Plasma morphine and metabolite concentrations are associated with clinical effects of morphine in cancer patients.

CONTEXT: Morphine is the opioid of choice for cancer-related pain, but for many patients the benefits of morphine are outweighed by its side effect profile. Morphine is metabolized to morphine-3-glucuronide and morphine-6-glucuronide; however, little is known about the contribution of these metabolites to analgesia and morphine-related side effects. OBJECTIVES: We investigated the association between plasma morphine and metabolite concentrations and the clinical effects of morphine in cancer patients. METHODS: A prospective study was performed in cancer patients taking oral morphine for moderate-to-severe cancer pain. Subjects who responded well to morphine (responders) and subjects who failed to respond to morphine because of lack of analgesia and/or the presence of intolerable side effects (nonresponders/switchers) were recruited. Pain and toxicity scores were recorded and blood samples were analyzed for plasma morphine, morphine-3-glucuronide, and morphine-6-glucuronide concentrations. RESULTS: Results showed that 1) morphine responders have higher plasma morphine and metabolite concentrations compared with nonresponders, 2) lower pain scores are associated with higher plasma morphine and metabolite concentrations, 3) central side effects are associated with a higher metabolite:plasma morphine ratio, and 4) myoclonus is associated with extremely high concentrations of plasma morphine and metabolites. CONCLUSION: This study has shown that plasma morphine and metabolite concentrations are associated with the clinical effects of morphine therapy. These results are important because they demonstrate the relevance of measuring plasma metabolite concentrations in clinical trials and the potential for metabolite data to deepen our understanding of factors that influence an individual's response to morphine.

Analgesia and central side-effects: two separate dimensions of morphine response.

AIMS: To present a statistical model for defining interindividual variation in response to morphine and to use this model in a preliminary hypothesis-generating multivariate genetic association study. METHODS: Two hundred and sixty-four cancer patients taking oral morphine were included in a prospective observational study. Pain and morphine side-effect scores were examined using principal components analysis. The resulting principal components were used in an exploratory genetic association study of single nucleotide polymorphisms across the genes coding for the three opioid receptors, OPRM1, OPRK1 and OPRD1. Associations in multivariate models, including potential clinical confounders, were explored. RESULTS: Two principal components corresponding to residual pain and central side-effects were identified. These components accounted for 42 and 18% of the variability in morphine response, respectively, were independent of each other and only mildly correlated. The genetic and clinical factors associated with these components were markedly different. Multivariate regression modelling, including clinical and genetic factors, accounted for only 12% of variability in residual pain on morphine and 3% of variability in central side-effects. CONCLUSIONS: Although replication is required, this data-driven analysis suggests that pain and central side-effects on morphine may be two separate dimensions of morphine response. Larger study samples are necessary to investigate potential genetic and clinical associations comprehensively.