Use of an algorithm applied to urine drug screening to assess adherence to a hydrocodone regimen.

WHAT IS KNOWN AND OBJECTIVE

This study examined the ability of an algorithm applied to urine drug levels of hydrocodone in healthy adult volunteers to differentiate among low, medium and high doses of hydrocodone.

METHODS

Twenty healthy volunteers received 20, 60 and 120 mg daily doses of hydrocodone dosed to steady-state at each level while under a naltrexone blockade. Using a florescence polarization immunoassay (FPIA), two urine samples were taken at each dosing level from each participant once steady-state was reached. The concordance was calculated for raw and adjusted FPIA urine hydrocodone values within each study participant across all doses. An analysis of medians was calculated for each of the dosage groupings using Bonett-Price confidence intervals for both raw and adjusted FPIA values. Finally, the Somers' D rank order analysis was performed for both raw and adjusted FPIA methods followed by a linear comparison of parameters to further determine which lab value reporting method produced a better fit with dosage.

RESULTS AND DISCUSSION

The concordance correlation coefficient for the pairs of raw urine FPIA values was 0·339, while the concordance correlation coefficient for the pairs of normalized FPIA values using the algorithm was 0·677. While some overlap of the confidence intervals was observed using the raw FPIA values, the intervals for the adjusted FPIA levels did not overlap between any dose levels, despite the application of a Bonferroni adjustment to correct for multiple comparisons. Results of the Somers' D analyses suggest that the adjusted FPIA method is 15% more likely to be concordant with dose than the raw value method.

WHAT IS NEW AND CONCLUSIONS

In contrast to raw FPIA values, an algorithm that normalizes hydrocodone urine drug levels for PH, specific gravity and lean body mass discriminates well between all three of the daily doses of hydrocodone tested (20, 60 and 120 mg), even when correcting for multiple analyses.