The Biostatistics/Epidemiology Core will be responsible for all statistical, data management, and epidemiological aspects of the Mayo Clinic Urology O'Brien Center research grant. It is expected to serve all major projects as well as pilot projects and will be staffed by members of the Divisions of Biomedical Statistics and Informatics and Epidemiology who have expertise in statistical analysis, data management, and study design. Further, the Core investigators have extensive experience in the applications of quantitative methods to urologic and kidney problems, including nephrolithiasis. The objectives of the Core are to 1) provide high quality consultation to project investigators regarding study design, data analysis and interpretation of results, 2) maintain and extend the existing Olmsted County kidney stone database, 3) develop additional high quality linkable databases and quality control procedures for O'Brien Center research grant studies , and 4) foster and develop junior faculty in the statistical and epidemiological approach to clinical questions in nephrolithiasis.

Public Health Relevance

The existence of the Biostatistics/Epidemiology Core will provide the O'Brien Center research grants with uniform and efficient plans for protocol design, data management, quality control, and statistical analysis. Further, Core investigators will have a broad view of the O'Brien Center research grant, which will allow them to identify potential new interdisciplinary hypotheses and projects.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
1U54DK100227-01
Application #
8626074
Study Section
Special Emphasis Panel (ZDK1-GRB-9 (M2))
Project Start
Project End
Budget Start
2013-09-29
Budget End
2014-06-30
Support Year
1
Fiscal Year
2013
Total Cost
$208,777
Indirect Cost
$77,471
Name
Mayo Clinic, Rochester
Department
Type
DUNS #
006471700
City
Rochester
State
MN
Country
United States
Zip Code
55905
Ferrero, A; Gutjahr, R; Henning, A et al. (2017) Renal Stone Characterization using High Resolution Imaging Mode on a Photon Counting Detector CT System. Proc SPIE Int Soc Opt Eng 10132:
Huang, Alice E; Montoya, Juan C; Shiung, Maria et al. (2017) Consistency of Renal Stone Volume Measurements Across CT Scanner Model and Reconstruction Algorithm Configurations. AJR Am J Roentgenol 209:116-121
Perinpam, Majuran; Enders, Felicity T; Mara, Kristin C et al. (2017) Plasma oxalate in relation to eGFR in patients with primary hyperoxaluria, enteric hyperoxaluria and urinary stone disease. Clin Biochem 50:1014-1019
Rossano, Adam J; Romero, Michael F (2017) Optical Quantification of Intracellular pH in Drosophila melanogaster Malpighian Tubule Epithelia with a Fluorescent Genetically-encoded pH Indicator. J Vis Exp :
Lieske, John C (2017) Probiotics for prevention of urinary stones. Ann Transl Med 5:29
Ferrero, Andrea; Chen, Baiyu; Li, Zhoubo et al. (2017) Technical Note: Insertion of digital lesions in the projection domain for dual-source, dual-energy CT. Med Phys 44:1655-1660
Pottel, Hans; Dubourg, Laurence; Schaeffner, Elke et al. (2017) Data on the relation between renal biomarkers and measured glomerular filtration rate. Data Brief 14:763-772
Kittanamongkolchai, Wonngarm; Mara, Kristin C; Mehta, Ramila A et al. (2017) Risk of Hypertension among First-Time Symptomatic Kidney Stone Formers. Clin J Am Soc Nephrol 12:476-482
Gutjahr, R; Polster, C; Henning, A et al. (2017) Dual Energy CT Kidney Stone Differentiation in Photon Counting Computed Tomography. Proc SPIE Int Soc Opt Eng 10132:
Canales, Benjamin K; Smith, Jennifer A; Weiner, I David et al. (2017) Polymorphisms in Renal Ammonia Metabolism Genes Correlate With 24-Hour Urine pH. Kidney Int Rep 2:1111-1121

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