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Benefits of a factorial design focusing on inclusion of female and male animals in one experiment

  • Thorsten BuchEmail author
  • Katharina Moos
  • Filipa M. Ferreira
  • Holger Fröhlich
  • Catherine Gebhard
  • Achim TreschEmail author
Original Article

Abstract

Disease occurrence, clinical manifestations, and outcomes differ between men and women. Yet, women and men are most of the time treated similarly, which is often based on experimental data over-representing one sex. Accounting for persisting sex bias in biomedical research is the misconception that the analysis of sex-specific effects would double sample size and costs. We designed an analysis to test the potential benefits of a factorial study design in the context of a study including male and female animals. We chose a 2 × 2 factorial design approach to study the effect of treatment, sex, and an interaction term of treatment and sex in a hypothetical situation. We calculated the sample sizes required to detect an effect of a given magnitude with sufficient power and under different experimental setups. We demonstrated that the inclusion of both sexes in experimental setups, without testing for sex effects, requires no or few additional animals in our scenarios. These experimental designs still allow for the exploration of sex effects at low cost. In a confirmatory instead of an exploratory design, we observed an increase in total sample sizes by 33%, at most. Since the complexities associated with this mathematical model require statistical expertise, we generated and provide a sample size calculator for planning factorial design experiments. For the inclusion of sex, a factorial design is advisable, and a sex-specific analysis can be performed without excessive additional effort. Our easy-to-use calculation tool provides help in designing studies with both sexes and addresses the current sex bias in preclinical studies.

Key messages

• Both sexes should be included into animal studies.

• Exploratory study of sex effects can be conducted with no or small increase in animal number.

• Confirmatory analysis of sex effects requires maximum 33% more animals per study.

• Our calculation tool supports the design of studies with both sexes.

Keywords

Sex Animal experimentation Factorial design Power 

Notes

Author contribution

Conceptualization and supervision were performed by TB and AT. Methodology and formal analysis were performed KM. Verification was performed by HF. Visualization was performed by FMF and KM. The original draft was written by TB, FMF, CG, KM, and AT. The manuscript was reviewed and edited by TB, FMF, HF, CG, KM, and AT.

Funding

TB was supported by the Hertie Foundation and the Swiss Multiple Sclerosis Society. CG was supported by grants from the Swiss National Science Foundation, the Olga Mayenfisch Foundation, Switzerland, the OPO Foundation, Switzerland, the Novartis Foundation, Switzerland, the Swissheart Foundation, and the Helmut Horten Foundation, Switzerland. KM was supported by the German Research Foundation (DFG).

Supplementary material

109_2019_1774_MOESM1_ESM.xlsx (2.8 mb)
ESM 1 (XLSX 2.77 mb)
109_2019_1774_MOESM2_ESM.docx (21 kb)
ESM 2 (DOCX 21 kb)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Institute of Laboratory Animal ScienceUniversity of ZurichZurichSwitzerland
  2. 2.Institute of Medical Statistics and Computational Biology, Faculty of MedicineUniversity of CologneCologneGermany
  3. 3.Center for Data and Simulation Science (CDS)University of CologneCologneGermany
  4. 4.Bonn-Aachen International Center for IT (b-it)University of BonnBonnGermany
  5. 5.Center for Molecular CardiologyUniversity of ZurichZurichSwitzerland

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