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Biomedical subjects

Dieter Hauschke

Publications and source records attributed to Dieter Hauschke.

9 recordsLinked to original sources
PubMed2006

Investigation of a potential food effect on the pharmacokinetics of roflumilast, an oral, once-daily phosphodiesterase 4 inhibitor, in healthy subjects.

This open, randomized, single-dose crossover study investigated effects of a high-fat meal on the pharmacokinetics of roflumilast and its major active N-oxide metabolite. Twelve healthy subjects received oral roflumilast 500 microg (2 x 250 microg) after overnight fasting and after breakfast. Blood was sampled up to 54 hours for pharmacokinetic profiling of roflumilast and N-oxide. Geometric mean ratios (fed/fasted) for point estimates (PE) and 90% confidence intervals (CI) were calculated for AUC(0-last), AUC(0-infinity), and C(max) of both compounds. After the meal, roflumilast C(max) (PE, 0.59; 90% CI, 0.49-0.70) was modestly reduced; N-oxide C(max) (PE, 0.95; 90% CI, 0.90-1.01) was unchanged. Roflumilast t(max) was delayed in fed state (2.0 +/- 0.4 hours) versus fasted state (1.0 +/- 0.2 hours); N-oxide t(max) was unaltered. No significant food effect on roflumilast AUC(0-last) (PE, 1.04; 90% CI, 0.90-1.21), AUC(0-infinity) (PE, 1.12; 90% CI, 1.00-1.25), and respective N-oxide AUCs (PE, 0.91; 90% CI, 0.79-1.04; PE, 0.99; 90% CI, 0.92-1.06) occurred. Because roflumilast N-oxide is the major contributor to roflumilast's overall pharmacologic effects, these findings suggest that roflumilast can be taken with or without food.

3',5'-Cyclic-AMP Phosphodiesterases↗
PubMed2005

Biostatistical assessment of mutagenicity studies by including the positive control.

Statistical analysis plays a fundamental part in the evaluation of mutagenicity experiments. However, a statistically significant or non-significant test result without incorporating the biological relevance cannot be a valid scientific criterion for concluding a positive or negative effect of the underlying compound (Hauschke et al., 1997). The classification of an experiment as being negative or positive should be based also on the magnitude of the responses in the positive control. We address the problem of determining the maximum safe dose by incorporating a biologically meaningful threshold value, which is expressed as a fraction of the difference between positive and vehicle control.

Biometry↗
PubMed2005

Establishing efficacy of a new experimental treatment in the 'gold standard' design.

Provided that there are no ethical concerns, the comparison of an active drug with placebo in a randomized two-arm clinical trial provides the most convincing way to demonstrate the efficacy of a new experimental treatment. However, in a placebo-controlled clinical trial it is not sufficient to demonstrate merely a statistically significant treatment difference. Regulatory authorities strongly recommend to assess additionally whether the observed treatment difference is also of clinical relevance. The inherent issue is the necessity of the a priori definition of what constitutes a clinically relevant difference in efficacy. This problem can be solved in a three-arm study by including an active control group. We address the necessary conditions in the gold standard design which allow the claim of efficacy for the new treatment with particular focus on assay sensitivity.

Algorithms↗
PubMed2003

Assessing non-inferiority of a new treatment in a three-arm clinical trial including a placebo.

In non-inferiority trials, where non-inferiority of a new experimental drug compared to an active control has to be shown, it may be advisable to use an additional placebo group for internal validation if ethically justifiable. The focus of this paper is on such designs. Assuming normality and homogeneity of variances we will derive a statistical test procedure which turns out to be equivalent to the assessment based on Fieller's confidence interval. Based on the power function of this test, sample size calculations are carried out to achieve a given power. Additionally, the optimal allocation of the total sample size is derived. As an alternative to this parametric procedure, the bootstrap percentile interval is discussed and finally compared with Fieller's confidence interval in a study on mildly asthmatic patients.

Anti-Asthmatic Agents↗
PubMed2003

The role of control groups in mutagenicity studies: matching biological and statistical relevance.

The statistical test of the conventional hypothesis of "no treatment effect" is commonly used in the evaluation of mutagenicity experiments. Failing to reject the hypothesis often leads to the conclusion in favour of safety. The major drawback of this indirect approach is that what is controlled by a prespecified level alpha is the probability of erroneously concluding hazard (producer risk). However, the primary concern of safety assessment is the control of the consumer risk, i.e. limiting the probability of erroneously concluding that a product is safe. In order to restrict this risk, safety has to be formulated as the alternative, and hazard, i.e. the opposite, has to be formulated as the hypothesis. The direct safety approach is examined for the case when the corresponding threshold value is expressed either as a fraction of the population mean for the negative control, or as a fraction of the difference between the positive and negative controls.

Animal Testing Alternatives↗
PubMed2003

Two-stage testing of safety: a statistical view.

Sample sizes given in regulatory guidelines are not based on statistical reasoning. However, from an ethical, scientific, and regulatory point of view, a mutagenicity experiment must have a reasonable chance of supporting the decision as to whether a result is negative or positive. Consequently, the sample size should be based on type I and type II errors, the underlying variability, and the specific size of a treatment effect. A two-stage adaptive interim analysis is presented, which permits an adaptive choice of sample size after an interim analysis of the data from the first stage. Because the sample size of the first stage is considered to be a minimum requirement, this stage can also be regarded as a pilot study.

Animal Testing Alternatives↗
PubMed2002

A note on sample size calculation in bioequivalence trials.

Based on fundamental pharmacokinetic relationships, a multiplicative model is commonly used in bioequivalence trials. With regard to the parametric analysis, this implies the assumption of a lognormal distribution. Statistical methods for sample size calculation has been consolidated over the last years. Recently, methods for sample size calculation in the additive model, i.e., under normality assumption, were presented. Hence, these methods are reviewed from a statistical and regulatory point of view.

Models, Biological↗