An Alternative to a Standard Crossover Study to Evaluate the Impact of an Assay Change in NHANES

• Activity Number: 267
• Type: Contributed
• Date/Time: Monday, August 10, 2015 : 2:00 PM to 3:50 PM
• Sponsor: Section on Physical and Engineering Sciences
• Author(s): Maya R. Sternberg* and Rosemary Schleicher
• Companies: CDC and CDC
• Keywords: multiple imputation ; crossover study ; assay

Abstract

The National Health and Nutrition Examination Survey (NHANES) is often used to monitor trends in various nutritional biomarkers. While NHANES tries to maintain the same biomarker assay over time, there are times when an assay may change. To minimize the impact these assay changes may have on changes in the biomarker concentration over time, the laboratory will perform a crossover study that measures the same samples with both the new and old measurement procedure. A regression equation is then derived and used to predict the values from one measurement procedure based on the other. These 'adjusted' results are used in any trend analysis. This approach has been used by NCHS on different occasions such as for serum and RBC folate when the Bio-Rad radioassay was discontinued and vitamin D where kit changes made by manufacturer caused assay fluctuations. A primary problem with the standard approach is that any inferences performed on the resulting 'adjusted' values will underestimate the variance as any uncertainty in the prediction equation is ignored at the time of data analysis. We propose a specific study design and a multiple imputation approach as an alternative.