Power analyses for negative binomial models with application to multiple sclerosis clinical trials

We use negative binomial (NB) models for the magnetic resonance imaging (MRI)-based brain lesion count data from parallel group (PG) and baseline versus treatment (BVT) trials for relapsing remitting multiple sclerosis (RRMS) patients, and describe the associated likelihood ratio (LR), score, and Wald tests. We perform power analyses and sample size estimation using the simulated percentiles of the exact distribution of the test statistics for the PG and BVT trials. When compared to the corresponding nonparametric test, the LR test results in 30-45% reduction in sample sizes for the PG trials and 25-60% reduction for the BVT trials.     

Bootstrap inference in a linear equation estimated by instrumental variables

Summary We study several tests for the coefficient of the single right‐hand‐side endogenous variable in a linear equation estimated by instrumental variables. We show that writing all the test statistics—Student's t, Anderson–Rubin, the LM statistic of Kleibergen and Moreira (K), and likelihood ratio (LR)—as functions of six random quantities leads to a number of interesting results about the properties of the tests under weak‐instrument asymptotics. We then propose several new procedures for bootstrapping the three non‐exact test statistics and also a new conditional bootstrap version of the LR test. These use more efficient estimates of the parameters of the reduced‐form equation than existing procedures. When the best of these new procedures is used, both the K and conditional bootstrap LR tests have excellent performance under the null. However, power considerations suggest that the latter is probably the method of choice.     

Maximum likelihood estimates for the Hildreth–Houck random coefficients model

We explore maximum likelihood (ML) estimation of the Hildreth–Houck random coefficients model. We show that the global ML estimator can be inconsistent. We develop an alternative LML (local ML) estimator and prove that it is consistent and asymptotically efficient for points in the interior of the parameters. Properties of the LML and comparisons with common method of moments (MM) estimates are done via Monte Carlo. Boundary parameters lead to nonstandard asymptotic distributions for the LML which are described. The LML is used to develop a modification of the LR test for random coefficients. Simulations suggest that the LR test is more powerful for distant alternatives than the Breusch–Pagan (BP) Lagrange multiplier test. A simple modification of the BP test also appears to be more powerful than the BP.     

月桂氮卓酮复合促吸收剂促胰岛素经舌下黏膜吸收的研究

目的研究促胰岛素经舌下黏膜吸收的月桂氮卓酮 (Azone)复合促吸收剂。方法应用正常大鼠的降血糖实验对Azone复合促吸收剂的组成进行正交筛选 ,研究胰岛素在不同组成的促吸收剂作用下对猪舌下黏膜的体外渗透扩散系数及促渗比。结果由正交实验确定了最佳组成中Azone复合促吸收剂的比例为 2 .5 %Azone、5 %丙二醇、2 .5 %吐温 80。胰岛素分别在 5 %丙二醇、5 %丙二醇 +2 .5 %吐温 80、5 %丙二醇 +2 .5 %吐温 80 +2 .5 %A zone促吸收剂作用下的促渗比分别为 1.9(P >0 .0 5 )、2 .6 (P >0 .0 5 )和 7.8(P <0 .0 5 )。结论Azone复合促吸收剂中Azone是使黏膜通透性发生变化的主要因素。     

Wilcoxon–Mann–Whitney Test: Stratify or Not?

The Wilcoxon–Mann–Whitney (WMW) test is the most commonly used nonparametric method to compare two treatments when the underlying distribution of the outcome variable is not normally distributed. In the presence of stratum effects, the van Elteren (vE) test, a stratified WMW test, can be used to adjust for the stratum effect. We provide guidance on how to choose between the two tests in the design phase of clinical trials and in the analysis of clinical data. We show by simulations that both tests preserve the type I error rate regardless of the presence of the stratum effects. Therefore, the test with greater power is preferred. In comparing powers, we found that the WMW test is better when the stratum effects are small, whereas the vE test is better when the stratum effects are large. Finally, when the stratum effects are moderate, the decision depends on the shape of the distribution and the ratio of the number of strata and the number of subjects. In this case, results presented in this article or from similar simulations may be used to determine which test is better.     

A non-peptide receptor inhibitor with selectivity for one of the neutrophil formyl peptide receptors, FPR 1

The neutrophil formyl peptide receptors (FPR1 and FPR2) are members of the G-protein coupled receptor family. The signals generated by occupied FPRs are both pro-inflammatory and anti-inflammatory. Accordingly, these receptors have become a therapeutic target for the development of novel drugs that may be used to reduce injuries in inflammatory diseases including asthma, rheumatoid arthritis, Alzheimer's disease and cardiovascular diseases. To support the basis for a future pharmacological characterization, we have identified a small molecular non-peptide inhibitor with selectivity for FPR1. We used the FPR1 and FPR2 specific ligands fMLF and WKYMVM, respectively, and an earlier described ratio technique, to determine inhibitory activity combined with selectivity. We show that the compound 3,5-dichloro-N-(2-chloro-5-methyl-phenyl)-2-hydroxy-benzamide (BVT173187) fulfills the criteria for an FPR1 inhibitor selective for FPR1 over FPR2, and it inhibits the same functional repertoire in neutrophils as earlier described peptide antagonists. Accordingly, the new inhibitor reduced neutrophil activation with FPR1 agonists, leading to mobilization of adhesion molecules (CR3) and the generation of superoxide anion from the neutrophil NADPH-oxidase. The effects of a number of structural analogs were determined but these were either without activity or less active/specific than BVT173187. The potency of the new inhibitor for reduction of FPR1 activity was the same as that of the earlier described FPR1 antagonist cyclosporine H, but signaling through the C5aR and CXCR (recognizing IL8) was also affected by BVT173187.     

Unified Sample Size Calculations Using the Competing Probability

Sample size formulas are functions of two categories of quantities. The first category does not depend on the analysis variables and contains randomization ratio, Type I error rate, and power. The second category depends on the analysis variables and includes means and standard deviations for the two-sample t-test, competing probabilities for the Wilcoxon–Mann–Whitney test, and median survival times for the logrank test. Quantities in the second category depend on subject matter knowledge and are much harder to specify than those in the first category. In addition, these quantities have different interpretations. In this article we propose using the competing probability as the only second category quantity when calculating sample sizes for the aforementioned three commonly used tests in clinical trials. Doing so unifies the interpretation of and sheds new light on the two-sample t-tests and the logrank tests in terms of sample size calculations.     

Benefits of combining the sexes when evaluating data from toxicological studies

In the assessment of the safety of a new drug, a large battery of toxicological studies is performed. In toxicological studies it is common practice to analyse the data from the sexes separately. We argue that this is not best practice and that much is to be gained from combining data from both sexes when evaluating studies. The main benefits and arguments in favour of combining the data are: (i) Improved efficiency, allowing fewer test animals and/or better precision. (ii) Other phases of drug development, clinical trials in particular, combine sexes. (iii) Most substances act similarly on both sexes and most drugs are prescribed without sex differentiation. (iv) If sex differences are of interest, combined data facilitates the quantification of the difference. (v) Reduced number of false positive and false negative findings. Although there might be some grounds to analysing the sexes separately, we argue that these are comparatively minor. We do not promote simply pooling the data and neglecting the existence of two sexes when comparing treatment groups. Rather, the analysis of combined data should allow for sex differences, for instance by using stratified procedures or by including a sex factor in a statistical model. We illustrate from real study data where the approach we propose has substantial benefits over traditional methods. A theoretical illustration is provided to quantify mathematically the potential gains and the corresponding sample size reduction, i.e. a reduction of animal use of ca. 50%, that would be possible without impairing the precision of studies.     

Margin of safety of pentylene glycol derived using measurements of cutaneous absorption and volatility

The safety assessment of pentylene glycol (PG) has been based on a bioavailability extrapolated from those of other 1,2-glycols or an assumed 100% absorption. To make a better safety assessment and an accurate calculation of the margin of safety (MoS), the skin penetration of PG present in a commercially available sunscreen was measured in pig skin at different exposure durations. The mass balance of PG decreased with increasing exposure durations, from 98% (1 h) to 29% (24 h) and the amount of PG detected in the skin wash decreased over time from 93% to 3%. The decrease in mass balance was attributed to an unexpected volatility of PG, which was confirmed in additional experiments. The maximum bioavailable amount of PG was 123 μg/cm2 after 24 h and was considered to be worst case scenario (10 mg/cm² i.e. 5-fold the recommended application standard dose, 2 mg/cm²). MoS values for the application of a standard dose of sunscreen after 1–24 h exposure were 140–671 in adults and, if calculated for children ratios, 87–217 Based on the available toxicological data for PG in comparison to the amounts determined to be potentially bioavailable, PG in the test sun protection product SPF 50 + does not show any safety concerns for daily usage at the recommended dosage of 2 mg/cm² or lower.     

Model based design and analysis of phase II HIV-1 trials

This work explores the advantages of a model based drug development (MBDD) approach for the design and analysis of antiretroviral phase II trials. Two different study settings were investigated: (1) a 5-arm placebo-controlled parallel group dose-finding/proof of concept (POC) study and (2) a comparison of investigational drug and competitor. Studies were simulated using a HIV-1 dynamics model in NONMEM. The Monte-Carlo Mapped Power method determined the sample size required for detecting a dose–response relationship and a significant difference in effect compared to the competitor using a MBDD approach. Stochastic simulation and re-estimation were used for evaluation of model parameter precision and bias given different sample sizes. Results were compared to those from an unpaired, two-sided t test and ANOVA (p ≤ 0.05). In all scenarios, the MBDD approach resulted in smaller study sizes and more precisely estimated treatment effect than conventional statistical analysis. Using a MBDD approach, a sample size of 15 patients could be used to show POC and estimate ED₅₀ with a good precision (relative standard error, 25.7 %). A sample size of 10 patients per arm was needed using the MBDD approach for detecting a difference in treatment effect of ≥20 % at 80 % power, a 3.4-fold reduction in sample size compared to a t test. The MBDD approach can be used to achieve more precise dose–response characterization facilitating decision making and dose selection. If necessitated, the sample size needed to reach a desired power can potentially be reduced compared to traditional statistical analyses. This may allow for comparison against competitors already in early clinical studies.     

A simple and flexible graphical approach for adaptive group-sequential clinical trials

In this article, we introduce a graphical approach to testing multiple hypotheses in group-sequential clinical trials allowing for midterm design modifications. It is intended for structured study objectives in adaptive clinical trials and extends the graphical group-sequential designs from Maurer and Bretz (Statistics in Biopharmaceutical Research 2013; 5: 311–320) to adaptive trial designs. The resulting test strategies can be visualized graphically and performed iteratively. We illustrate the methodology with two examples from our clinical trial practice. First, we consider a three-armed gold-standard trial with the option to reallocate patients to either the test drug or the active control group, while stopping the recruitment of patients to placebo, after having demonstrated superiority of the test drug over placebo at an interim analysis. Second, we consider a confirmatory two-stage adaptive design with treatment selection at interim.     

Noninferiority Testing Beyond Simple Two-Sample Comparison∗

In order to fulfill the requirement of a new drug application, a sponsor often need to conduct multiple clinical trials. Often these trials are of designs more complicated than a randomized two-sample single-factor study. For example, these trials could be designed with multiple centers, multiple factors, covariates, group sequential and/or adaptive scheme, etc. When an active standard treatment used as the control treatment in a two-arm clinical trial, the efficacy of the test treatment is often established by performing a noninferiority test through comparison of the test treatment and the active standard treatment. Typically, the noninferiority trials are designed with either a generalized historical control approach (i.e., noninferiority margin approach or δ-margin approach) or a cross-trial comparison approach (i.e., synthesis approach or λ-margin approach). Many of the statistical properties of the approaches discussed in the literature were focused on testing in a simple two sample comparison form. We studied the limitations of the two approaches for the consideration of switching between superiority and noninferiority testing, feasibility to be applied with group sequential design, constancy assumption requirements, test dependency in multiple trials, analysis of homogeneity of efficacy among centers in a multi-center trial, data transformation and changing analysis method from the historical studies. Our evaluation shows that the cross-trial comparison approach is more restricted to simple two sample comparison with normal approximation test because of its poor properties with more complicated design and analysis. On the other hand, the generalized historical control comparison approach may have more flexible properties when the variability of the margin δ is indeed negligibly small.     

Resistance to gemcitabine in a human follicular lymphoma cell line is due to partial deletion of the deoxycytidine kinase gene

Background

3-guanidinopropionic acid derivatives reduce body weight in obese, diabetic mice. We have assessed whether one of these analogues, the aminoguanidine carboxylate BVT.12777, opens K_ATP channels in rat insulinoma cells, by the same mechanism as leptin.

Results

BVT.12777 hyperpolarized CRI-G1 rat insulinoma cells by activation of K_ATP channels. In contrast, BVT.12777 did not activate heterologously expressed pancreatic β-cell K_ATP subunits directly. Although BVT.12777 stimulated phosphorylation of MAPK and STAT3, there was no effect on enzymes downstream of PI3K. Activation of K_ATP in CRI-G1 cells by BVT.12777 was not dependent on MAPK or PI3K activity. Confocal imaging showed that BVT.12777 induced a re-organization of cellular actin. Furthermore, the activation of K_ATP by BVT.12777 in CRI-G1 cells was demonstrated to be dependent on actin cytoskeletal dynamics, similar to that observed for leptin.

Conclusions

This study shows that BVT.12777, like leptin, activates K_ATP channels in insulinoma cells. Unlike leptin, BVT.12777 activates K_ATP channels in a PI3K-independent manner, but, like leptin, channel activation is dependent on actin cytoskeleton remodelling. Thus, BVT.12777 appears to act as a leptin mimetic, at least with respect to K_ATP channel activation, and may bypass up-stream signalling components of the leptin pathway.     

Characteristics of Adverse Events in Bee Venom Therapy Reported in South Korea: A Survey Study

This study was aimed at investigating Korean patients’ experience with bee venom therapy (BVT) and providing evidence to enhance BVT safety. Thus, an anonymous online survey was conducted between August 22 and 28, 2018. Five hundred respondents who underwent pharmacopuncture (PA) within one year were surveyed (sample error: 95 ± 4.38%). Of these, 32 respondents were excluded and 468 were evaluated. Of the 468, 61 reported experiencing adverse events after PA. The adverse event rate was higher in the BV-PA(Bee venom-Pharmacopuncture) group than in the non-A group; however, intergroup differences were insignificant. There were no significant differences in mild symptom intensity between the BV-PA and non-BV-PA groups (p = 0.572). However, there was a significant intergroup difference in severe symptom intensity (p < 0.001). Additionally, the BV-PA and non-BV-PA groups did not significantly differ in their level of satisfaction either overall or in terms of effectiveness and safety (p = 0.414, p = 0.339, and p = 0.675, respectively). Furthermore, the BV-PA and non-BV-PA groups did not differ regarding intent to re-treat (p = 0.722). Severe adverse events such as anaphylactic shock were not reported; however, BVT practitioners should be cautious when applying it.     

The Joint Modeling of Drug and Positive Control Effects to Estimate Sample Size and Power in Crossover “Thorough” QT/QTc Studies

We present analytical results for computing the power and sample size in a thorough QT/QTc study with a four-period crossover design in which the treatments are placebo, positive control, supratherapeutic dose of investigational drug, and therapeutic dose of investigational drug. An assessment of noninferiority of the supratherapeutic dose to placebo is performed by the intersection–union test and assay sensitivity is tested (union–intersection test) at prespecified time points using positive control within the framework of a linear mixed-effects analysis. The power and sample size estimates are obtained using the joint distribution of statistics to test noninferiority of the supratherapeutic dose to placebo and to test assay sensitivity using positive control.     

Analysis of homogeneity of treatment effect in adaptive multicenter clinical trials

In this paper, an exact test for analyzing the homogeneity of treatment effect in adaptive multicenter clinical trials is proposed. Extensive simulation studies are performed to investigate the large sample behavior of a commonly used test statistic for testing homogeneity of treatment effect. When the sample size in each center is large relative to the number of centers the asymptotic null distribution of the test statistic is reasonable. On the other hand when the data are relatively sparse the proposed exact test should be used to incorporate the adaptive nature of the design.     

Characterization of the cytochrome P450 enzymes and enzyme kinetic parameters for metabolism of BVT.2938 using different in vitro systems

An important step in the drug development process is identification of enzymes responsible for metabolism of drug candidates and determination of enzyme kinetic parameters. These data are used to increase understanding of the pharmacokinetics and possible metabolic-based drug interactions of drug candidates. The aim of the present study was to characterize the cytochrome P450 enzymes and enzyme kinetic parameters for metabolism of BVT.2938 [1-(3-{2-[(2-ethoxy-3-pyridinyl)oxy]ethoxy}-2-pyrazinyl)-2(R)-methylpiperazine], a potent and selective 5HT2c-receptor agonist. The enzyme kinetic parameters were determined for formation of three main metabolites of BVT.2938 using human liver microsomes and expressed cytochrome P450 (CYP) isoforms. The major metabolite was formed by hydroxylation of the pyridine ring (CL_int = 27 μl/mg min), and was catalysed by both CYP2D6*1 and CYP1A1, with K_m values corresponding to 1.4 and 2.7 μM, respectively. The results from enzyme kinetic studies were confirmed by incubation of BVT.2938 in the presence of the chemical inhibitor of CYP2D6*1, quinidine. Quinidine inhibited the formation of the major metabolite by approximately 90%. Additionally, studies with recombinant expressed CYP isoforms from rat indicated that formation of the major metabolite of BVT.2938 was catalysed by CYP2D2. This result was further confirmed by experiments with liver slices from different rat strains, where the formation of the metabolite correlated with phenotype of CYP2D2 isoform (Sprague–Dawley male, extensive; Dark Agouti male, intermediate; Dark Agouti female, poor metabolizer). The present study showed that the major metabolite of BVT.2938 is formed by hydroxylation of the pyridine ring and catalysed by CYP2D6*1. CYP1A1 is also involved in this reaction and its role in extra-hepatic metabolism of BVT.2938 might be significant.     

RU486 did not exacerbate cytokine release in mice challenged with LPS nor in db/db mice

Background

A substantial body of evidence indicates that reduced plasma adiponectin levels may be key in the development of insulin resistance, type 2 diabetes and the metabolic syndrome. Glucocorticoids decrease the levels of adiponectin in animals and humans. Cortisone is transformed to its active form cortisol, via 11β-hydroxysteroid dehydrogenase (HSD) type 1. This study sought to ascertain if inhibition of 11β HSD1 with a new selective inhibitor, BVT116429, affects the concentrations of circulating adiponectin with concomitant effects on glucose homeostasis in diabetic mice.

Results

KKA^y mice were treated with BVT116429 (3, 10, 30 mg/kg), rosiglitazone (5 mg/kg) or vehicle once daily for ten days. Plasma adiponectin levels rose in mice treated with BVT116429 and this was found to be both the hexameric and the high molecular weight multimeric forms of adiponectin. Seven days of treatment with the 11β HSD1-inhibitor BVT116429 decreased basal insulin levels but no changes in glucose tolerance were seen. After ten days of treatment, fasting blood glucose level was decreased by BVT116429 comparable to the effects of rosiglitazone. Another 11β HSD1 inhibitor, BVT2733, improved HbA1c but had no effect on adiponectin.

Conclusion

Inhibition of 11β HSD1 can be expected to be beneficial for treating the pathology of type 2 diabetes mellitus. The differences seen in adiponectin between BVT116429 and BVT2733 could be explained by different pharmacodynamics exerted by the compounds in different tissues in the body. Increases in adiponectin concentrations may be an integral component in the mechanism of action of this new11β HSD1 inhibitor and may be a useful marker of efficacy during the clinical development of 11β HSD1 inhibitor compounds.     

Inter-individual differences in novelty-seeking behavior in rats predict differential responses to desipramine in the forced swim test

RATIONALE: Antidepressant medications are effective only in a subpopulation of patients with depression, and some patients respond to certain drugs, but not others. The biological bases for these clinical observations remain unexplained. OBJECTIVE: To investigate individual differences in response to antidepressants, we have examined the effects of the norepinephrine reuptake inhibitor desipramine (DMI) and the selective serotonin reutake inhibitor fluoxetine (FLU) in the forced swim test (FST) in rats that differ in their emotional behavior. METHODS: As response to novelty correlates with numerous other measures of emotionality and substance abuse, we contrasted animals that are high responders (HR) in a novel environment with animals that are low responders (LR) and asked whether the two groups exhibit differential responses to DMI (10mg/kg) and FLU (20mg/kg). RESULTS: At the behavioral level, DMI caused a significant decrease in immobility in LR animals only, while FLU caused a significant reduction in immobility in both groups. Moreover, at the neural level, DMI treatment led to a decrease in FST-induced c-fos messenger RNA levels in medial prefrontal cortex (PFC) and paraventricular nucleus of the hypothalamus (PVN) in LR but not HR animals. CONCLUSIONS: Taken together, our results suggest that the HR-LR model is a useful tool to investigate individual differences in responses to norepinephrine reuptake inhibitors (NRIs) and that a differential activation of PFC and/or PVN could underlie some of the inter-individual differences in the efficacy of NRIs.     

Power Approximation for the Van Elteren Test Based on Location-Scale Family of Distributions

The van Elteren test, as a type of stratified Wilcoxon-Mann-Whitney test for comparing two treatments accounting for stratum effects, has been used to replace the analysis of variance when the normality assumption was seriously violated. The sample size estimation methods for the van Elteren test have been proposed and evaluated previously. However, in designing an active-comparator trial where a sample of responses from the new treatment is available but the patient response data to the comparator are limited to summary statistics, the existing methods are either inapplicable or poorly behaved. In this paper we develop a new method for active-comparator trials assuming the responses from both treatments are from the same location-scale family. Theories and simulations have shown that the new method performs well when the location-scale assumption holds and works reasonably when the assumption does not hold. Thus, the new method is preferred when computing sample sizes for the van Elteren test in active-comparator trials.