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Design, analysis and reporting of tumor models

Lab Animal volume 46, pages 207–211 (2017)Cite this article

To the editor:

Statistical design and data analysis play a key role in ensuring scientific integrity and contributing to ethical standards and the 3Rs (refinement, reduction, replacement). Within AstraZeneca we have implemented a systematic approach for reviewing animal study protocols against a number of key statistical principles that include: animal numbers, blocking, randomization, controls and monitoring. This has led to a reduction in overall animal use through improved study design, and furthermore has improved confidence in scientific conclusions. We offer some user-friendly procedures for visualizing, analyzing, powering and monitoring xenograft studies as well as statistical methods to be used in study planning to ensure scientific robustness and ethical justification.

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Figure 1
Figure 2: Different plots of tumor data.
Figure 3: Consider situations where there is one control group compared to ten treatment groups.
Figure 4: This is an example of output from the randomization tool.
Figure 5: The variance (standard deviation squared) has been calculated from 38 different control groups for a particular tumor line.

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Authors and Affiliations

  1. Discovery Sciences Statistics, AstraZeneca Pharmaceuticals, Macclesfield, Cheshire, United Kingdom

    Robert Shaw

  2. Oncology Bioscience, AstraZeneca Pharmaceuticals, Cheshire, United Kingdom

    Sharon Miller & Jon Curwen

  3. Discovery Sciences Statistics, AstraZeneca Pharmaceuticals, Cheshire, United Kingdom

    Mike Dymond

Authors
  1. Robert Shaw
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  2. Sharon Miller
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  3. Jon Curwen
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  4. Mike Dymond
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Correspondence to Robert Shaw.

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Shaw, R., Miller, S., Curwen, J. et al. Design, analysis and reporting of tumor models. Lab Anim 46, 207–211 (2017). https://doi.org/10.1038/laban.1257

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