In a clinical laboratory setting, drug testing is most commonly performed to compliment and improve patient care. Drug testing results are used as a tool, along with other clinical data, behavioral monitoring, and self-report, for guiding how a patient is managed, and for assuring that “all is well.” Sometimes the actual concentration of drug is not very important clinically. As such, qualitatitive drug testing can help simply detect or exclude a drug exposure (intentional or unintentional). Conversely, actual concentration of drug, particularly in timed specimens, is the foundation upon which routine therapeutic drug monitoring (TDM) is based, and may help determine if clinical signs and symptoms of either therapeutic failure or toxicity could be related to drug dose. Serial monitoring of drug concentrations can help guide treatment of a drug overdose, or evaluate the effect of dose adjustment or a change in drug formulation. Drug concentrations may also help detect a drug-drug interaction or some other change in patient pharmacokinetics. In any case, a clinical drug test is usually associated with a “pre-test” expectation. When a result is inconsistent with that pre-test expectation, the result and the surrounding variables should be investigated before concluding that a patient has inappropriately taken, or not taken, a particular drug. Wrongly suggesting or accusing a patient of drug use could be associated with serious social, legal, economic, and medical consequences.
At AACC this year, Short Course 74219 was designed to discuss “detective” tools for “investigating” an unexpected drug testing result. Examples of preanalytical, analytical, and post-analytical considerations surrounding unexpected drug testing results were provided to (hopefully) prevent any patient from being mismanaged, or wrongfully accused of either taking, or not taking a drug. Of course, the course provided the whole story! There were many interesting “cases” to learn from. One such case related to the fact that some laboratory tests are sensitive enough to detect impurities in drug manufacturing. For example, it is entirely possible that a laboratory would detect hydrocodone (e.g. Lortab) in a urine sample collected from someone who was prescribed oxycodone (e.g. Percocet). Even though the names of these drugs are similar, neither is recognized to be a metabolite of the other, and therefore, the most obvious interpretation of finding both drugs in a urine specimen, is that a patient took both drugs. Don’t be fooled into the wrong interpretation! Depending on the proportion of the two drugs in that urine specimen, and the performance characteristics of the lab test used, it may be reasonable to suspect that the hydrocodone represents a process impurity, based on the manufacturing specifications for Percocet. Accusing a patient of taking an unprescribed drug (eg, Lortab) could deny that patient much-needed pain medication. Correct interpretation of drug testing results for patients treated with opioids for chronic pain is an important and sometimes very challenging aspect of patient care today.
Dozens of other potentially useful “cases” to help sleuth out confounding factors in the interpretation of drug testing results were discussed in the short course, but the “take home message” was to always consider a drug test result, particularly one that is unexpected, in the context of the individual patient scenario.