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A quantitative analysis of statistical power identifies obesity end points for improved in vivo preclinical study design.

ABSTRACT: The design of well-powered in vivo preclinical studies is a key element in building the knowledge of disease physiology for the purpose of identifying and effectively testing potential antiobesity drug targets. However, as a result of the complexity of the obese phenotype, there is limited understanding of the variability within and between study animals of macroscopic end points such as food intake and body composition. This, combined with limitations inherent in the measurement of certain end points, presents challenges to study design that can have significant consequences for an antiobesity program. Here, we analyze a large, longitudinal study of mouse food intake and body composition during diet perturbation to quantify the variability and interaction of the key metabolic end points. To demonstrate how conclusions can change as a function of study size, we show that a simulated preclinical study properly powered for one end point may lead to false conclusions based on secondary end points. We then propose the guidelines for end point selection and study size estimation under different conditions to facilitate proper power calculation for a more successful in vivo study design.

SUBMITTER: Selimkhanov J

PROVIDER: S-EPMC5568066 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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A quantitative analysis of statistical power identifies obesity end points for improved in vivo preclinical study design.

Selimkhanov J J Thompson W C WC Guo J J Hall K D KD Musante C J CJ

International journal of obesity (2005) 20170410 8

The design of well-powered in vivo preclinical studies is a key element in building the knowledge of disease physiology for the purpose of identifying and effectively testing potential antiobesity drug targets. However, as a result of the complexity of the obese phenotype, there is limited understanding of the variability within and between study animals of macroscopic end points such as food intake and body composition. This, combined with limitations inherent in the measurement of certain end ...[more]

PMID: 28392555

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Project description:For nearly five decades long-term studies in rodents have been the accepted benchmark for assessing chronic long-term toxic effects, particularly carcinogenicity, of chemicals. The European Food Safety Authority (EFSA) and the World Health Organization (WHO) have pointed out that the current set of internationally utilized test methods capture only some of the potential adverse effects associated with exposures to these agents over the lifetime.In this paper, we propose the adaption of the carcinogenicity bioassay to integrate additional protocols for comprehensive long-term toxicity assessment that includes developmental exposures and long-term outcomes, capable of generating information on a broad spectrum of different end points.An integrated study design based on a stepwise process is described that includes the priority end points of the Economic Co-operation and Development and the National Toxicology Program guidelines on carcinogenicity and chronic toxicity and developmental and reproductive toxicity. Integrating a comprehensive set of relevant toxicological end points in a single protocol represents an opportunity to optimize animal use in accordance with the 3Rs (replacement, reduction and refinement). This strategy has the potential to provide sufficient data on multiple windows of susceptibility of specific interest for risk assessments and public health decision-making by including prenatal, lactational, neonatal exposures and evaluating outcomes over the lifespan.This integrated study design is efficient in that the same generational cohort of rats used for evaluating long-term outcomes can be monitored in satellite parallel experiments to measure biomarkers and other parameters related to system-specific responses including metabolic alterations and endocrine disturbances. Citation: Manservisi F, Babot Marquillas C, Buscaroli A, Huff J, Lauriola M, Mandrioli D, Manservigi M, Panzacchi S, Silbergeld EK, Belpoggi F. 2017. An integrated experimental design for the assessment of multiple toxicological end points in rat bioassays. Environ Health Perspect 125:289-295;?http://dx.doi.org/10.1289/EHP419.

Dataset Information

A quantitative analysis of statistical power identifies obesity end points for improved in vivo preclinical study design.

Publications

A quantitative analysis of statistical power identifies obesity end points for improved in vivo preclinical study design.

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