The journal of pain : official journal of the American Pain Society
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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.
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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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Review Historical Article
The infancy of infant pain research: the experimental origins of infant pain denial.
Skepticism toward infant pain characterized much of 20th century research and clinical practice, with infant surgery routinely conducted with minimal or no anesthesia into the 1980s. This paper offers a historical exploration of how this view became common by reviewing and analyzing the experimental infant pain research of the 19th and early 20th centuries that contributed to the development of infant pain denial. These experiments used pinprick and electric shock, and the results were generally interpreted as evidence of infants' underdeveloped pain perception, attributed to their lack of brain maturation. Even clear responses to noxious stimuli were often dismissed as reflex responding. Later these experimental findings were used by anesthesiologists to support the lessened use of anesthesia for infants. Based on the reviewed literature, this paper suggests that 4 interrelated causes contributed to the denial of infant pain: the Darwinian view of the child as a lower being, extreme experimental caution, the mechanistic behaviorist perspective, and an increasing emphasis on brain and nervous system development. Ultimately this history can be read as a caution to modern researchers to be aware of their own biases, the risks of null hypothesis testing, and a purely mechanistic view of infants. ⋯ This article reviews the history of 19th and early 20th century infant pain research, tracing how the widely accepted belief that infants could not feel pain developed in the period prior to the growing acceptance of infant pain. Four interrelated causes are posited to help explain the tolerance of infant pain denial until recent times.
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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.