Randomized controlled trial is widely accepted as the best design for evaluating the efficacy of a new treatment because of the advantages of randomization (random allocation). Randomization eliminates accidental bias, including selection bias, and provides a base for allowing the use of probability theory. Despite its importance, randomization has not been properly understood. This article introduces the different randomization methods with examples: simple randomization; block randomization; adaptive randomization, including minimization; and response-adaptive randomization. Ethics related to randomization are also discussed. The study is helpful in understanding the basic concepts of randomization and how to use R software.

This article introduces a crossover design that is often used in clinical studies, with the advantage of comparing treatment effects within one study subject. In particular, the advantages and disadvantages of the two-period, two-sequence crossover design (2 × 2 or AB/BA crossover design), which is widely used in clinical practice, are identified, and the elements necessary for analysis are introduced. This article explains the carryover effect, period effect, sequence effect, and period-by-treatment interaction in a crossover design and examines the analysis commands of SAS along with example data. After confirming the carryover effect using a general linear model, the treatment effect is analyzed using a linear mixed effect model.

Mendelian randomization (MR) in epidemiology is the use of genetic variants as instrumental variables (IVs) in non-experimental design to make causality of a modifiable exposure on an outcome or disease. It assesses the causal effect between risk factor and a clinical outcome. The main reason to approach MR is to avoid the problem of residual confounding. There is no association between the genotype of early pregnancy and the disease, and the genotype of an individual cannot be changed. For this reason, it results with randomly assigned case-control studies can be set by regressing the measurements. IVs in MR are used genetic variants for estimating the causality. Usually an outcome is a disease and an exposure is risk factor, intermediate phenotype which may be a biomarker. The choice of the genetic variable as IV (Z) is essential to a successful in MR analysis. MR is named ‘Mendelian deconfounding’ as it gives to estimate of the causality free from biases due to confounding (C). To estimate unbiased estimation of the causality of the exposure (X) on the clinically relevant outcome (Y), Z has the 3 core assumptions (A1-A3). A1) Z is independent of C; A2) Z is associated with X; and A3) Z is independent of Y given X and C; The purpose of this review provides an overview of the MR analysis and is to explain that using an IV is proposed as an alternative statistical method to estimate causal effect of exposure and outcome under controlling for a confounder.

Kim YJ, et al. J Korean Med Sci. 2014 Dec;29(12):1706-1710. http://dx.doi.org/10.3346/jkms.2014.29.12.1706

The leaves ofArtemisia argyiLev. et Vant. andA. princepsPamp. are well known medicinal herbs used to treat patients in China, Japan, and Korea with skin problems such as eczema and itching, as well as abdominal pain and dysmenorrhoea. We investigated the anti-inflammatory effects ofArtemisialeaf extract (ALE) using CD mice and Raw 264.7 cells. The effects of ALE on histopathological changes and cytokine production in ear tissues were assessed in mice with CD induced by 1-fluoro-2,4-dinitrobenzene (DNFB). Moreover, the anti-inflammatory effects on production levels of prostaglandin E₂(PGE₂) and nitric oxide (NO) and expression levels of cyclooxygenase 2 (COX-2) and inducible nitric oxide synthase (iNOS) were investigated in Raw 264.7 cells. Topical application of ALE effectively prevented ear swelling induced by repeated DNFB application. ALE prevented epidermal hyperplasia and infiltration of immune cells and lowered the production of interferon- (IFN-) gamma (γ), tumour necrosis factor- (TNF-) alpha (α), and interleukin- (IL-) 6 in inflamed tissues. In addition, ALE inhibited expression of COX-2 and iNOS and production of NO and PGE₂in Raw 264.7 cells. These results indicate thatArtemisialeaf can be used as a therapeutic agent for inflammatory skin diseases and that its anti-inflammatory effects are closely related to the inhibition of inflammatory mediator release from macrophages and inflammatory cytokine production in inflamed tissues.

The aim of this paper is to introduce basic concepts and methods for calculating sample size in animal studies. At the planning stage of clinical studies, the determination of the sample size is a very important process to show the validity, accuracy, and reliability of the study. However, not all studies require a sample size to be calculated. Before conducting the study, it is essential to determine whether the study objectives suggest a pilot and exploratory study, as well as the purpose of testing the hypothesis of interest. Since most animal experiments are pilot and exploratory studies, it would be more appropriate to review other considerations for conducting an experiment while maintaining scientific and qualitative levels rather than sample size estimation. Sample size is calculated in various situations in animal studies. Therefore, it can be estimated according to the situations and objectives through the methods of precision analysis, power analysis, and so on. In some cases, nonparametric methods can be employed if the assumptions of normality is not met or a small sample is available for the study.