Patient-Reported Outcomes and Opioid Use in Outpatients With Chronic Pain

12/15-Lipoxygenases mediate neuropathic-like pain hypersensitivity in female mice

It is estimated that chronic neuropathic pain conditions exhibit up to 10% prevalence in the general population, with increased incidence in females. However, nonsteroidal inflammatory drugs (NSAIDs) are ineffective, and currently indicated prescription treatments such as opioids, anticonvulsants, and antidepressants provide only limited therapeutic benefit. In the current work, we extended previous studies in male rats utilizing a paradigm of central Toll-like receptor 4 (TLR4)-dependent, NSAID-unresponsive neuropathic-like pain hypersensitivity to male and female C57BL/6N mice, uncovering an unexpected hyperalgesic phenotype in female mice following intrathecal (IT) LPS. In contrast to previous reports in female C57BL/6J mice, female C57BL/6N mice displayed tactile and cold allodynia, grip force deficits, and locomotor hyperactivity in response to IT LPS. Congruent with our previous observations in male rats, systemic inhibition of 12/15-Lipoxygenases (12/15-LOX) in female B6N mice with selective inhibitors - ML355 (targeting 12-LOX-p) and ML351 (targeting 15-LOX-1) - completely reversed allodynia and grip force deficits. We demonstrate here that 12/15-LOX enzymes also are expressed in mouse spinal cord and that 12/15-LOX metabolites produce tactile allodynia when administered spinally (IT) or peripherally (intraplantar in the paw, IPLT) in a hyperalgesic priming model, similar to others observations with the cyclooxygenase (COX) metabolite Prostaglandin E 2 (PGE 2 ). Surprisingly, we did not detect hyperalgesic priming following IT administration of LPS, indicating that this phenomenon likely requires peripheral activation of nociceptors. Collectively, these data suggest that 12/15-LOX enzymes contribute to neuropathic-like pain hypersensitivity in rodents, with potential translatability as druggable targets across sexes and species using multiple reflexive and non-reflexive outcome measures.

Distinct Worst Pain Profiles in Oncology Outpatients Undergoing Chemotherapy

BACKGROUND

While pain is a significant problem for oncology patients, little is known about interindividual variability in pain characteristics.

OBJECTIVE

The aims of this study were to identify subgroups of patients with distinct worst pain severity profiles and evaluate for differences among these subgroups in demographic, clinical, and pain characteristics and stress and symptom scores.

METHODS

Patients (n = 934) completed questionnaires 6 times over 2 chemotherapy cycles. Worst pain intensity was assessed using a 0- to 10-point numeric rating scale. Brief Pain Inventory was used to assess various pain characteristics. Latent profile analysis was used to identify subgroups of patients with distinct pain profiles.

RESULTS

Three worst pain profiles were identified (low [17.5%], moderate [39.9%], severe [42.6%]). Compared with the other 2 classes, severe class was more likely to be single and unemployed and had a lower annual household income, a higher body mass index, a higher level of comorbidity, and a poorer functional status. Severe class was more likely to have both cancer and noncancer pain, a higher number of pain locations, higher frequency and duration of pain, worse pain quality scores, and higher pain interference scores. Compared with the other 2 classes, severe class reported lower satisfaction with pain management and higher global, disease-specific, and cumulative life stress, as well as higher anxiety, depression, fatigue, sleep disturbance, and cognitive dysfunction scores.

CONCLUSIONS

Unrelieved pain is a significant problem for more than 80% of outpatients.

IMPLICATIONS FOR PRACTICE

Clinicians need to perform comprehensive pain assessments; prescribe pharmacologic and nonpharmacologic interventions; and initiate referrals for pain management and psychological services.

Sex differences in neuroimmune and glial mechanisms of pain

ABSTRACT

Pain is the primary motivation for seeking medical care. Although pain may subside as inflammation resolves or an injury heals, it is increasingly evident that persistency of the pain state can occur with significant regularity. Chronic pain requires aggressive management to minimize its physiological consequences and diminish its impact on quality of life. Although opioids commonly are prescribed for intractable pain, concerns regarding reduced efficacy, as well as risks of tolerance and dependence, misuse, diversion, and overdose mortality rates limit their utility. Advances in development of nonopioid interventions hinge on our appreciation of underlying mechanisms of pain hypersensitivity. For instance, the contributory role of immunity and the associated presence of autoimmune syndromes has become of particular interest. Males and females exhibit fundamental differences in innate and adaptive immune responses, some of which are present throughout life, whereas others manifest with reproductive maturation. In general, the incidence of chronic pain conditions, particularly those with likely autoimmune covariates, is significantly higher in women. Accordingly, evidence is now accruing in support of neuroimmune interactions driving sex differences in the development and maintenance of pain hypersensitivity and chronicity. This review highlights known sexual dimorphisms of neuroimmune signaling in pain states modeled in rodents, which may yield potential high-value sex-specific targets to inform future analgesic drug discovery efforts.

Pain Management in Clinical Practice Research Using Electronic Health Records

BACKGROUND

The use of electronic health record (EHR) systems encourages and facilitates the use of data for the development and surveillance of quality indicators, including pain management.

AIM

to conduct an integrative review on pain management research using data extracted from EHR in order to synthesize and analyze the following elements: pain management (assessments, interventions, and outcomes) and study results with potential clinical implications, data source, clinical sample characteristics, and method description.

DESIGN

An integrative review of the literature was undertaken to identify exemplars of scientific research studies that explore pain management using data from EHR, using Cooper's framework.

RESULTS

Our search of 1,061 records from PubMed, Scopus, and Cinahl was narrowed down to 28 eligible articles to be analyzed.

CONCLUSION

Results of this integrative review will make a critical contribution, assisting others in developing research proposals and sound research methods, as well as providing an overview of such studies over the past 10 years. Through this review it is therefore possible to guide new research on clinical pain management using EHR.

Patient-Reported Outcomes and Opioid Use by Outpatient Cancer Patients

The Memorial Sloan Kettering Pain Registry contains patient characteristics, treatments, and outcomes for a prospective cohort of 1,534 chronic pain cancer patients who were seen at outpatient pain service clinics. Average pain intensity (Brief Pain Inventory) was reported as mild by 24.6% of patients, moderate by 41.5%, and severe by 33.9%. The patient's report of average percent pain relief and health state (EuroQOL 5 dimensions) was inversely related to average pain intensity category, whereas measures of pain interference, number of worst pain locations, and physical and psychological distress were directly related to pain intensity category. Eighty-six percent of patients received an opioid at 1 or more clinic encounters. Regression analysis revealed that male sex or being younger (65 years of age or younger) was associated with a greater likelihood of an opioid ordered. Male sex nearly doubled the likelihood of a higher dose being ordered than female sex. Bivariate analysis found that patients receiving opioids reported significantly more pain relief than no-opioid patients. However, patients receiving opioids had higher pain interference scores, lower index of health state, and more physical distress than no-opioid patients Our results identify the need to consider opioid use and dosage when attempting to understand patient-reported outcomes (PROs) and factors affecting pain management.

PERSPECTIVE

This report describes the results of the analyses of PROs and patient-related electronic health record data collected under standard of care from cancer patients at outpatient pain management clinics of Anesthesiology and Palliative Care at the Memorial Sloan Kettering Cancer Center. Consideration of sex and age as predictors of opioid use is critical in attempting to understand PROs and their relationship to pain management.

Patterns of User Engagement With the Mobile App, Manage My Pain: Results of a Data Mining Investigation

BACKGROUND

Pain is one of the most prevalent health-related concerns and is among the top 3 most common reasons for seeking medical help. Scientific publications of data collected from pain tracking and monitoring apps are important to help consumers and healthcare professionals select the right app for their use.

OBJECTIVE

The main objectives of this paper were to (1) discover user engagement patterns of the pain management app, Manage My Pain, using data mining methods; and (2) identify the association between several attributes characterizing individual users and their levels of engagement.

METHODS

User engagement was defined by 2 key features of the app: longevity (number of days between the first and last pain record) and number of records. Users were divided into 5 user engagement clusters employing the k-means clustering algorithm. Each cluster was characterized by 6 attributes: gender, age, number of pain conditions, number of medications, pain severity, and opioid use. Z tests and chi-square tests were used for analyzing categorical attributes. Effects of gender and cluster on numerical attributes were analyzed using 2-way analysis of variances (ANOVAs) followed up by pairwise comparisons using Tukey honest significant difference (HSD).

RESULTS

The clustering process produced 5 clusters representing different levels of user engagement. The proportion of males and females was significantly different in 4 of the 5 clusters (all P ≤.03). The proportion of males was higher than females in users with relatively high longevity. Mean ages of users in 2 clusters with high longevity were higher than users from other 3 clusters (all P <.001). Overall, males were significantly older than females (P <.001). Across clusters, females reported more pain conditions than males (all P <.001). Users from highly engaged clusters reported taking more medication than less engaged users (all P <.001). Females reported taking a greater number of medications than males (P =.04). In 4 of 5 clusters, the percentage of males taking an opioid was significantly greater (all P ≤.05) than that of females. The proportion of males with mild pain was significantly higher than that of females in 3 clusters (all P ≤.008).

CONCLUSIONS

Although most users of the app reported being female, male users were more likely to be highly engaged in the app. Users in the most engaged clusters self-reported a higher number of pain conditions, a higher number of current medications, and a higher incidence of opioid usage. The high engagement by males in these clusters does not appear to be driven by pain severity which may, in part, be the case for females. Use of a mobile pain app may be relatively more attractive to highly-engaged males than highly-engaged females, and to those with relatively more complex chronic pain problems.