stroke outcome and therapeutic efficacy.

Optimizing bladder cancer locoregional failure risk stratification after radical cystectomy using SWOG 8710.

BACKGROUND: Clinical trials of radiation after radical cystectomy (RC) and chemotherapy for bladder cancer are in development, but inclusion and stratification factors have not been clearly established. In this study, the authors evaluated and refined a published risk stratification for locoregional failure (LF) by applying it to a multicenter patient cohort. METHODS: The original stratification, which was developed using a single-institution series, produced 3 subgroups with significantly different LF risk based on pathologic tumor (pT) classification and the number of lymph nodes identified. This model was then applied to patients in Southwest Oncology Group (SWOG) 8710, a randomized trial of RC with or without chemotherapy. LF was defined as any pelvic failure before or within 3 months of distant failure. RESULTS: Patients in the development cohort and the SWOG cohort had significantly different baseline characteristics. The original risk model was not fully validated in the SWOG cohort, because lymph node yield was not as strongly associated with LF as in the development cohort. Regression analysis indicated that margin status could improve the model. A revised stratification using pT classification, margin status, and the number of lymph nodes identified produced 3 subgroups with significantly different LF risk in both cohorts: low risk (≤pT2), intermediate risk (≥pT3 with negative margins AND ≥10 lymph nodes identified), and high risk (≥pT3 with positive margins OR <10 lymph nodes identified) with 5-year LF rates of 8%, 20%, and 41%, respectively, in the SWOG cohort and 8%, 19%, and 41%, respectively, in the development cohort. CONCLUSIONS: A model incorporating pT classification, margin status, and the number of lymph nodes identified stratified LF risk in 2 different RC populations and may inform the design of future trials.

Longitudinal strain in Friedreich Ataxia: a potential marker for early left ventricular dysfunction.

BACKGROUND: Friedreich's ataxia (FRDA) is a neurodegenerative disorder resulting from deficiency of frataxin, characterized by cardiac hypertrophy associated with heart failure and sudden cardiac death. However, the relationship between remodeling and novel measures of cardiac function such as strain, and the time-dependent changes in these measures are poorly defined. METHODS AND RESULTS: We compared echocardiographic parameters of cardiac size, hypertrophy, and function in 50 FRDA patients with 50 normal controls and quantified the following measures of cardiac remodeling and function: left ventricular (LV) volumes, mass, relative wall thickness (RWT), ejection fraction (EF), and myocardial strain. Linear regression analysis was used to identify significant differences in echocardiographic parameters in FRDA compared with normal subjects. In analyses adjusted for age, sex, and body surface area, significant differences were observed between parameters of remodeling (LV mass, RWT, and volumes) and function in FRDA patients compared with controls. In particular, longitudinal strain was significantly decreased in FRDA patients compared with controls (-12.4% vs. -16.0%, P < 0.001), despite similar and normal left ventricular ejection fraction (LVEF). Over 3 years of follow-up, there was no change in strain, LV size, LV mass, or LVEF among FRDA patients. CONCLUSION: Longitudinal strain is reduced in FRDA despite normal LVEF, indicative of subclinical cardiac dysfunction. Given late declines in LVEF in FRDA, longitudinal strain may provide an earlier index of myocardial dysfunction in FRDA.

A mixture model using likelihood-based and Bayesian approaches for identifying responders and non-responders in longitudinal clinical trials.

A longitudinal mixture model for classifying patients into responders and non-responders is established using both likelihood-based and Bayesian approaches. The model takes into consideration responders in the control group. Therefore, it is especially useful in situations where the placebo response is strong, or in equivalence trials where the drug in development is compared with a standard treatment. Under our model, a treatment shows evidence of being effective if it increases the proportion of responders or increases the response rate among responders in the treated group compared with the control group. Therefore, the model has flexibility to accommodate different situations. The proposed method is illustrated using simulation and a depression clinical trial dataset for the likelihood-based approach, and the same depression clinical trial dataset for the Bayesian approach. The likelihood-based and Bayesian approaches generated consistent results for the depression trial data. In both the placebo group and the treated group, patients are classified into two components with distinct response rate. The proportion of responders is shown to be significantly higher in the treated group compared with the control group, suggesting the treatment paroxetine is effective.

[Biological and genome characteristics of a novel broad host-range phage ΦEP1 infecting enteroinvasive Escherichia coli].

We analyzed the biological and genome characteristics of a phage infecting enteroinvasive Escherichia coli (EIEC), aiming to provide resources and a reference for the prevention and treatment of EIEC. With the EIEC preserved in our laboratory as the host bacterium, one strain of phage was isolated from the effluent sample from a chicken farm in Huzhou, Zhejiang and named ΦEP1. The titer, optimal multiplicity of infection, one-step growth curve, temperature, pH value, chloroform and bile salt sensitivity of ΦEP1 were determined by the double-layer agar plate method. The morphology of the phage was observed by transmission electron microscopy. The biocontrol effects of ΦEP1 in different food matrixes and the protective effect of this phage on Caco-2 cells were tested. The phage ΦEP1 showed the optimal multiplicity of infection of 0.1, the titer of 1.3×1010 PFU/mL, strong tolerance to temperature, pH, chloroform, and bile salt, and a broad host spectrum. Furthermore, it expressed lysis activity against multiple strains of multiple antibiotic-resistant pathogenic E. coli and Shigella with different serotypes. Phage ΦEP1 had an incubation period of 10 min, an outbreak period of 80 min, and an outbreak volume of 48 PFU/cell. According to the morphology observed by transmission electron microscopy, phage ΦEP1 belonged to the order of Caudovirales, and it had a good protective effect on Caco-2 cells. Phage ΦEP1 had a genome of 87 182 bp with the GC content of 39.80%, 128 putative open reading frames, and no antibiotic resistance genes or virulence genes. ΦEP1 inhibited the growth of EIEC in artificially contaminated milk and beef and eliminated EIEC in cell protection experiments. It significantly increased the survival rate of Caco-2 cells and down-regulated the expression of interleukin (IL)-6 and IL-1ß to reduce inflammation. We obtained an EIEC-targeting phage ΦEP1 with a high titer and strong tolerance to the environment, which provided a basis for the application of phages in food preservation and other fields.

Olfactory marker protein is critical for functional maturation of olfactory sensory neurons and development of mother preference.

Survival of many altricial animals critically depends on the sense of smell. Curiously, the olfactory system is rather immature at birth and undergoes a maturation process, which is poorly understood. Using patch-clamp technique on mouse olfactory sensory neurons (OSNs) with a defined odorant receptor, we demonstrate that OSNs exhibit functional maturation during the first month of postnatal life by developing faster response kinetics, higher sensitivity, and most intriguingly, higher selectivity. OSNs expressing mouse odorant receptor 23 (MOR23) are relatively broadly tuned in neonates and become selective detectors for the cognate odorant within 2 weeks. Remarkably, these changes are prevented by genetic ablation of olfactory marker protein (OMP), which is exclusively expressed in mature OSNs. Biochemical and pharmacological evidence suggests that alteration in odorant-induced phosphorylation of signaling proteins underlie some of the OMP(-/-) phenotypes. Furthermore, in a novel behavioral assay in which the mouse pups are given a choice between the biological mother and another unfamiliar lactating female, wild-type pups prefer the biological mother, while OMP knock-out pups fail to show preference. These results reveal that OSNs undergo an OMP-dependent functional maturation process that coincides with early development of the smell function, which is essential for pups to form preference for their mother.

Cerebrovascular responses of the rat brain to noxious stimuli as examined by functional near-infrared whole brain imaging.

While near-infrared (NIR) spectroscopy has been increasingly used to detect stimulated brain activities with an advantage of dissociating regional oxy- and deoxyhemoglobin concentrations simultaneously, it has not been utilized much in pain research. Here, we investigated and demonstrated the feasibility of using this technique to obtain whole brain hemodynamics in rats and speculated on the functional relevance of the NIR-based hemodynamic signals during pain processing. NIR signals were emitted and collected using a 26-optodes array on rat's dorsal skull surface after the removal of skin. Following the subcutaneous injection of formalin (50 µl, 3%) into a hindpaw, several isolable brain regions showed hemodynamic changes, including the anterior cingulate cortex, primary/secondary somatosensory cortexes, thalamus, and periaqueductal gray (n = 6). Time courses of hemodynamic changes in respective regions matched with the well-documented biphasic excitatory response. Surprisingly, an atypical pattern (i.e., a decrease in oxyhemoglobin concentration with a concomitant increase in deoxyhemoglobin concentration) was seen in phase II. In a separate group of rats with innocuous brush and noxious pinch of the same area (n = 11), results confirmed that the atypical pattern occurred more likely in the presence of nociception than nonpainful stimulation, suggesting it as a physiological substrate when the brain processes pain. In conclusion, the NIR whole brain imaging provides a useful alternative to study pain in vivo using small-animal models. Our results support the notion that neurovascular response patterns depend on stimuli, bringing attention to the interpretation of vascular-based neuroimaging data in studies of pain.

Postnatal experience modulates functional properties of mouse olfactory sensory neurons.

Early experience considerably modulates the organization and function of all sensory systems. In the mammalian olfactory system, deprivation of the sensory inputs via neonatal, unilateral naris closure has been shown to induce structural, molecular and functional changes from the olfactory epithelium to the olfactory bulb and cortex. However, it remains unknown how early experience shapes the functional properties of individual olfactory sensory neurons (OSNs), the primary odor detectors in the nose. To address this question, we examined the odorant response properties of mouse OSNs in both the closed and open nostril after 4 weeks of unilateral naris closure, with age-matched untreated animals as control. Using a patch-clamp technique on genetically tagged OSNs with defined odorant receptors (ORs), we found that sensory deprivation increased the sensitivity of MOR23 neurons in the closed side, whereas overexposure caused the opposite effect in the open side. We next analyzed the response properties, including rise time, decay time, and adaptation, induced by repeated stimulation in MOR23 and M71 neurons. Even though these two types of neuron showed distinct properties with regard to dynamic range and response kinetics, sensory deprivation significantly slowed down the decay phase of odorant-induced transduction events in both types. Using western blotting and antibody staining, we confirmed the upregulation of several signaling proteins in the closed side as compared with the open side. This study suggests that early experience modulates the functional properties of OSNs, probably by modifying the signal transduction cascade.

Quantification of light reflectance spectroscopy and its application: determination of hemodynamics on the rat spinal cord and brain induced by electrical stimulation.

Two quantification methods for light reflectance spectroscopy (LRS) were developed and validated to determine absolute and relative values of hemodynamic parameters and light scattering, followed by a specific application using in vivo animal experiments. A single-channel LRS system consisted of a light source, CCD-array detector, and a computer along with a bifurcated, 2-mm-diameter optical probe; this system was utilized to perform laboratory tissue phantoms for validation of the algorithms. In the animal study, a multi-channel, multisite approach was used to measure several reflectance spectra from rat brain and spinal cord on both the ipsi-lateral and contra-lateral sides, using thin 800-µm-diameter optic probes. The neuro-hemodynamic changes were induced by 10-V electrical stimulation in rat hind paw. The LRS data of the animals were analyzed using both absolute and relative methods. The results show that the relative method is computation-efficient and offers a quick estimation of changes in oxy-hemoglobin concentration for real-time monitoring. The absolute quantification method, on the other hand, provides us with an accurate computational tool to calculate absolute values of oxy-, deoxy-, total hemoglobin concentrations, and light scattering coefficients. We also observe that the hemodynamic responses in rat spinal cord were delayed with a few seconds and have an overall broader full width at half maximum, as compared to those from rat somatosensory cortex. LRS as a measurement system provides a robust method for studying local hemodynamic changes and a potential technique to investigate hemo-neural mechanisms in pain processing.

Inhibition of spinal cord dorsal horn neuronal activity by electrical stimulation of the cerebellar cortex.

The cerebellum plays a major role in not only modulating motor activity, but also contributing to other functions, including nociception. The intermediate hemisphere of the cerebellum receives sensory input from the limbs. With the extensive connection between the cerebellum to brain-stem structures and cerebral cortex, it is possible that the cerebellum may facilitate the descending system to modulate spinal dorsal horn activity. This study provided the first evidence to support this hypothesis. Thirty-one wide-dynamic-range neurons from the left lumbar and 27 from the right lumbar spinal dorsal horn were recorded in response to graded mechanical stimulation (brush, pressure, and pinch) at the hind paws. Electrical stimulation of the cerebellar cortex of the left intermediate hemisphere significantly reduced spinal cord dorsal horn neuron-evoked responses bilaterally in response to peripheral high-intensity mechanical stimuli. It is concluded that the cerebellum may play a potential antinociceptive role, probably through activating descending inhibitory pathways indirectly.

Local field potentials identify features of cortico-hippocampal communication impacted by stroke and environmental enrichment therapy.

Objective. Cognitive and memory impairments are common sequelae after stroke, yet how middle cerebral artery (MCA) stroke chronically affects the neural activity of the hippocampus, a brain region critical for memory but remote from the stroke epicenter, is poorly understood. Environmental enrichment (EE) improves cognition following stroke; however, the electrophysiology that underlies this behavioral intervention is still elusive.Approach.We recorded extracellular local field potentials simultaneously from sensorimotor cortex and hippocampus in rats during urethane anesthesia following MCA occlusion and subsequent EE treatment.Main results.We found that MCA stroke significantly impacted the electrophysiology in the hippocampus, in particular it disrupted characteristics of sharp-wave associated ripples (SPW-Rs) altered brain state, and disrupted phase amplitude coupling (PAC) within the hippocampus and between the cortex and hippocampus. Importantly, we show that EE mitigates stroke-induced changes to SPW-R characteristics but does not restore hippocampal brain state or PAC.Significance.These results begin to uncover the complex interaction between cognitive deficit following stroke and EE treatment, providing a testbed to assess different strategies for therapeutics following stroke.

Experimental cortical stroke induces aberrant increase of sharp-wave-associated ripples in the hippocampus and disrupts cortico-hippocampal communication.

The functional consequences of ischemic stroke in the remote brain regions are not well characterized. The current study sought to determine changes in hippocampal oscillatory activity that may underlie the cognitive impairment observed following distal middle cerebral artery occlusion (dMCAO) without causing hippocampal structural damage. Local field potentials were recorded from the dorsal hippocampus and cortex in urethane-anesthetized rats with multichannel silicon probes during dMCAO and reperfusion, or mild ischemia induced by bilateral common carotid artery occlusion (CCAO). Bilateral change of brain state was evidenced by reduced theta/delta amplitude ratio and shortened high theta duration following acute dMCAO but not CCAO. An aberrant increase in the occurrence of sharp-wave-associated ripples (150-250 Hz), crucial for memory consolidation, was only detected after dMCAO reperfusion, coinciding with an increased occurrence of high-frequency discharges (250-450 Hz). dMCAO also significantly affected the modulation of gamma amplitude in the cortex coupled to hippocampal theta phase, although both hippocampal theta and gamma power were temporarily decreased during dMCAO. Our results suggest that MCAO may disrupt the balance between excitatory and inhibitory circuits in the hippocampus and alter the function of cortico-hippocampal network, providing a novel insight in how cortical stroke affects function in remote brain regions.

Cellular mechanisms of cobalt-induced hippocampal epileptiform discharges.

PURPOSE: To explore the cellular mechanisms of cobalt-induced epileptiform discharges in mouse hippocampal slices. METHODS: Hippocampal slices were prepared from adult mice and briefly exposed to a CoCl(2)-containing external solution. Population and single cell activities were examined via extracellular and whole-cell patch recordings. RESULTS: Brief cobalt exposure induced spontaneous, ictal-like discharges originating from the CA3 area. These discharges were suppressed by anticonvulsants, gap junction blockers, or by raising extracellular Ca(2+), but their generation was not associated with overall hyperexcitability or impairment in GABAergic inhibition in the CA3 circuit. Electroencephalographic ictal discharges of similar waveforms were observed in behaving rats following intrahippocampal cobalt infusion. DISCUSSION: Mechanisms involving activity-dependent facilitation of gap junctional communication may play a major role in cobalt-induced epileptiform discharges.

Marginal structural models to estimate the effects of time-varying treatments on clustered outcomes in the presence of interference.

Marginal structural models are a class of causal models useful for characterizing the effect of treatment in the presence of time-varying confounding. They are more widely used than structural nested models, partly because these models are easier to understand and to implement. We extend marginal structural models to situations with clustered observations with unit- and cluster-level treatment and introduce an appropriate inferential method. We consider how to formulate models with cluster-level and unit-level treatments. For unit-level treatments, we consider cases with and without interference. We also consider the use of unit-specific inverse probability weights and certain working correlation structures to improve the efficiency of estimators in some situations. We apply our method to different scenarios including 2 or 3 units per cluster and a mixture of larger clusters. Simulation examples and data from the treatment arm of a glaucoma clinical trial were used to illustrate our method.