Transforming pain medicine: adapting to science and society

Advancements in Understanding and Classifying Chronic Orofacial Pain: Key Insights from Biopsychosocial Models and International Classifications (ICHD-3, ICD-11, ICOP)

In exploring chronic orofacial pain (COFP), this review highlights its global impact on life quality and critiques current diagnostic systems, including the ICD-11, ICOP, and ICHD-3, for their limitations in addressing COFP's complexity. Firstly, this study outlines the global burden of chronic pain and the importance of distinguishing between different pain types for effective treatment. It then delves into the specific challenges of diagnosing COFP, emphasizing the need for a more nuanced approach that incorporates the biopsychosocial model. This review critically examines existing classification systems, highlighting their limitations in fully capturing COFP's multifaceted nature. It advocates for the integration of these systems with the DSM-5's Somatic Symptom Disorder code, proposing a unified, multidisciplinary diagnostic approach. This recommendation aims to improve chronic pain coding standardization and acknowledge the complex interplay of biological, psychological, and social factors in COFP. In conclusion, here, we highlight the need for a comprehensive, universally applicable classification system for COFP. Such a system would enable accurate diagnosis, streamline treatment strategies, and enhance communication among healthcare professionals. This advancement holds potential for significant contributions to research and patient care in this challenging field, offering a broader perspective for scientists across disciplines.

A Novel Molecular Reservoir Based on Reverse Self-Assembled Liquid Crystals - A New Strategy for Prolonging the Duration in Action of Analgesics

PURPOSE

The aim of this study was to develop liquid crystal (LC) precursors to obtain novel long-acting analgesics for injection based on depot systems and compare the difference between the cubic and hexagonal precursors in delivering Diclofenac sodium (DS).

METHODS

Diclofenac sodium liquid crystal precursor injections were prepared and characterized, followed by in vitro release, pharmacodynamic, and pharmacokinetic studies.

RESULTS

The optimal formulations were prepared with a ratio of Phytantriol/ethanol/water as 76:19:5 for cubic LC precursors, and a ratio of Phytantriol/ethanol/water/Vitamine-E acetate as 72:18:5:5 for hexagonal, both loading various drug dosages (2.5%, 3.75% and 5%), respectively. Polarized light microscopy and small angle diffraction confirmed that the precursors were isotropic fluids and transformed into gels with Pn3m or HII framework in water. Rheological studies have shown that precursors belong to Newtonian fluids and gels to pseudoplastic fluids. The release showed that the DS in the commercial injection (DS-inj) was completely liberated within 6 h, whereas only 46.55% and 49.73% of the DS in 2.5% cubic precursors and 2.5% hexagonal precursors were freed, respectively. Pharmacodynamic studies have shown that cubic, hexagonal and DS-inj raised the pain threshold in mice by 169.4%, 157.3% and 113.79%, respectively. The mean retention times of DS in cubic and hexagonal were 3.16 and 2.67 times longer than DS-inj, respectively, according to pharmacokinetic results.

CONCLUSION

In conclusion, cubic and hexagonal are both promising analgesic sustained release formulations. In addition, based only on the current comparison, cubic seems to have a better long-acting effect.

Signature for Pain Recovery IN Teens (SPRINT): protocol for a multisite prospective signature study in chronic musculoskeletal pain

INTRODUCTION

Current treatments for chronic musculoskeletal (MSK) pain are suboptimal. Discovery of robust prognostic markers separating patients who recover from patients with persistent pain and disability is critical for developing patient-specific treatment strategies and conceiving novel approaches that benefit all patients. Given that chronic pain is a biopsychosocial process, this study aims to discover and validate a robust prognostic signature that measures across multiple dimensions in the same adolescent patient cohort with a computational analysis pipeline. This will facilitate risk stratification in adolescent patients with chronic MSK pain and more resourceful allocation of patients to costly and potentially burdensome multidisciplinary pain treatment approaches.

METHODS AND ANALYSIS

Here we describe a multi-institutional effort to collect, curate and analyse a high dimensional data set including epidemiological, psychometric, quantitative sensory, brain imaging and biological information collected over the course of 12 months. The aim of this effort is to derive a multivariate model with strong prognostic power regarding the clinical course of adolescent MSK pain and function.

ETHICS AND DISSEMINATION

The study complies with the National Institutes of Health policy on the use of a single internal review board (sIRB) for multisite research, with Cincinnati Children's Hospital Medical Center Review Board as the reviewing IRB. Stanford's IRB is a relying IRB within the sIRB. As foreign institutions, the University of Toronto and The Hospital for Sick Children (SickKids) are overseen by their respective ethics boards. All participants provide signed informed consent. We are committed to open-access publication, so that patients, clinicians and scientists have access to the study data and the signature(s) derived. After findings are published, we will upload a limited data set for sharing with other investigators on applicable repositories.

TRIAL REGISTRATION NUMBER

NCT04285112.

Health-related quality of life in patients with chronic orofacial pain compared with other chronic pain patients

Background

Health‐related quality of life (HRQoL) of orofacial pain patients is lower than that of the general population and impaired in multiple dimensions. The aim of the present study was to investigate HRQoL of orofacial pain patients in comparison with patients suffering from other chronic pain disorders.

Materials and Methods

One hundred and fifty‐one tertiary care facial pain patients (mean age, 50 years; standard deviation [SD], 15; 119 females), were compared with 312 other non‐cancer chronic pain patients (mean age, 46 years; SD, 13; 204 women), recruited from three multidisciplinary pain clinics in Finland. The groups were compared using the 15D, and pain‐related measures such as pain interference, pain acceptance, anxiety, depression, and sleep. Statistical comparisons between groups were done using t test, χ² test, or analysis of covariance. Multivariate linear regression analysis was used to study whether pain‐related aspects influencing HRQoL are similar between the patient groups.

Results

The 15D score was significantly higher in facial pain patients (0.823; SD, 0.114) indicating better HRQoL in comparison with other chronic pain patients (0.732; SD, 0.107) (p < .001). The 15D profiles of studied populations resembled each other but orofacial pain patients showed significantly higher scores for most individual 15D dimensions. Dimensions regarding discomfort and symptoms and sleep were most affected in both groups. Orofacial pain patients showed less psychosocial disability and better acceptance of their pain. Pain acceptance was a weaker explanatory factor of HRQoL in orofacial pain patients.

Conclusion

Compared to other non‐cancer chronic pain, chronic pain in the orofacial area causes less impairment in HRQoL. Orofacial pain patients showed less psychosocial disability and better pain acceptance.

Assessing the Value of Time Series Real-World and Clinical Trial Data vs. Baseline-Only Data in Predicting Responses to Pregabalin Therapy for Patients with Painful Diabetic Peripheral Neuropathy

BACKGROUND AND OBJECTIVE

Treatment challenges necessitate new approaches to customize care to individual patient needs. Integrating data from randomized controlled trials and observational studies may reduce potential covariate biases, yielding information to improve treatment outcomes. The objective of this study was to predict pregabalin responses, in individuals with painful diabetic peripheral neuropathy, by examining time series data (lagged inputs) collected after treatment initiation vs. baseline using microsimulation.

METHODS

The platform simulated pregabalin-treated patients to estimate hypothetical future pain responses over 6 weeks based on six distinct time series regressions with lagged variables as inputs (hereafter termed "time series regressions"). Data were from three randomized controlled trials (N = 398) and an observational study (N = 3159). Regressions were derived after performing a hierarchical cluster analysis with a matched patient dataset from coarsened exact matching. Regressions were validated using unmatched (observational study vs. randomized controlled trial) patients. Predictive implications (of 6-week outcomes) were compared using only baseline vs. 1- to 2-week prior data.

RESULTS

Time series regressions for pain performed well (adjusted R² 0.85-0.91; root mean square error 0.53-0.57); those with only baseline data performed less well (adjusted R² 0.13-0.44; root mean square error 1.11-1.40). Simulated patient distributions yielded positive predictive values for > 50% pain score improvements from baseline for the six clusters (287-777 patients each; range 0.87-0.98).

CONCLUSIONS

Effective prediction of pregabalin response for painful diabetic peripheral neuropathy was accomplished through combining cluster analyses, coarsened exact matching, and time series regressions, reflecting distinct patterns of baseline and "on-treatment" variables. These results advance the understanding of microsimulation to predict patient treatment responses through integration and inter-relationships of multiple, complex, and time-dependent characteristics.

Ten simple rules for predictive modeling of individual differences in neuroimaging

Establishing brain-behavior associations that map brain organization to phenotypic measures and generalize to novel individuals remains a challenge in neuroimaging. Predictive modeling approaches that define and validate models with independent datasets offer a solution to this problem. While these methods can detect novel and generalizable brain-behavior associations, they can be daunting, which has limited their use by the wider connectivity community. Here, we offer practical advice and examples based on functional magnetic resonance imaging (fMRI) functional connectivity data for implementing these approaches. We hope these ten rules will increase the use of predictive models with neuroimaging data.

When pain gets stuck: the evolution of pain chronification and treatment resistance

It is well-recognized that, despite similar pain characteristics, some people with chronic pain recover, whereas others do not. In this review, we discuss possible contributions and interactions of biological, social, and psychological perturbations that underlie the evolution of treatment-resistant chronic pain. Behavior and brain are intimately implicated in the production and maintenance of perception. Our understandings of potential mechanisms that produce or exacerbate persistent pain remain relatively unclear. We provide an overview of these interactions and how differences in relative contribution of dimensions such as stress, age, genetics, environment, and immune responsivity may produce different risk profiles for disease development, pain severity, and chronicity. We propose the concept of "stickiness" as a soubriquet for capturing the multiple influences on the persistence of pain and pain behavior, and their stubborn resistance to therapeutic intervention. We then focus on the neurobiology of reward and aversion to address how alterations in synaptic complexity, neural networks, and systems (eg, opioidergic and dopaminergic) may contribute to pain stickiness. Finally, we propose an integration of the neurobiological with what is known about environmental and social demands on pain behavior and explore treatment approaches based on the nature of the individual's vulnerability to or protection from allostatic load.

Predicting Responses to Pregabalin for Painful Diabetic Peripheral Neuropathy Based on Trajectory-Focused Patient Profiles Derived from the First 4 Weeks of Treatment

Introduction

Prediction of final clinical outcomes based on early weeks of treatment can enable more effective patient care for chronic pain. Our goal was to predict, with at least 90% accuracy, 12- to 13-week outcomes for pregabalin-treated painful diabetic peripheral neuropathy (pDPN) patients based on 4 weeks of pain and pain-related sleep interference data.

Methods

We utilized active treatment data from six placebo-controlled randomized controlled trials (n = 939) designed to evaluate efficacy of pregabalin for reducing pain in patients with pDPN. We implemented a three-step, trajectory-focused analytics approach based upon patient responses collected during the first 4 weeks using monotonicity, path length, frequency domain (FD), and k-nearest neighbor (kNN) methods. The first two steps were based on combinations of baseline pain, pain at 4 weeks, weekly monotonicity and path length during the first 4 weeks, and assignment of patients to one of four responder groups (based on presence/absence of 50% or 30% reduction from baseline pain at 4 and at 12/13 weeks). The third step included agreement between prediction of logistic regression of daily FD amplitudes and assignment made from kNN analyses.

Results

Step 1 correctly assigned 520/939 patients from the six studies to a responder group using a 3-metric combination approach based on unique assignment to a 50% responder group. Step 2 (applied to the remaining 419 patients) predicted an additional 121 patients, using a blend of 50% and 30% responder thresholds. Step 3 (using a combination of FD and kNN analyses) predicted 204 of the remaining 298 patients using the 50% responder threshold. Our approach correctly predicted 90.0% of all patients.

Conclusion

By correctly predicting 12- to 13-week responder outcomes with 90% accuracy based on responses from the first month of treatment, we demonstrated the value of trajectory measures in predicting pDPN patient response to pregabalin.

Trial Registration

www.clinicaltrials.gov identifiers, NCT00156078/NCT00159679/NCT00143156/NCT00553475.

Funding

Pfizer.

Plain Language Summary

Plain language summary available for this article.

Electronic supplementary material

The online version of this article (10.1007/s12325-018-0780-3) contains supplementary material, which is available to authorized users.

Region-Resolved Quantitative Proteome Profiling Reveals Molecular Dynamics Associated With Chronic Pain in the PNS and Spinal Cord

To obtain a thorough understanding of chronic pain, large-scale molecular mapping of the pain axis at the protein level is necessary, but has not yet been achieved. We applied quantitative proteome profiling to build a comprehensive protein compendium of three regions of the pain neuraxis in mice: the sciatic nerve (SN), the dorsal root ganglia (DRG), and the spinal cord (SC). Furthermore, extensive bioinformatics analysis enabled us to reveal unique protein subsets which are specifically enriched in the peripheral nervous system (PNS) and SC. The immense value of these datasets for the scientific community is highlighted by validation experiments, where we monitored protein network dynamics during neuropathic pain. Here, we resolved profound region-specific differences and distinct changes of PNS-enriched proteins under pathological conditions. Overall, we provide a unique and validated systems biology proteome resource (summarized in our online database painproteome.em.mpg.de), which facilitates mechanistic insights into somatosensory biology and chronic pain—a prerequisite for the identification of novel therapeutic targets.

Validation of EQ-5D and 15D in the assessment of health-related quality of life in chronic pain

Chronic pain has a significant impact on quality of life. Measurement of health-related quality of life (HRQoL) is essential in the assessment of pain management outcomes, but different instruments have produced varying results. We assessed the validity of 2 HRQoL instruments, EuroQol 5 dimensions questionnaire (EQ-5D) and 15-dimensional health-related quality of life measure (15D), in patients with challenging chronic pain. Three hundred ninety-one chronic noncancer pain patients referred to tertiary pain clinics completed EQ-5D, 15D, and a broad set of questionnaires mapping socioeconomic factors, self-rated health, pain intensity and interference, depression, pain acceptance, pain-related anxiety, and sleep. The 2 HRQoL instruments were compared with each other, and head-to-head comparisons were made with self-rated health and the symptom-specific questionnaires. 15D and EQ-5D showed moderate agreement (ρ = 0.66), but there were also considerable differences between the instruments. 15D correlated better with self-rated health than EQ-5D (ρ = -0.62 vs -0.45, P < 0.001). The EQ-5D appeared less sensitive than 15D especially in those patients with chronic pain who had a better health status. The principal component constructed from measures of pain intensity and interference, anxiety, pain acceptance, depression, and sleep had higher standardized beta coefficients with 15D than with EQ-5D (P = 0.038). The principal component explained more variance in the 15D (R = 0.65) than in the EQ-5D (R = 0.43). The study identified differences in the pain-related variables between the EQ-5D and the 15D. In patients with chronic pain, both instruments are valid, but 15D appears somewhat more sensitive than EQ-5D.

Dose Titration of Pregabalin in Patients with Painful Diabetic Peripheral Neuropathy: Simulation Based on Observational Study Patients Enriched with Data from Randomized Studies

INTRODUCTION

Achieving a therapeutic response to pregabalin in patients with painful diabetic peripheral neuropathy (pDPN) requires adequate upward dose titration. Our goal was to identify relationships between titration and response to pregabalin in patients with pDPN.

METHODS

Data were integrated from nine randomized, placebo-controlled clinical trials as well as one 6-week open-label observational study conducted by 5808 physicians (2642 patients with pDPN) in standard outpatient settings in Germany. These studies evaluated pregabalin for treatment of pDPN. Using these data, we examined "what if" scenarios using a microsimulation platform that integrates data from randomized and observational sources as well as autoregressive-moving-average with exogenous inputs models that predict pain outcomes, taking into account weekly changes in pain, sleep interference, dose, and other patient characteristics that were unchanging.

RESULTS

Final pain levels were significantly different depending on dose changes (P < 0.0001), with greater proportions improving with upward titration regardless of baseline pain severity. Altogether, 78.5% of patients with pDPN had 0-1 dose change, and 15.2% had ≥ 2 dose changes. Simulation demonstrated that the 4.8% of inadequately titrated patients who did not improve/very much improve their pain levels would have benefited from ≥ 2 dose changes. Patient satisfaction with tolerability (range 90.3-96.2%) was similar, regardless of baseline pain severity, number of titrations, or extent of improvement, suggesting that tolerability did not influence treatment response patterns.

CONCLUSION

Upward dose titration reduced pain in patients with pDPN who actually received it. Simulation also predicted pain reduction in an inadequately titrated nonresponder subgroup of patients had they actually received adequate titration. The decision not to uptitrate must have been driven by factors other than tolerability.

FUNDING

Pfizer, Inc.

Vulvodynia: a consideration of clinical and methodological research challenges and recommended solutions

Vulvodynia, an idiopathic chronic vulvar pain, is a prevalent genital pain condition that results in significant impairment to sexual, relational, and psychological functioning of affected women and their romantic partners. Despite its high prevalence, there remain gaps in knowledge and health care access for women coping with vulvodynia, given its varied clinical presentation and no widely accepted treatment protocol. The past several decades have seen important advancements in understanding vulvodynia and developing effective treatments; however, progress has been impeded due to clinical and methodological challenges in conducting research with this vulnerable population. This review presents a brief overview of vulvodynia correlates, consequences, etiology, and treatment, and then turns its attention to considering the clinical and methodological challenges that hinder vulvodynia research. Identifying these barriers alongside potential mitigating solutions is essential to developing empirically supported treatments for all women affected by vulvodynia, across all age and minority groups. Potential solutions will require researchers to broaden eligibility criteria, examine subgroups of women, and expand definitions of treatment outcomes, and may be best facilitated by more active collaboration among research groups and across relevant disciplines. Engagement in these solutions may contribute to more representative findings and the development and dissemination of empirically based treatment options for this complex pain condition.

Brain imaging tests for chronic pain: medical, legal and ethical issues and recommendations

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.

Integrating data from randomized controlled trials and observational studies to predict the response to pregabalin in patients with painful diabetic peripheral neuropathy

BACKGROUND

More patient-specific medical care is expected as more is learned about variations in patient responses to medical treatments. Analytical tools enable insights by linking treatment responses from different types of studies, such as randomized controlled trials (RCTs) and observational studies. Given the importance of evidence from both types of studies, our goal was to integrate these types of data into a single predictive platform to help predict response to pregabalin in individual patients with painful diabetic peripheral neuropathy (pDPN).

METHODS

We utilized three pivotal RCTs of pregabalin (398 North American patients) and the largest observational study of pregabalin (3159 German patients). We implemented a hierarchical cluster analysis to identify patient clusters in the Observational Study to which RCT patients could be matched using the coarsened exact matching (CEM) technique, thereby creating a matched dataset. We then developed autoregressive moving average models (ARMAXs) to estimate weekly pain scores for pregabalin-treated patients in each cluster in the matched dataset using the maximum likelihood method. Finally, we validated ARMAX models using Observational Study patients who had not matched with RCT patients, using t tests between observed and predicted pain scores.

RESULTS

Cluster analysis yielded six clusters (287-777 patients each) with the following clustering variables: gender, age, pDPN duration, body mass index, depression history, pregabalin monotherapy, prior gabapentin use, baseline pain score, and baseline sleep interference. CEM yielded 1528 unique patients in the matched dataset. The reduction in global imbalance scores for the clusters after adding the RCT patients (ranging from 6 to 63% depending on the cluster) demonstrated that the process reduced the bias of covariates in five of the six clusters. ARMAX models of pain score performed well (R ² : 0.85-0.91; root mean square errors: 0.53-0.57). t tests did not show differences between observed and predicted pain scores in the 1955 patients who had not matched with RCT patients.

CONCLUSION

The combination of cluster analyses, CEM, and ARMAX modeling enabled strong predictive capabilities with respect to pain scores. Integrating RCT and Observational Study data using CEM enabled effective use of Observational Study data to predict patient responses.

Circles of engagement: Childhood pain and parent brain

Social interaction can have a profound effect on individual behavior, perhaps most salient in interactions between sick suffering children and their parents. Chronic pain is a difficult condition that can produce considerable changes in children's behaviors that can secondarily have profound effects on their parents. It may create a functionally disabling negative feedback loop. Research supports the notion of alterations in the brain of individuals who observe and empathize with loved ones in acute pain. However, neural activity in relation to empathic responses in the context of chronic pain has not been examined. Ongoing suffering with chronic pain in a child can result in child's brain circuit alterations. Moreover, prolonged suffering jointly experienced by the parent may putatively produce maladaptive changes in their neural networks and consequently in parental behaviors. Here we put forth the conceptual framework for 'Chronic pain contagion' (CPC). We review the underlying processes in CPC and discuss implications for devising and implementing treatments for children in chronic pain and their parents.

Pain in an era of armed conflicts: Prevention and treatment for warfighters and civilian casualties

Chronic pain is a common squealae of military- and terror-related injuries. While its pathophysiology has not yet been fully elucidated, it may be potentially related to premorbid neuropsychobiological status, as well as to the type of injury and to the neural alterations that it may evoke. Accordingly, optimized approaches for wounded individuals should integrate primary, secondary and tertiary prevention in the form of thorough evaluation of risk factors along with specific interventions to contravene and mitigate the ensuing chronicity. Thus, Premorbid Events phase may encompass assessments of psychological and neurobiological vulnerability factors in conjunction with fostering preparedness and resilience in both military and civilian populations at risk. Injuries per se phase calls for immediate treatment of acute pain in the field by pharmacological agents that spare and even enhance coping and adaptive capabilities. The key objective of the Post Injury Events is to prevent and/or reverse maladaptive peripheral- and central neural system's processes that mediate transformation of acute to chronic pain and to incorporate timely interventions for concomitant mental health problems including post-traumatic stress disorder and addiction We suggest that the proposed continuum of care may avert more disability and suffering than the currently employed less integrated strategies. While the requirements of the armed forces present a pressing need for this integrated continuum and a framework in which it can be most readily implemented, this approach may be also instrumental for the care of civilian casualties.

Psychological processing in chronic pain: a neural systems approach

Our understanding of chronic pain involves complex brain circuits that include sensory, emotional, cognitive and interoceptive processing. The feed-forward interactions between physical (e.g., trauma) and emotional pain and the consequences of altered psychological status on the expression of pain have made the evaluation and treatment of chronic pain a challenge in the clinic. By understanding the neural circuits involved in psychological processes, a mechanistic approach to the implementation of psychology-based treatments may be better understood. In this review we evaluate some of the principle processes that may be altered as a consequence of chronic pain in the context of localized and integrated neural networks. These changes are ongoing, vary in their magnitude, and their hierarchical manifestations, and may be temporally and sequentially altered by treatments, and all contribute to an overall pain phenotype. Furthermore, we link altered psychological processes to specific evidence-based treatments to put forth a model of pain neuroscience psychology.