Recalibration of Blood Analytes over 25 Years in the Atherosclerosis Risk in Communities Study: Impact of Recalibration on Chronic Kidney Disease Prevalence and Incidence

C. M. Parrinello, M. E. Grams, D. Couper, C. M. Ballantyne, R. C. Hoogeveen, J. H. Eckfeldt, E. Selvin, J. Coresh
2015 Clinical Chemistry  
BACKGROUND: Equivalence of laboratory tests over time is important for longitudinal studies. Even a small systematic difference (bias) can result in substantial misclassification. METHODS: We selected 200 Atherosclerosis Risk in Communities Study participants attending all 5 study visits over 25 years. Eight analytes were remeasured in 2011-13 from stored blood samples from multiple visits: creatinine, uric acid, glucose, total cholesterol, HDL cholesterol, LDL cholesterol, triglycerides, and
more » ... gh-sensitivity C-reactive protein. Original values were recalibrated to remeasured values with Deming regression. Differences Ͼ10% were considered to reflect substantial bias, and correction equations were applied to affected analytes in the total study population. We examined trends in chronic kidney disease (CKD) pre-and postrecalibration. RESULTS: Repeat measures were highly correlated with original values [Pearson r Ͼ 0.85 after removing outliers (median 4.5% of paired measurements)], but 2 of 8 analytes (creatinine and uric acid) had differences Ͼ10%. Original values of creatinine and uric acid were recalibrated to current values with correction equations. CKD prevalence differed substantially after recalibration of creatinine (visits 1, 2, 4, and 5 prerecalibration: 21.7%, 36.1%, 3.5%, and 29.4%, respectively; postrecalibration: 1.3%, 2.2%, 6.4%, and 29.4%). For HDL cholesterol, the current direct enzymatic method differed substantially from magnesium dextran precipitation used during visits 1-4. CONCLUSIONS: Analytes remeasured in samples stored for approximately 25 years were highly correlated with orig-inal values, but 2 of the 8 analytes showed substantial bias at multiple visits. Laboratory recalibration improved reproducibility of test results across visits and resulted in substantial differences in CKD prevalence. We demonstrate the importance of consistent recalibration of laboratory assays in a cohort study. Equivalence of laboratory measurements over time is of central importance for studies of trends in disease prevalence, incidence, and progression. Assay recalibration is especially crucial when a disease is defined categorically with biomarker concentrations above or below a certain cut point. Even a small amount of systematic difference can lead to substantial misclassification of disease (1-7 ) . Small differences (e.g., Ͻ10%) may have little impact on clinical decision making or classification of individuals with values far from a clinical cutoff. However, at the population level, small, systematic differences shift the entire distribution of a biomarker, resulting in biased estimates of prevalence and incidence. Large epidemiologic studies must carefully assess the recalibration and reproducibility of their biomarker measurements to ensure equivalence across study visits and accurate comparisons over time. Leveraging previous experience in the laboratory recalibration of biomarkers in large epidemiologic studies (1, 2, 5, 8 -10 ), we undertook recalibration of 8 key laboratory tests in the Atherosclerosis Risk in Communities (ARIC) 7 Study. The ARIC Study is a prospective cohort with Ͼ25 years of follow-up and 5 study visits during which blood samples were collected. Our objectives were
doi:10.1373/clinchem.2015.238873 pmid:25952043 pmcid:PMC4782184 fatcat:sknsuxo2fzhute2452ftfgkihu