Showing papers by "Kenneth L. Campbell published in 2003"

Urinary Estrone Conjugate and Pregnanediol 3-Glucuronide Enzyme Immunoassays for Population Research

Abstract: Background: Monitoring of reproductive steroid hormones at the population level requires frequent measurements, hormones or metabolites that remain stable under less than ideal collection and storage conditions, a long-term supply of antibodies, and assays useful for a range of populations. We developed enzyme immunoassays for urinary pregnanediol 3-glucuronide (PDG) and estrone conjugates (E1Cs) that meet these criteria. Methods: Enzyme immunoassays based on monoclonal antibodies were evaluated for specificity, detection limit, parallelism, recovery, and imprecision. Paired urine and serum specimens were analyzed throughout menstrual cycles of 30 US women. Assay application in different populations was examined with 23 US and 42 Bangladeshi specimens. Metabolite stability in urine was evaluated for 0–8 days at room temperature and for 0–10 freeze-thaw cycles. Results: Recoveries were 108% for the PDG assay and 105% for the E1C assay. Serially diluted specimens exhibited parallelism with calibration curves in both assays. Inter- and intraassay CVs were <11%. Urinary and serum concentrations were highly correlated: r = 0.93 for E1C–estradiol; r = 0.98 for PDG–progesterone. All Bangladeshi and US specimens were above detection limits (PDG, 21 nmol/L; E1C, 0.27 nmol/L). Bangladeshi women had lower follicular phase PDG and lower luteal phase PDG and E1Cs than US women. Stability experiments showed a maximum decrease in concentration for each metabolite of <4% per day at room temperature and no significant decrease associated with number of freeze-thaw cycles. Conclusions: These enzyme immunoassays can be used for the field conditions and population variation in hormone metabolite concentrations encountered in cross-cultural research.

Statistical Correction for Non-Parallelism in a Urinary Enzyme Immunoassay Running Title: Statistical Correction for Non-parallelism

Abstract: Abstract Our aim was to develop a statistical method to correct for non‐parallelism in an estrone‐3‐glucuronide (E1G) enzyme immunoassay (EIA). Non‐parallelism of serially diluted urine specimens with a calibration curve was demonstrated in an EIA for E1G. A linear mixed‐effects analysis of 40 urine specimens was used to model the relationship of E1G concentration with urine volume and derive a statistical correction. The model was validated on an independent sample and applied to 30 menstrual cycles from American women. Specificity, detection limit, paral‐lelism, recovery, correlation with serum estradiol, and imprecision of the assay were determined. Intra‐and inter‐assay CVs were less than 14% for high‐ and low‐urine controls. Urinary E1G across the menstrual cycle was highly correlated with serum estradiol (r = 0.94). Non‐parallelism produced decreasing E1G concentration with increase in urine volume (slope = −0.210, p < 0.0001). At 50% inhibition, the assay had 100% cross‐reactivity with E1G and 83% with 17β‐estradiol 3‐glucuronide. The dose–response curve of the latter did not parallel that of E1G and is a possible cause of the non‐parallelism. The statistical correction adjusting E1G concentration to a standardized urine volume produced parallelism in 24 independent specimens (slope = −0.043 ± 0.010), and improved the average CV of E1G concentration across dilutions from 19.5% ± 5.6% before correction to 10.3% ± 5.3% after correction. A statistical method based on linear mixed effects modeling is an expedient approach for correction of non‐parallelism, particularly for hormone data that will be analyzed in aggregate.