The journal of pain : official journal of the American Pain Society
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There is a well-established comorbidity between migraine and anxiety and depression (A/D). Here, we investigate whether this relationship is specific for migraine and A/D or whether other types of pain are also consistently associated with A/D. In addition, we test whether there is a consistent association between migraine and other types of pain when comorbidity with A/D is controlled for. Data on A/D, migraine, and 6 nonheadache pain locations (back, neck, orofacial area, abdomen, joints, and chest) were analyzed in 2,981 participants from the Netherlands Study of Depression and Anxiety (NESDA). It was tested whether the prevalence of pain in each individual location, as well as the total number of pain locations, depended on A/D and migraine status. A/D was consistently associated with pain in all measured locations. Migraine was also associated with pain in all anatomical sites, but these associations weakened substantially after correction for A/D severity, suggesting that a considerable part of the comorbidity of migraine and other types of pain may be explained by A/D. These findings emphasize the importance of accounting for A/D in studies of pain comorbidity. This will contribute to a better understanding of the mechanisms underlying A/D and pain. ⋯ Anxiety and depression are consistently associated with pain, regardless of anatomical site. These disorders may be important factors in the co-occurrence of different pain disorders. Awareness of this comorbidity and a better understanding of the underlying mechanisms may facilitate adequate treatment of both types of conditions.
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Arguments made for the advantages of replacing pain ratings with brain-imaging data include assumptions that pain ratings are less reliable and objective and that brain image data would greatly benefit the measurement of treatment efficacy. None of these assumptions are supported by available evidence. Self-report of pain is predictable and does not necessarily reflect unreliability or error. Because pain is defined as an experience, magnitudes of its dimensions can be estimated by well-established methods, including those used to validate brain imaging of pain. Brain imaging helps to study pain mechanisms and might be used as proxy measures of pain in persons unable to provide verbal reports. Yet eliminating pain ratings or replacing them with neuroimaging data is misguided because brain images only help explain pain if they are used in conjunction with self-report. There is no objective readout mechanism of pain (pain thermometer) that is unaffected by psychological factors. Benefits from including neuroimaging data might include increased understanding of underlying neural mechanisms of treatment efficacy, discovery of new treatment vectors, and support of conclusions derived from self-report. However, neither brain imaging nor self-report data are privileged over the other. The assumption that treatment efficacy is hampered by self-report has not been shown; there is a plethora of treatment studies showing that self-report is sensitive to treatment. Dismissal of patients' self-reports (pain ratings) by brain-imaging data is potentially harmful. The aim of replacing self-report with brain-imaging data is misguided and has no scientific or philosophical foundation. ⋯ Although brain imaging may offer considerable insight into the neural mechanisms of pain, including relevant causes and correlations, brain images cannot and should not replace self-report. Only the latter assesses the experience of pain, which is not identical to neural activity. Brain imaging may help to explain pain, but replacing self-report with brain-imaging data would be philosophically and scientifically misguided and potentially harmful to pain patients.
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ClinicalTrials.gov is a registry and results database of federally and privately supported clinical trials conducted worldwide. We sought to answer: what are the characteristics of pain trials; how frequently are these trials stopped and why; what is the magnitude of attrition due to lack of efficacy or adverse events; and whether the withdrawal rates depend on pain syndrome. To facilitate this and subsequent studies, we have developed a system called Sherlock that automatically downloads data from ClinicalTrials.gov into a relational database. We included pain interventional trials. To evaluate attrition, we restricted consideration to prospective randomized, parallel, double-blind, placebo-controlled trials. Of the 82,867 trials, 6% reported results and 5.6% terminated before the planned number of subjects was accrued. Of these early terminations, 38% were due to enrollment difficulties. In the placebo arms, 3.8% of participants withdrew due to lack of efficacy and 4.9% due to adverse events, with proportions differing among pain conditions. Compared with migraine trials, in fibromyalgia trials 5.1% more participants withdrew due to lack of efficacy (95% confidence interval [CI], 2.5-7.8%), and 6.4% more withdrew due to adverse events (95% CI, 4.3-8.6%). Nonsteroidal anti-inflammatory drugs were the treatment class with the lowest adverse events withdrawals. Recruitment challenges account for the largest proportion of noncompleted trials. Attrition rates differ across pain conditions. Migraine studies had the lowest withdrawal rate. Tools like Sherlock facilitate conducting research in the ClinicalTrials.gov registry. ⋯ ClinicalTrials.gov registry enables researchers to get a snapshot of a specific field and observe changes over time in trial design, including numbers of subjects accrued, and it can inform clinical trial design. We learned that recruitment challenges account for the largest proportion of noncompleted trials, attrition rates differed across pain conditions, and migraine studies had the lowest withdrawal rate.
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Multiple investigators have recently asked whether neuroimaging has shown that chronic pain is a brain disease. We review the clinical implications of seeing chronic pain as a brain disease. Abnormalities noted on imaging of peripheral structures have previously misled the clinical care of patients with chronic pain. We also cannot assume that the changes associated with chronic pain on neuroimaging are causal. When considering the significance of neuroimaging results, it is important to remember that "disease" is a concept that arises out of clinical medicine, not laboratory science. Following Canguilhem, we believe that disease is best defined as a structural or functional change that causes disvalue to the whole organism. It is important to be cautious in our assertions about chronic pain as a brain disease because these may have negative effects on 1) the therapeutic dialogue between clinicians and patients; 2) the social dialogue about reimbursement for pain treatments and disability due to pain; and 3) the chronic pain research agenda. Considered scientifically, we may be looking for the cause of chronic pain through neuroimaging, but considered clinically, we are in fact often looking to validate pain complaints. We should not yield to the temptation to validate pain with the magnetic resonance imaging scanner (structural or functional). We should not see pain as caused by the brain alone. Pain is not felt by the brain, but by the person. ⋯ Neuroimaging investigators have argued that brain imaging may demonstrate that chronic pain is a brain disease. We argue that "disease" is a clinical concept and that conceiving of chronic pain as a brain disease can have negative consequences for research and clinical care of patients with chronic pain.