The journal of pain : official journal of the American Pain Society
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Measurement of inappropriate medication use events (eg, abuse or misuse) in clinical trials is important in characterizing a medication's abuse potential. However, no gold standard assessment of inappropriate use events in clinical trials has been identified. In this systematic review, we examine the measurement properties (ie, content validity, cross-sectional reliability and construct validity, longitudinal construct validity, ability to detect change, and responder definitions) of instruments assessing inappropriate use of opioid and nonopioid prescription medications to identify any that meet U.S. and European regulatory agencies' rigorous standards for outcome measures in clinical trials. Sixteen published instruments were identified, most of which were not designed for the selected concept of interest and context of use. For this reason, many instruments were found to lack adequate content validity (or documentation of content validity) to evaluate current inappropriate medication use events; for example, evaluating inappropriate use across the life span rather than current use, including items that did not directly assess inappropriate use (eg, questions about anger), or failing to capture information pertinent to inappropriate use events (eg, intention and route of administration). In addition, the psychometric data across all instruments were generally limited in scope. A further limitation is the heterogeneous, nonstandardized use of inappropriate medication use terminology. These observations suggest that available instruments are not well suited for assessing current inappropriate medication use within the specific context of clinical trials. Further effort is needed to develop reliable and valid instruments to measure current inappropriate medication use events in clinical trials. ⋯ This systematic review evaluates the measurement properties of inappropriate medication use (eg, abuse or misuse) instruments to determine whether any meet regulatory standards for clinical trial outcome measures to assess abuse potential.
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Studies indicate that improving sleep decreases reported pain in patients with knee osteoarthritis, but it is unclear if this association extends to experimentally induced pain responses. A community-based sample of 88 African American and 52 non-Hispanic white adults (45-76 years) with knee osteoarthritis completed the Insomnia Severity Index and the arousal subscale of the Sleep Hygiene and Practices Scale. Participants underwent quantitative sensory testing, including measures of pain sensitivity and facilitation at the knee, and pain inhibition. Outcomes were analyzed with multiple Tobit hierarchical regression models, with adjustment for relevant covariates. Ethnicity and sex by sleep interactions were also entered into the models. After covariate adjustment, main associations were not observed. However, sex interacted with insomnia severity to predict greater temporal summation of heat and punctate pressure pain among women and lower heat temporal summation among men. Men and women who engaged in frequent arousal-associated sleep behaviors demonstrated higher and lower heat temporal summation, respectively. Non-Hispanic whites with greater insomnia severity displayed lower pressure pain thresholds and pain inhibition. Our findings are the first to demonstrate that disrupted sleep is associated with altered pain processing differentially by sex and ethnicity/race among people with knee osteoarthritis. ⋯ This article presents the association between insomnia severity, maladaptive sleep behaviors, and experimentally induced pain responses among people with knee osteoarthritis. Disrupted sleep was associated with altered pain processing by sex and ethnicity/race. Offering sleep interventions may help ameliorate pain, but treatment may need to be tailored by sex and ethnicity/race.
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Belief in the effectiveness of a placebo treatment is widely thought to be critical for placebo analgesia. Many types of placebo responses--even those that depend on conditioning--appear to be mediated by expectations that are strengthened as treatment cues are reinforced with positive outcomes. However, placebo effects may occur even when participants are aware they are receiving a placebo. To address the question of whether conditioned placebo analgesia can persist in the absence of expectations, we studied the effects of long (4 days) versus short (1 day) conditioning to a placebo treatment. After an initial placebo test, a "reveal" manipulation convincingly demonstrated to participants that they had never received an active drug. Placebo analgesia persisted after the reveal in the long conditioning group only. These findings suggest that reinforcing treatment cues with positive outcomes can create placebo effects that are independent of reported expectations for pain relief. ⋯ This article demonstrates a form of placebo analgesia that relies on prior conditioning rather than current expected pain relief. This highlights the importance of prior experience on pain relief and offers insight into the variability of placebo effects across individuals.
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Comparative Study
Comparison of machine classification algorithms for fibromyalgia: neuroimages versus self-report.
Recent studies have posited that machine learning (ML) techniques accurately classify individuals with and without pain solely based on neuroimaging data. These studies claim that self-report is unreliable, making "objective" neuroimaging classification methods imperative. However, the relative performance of ML on neuroimaging and self-report data have not been compared. This study used commonly reported ML algorithms to measure differences between "objective" neuroimaging data and "subjective" self-report (ie, mood and pain intensity) in their ability to discriminate between individuals with and without chronic pain. Structural magnetic resonance imaging data from 26 individuals (14 individuals with fibromyalgia and 12 healthy controls) were processed to derive volumes from 56 brain regions per person. Self-report data included visual analog scale ratings for pain intensity and mood (ie, anger, anxiety, depression, frustration, and fear). Separate models representing brain volumes, mood ratings, and pain intensity ratings were estimated across several ML algorithms. Classification accuracy of brain volumes ranged from 53 to 76%, whereas mood and pain intensity ratings ranged from 79 to 96% and 83 to 96%, respectively. Overall, models derived from self-report data outperformed neuroimaging models by an average of 22%. Although neuroimaging clearly provides useful insights for understanding neural mechanisms underlying pain processing, self-report is reliable and accurate and continues to be clinically vital. ⋯ The present study compares neuroimaging, self-reported mood, and self-reported pain intensity data in their ability to classify individuals with and without fibromyalgia using ML algorithms. Overall, models derived from self-reported mood and pain intensity data outperformed structural neuroimaging models.
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Use of multiple pharmacies concurrently (pharmacy shopping) and overlapping prescriptions may be indicators of potential misuse or abuse of prescription opioid medications. To evaluate strategies for identifying patients at high risk, we first compared different definitions of pharmacy shopping and then added the indicator of overlapping opioid prescriptions. We identified a cohort of 90,010 Medicaid enrollees who used ≥ 3 opioid prescriptions for ≥ 90 days during 2008 to 2010 from a multistate Medicaid claims database. We compared the diagnostic odds ratios for opioid overdose events of 9 pharmacy shopping definitions. Within a 90-day interval, a threshold of 4 pharmacies had the highest diagnostic odds ratio and was used to define pharmacy shopping. The overdose rate was higher in the subgroup with overlapping prescriptions (18.5 per 1,000 person-years [PYs]) than in the subgroup with pharmacy shopping as the sole indicator (10.7 per 1,000 PYs). Among the subgroup with both conditions, the overdose rate was 26.3 per 1,000 PYs, compared with 4.3 per 1,000 PYs for those with neither condition. Overlapping opioid prescriptions and pharmacy shopping measures had adjusted hazard ratios of 3.0 and 1.8, respectively, for opioid overdose. Using these measures will improve accurate identification of patients at highest risk of opioid overdose, the first step in implementing targeted prevention policies. ⋯ Long-term prescription opioid use may lead to adverse events, including overdose. Both pharmacy shopping and overlapping opioid prescriptions are associated with adverse outcomes. This study demonstrates that using both indicators will better identify those at high risk of overdose.