• Brittany B Dennis, Pavel S Roshanov, Monica Bawor, James Paul, Michael Varenbut, Jeff Daiter, Carolyn Plater, Guillame Pare, David C Marsh, Andrew Worster, Dipika Desai, Lehana Thabane, and Zainab Samaan.
• Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Canada; Population Genomic Program, Chanchalani Research Centre, McMaster University, Hamilton, Canada.
• Pain Physician. 2016 Jan 1; 19 (1): E181-95.

BackgroundChronic pain is implicated as a risk factor for illicit opioid use among patients with opioid addiction treated with methadone. However, there exists conflicting evidence that supports and refutes this claim. These discrepancies may stem from the large variability in pain measurement reported across studies.ObjectivesWe aim to determine the clinical and demographic characteristics of patients reporting pain and evaluate the prognostic value of different pain classification measures in a sample of opioid addiction patients.Study DesignMulti-center prospective cohort study.SettingMethadone maintenance treatment facilities for managing patients with opioid addiction.MethodsThis study includes participants from the Genetics of Opioid Addiction (GENOA) prospective cohort study. We assessed the prognostic value of different pain measures for predicting opioid relapse. Pain measures include the Brief Pain Inventory (BPI) and patients' response to a direct pain question all study participants were asked from the GENOA case report form (CRF) "are you currently experiencing or have been diagnosed with chronic pain?" Performance characteristics of the GENOA CRF pain measure was estimated with sensitivity and specificity using the BPI as the gold standard reference. Prognostic value was assessed using pain classification as the primary independent variable in an adjusted analysis using 1) the percentage of positive opioid urine screens and 2) high-risk opioid use (= 50% positive opioid urine screens) as the dependent variables in a linear and logistic regression analyses, respectively.ResultsAmong participants eligible for inclusion (n = 444) the BPI was found to be highly sensitive, classifying a large number of GENOA participants with pain (n = 281 of the 297 classified with pain, 94.6%) in comparison to the GENOA CRF (n = 154 of 297 classified with pain, 51.8%). Participants concordantly classified as having pain according to the GENOA CRF and BPI were found to have an estimated 7.79% increase in positive opioid urine screens (estimated coefficient: 7.79; 95% CI 0.74, 14.85: P = 0.031) and a 4 times greater odds (odds ratio [OR]: 4.10 P = 0.008; 95% CI: 1.44, 11.63) of engaging in a "high risk" level of illicit opioids use. The prognostic relevance of pain classification was not maintained for the additional participants classified by the BPI (n = 143 discordant).ConclusionThese results suggest that while the BPI may be more sensitive in capturing pain among patients with opioid addiction, this tool is of less value for predicting the impact of pain on illicit opioid use for opioid addiction patients on methadone maintenance treatment. The GENOA CRF showed high predictive ability, whereby patients classified according to the GENOA CRF are at serious risk for opioid relapse. Using the appropriate tool to assess pain in opioid addiction may serve to improve the current detection and management of comorbid pain.LimitationsWe caution the interpretation of these result since they are still reflective of participants already maintained on an opioid substitution therapy (OST), which can largely differ from patients who drop out of methadone maintenance treatment (MMT) or never seek treatment altogether.

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