Influence from genetic variability on opioid use for cancer pain: A European genetic association study of 2294 cancer pain patients

Abstract

Cancer pain patients need variable opioid doses. Preclinical and clinical studies suggest that opioid efficacy is related to genetic variability. However, the studies have small samples, findings are not replicated, and several candidate genes have not been studied. Therefore, a study of genetic variability with opioid doses in a large population using a confirmatory validation population was warranted. We recruited 2294 adult European patients using a World Health Organization (WHO) step III opioid and analyzed single nucleotide polymorphisms (SNPs) in genes with a putative influence on opioid mechanisms. The patients' mean age was 62.5 years, and the average pain intensity was 3.5. The patients' primary opioids were morphine (n=830), oxycodone (n=446), fentanyl (n=699), or other opioids (n=234). Pain intensity, time on opioids, age, gender, performance status, and bone or CNS metastases predicted opioid dose and were included as covariates. The patients were randomly divided into 1 development sample and 1 validation sample. None of 112 SNPs in the 25 candidate genes OPRM1, OPRD1, OPRK1, ARRB2, GNAZ, HINT1, Stat6, ABCB1, COMT, HRH1, ADRA2A, MC1R, TACR1, GCH1, DRD2, DRD3, HTR3A, HTR3B, HTR2A, HTR3C, HTR3D, HTR3E, HTR1, or CNR1 showed significant associations with opioid dose in both the development and the validation analyzes. These findings do not support the use of pharmacogenetic analyses for the assessed SNPs to guide opioid treatment. The study also demonstrates the importance of validating findings obtained in genetic association studies to avoid reporting spurious associations as valid findings. To elicit knowledge about new genes that influence pain and the need for opioids, strategies other than the candidate gene approach is needed.

Clinical and Genetic Factors Related to Cancer-Induced Bone Pain and Bone Pain Relief

“…A total of 2,294 patients with cancer were recruited in the international, multicenter, cross-sectional EPOS [27], with the principal aim to examine the association between genetic variations and opioid efficacy on cancer pain relief. Patients were eligible if they had verified malignant disease, were aged $18 years, and were scheduled with opioid treatment for moderate to severe pain for at least 3 days.…”

“…Whole blood samples were obtained and DNA extraction and SNP analyses were performed as previously described [27]. Individuals with a minimum allele frequency of less than 5% or in violation with the Hardy-Weinberg equilibrium (chi-square test, p , .0005) were excluded [36].…”

Prospective replication study implicates the catechol-O-methyltransferase Val158Met polymorphism as a biomarker for the response to morphine in patients with cancer

“…A large sample study has indicated that none of 112 SNPs in the 25 candidate genes showed significant associations with opioid dose (15); however, this study lacked clarity regarding the doses of concomitant analgesics, the dose determination of opioids, and the high average total dose of morphine of 90 mg/day. Despite this dose, residual pain was relatively high (pain NRS in the past 24 h, 3.20±2.10 subsequent to analgesic use and no data for pain NRS prior to analgesic use) (15). This suggests a high proportion of refractory pain.…”

“…A large sample study has indicated that none of the 112 single nucleotide polymorphisms (SNPs) in 25 candidate genes demonstrated significant associations with opioid dose (15); however, the quantity of concomitant analgesics [non-steroidal anti-inflammatory drugs (NSAIDs) and acetaminophen] and the method for dose determination of opioids remain unclear. Furthermore, the mean Brief Pain Index (16) following treatment was relatively high (15).…”

Cancer pain research: Time to reset the strategy and the agenda

“…Examining 123 single nucleotide polymorphisms (SNPs) from the most relevant candidates, 9 showed significant association with opioid dosage. 1 Based on DNA pools from 'good' and 'poor' opioid responders, a novel set of 17 SNPs was identified, explaining as much as 25% of the phenotypic variation in a regression model. 2 A major challenge in the gene studies was to agree upon a valid system for classification (categorization) of cancer patients with pain, or in other words, how to phenotype the patient.…”