Identification of Predictive Markers of the Effects of Opioid Therapy in Patients With Chronic Pain.

Overview

Chronic pain is a significant problem for a large part of the adult population. Opioids are the mainstay of therapy for moderate to severe pain because of their safety, multiple routes of administration, reliability, and effectiveness for all types of pain. However, there is a wide variation in treatment response and a high frequency of side effects associated with the use of opioids. Thus it is important to identify patients who will experience successful pain control with treatment. Unfortunately, as of today no robust objective measures exist for the assessment of the pain-relieving effect of opioids. The pain treatment offered to any given patient is thus largely dependent on the treating physician's experience and the primary pain diagnosis, rather than the characteristics of the individual patient. Unfortunately, this strategy often leads to inadequate treatment, side effects and distress. An implementable clinical tool that can predict and distinguish successful pain control with opioid treatment is therefore warranted. Quantitative sensory testing (QST) is a method to evaluate the individual pain system. It has been successfully used to describe the problems of individual variation in pain and to predict and measure the responses to an intervention. The investigators recently examined how advanced analyses of QST and pain-related catastrophic thinking could predict opioid response in chronic pain patients whom had not previously received opioid treatment. This study showed that the effect of opioid treatment was predicted by certain pain system responses, catastrophic thinking related to pain and brainwave patterns. The investigators now want to expand on this study by including all patients assigned to opioid treatment by their treating physician. The investigators are also increasing their data collection and using a more elaborate pain system characterization, investigating pain-relevant psychological factors and sleep patter by questionnaires, socio-demographic parameters and collecting descriptive genetic information. The overall goal of the ABILITY-2 study is to help improve pain diagnostics and treatment by developing an implementable algorithm based on individual patient characteristics to be used in the clinic. The investigators hypothesize that successful pain control with opioids can be predicted before treatment initiation with advanced analyses of QST, pain-related psychological factors and socio-demographic data.