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Olivia Hogue dissertation 4.3.2022.pdf (1.2 MB)

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Statistical practice in preclinical neurosciences: Implications for successful translation of research evidence from humans to animals

Hogue, Olivia
http://rave.ohiolink.edu/etdc/view?acc_num=case1649159087978041

Abstract Details

2022, Doctor of Philosophy, Case Western Reserve University, Clinical Translational Science.
The translation of medical therapies from basic and preclinical research to efficacious human interventions is challenging. The majority of candidate therapies fail in early-stage human trials, after showing promise in preclinical work. The primary aim of the research presented herein is to explore the potential role that poor statistical practice in preclinical animal trials might play in contributing to translational failure. First, a comprehensive appraisal of current statistical practice in one area of preclinical neuroscience research was carried out. A close review of the current related literature is presented, and the appraisal includes a tutorial to explain how certain statistical mistakes might result in overly optimistic results, as well as practical recommendations for improvement. A majority of articles included in this appraisal failed to account for sources of non-independence in the data (74-93%) and/or did not analytically account for mid-treatment animal attrition (78%). Ordinal variables were often treated as continuous (37%), outliers were predominantly not mentioned (83%), and plots often concealed the distribution of the data (51%). Next, a sample including both successful and failed human trials for neurologic targets was identified, and rates of statistical mistakes in the associated preceding rodent trials were compared. Failed human trials were found to have higher rates of select sources of potential statistical bias in preceding rodent trials, compared to successful trials. This research provides evidence that a contributing factor to translational failure is statistical misapplication in preclinical animal research in the neurosciences. It provides the groundwork for future research that will provide practical solutions to translational researchers and funders, facilitating preclinical experimental validity to increase the translational success rate.
Mary Dolansky, PhD RN FAAN (Committee Chair)
Kenneth Baker, PhD (Committee Member)
Nancy Obuchowski, PhD (Committee Member)
Jill Barnholtz-Sloan, PhD (Advisor)
Animal Sciences; Biostatistics; Neurosciences; Statistics
biostatistics; applied statistics; translational science; neurosciences; animal research; translation; statistical practice; transparent reporting; clinical trials; clinical trial success; neurodegeneration; neurologic disease; meta-research; meta-science

Recommended Citations

Citations

  • Hogue, O. (2022). Statistical practice in preclinical neurosciences: Implications for successful translation of research evidence from humans to animals [Doctoral dissertation, Case Western Reserve University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=case1649159087978041

    APA Style (7th edition)

  • Hogue, Olivia. Statistical practice in preclinical neurosciences: Implications for successful translation of research evidence from humans to animals. 2022. Case Western Reserve University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=case1649159087978041.

    MLA Style (8th edition)

  • Hogue, Olivia. "Statistical practice in preclinical neurosciences: Implications for successful translation of research evidence from humans to animals." Doctoral dissertation, Case Western Reserve University, 2022. http://rave.ohiolink.edu/etdc/view?acc_num=case1649159087978041

    Chicago Manual of Style (17th edition)

case1649159087978041
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© 2022, all rights reserved.
This open access ETD is published by Case Western Reserve University School of Graduate Studies and OhioLINK.