Cancer Institute A national cancer institute
designated cancer center

Atul Butte

Publication Details

  • Validating pathophysiological models of aging using clinical electronic medical records JOURNAL OF BIOMEDICAL INFORMATICS Chen, D. P., Morgan, A. A., Butte, A. J. 2010; 43 (3): 358-364


    Bioinformatics methods that leverage the vast amounts of clinical data promises to provide insights into underlying molecular mechanisms that help explain human physiological processes. One of these processes is adolescent development. The utility of predictive aging models generated from cross-sectional cohorts and their applicability to separate populations, including the clinical population, has yet to be completely explored. In order to address this, we built regression models predictive of adolescent chronological age from 2001 to 2002 National Health and Nutrition Examination Survey (NHANES) data and validated them against independent 2003-2004 NHANES data and clinical data from an academic tertiary-care pediatric hospital. The results indicate distinct differences between male and female models with both alkaline phosphatase and creatinine as predictive biomarkers for both genders, hematocrit and mean cell volume for males, and total serum globulin for females. We also suggest that the models are generalizable, are clinically relevant, and imply underlying molecular and clinical differences between males and females that may affect prediction accuracy. The integration of both epidemiological and clinical data promises to create more robust models that shed new light on physiological processes.

    View details for DOI 10.1016/j.jbi.2009.11.007

    View details for Web of Science ID 000278780800002

    View details for PubMedID 19958842

Stanford Medicine Resources:

Footer Links: