Validating pathophysiological models of aging using clinical electronic medical records.
ABSTRACT 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.
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ABSTRACT: Even though laboratory data provide the best indicators for systemic toxicities in clinical trials of investigational medications, many applied statisticians lack a basic understanding of the interpretation of such data. Understanding is essential to a statistician's ability to help evaluate a patient's overall safety experience in a trial, the latter being the primary objective for collecting laboratory data in the trial. In this paper, we discuss the purpose of conducting laboratory evaluations as well as some hidden issues concerning the current practice of laboratory data analysis. The issues include the use of reference ranges, the one-parameter-at-a-time approach, and the exploratory nature of safety data analyses.Controlled Clinical Trials 04/1998; 19(2):167-77.