4.6 Review

Statistical evaluation and experimental design of a psoriasis xenograft transplantation model treated with cyclosporin A

Journal

EXPERIMENTAL DERMATOLOGY
Volume 20, Issue 5, Pages 441-444

Publisher

WILEY-BLACKWELL
DOI: 10.1111/j.1600-0625.2011.01251.x

Keywords

ANOVA; psoriasis; study power; xenograft mouse model

Categories

Funding

  1. Aage Bangs Foundation
  2. Danish Psoriasis Foundation

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Psoriasis xenograft transplantation models where human skin is transplanted onto immune-deficient mice are generally accepted in psoriasis research. Over the last decade, they have been widely employed to screen for new therapeutics with a potential anti-psoriatic effect. However, experimental designs differ in several parameters. Especially, the number of donors and grafts per experimental design varies greatly; numbers that are directly related to the probability of detecting statistically significant drug effects. In this study, we performed a statistical evaluation of the effect of cyclosporine A, a recognized anti-psoriatic drug, to generate a statistical model employable to simulate different scenarios of experimental designs and to calculate the associated statistical study power, defined as the probability of detecting a statistically significant anti-psoriatic drug treatment effect. Results showed that to achieve a study power of 0.8, at least 20 grafts per treatment group and a minimum of five donors should be included in the chosen experimental setting. To our knowledge, this is the first time that study power calculations have been performed to evaluate treatment effects in a psoriasis xenograft transplantation model. This study was based on a defined experimental protocol, thus other parameters such as drug potency, treatment protocol, mouse strain and graft size should, also, be taken into account when designing an experiment. We propose that the results obtained in this study may lend a more quantitative support to the validity of results obtained when exploring new potential anti-psoriatic drug effects.

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