Normalizing Oral Fluid Hydrocodone Data Using Calculated Blood Volume

Abstract

Oral fluid testing to assist in the assessment of treatment adherence for chronic pain patients is attractive for a number of reasons. However, efforts focused on interpreting patient results have been modest when compared to urine drug testing. This work details a retrospective approach developed to transform and normalize oral fluid testing results to provide a historical picture of patient values in this important test fluid. Using this approach, a model was developed using data from 6,800 independent patients who were both prescribed hydrocodone and tested positive (with limitations: reporting cutoff < X < upper limit of quantitation) by liquid chromatography-mass spectrometry. Patient demographic data were used to calculate the relevant parameters (e.g., calculated blood volume (CBV)) used in the transformation and normalization of the oral fluid data. The crucial normalizing factor in oral fluids was found to be the CBV which parallels the use of creatinine to normalize drug concentration levels in urine and is consistent with the view that oral fluid samples reflect plasma concentrations of the respective drugs. The resulting near Gaussian distribution is dose independent and as such should be of value to physicians in quickly assessing whether their patient is consistent with this historical population in the broad terms of this model. While this comparison alone is not definitive for adherence with a treatment regimen, together with patient interviews, prescription history and other clinical criteria, it can add an idea of expected patient values from oral fluid testing.

Nicotine and cotinine in oral fluid: Passive exposure vs active smoking

“…These results are interesting but don’t contradict the observations from the initial clinical trial [1] . They are consistent with the conclusion of the earlier work [1] that a cutoff of 10 ng/mL for nicotine is appropriate to identify active smoking via oral fluid samples and that oral fluid data can be normalized via calculated blood volume [7] .…”

“…The raw nicotine concentration measured in oral fluid of a patient is normalized and transformed as a function of patient lean body weight (LBW), body surface area (BSA), and calculated blood volume (CBV) as described in Eq. (1) which is similar but not identical to the earlier report [7] : …”

“…3 ). Using this process, a “normal” population is defined where the status of individual patient results can easily be interpreted as “consistent” or “inconsistent” with 95% (e.g., 2 standard deviations) of that population [7] . Interestingly, not having the individual doses of nicotine and thus not being able to normalize to dose as per reference [6] does not seem to hamper the modelling process.…”

“…In an effort to define “normal” populations of smokers vs passive nicotine exposure, nicotine smoking data were modelled as per the report of Cummings, et al [7] and compared with the reporting cutoffs from the earlier clinical study [1] . Finally, using this modelling approach, test results from patients who smoked are compared with those from patients who used transdermal nicotine patches.…”

Dose Dependent Urine Concentrations of Gabapentin (Neurontin®)

“…In short, the raw data are generally only useful for determining positive or negative for gabapentin. Figure 3 shows an attempt to normalize the raw gabapentin data to patient creatinine values [13,18]. The reported concentration divided by the respective creatinine concentration is then transformed via a logarithmic function to afford the result seen in Figure 3 (Equation 2).…”