Two-stage designs for dose-finding trials with a biologic endpoint using stepwise tests

Summary.   We deal with the design problem of early phase dose-finding clinical trials with monotone biologic endpoints, such as biological measurements, laboratory values of serum level, and gene expression. A specific objective of this type of trial is to identify the minimum dose that exhibits adequate drug activity and shifts the mean of the endpoint from a zero dose to the so-called minimum effective dose. Stepwise test procedures for dose finding have been well studied in the context of nonhuman studies where the sampling plan is done in one stage. In this article, we extend the notion of stepwise testing to a two-stage enrollment plan in an attempt to reduce the potential sample size requirement by shutting down unpromising doses in a futility interim. In particular, we examine four two-stage designs and apply them to design a statin trial with four doses and a placebo in patients with Hodgkin's disease. We discuss the calibration of the design parameters and the implementation of these proposed methods. In the context of the statin trial, a calibrated two-stage design can reduce the average total sample size up to 38% (from 125 to 78) from a one-stage step-down test, while maintaining comparable error rates and probability of correct selection. The price for the reduction in the average sample size is the slight increase in the maximum total sample size from 125 to 130.     

Adjustment for exploratory cut-off selection in randomized clinical trials with survival endpoint

Defining the target population based on predictive biomarkers plays an important role during clinical development. After establishing a relationship between a biomarker candidate and response to treatment in exploratory phases, a subsequent confirmatory trial ideally involves only subjects with high potential of benefiting from the new compound. In order to identify those subjects in case of a continuous biomarker, a cut-off is needed. Usually, a cut-off is chosen that resulted in a subgroup with a large observed treatment effect in an exploratory trial. However, such a data-driven selection may lead to overoptimistic expectations for the subsequent confirmatory trial. Treatment effect estimates, probability of success, and posterior probabilities are useful measures for deciding whether or not to conduct a confirmatory trial enrolling the biomarker-defined population. These measures need to be adjusted for selection bias. We extend previously introduced Approximate Bayesian Computation techniques for adjustment of subgroup selection bias to a time-to-event setting with cut-off selection. Challenges in this setting are that treatment effects become time-dependent and that subsets are defined by the biomarker distribution. Simulation studies show that the proposed method provides adjusted statistical measures which are superior to naïve Maximum Likelihood estimators as well as simple shrinkage estimators.     

On the need for a control line in selection experiments: A likelihood analysis

The question of whether selection experiments ought to include a control line, as opposed to investing all facilities in a single selected line, is addressed using a likelihood perspective. The consequences of using a control line are evaluated under two scenarios. In the first one, environmental trend is modeled and inferred from the data. In this case, a control line is shown to be highly beneficial in terms of the efficiency of inferences about eheritability and response to selection. In the second scenario, environmental trend is not modeled. One can imagine that a previous analysis of the experimental data had lent support to this decision. It is shown that in this situation where a control line may seem superfluous, inclusion of a control line can result in minor gains in efficiency if a high selection intensity is practiced in the selected line. Further, if there is a loss, it is moderately small. The results are verified to hold under more complicated data structures via Monte Carlo simulation. For completeness, divergent selection designs are also reviewed, and inferences based on a conditional and full likelihood approach are contrasted.     

A comparison of methods for estimating the causal effect of a treatment in randomized clinical trials subject to noncompliance

Summary .  We consider the analysis of clinical trials that involve randomization to an active treatment ( T  = 1) or a control treatment ( T  = 0), when the active treatment is subject to all-or-nothing compliance. We compare three approaches to estimating treatment efficacy in this situation: as-treated analysis, per-protocol analysis, and instrumental variable (IV) estimation, where the treatment effect is estimated using the randomization indicator as an IV. Both model- and method-of-moment based IV estimators are considered. The assumptions underlying these estimators are assessed, standard errors and mean squared errors of the estimates are compared, and design implications of the three methods are examined. Extensions of the methods to include observed covariates are then discussed, emphasizing the role of compliance propensity methods and the contrasting role of covariates in these extensions. Methods are illustrated on data from the Women Take Pride study, an assessment of behavioral treatments for women with heart disease.     

A mixed approach for proving non-inferiority in clinical trials with binary endpoints

When a new treatment is compared to an established one in a randomized clinical trial, it is standard practice to statistically test for non-inferiority rather than for superiority. When the endpoint is binary, one usually compares two treatments using either an odds-ratio or a difference of proportions. In this paper, we propose a mixed approach which uses both concepts. One first defines the non-inferiority margin using an odds-ratio and one ultimately proves non-inferiority statistically using a difference of proportions. The mixed approach is shown to be more powerful than the conventional odds-ratio approach when the efficacy of the established treatment is known (with good precision) and high (e.g. with more than 56% of success). The gain of power achieved may lead in turn to a substantial reduction in the sample size needed to prove non-inferiority. The mixed approach can be generalized to ordinal endpoints.     

A versatile selection system for folding competent proteins using genetic complementation in a eukaryotic host

Recombinant expression of native or modified eukaryotic proteins is pivotal for structural and functional studies and for industrial and pharmaceutical production of proteins. However, it is often impeded by the lack of proper folding. Here, we present a stringent and broadly applicable eukaryotic in vivo selection system for folded proteins. It is based on genetic complementation of the Schizosaccharomyces pombe growth marker gene invertase fused C‐terminally to a protein library. The fusion proteins are directed to the secretion system, utilizing the ability of the eukaryotic protein quality‐control systems to retain misfolded proteins in the ER and redirect them for cytosolic degradation, thereby only allowing folded proteins to reach the cell surface. Accordingly, the folding potential of the tested protein determines the ability of autotrophic colony growth. This system was successfully demonstrated using a complex insertion mutant library of TNF‐α, from which different folding competent mutant proteins were uncovered.     

Mass treatment with ivermectin for filariasis control in Papua New Guinea: impact on mosquito survival

Field studies were carried out to determine the impact of mass human treatment with ivermectin on the survival of anthropophagic mosquitoes of the Anopheles punctulatus complex (Diptera: Culicidae), the vectors of lymphatic filariasis and malaria in Papua New Guinea. In a village where mass treatment had been given, using 400 microg/kg ivermectin plus 6 mg/kg diethylcarbamazine citrate (DEC), we performed pre- and post-treatment collections of freshly blood-engorged mosquitoes from the same nine bedrooms. All blood-fed mosquitoes collected less than 4 days after mass treatment died within 9 days, whereas 67% of those collected before treatment survived for >9 days. Comparison (using the log-rank test) of the survival curves for mosquitoes collected (i) before treatment, (ii)<4 days after treatment, and (iii) 28 days after treatment, showed the survival rate of group (ii) to be significantly lower than the other two (chi2=176, df=2, P<0.0001). Pre- and post-treatment all-night landing catches showed no reduction in human biting rates in the experimental village. In another village, where people were mass treated with ivermectin (400 microg/kg) only, the survival rates of freshly blood-engorged An. punctulatus collected from bedroom resting-sites less than 1 day after treatment, were compared to similar collections carried out at the same time in a nearby village where people were not treated with ivermectin. The 48-h survival rate for the ivermectin-treated village was 31% compared to 94% for the other; this difference was highly significant (chi2=32.42, df=1, P<0.0001). Mosquitoes fed 2 months post-treatment with DEC or collected 38 days post-treatment with ivermectin had normal survival rates. We conclude that the duration of the systemic lethal effect of ivermectin on mosquitoes is insufficient to be of epidemiological significance in filariasis control programmes that are based on biannual and annual single-dose treatments, but might reduce vectorial capacity sufficiently to block epidemics of dengue or even malaria.     

Two criteria for the comparison of multiple arrangements of experiments and their use to answer the question: Is it better to compare p treatment groups with p controls or with a single control

In experimental situations examining the effectiveness of p(p>1) treatments by comparing treated groups and untreated controls the following question arose: Which experimental arrangement is more appropriate, an arrangement A₁ using for the p comparisons only one single control, or an arrangement A₂ using for every comparison another control. To answer this question two criteria are formulated. The first criterion takes into consideration the expected numbers of type I and type II errors, and the second criterion the probabilities of type I and of type II errors. According to the first criterion A₁ and A₂ do not differ, generally. According to the second criterion A₁ with the comparison of means of normal distributed variables is better than A₂. Pooling of all p controls is better than A₂ according to both criteria. A₁ is better also according to the often used experimentwise type I error rate. The formulated criteria have some analogy to those of MILLER (1966). It may be possible to use them not only for comparing experimental arrangements but also tests.     

Poloxamer-chitosan-based Naringenin nanoformulation used in brain targeting for the treatment of cerebral ischemia

ObjectiveHere, the aim is to improve the bioavailability of Naringenin (NRG) in brain and to establish the highest remedial benefit from a novel anti-ischemic medicine i.e. NRG.MethodsA novel Naringenin-loaded-nanoemulsion (NE)-(in situ)-gel (i.e. thermoresponsive), was formulated with the help of Poloxamer-407 (20.0% w/v). Chitosan (CS, 0.50% w/v) was used to introduce the mucoadhesive property of NE-(in situ)-gel and finally called as NRG-NE-gel + 0.50%CS. A novel UHPLC-ESI-Q-TOF-MS/MS-method was optimized and used for NRG-NE-gel + 0.50%CS to quantify the Pharmacokinetic-(PK)-parameters in plasma as well as brain and to evaluate the cerebral ischemic parameters after MCAO i.e. locomotor activity, grip strength, antioxidant activity, and quantity the infarction volume in neurons with the safety/toxicity of NRG-NE-gel + 0.50%CS after i.n. administration in the rats.ResultsThe mucoadhesive potency and gelling temperature of NRG-NE-gel + 0.50%CS were observed 6245.38 dynes/cm² and 28.3 ± 1.0 °C, respectively. Poloxamer-407 based free micelles size was observed 98.31 ± 1.17 nm with PDI (0.386 ± 0.021). The pH and viscosity of NRG-NE-gel + 0.50%CS were found to be 6.0 ± 0.20 and 2447 ± 24cp (at 35.0 ± 1.0 °C temperature), respectively. An elution time and m/z NRG were observed 1.78 min and 270.97/150.96 with 1.22 min and m/z of 301.01/150.98 for Quercetin (IS) respectively. Inter and intra %precision and %accuracy was validated 1.01–3.37% and 95.10–99.30% with a linear dynamic range (1.00 to 2000.00 ng/ml). AUC_0-24 of plasma & brain were observed 995.60 ± 24.59 and 5600.99 ± 144.92 (ng min/ml g) in the rats after the intranasal (i.n.) administration of NRG-NE-gel + 0.50%CS. No toxicological response were not found in terms of mortalities, any-change morphologically i.e. in the microstructure of brain as well as nasal mucosa tissues, and also not found any visual signs in terms of inflammatory or necrosis.ConclusionIntranasally administered NRG-NE-gel + 0.50%CS enhanced the bioavailability of Naringenin in the brain. In the cerebral ischemic rats, significantly improved the neurobehavioral activity (locomotor & grip strength) followed by antioxidant activity as well as infarction volume. Finally, the toxicity studies carried out and established the safe nature of optimized-NRG-NE-gel + 0.50%CS.