Utilization of Pharmacogenomics and Therapeutic Drug Monitoring for Opioid Pain Management

Paul J Jannetto; Nancy C Bratanow


Pharmacogenomics. 2009;10(7):1157-1167. 

In This Article


A total of 61 chronic-pain patients from three separate pain management clinics were enrolled from November 2002 until February 2004. Of the 61 patients, 51% were male and 49% were female. The average age of all the chronic pain patients was 51, but ranged from 25 to 86. The most common diagnosis and reason the patient's sought pain relief was due to chronic lower back pain (38%), followed by migraines (8%). Since the prevalence of various genetic polymorphisms varies depending on ethnic background, it is important to note that the majority of chronic pain patients enrolled in the study were Caucasian (90%) followed by African-American (8%), Hispanic (1%) and American-Indian (1%). Table 1 shows the demographics, diagnosis, pain management therapy and CYP2D6 genotype of all 61 subjects. The most commonly prescribed opioid, alone or in combination, for pain management was oxycodone (54%) followed by tramadol and methadone (31 and 28%, respectively). The vast majority of patients included in this study (75%) were prescribed either an antidepressant or an anticonvulsant concomitantly with opioids. Only 15% of all the patients had an opioid as their sole therapeutic agent for pain therapy. The most commonly prescribed opioid for monotherapy was oxycodone (50%) followed by tramadol (24%), methadone (17%) and hydrocodone (9%).

Due to the risk of abuse or diversion, pain management patients who are being prescribed opioid medications usually have their urine monitored to determine compliance. In this study, the ability to detect the opioid in the patient's plasma was used as an indicator of compliance. Compliance was defined as detectable plasma concentrations (≥1 ng/ml) of the prescribe opioid(s). Patients with undetectable (<1 ng/ml) plasma opioid concentrations were considered noncompliant and were excluded in comparisons between Css and CYP2D6 genotype or pain relief. Compliance varied depending on the opioid prescribed. For tramadol, hydrocodone, oxycodone and methadone, 41, 29, 14 and 0% of the patient's prescribed these medications had no detectable drug concentration in their plasma, respectively. The low level of compliance for tramadol and hydrocodone does reflect a limitation of the current study, but is one of the challenges that pain management physicians face. Based on the genetic information, no patients were UMs. In addition, the CYP2D6 metabolites of each opioid (i.e., oxymorphone the CYP2D6 metabolite of oxycodone) were also measured but provided no additional information. In future studies, the parent:metabolite ratios could be used to correlate the phenotype with the genotype.

Based on the VAS, 16% of the chronic pain patients experienced no pain relief, 64% had partial pain relief and 20% had complete pain relief. When pain relief was correlated with the patient's CYP2D6 genotype, individuals with impaired CYP2D6 metabolism generally had less pain relief. For EMs of CYP2D6, 21% of the chronic pain patients stated they had complete relief, 58% partial relief and 21% no relief. For IMs of CYP2D6, 20% of the patients stated they had complete relief, 68% partial relief and 12% no pain relief. All the CYP2D6 PMs stated that they only experienced partial pain relief.

The relationship between the Css of each opioid was also correlated to the clinical effectiveness (pain relief). Only oxycodone showed a clear relationship between the plasma Css and pain relief (Figure 1). Chronic pain patients had partial to complete pain relief when the Css of oxycodone was between 15 and 32 ng/ml. However, if the Css of oxycodone was less than 15 ng/ml no pain relief was reported. A clear relationship between Css and clinical effectiveness was not found with methadone (17 patients), tramadol (19 patients), or hydrocodone (7 patients), which could be due to the small number of patients prescribed these medications. Alternatively, the lack of correlation for pain severity and parent drug concentration might indicate that some of the opioids (i.e., hydrocodone) have active metabolites that might contribute to the pharmacological action.

Figure 1.

Correlation of steady-state oxycodone concentrations and clinical efficacy (pain relief).

Overall, the prevalence of CYP2D6 polymorphisms in the pain management population was not statistically different from the general population based on published studies (Figure 2). The majority of patients were EMs (54%) followed by IMs (41%) and PMs (5%). Furthermore, no statistically significant relationship was seen between the opioid Css and the patient's CYP2D6 genotype. Table 2 shows the Css of hydrocodone, oxycodone, methadone and tramadol based on the CYP2D6 genotype. Despite the lack of significance, a general trend was observed in which the Css of hydrocodone, methadone and tramadol, based on genotype, went as follows: PM > IM > EM. However, the Css of oxycodone for PMs was actually lower than both the IMs and EMs. Upon further investigation, it was discovered that the two PM patients had skipped one or more doses of their oxycodone. Therefore, the Css of oxycodone was falsely decreased and a true Css value was not measured.

Figure 2.

Prevalence of CYP2D6 predicted phenotypes in the pain management patients versus the general population.
EM: Extensive metabolizer; IM: Intermediate metabolizer; PM: Poor metabolizer; UM: Ultrarapid metabolizer.
General population prevalence data taken from.[44]


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