Jefferson School of Population Health, Thomas Jefferson University, Philadelphia, PA 10107, USA.
J Clin Pharm Ther. 2011 Apr;36(2):200-7. doi: 10.1111/j.1365-2710.2010.01236.x. Epub 2010 Dec 19.
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.
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.
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.
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.
本研究旨在检验应用于健康成年志愿者尿液中美托吗啡浓度的算法，区分美托吗啡低、中、高剂量的能力。
20 名健康志愿者接受 20、60 和 120mg 每日剂量的美托吗啡，在每个剂量水平下达到稳态时，同时接受纳曲酮阻断。使用荧光偏振免疫分析法（FPIA），在每个参与者达到稳态时，从每个剂量水平采集两个尿液样本。在所有剂量下，对每个研究参与者的原始和调整后的 FPIA 尿液美托吗啡值进行一致性计算。使用原始和调整后的 FPIA 值，使用 Bonett-Price 置信区间计算每个剂量分组的中位数。最后，对原始和调整后的 FPIA 方法进行 Somers'D 秩相关分析，然后对参数进行线性比较，以进一步确定哪种实验室值报告方法与剂量更匹配。
原始尿液 FPIA 值对的一致性相关系数为 0.339，而使用算法对归一化 FPIA 值对的一致性相关系数为 0.677。虽然原始 FPIA 值的置信区间有一些重叠，但调整后的 FPIA 水平的置信区间在任何剂量水平之间都没有重叠，尽管应用了 Bonferroni 调整来校正多重比较。Somers'D 分析的结果表明，调整后的 FPIA 方法比原始值方法更有可能与剂量一致，其一致性的可能性高 15%。
与原始 FPIA 值相比，一种用于美托吗啡尿液药物水平的算法，用于 PH、比重和瘦体重进行归一化，可很好地区分三种每日剂量（20、60 和 120mg）的美托吗啡，即使在对多个分析进行校正时也是如此。
