1. Factors Associated With Missing Biological Samples in the Dog Ageing Project.
- Author
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Holland, Sydney N., Tinkle, Amanda K., Prescott, Jena N., Blattman, Brianna L., McClelland, Robyn L., Nam, Yunbi, Creevy, Kate E., and Fajt, Virginia R.
- Subjects
MONONUCLEAR leukocytes ,MISSING data (Statistics) ,BLOOD collection ,STATISTICAL power analysis ,FLOW cytometry - Abstract
Background: The Dog Aging Project (DAP) is a longitudinal study examining aging in US companion dogs, where missing data pose a challenge to result validity and statistical power. Early recognition and procedural adjustments are vital to address missing samples. Objectives: This research assesses missing biospecimen samples within the PRECISION cohort of the DAP, aiming to identify contributing factors and propose mitigation strategies. Methods: Ninety sample kits collected between August 2021 and October 2021 were evaluated for the missingness of individual kit components. A primary assessment reviewed the missingness of each sample type with hypothesized associated factors. A secondary assessment addressed the missingness of plasma and serum aliquots made after check‐in. Results: EDTA samples for flow cytometry, peripheral blood mononuclear cells (PBMCs), DNA and biobanking were missing at rates of 18.9%, 13.3%, 6.7% and 5.6%, respectively. Faecal samples were missing at 5.6%. Urine and plasma were each missing at 2.2%. Serum, hair and dried blood spot cards were each missing at 1.1%. No statistically significant difference in missingness was seen across regions, ease of blood collection, or cooperativeness of dog during sample collection. Higher time‐to‐receipt was associated with a higher missingness proportion. Increasing missingness proportions were seen across plasma and serum aliquots that were created in sequential order. Conclusion: The study suggests reevaluating sample collection instructions to address frequently missing sample types and prevent further loss. Investigation into collection procedures for these types is recommended to identify potential causes of sample yield loss. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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