Association of 152 Biomarker Reference Intervals with All-Cause Mortality in Participants of a General United States Survey from 1999 to 2010

Author:

Pho Nam1,Manrai Arjun K1,Leppert John T23,Chertow Glenn M24,Ioannidis John P A2456,Patel Chirag J1ORCID

Affiliation:

1. Department of Biomedical Informatics, Harvard Medical School, Boston, MA

2. Department of Medicine, Stanford University School of Medicine, Stanford, CA

3. Department of Urology, Stanford University School of Medicine, Stanford, CA

4. Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA

5. Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA

6. Department of Statistics, Stanford University School of Humanities and Sciences, Stanford, CA

Abstract

Abstract Background Physicians sometimes consider whether or not to perform diagnostic testing in healthy people, but it is unknown whether nonextreme values of diagnostic tests typically encountered in such populations have any predictive ability, in particular for risk of death. The goal of this study was to quantify the associations among population reference intervals of 152 common biomarkers with all-cause mortality in a representative, nondiseased sample of adults in the United States. Methods The study used an observational cohort derived from the National Health and Nutrition Examination Survey (NHANES), a representative sample of the United States population consisting of 6 survey waves from 1999 to 2010 with linked mortality data (unweighted N = 30 651) and a median followup of 6.1 years. We deployed an X-wide association study (XWAS) approach to systematically perform association testing of 152 diagnostic tests with all-cause mortality. Results After controlling for multiple hypotheses, we found that the values within reference intervals (10–90th percentiles) of 20 common biomarkers used as diagnostic tests or clinical measures were associated with all-cause mortality, including serum albumin, red cell distribution width, serum alkaline phosphatase, and others after adjusting for age (linear and quadratic terms), sex, race, income, chronic illness, and prior-year healthcare utilization. All biomarkers combined, however, explained only an additional 0.8% of the variance of mortality risk. We found modest year-to-year changes, or changes in association from survey wave to survey wave from 1999 to 2010 in the association sizes of biomarkers. Conclusions Reference and nonoutlying variation in common biomarkers are consistently associated with mortality risk in the US population, but their additive contribution in explaining mortality risk is minor.

Publisher

Oxford University Press (OUP)

Subject

Biochemistry (medical),Clinical Biochemistry

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