Chronic pain is the greatest source of disability globally and claims related to chronic pain feature in many insurance and medico-legal cases. Brain imaging (for example, functional MRI, PET, EEG and magnetoencephalography) is widely considered to have potential for diagnosis, prognostication, and prediction of treatment outcome in patients with chronic pain. In this Consensus Statement, a presidential task force of the International Association for the Study of Pain examines the capabilities of brain imaging in the diagnosis of chronic pain, and the ethical and legal implications of its use in this way. The task force emphasizes that the use of brain imaging in this context is in a discovery phase, but has the potential to increase our understanding of the neural underpinnings of chronic pain, inform the development of therapeutic agents, and predict treatment outcomes for use in personalized pain management. The task force proposes standards of evidence that must be satisfied before any brain imaging measure can be considered suitable for clinical or legal purposes. The admissibility of such evidence in legal cases also strongly depends on laws that vary between jurisdictions. For these reasons, the task force concludes that the use of brain imaging findings to support or dispute a claim of chronic pain - effectively as a pain lie detector - is not warranted, but that imaging should be used to further our understanding of the mechanisms underlying pain.
Hah JM, Sturgeon JA, Zocca J, Sharifzadeh Y, Mackey SC. Factors associated with prescription opioid misuse in a cross-sectional cohort of patients with chronic non-cancer pain. J. Pain Res. 2017;10:979-987.
OBJECTIVE: To examine demographic features, psychosocial characteristics, pain-specific behavioral factors, substance abuse history, sleep, and indicators of overall physical function as predictors of opioid misuse in patients presenting for new patient evaluation at a tertiary pain clinic. METHODS: Overall, 625 patients with chronic non-cancer pain prospectively completed the Collaborative Health Outcomes Information Registry, assessing pain catastrophizing, National Institutes of Health Patient-Reported Outcomes Measurement Information System standardized measures (pain intensity, pain behavior, pain interference, physical function, sleep disturbance, sleep-related impairment, anger, depression, anxiety, and fatigue), and substance use history. Additional information regarding current opioid prescriptions and opioid misuse was examined through retrospective chart review. RESULTS: In all, 41 (6.6%) patients presented with some indication of prescription opioid misuse. In the final multivariable logistic regression model, those with a history of illicit drug use (odds ratio [OR] 5.45, 95% confidence interval [CI] 2.48-11.98, p\textless0.0001) and a current opioid prescription (OR 4.06, 95% CI 1.62-10.18, p=0.003) were at elevated risk for opioid misuse. Conversely, every 1-h increase in average hours of nightly sleep decreased the risk of opioid misuse by 20% (OR 0.80, 95% CI 0.66-0.97, p=0.02). CONCLUSION: These findings indicate the importance of considering substance use history, current opioid prescriptions, and sleep in universal screening of patients with chronic non-cancer pain for opioid misuse. Future work should target longitudinal studies to verify the causal relationships between these variables and subsequent opioid misuse.
Clinical diagnosis of complex regional pain syndrome (CRPS) is a dichotomous (yes/no) categorization, a format necessary for clinical decision making. Such dichotomous diagnostic categories do not convey an individual s subtle gradations in the severity of the condition over time and have poor statistical power when used as an outcome measure in research. This prospective, international, multicenter study slightly modified and further evaluated the validity of the CRPS Severity Score (CSS), a continuous index of CRPS severity. Using a prospective design, medical evaluations were conducted in 156 patients with CRPS to compare changes over time in CSS scores between patients initiating a new treatment program and patients on stable treatment regimens. New vs stable categorizations were supported by greater changes in pain and function in the former. Results indicated that CSS values in the stable CRPS treatment group exhibited much less change over time relative to the new treatment group, with intraclass correlations nearly twice as large in the former. A calculated smallest real difference value revealed that a change in the CSS of \$\geq\$4.9 scale points would indicate real differences in CRPS symptomatology (with 95% confidence). Across groups, larger changes in CRPS features on the CSS over time were associated in the expected direction with greater changes in pain intensity, fatigue, social functioning, ability to engage in physical roles, and general well-being. The overall pattern of findings further supports the validity of the CSS as a measure of CRPS severity and suggests it may prove useful in clinical monitoring and outcomes research.
Jarrahi B, Martucci KT, Nilakantan AS, Mackey S. Investigating the BOLD spectral power of the intrinsic connectivity networks in fibromyalgia patients: A resting-state fMRI study. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2017;2017:497-500.
Recent advances in multivariate statistical analysis of blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) have provided novel insights into the network organization of the human brain. Here, we applied group independent component analysis, a well-established approach for detecting brain intrinsic connectivity networks, to examine the spontaneous BOLD fluctuations in patients with fibromyalgia and healthy controls before and after exposure to a stressor. The BOLD spectral power characteristics of component time courses were calculated using the fast Fourier transform (FFT) algorithm, and group comparison was performed at six frequency bins between 0 and 0.24 Hz at 0.04 Hz intervals. Relative to controls, patients with fibromyalgia displayed significant BOLD spectral power differences in the default-mode, salience, and subcortical networks at the baseline level (PBon ferroni-corrected \textless; 0.05). Multivariate analysis of covariance (MANCOVA) further revealed significant effects of the cold water temperature, and pain rating on the spectral power of the sensorimotor, salience, and prefrontal networks, while the diagnosis of fibromyalgia influenced the BOLD spectral power of the salience and subcortical networks (PFDR-corrected \textless; 0.05). Since the BOLD spectral power reflects the degree of fluctuations within a network, future studies of the correlation between BOLD spectral power and pain processing can cast additional light on the nature of the central nervous system dysfunction in patients with chronic pain syndromes.
Karayannis N V, Sturgeon JA, Chih-Kao M, Cooley C, Mackey SC. Pain interference and physical function demonstrate poor longitudinal association in people living with pain: a PROMIS investigation. Pain. 2017;158(6):1063-1068.
A primary goal in managing pain is to reduce pain and increase physical function (PF). This goal is also tied to continuing payment for treatment services in many practice guidelines. Pain interference (PI) is often used as a proxy for measurement and reporting of PF in these guidelines. A common assumption is that reductions in PI will translate into improvement in PF over time. This assumption needs to be tested in a clinical environment. Consequently, we used the patient-reported outcomes measurement information system (PROMIS) to describe the topology of the longitudinal relationship between PI in relation to PF. Longitudinal data of 389 people with chronic pain seeking health care demonstrated that PI partially explained the variance in PF at baseline (r = -0.50) and over 90 days of care (r = -0.65). The relationship between pain intensity and PF was not significant when PI was included as a mediator. A parallel process latent growth curve model analysis showed a weak, unidirectional relationship (β = 0.18) between average PF scores and changes in PI over the course of 90 days of care, and no relationship between average PI scores and changes in PF across time. Although PI and PF seem moderately related when measured concurrently, they do not cluster closely together across time. The differential pathways between these 2 domains suggest that therapies that target both the consequences of pain on relevant aspects of persons lives, and capability to perform physical activities are likely required for restoration of a vital life.
Kutch JJ, Labus JS, Harris RE, et al. Resting-state functional connectivity predicts longitudinal pain symptom change in urologic chronic pelvic pain syndrome: a MAPP network study. Pain. 2017;158(6):1069-1082.
Chronic pain symptoms often change over time, even in individuals who have had symptoms for years. Studying biological factors that predict trends in symptom change in chronic pain may uncover novel pathophysiological mechanisms and potential therapeutic targets. In this study, we investigated whether brain functional connectivity measures obtained from resting-state functional magnetic resonance imaging at baseline can predict longitudinal symptom change (3, 6, and 12 months after scan) in urologic chronic pelvic pain syndrome. We studied 52 individuals with urologic chronic pelvic pain syndrome (34 women, 18 men) who had baseline neuroimaging followed by symptom tracking every 2 weeks for 1 year as part of the Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) Research Network study. We found that brain functional connectivity can make a significant prediction of short-term (3 month) pain reduction with 73.1% accuracy (69.2% sensitivity and 75.0% precision). In addition, we found that the brain regions with greatest contribution to the classification were preferentially aligned with the left frontoparietal network. Resting-state functional magnetic resonance imaging measures seemed to be less informative about 6- or 12-month symptom change. Our study provides the first evidence that future trends in symptom change in patients in a state of chronic pain may be linked to functional connectivity within specific brain networks.
Kutch JJ, Ichesco E, Hampson JP, et al. Brain signature and functional impact of centralized pain: a multidisciplinary approach to the study of chronic pelvic pain (MAPP) network study. Pain. 2017;158(10):1979-1991.
Chronic pain is often measured with a severity score that overlooks its spatial distribution across the body. This widespread pain is believed to be a marker of centralization, a central nervous system process that decouples pain perception from nociceptive input. Here, we investigated whether centralization is manifested at the level of the brain using data from 1079 participants in the Multidisciplinary Approach to the Study of Chronic Pelvic Pain Research Network (MAPP) study. Participants with a clinical diagnosis of urological chronic pelvic pain syndrome (UCPPS) were compared to pain-free controls and patients with fibromyalgia, the prototypical centralized pain disorder. Participants completed questionnaires capturing pain severity, function, and a body map of pain. A subset (UCPPS N = 110; fibromyalgia N = 23; healthy control N = 49) underwent functional and structural magnetic resonance imaging. Patients with UCPPS reported pain ranging from localized (pelvic) to widespread (throughout the body). Patients with widespread UCPPS displayed increased brain gray matter volume and functional connectivity involving sensorimotor and insular cortices (P \textless 0.05 corrected). These changes translated across disease diagnoses as identical outcomes were present in patients with fibromyalgia but not pain-free controls. Widespread pain was also associated with reduced physical and mental function independent of pain severity. Brain pathology in patients with centralized pain is related to pain distribution throughout the body. These patients may benefit from interventions targeting the central nervous system.
Sharifzadeh Y, Kao MC, Sturgeon JA, Rico TJ, Mackey S, Darnall BD. Pain Catastrophizing Moderates Relationships between Pain Intensity and Opioid Prescription: Nonlinear Sex Differences Revealed Using a Learning Health System. Anesthesiology. 2017;127(1):136-146.
BACKGROUND: Pain catastrophizing is a maladaptive response to pain that amplifies chronic pain intensity and distress. Few studies have examined how pain catastrophizing relates to opioid prescription in outpatients with chronic pain. METHODS: The authors conducted a retrospective observational study of the relationships between opioid prescription, pain intensity, and pain catastrophizing in 1,794 adults (1,129 women; 63%) presenting for new evaluation at a large tertiary care pain treatment center. Data were sourced primarily from an open-source, learning health system and pain registry and secondarily from manual review of electronic medical records. A binary opioid prescription variable (yes/no) constituted the dependent variable; independent variables were age, sex, pain intensity, pain catastrophizing, depression, and anxiety. RESULTS: Most patients were prescribed at least one opioid medication (57%; n = 1,020). A significant interaction and main effects of pain intensity and pain catastrophizing on opioid prescription were noted (P \textless 0.04). Additive modeling revealed sex differences in the relationship between pain catastrophizing, pain intensity, and opioid prescription, such that opioid prescription became more common at lower levels of pain catastrophizing for women than for men. CONCLUSIONS: Results supported the conclusion that pain catastrophizing and sex moderate the relationship between pain intensity and opioid prescription. Although men and women patients had similar Pain Catastrophizing Scale scores, historically “subthreshold” levels of pain catastrophizing were significantly associated with opioid prescription only for women patients. These findings suggest that pain intensity and catastrophizing contribute to different patterns of opioid prescription for men and women patients, highlighting a potential need for examination and intervention in future studies.
According to the Institute of Medicine Relieving Pain in America Report and the soon to be released National Pain Strategy, pain affects over 100 million Americans and costs our country in over \$500 billion per year. We have a greater appreciation for the complex nature of pain and that it can develop into a disease in itself. As such, we need more efforts on prevention of chronic pain and for interdisciplinary approaches. For precision pain medicine to be successful, we need to link learning health systems with pain biomarkers (eg, genomics, proteomics, patient reported outcomes, brain markers) and its treatment.