Predictors of opioid efficacy in patients with chronic pain: A prospective multicenter observational cohort study

Abstract

Opioids are increasingly used for treatment of chronic pain. However, they are only effective in a subset of patients and have multiple side effects. Thus, studies using biomarkers for response are highly warranted. The current study prospectively examined 63 opioid-naïve patients initiating opioid use for diverse types of chronic pain at five European centers. Quantitative sensory testing, electroencephalography (EEG) recordings, and assessment of pain catastrophizing were performed prior to treatment. The co-primary outcomes were change from baseline in ratings of chronic pain and quality of life after 14 days of opioid treatment. Secondary outcomes included patient’s global impression of clinical change and side effects. Logistic regression models adjusted for age and sex were used to identify biomarkers predictive for successful treatment, defined as at least a 30% reduction in average pain intensity or an improvement in quality of life of at least 10 scale points. Fifty-nine patients (94%) completed the study. The mean age was 55 ± 16 years and 69% were females. Pain reduction was predicted by cold pain intensity (OR: 0.69; P = 0.01), pain catastrophizing (OR: 0.82; P = 0.03), relative delta (OR: 0.76; P = 0.03) and beta EEG activity (OR: 1.18; P = 0.04) induced by experimental cold pain. None of the study variables were related to improvement in quality of life. For the first time, individual pain processing characteristics have been linked to opioid response in a mixed chronic pain population. This has the potential to personalize treatment of chronic pain and restrict opioid use to patients with high likelihood for response.

Predicting drug efficacy in chronic low back pain by quantitative sensory tests

“…Yet, the study by Grosen et al. (Grosen et al., ) identified pain catastrophizing as a significant predictor for opioid efficacy. It must be noted, however, that their study population included patients with various pain syndromes, including head, neck and other musculoskeletal as well as neuropathic pain patients.…”

“…These studies identified a selection of QST to predict treatment response, but the sample sizes were generally small, and the results are not consistent across studies. The most recent evidence (Grosen et al., ) showed that opioid efficacy was predicted by low levels of pain catastrophizing, low pain intensity during cold pressor stimulus of the hand and certain EEG patterns. The patient population in this study was very heterogeneous in terms of pain syndrome and pain location.…”

The search for pain biomarkers in the human brain

“…Three arguments are usually set forth to uphold this prospect in the field of pain neuroimaging ( Kupers and Kehlet, 2006 ; Borsook et al , 2007 , 2010 ; de Vries et al , 2013 ; Lee and Tracey, 2013 ; Morton et al , 2016 ; Grosen et al , 2017 ; Tracey, 2017 ). First, it is often claimed that functional neuroimaging could be used to derive brain biomarkers that measure pain ‘objectively’.…”

Designing and conducting proof-of-concept chronic pain analgesic clinical trials

“…In brief, baseline QST responses have been associated with the efficacy of lidocaine, lamotrigine, pregabalin, oxycodone, oxcarbazepine, and placebo analgesia. 50 In a multicenter observational cohort study, Grosen et al 76 found that opioid response was predicted by cold pain intensity, pain catastrophizing, and beta EEG activity induced by laboratory cold pain in a small sample of mixed-type chronic pain patients. Pretreatment pain inhibition, often measured through conditioned pain modulation (counterirritation believed to reflect descending pain control 156 ), has been associated with postoperative pain outcomes, 13,183 the benefits of exercise, 103 morphine consumption after chest wall surgery, 77 duloxetine benefit in painful diabetic neuropathy patients, 185 and NSAID efficacy.…”