Ratio-based vs. model-based methods to correct for urinary creatinine concentrations

摘要

Creatinine-corrected urinary analyte concentration is usually computed as the ratio of the observed level of analyte concentration divided by the observed level of the urinary creatinine concentration (UCR). This ratio-based method is flawed since it implicitly assumes that hydration is the only factor that affects urinary creatinine concentrations. On the contrary, it has been shown in the literature, that age, gender, race/ethnicity, and other factors also affect UCR. Consequently, an optimal method to correct for UCR should correct for hydration as well as other factors like age, gender, and race/ethnicity that affect UCR. Model-based creatinine correction in which observed UCRs are used as an independent variable in regression models has been proposed. This study was conducted to evaluate the performance of ratio-based and model-based creatinine correction methods when the effects of gender, age, and race/ethnicity are evaluated one factor at a time for selected urinary analytes and metabolites. It was observed that ratio-based method leads to statistically significant pairwise differences, for example, between males and females or between non-Hispanic whites (NHW) and non-Hispanic blacks (NHB), more often than the model-based method. However, depending upon the analyte of interest, the reverse is also possible. The estimated ratios of geometric means (GM), for example, male to female or NHW to NHB, were also compared for the two methods. When estimated UCRs were higher for the group (for example, males) in the numerator of this ratio, these ratios were higher for the model-based method, for example, male to female ratio of GMs. When estimated UCR were lower for the group (for example, NHW) in the numerator of this ratio, these ratios were higher for the ratio-based method, for example, NHW to NHB ratio of GMs. Model-based method is the method of choice if all factors that affect UCR are to be accounted for.