Objective: To compare fibromyalgia (FM) characteristics among patients identified in a community-based chronic pain cohort based on traditional International Classification of Diagnoses 9th revision (ICD-9) diagnostic coding, with that of patients identified using a novel predictive model. Methods: This retrospective study used data collected from July 1999 to February 17, 2015, in multiple chronic pain clinics in the United States. Patients were assigned to the FM case group based on specific inclusion criteria using ICD-9 codes or, separately, from results of a novel FM predictive model that was developed using random forest and logistic regression techniques. Propensity scoring (1:1) matched FM patients (cases) to nonmalignant chronic pain patients without FM (controls). Patient-reported measures (eg, pain, fatigue, quality of sleep) and clinical characteristics (ie, comorbidities, procedures, and regions of pain) were outcomes for analysis.Results: Nine ICD-9 clinical modification diagnoses had odds ratios with large effect sizes (Cohen's d > 0.8), demonstrating the magnitude of the difference between the FM and matched non-FM cohorts: chronic pain syndrome, latex allergy, muscle spasm, fasciitis, cervicalgia, thoracic pain, shoulder pain, arthritis, and cervical disorders (all P < 0.0001). Six diagnoses were found to have a moderate effect size (Cohen's 0.5 < d > 0.8): cystitis, cervical degeneration, anxiety, joint pain, lumbago, and cervical radiculitis. Conclusions: The identification of multiple comorbidities, diagnoses, and musculoskeletal procedures that were significantly associated with FM may facilitate differentiation of FM patients from other conditions characterized by chronic widespread pain. Predictive modeling may enhance identification of FM patients who may otherwise go undiagnosed. &

BackgroundWhile fibromyalgia (FM) is characterized by chronic widespread pain and tenderness, its presentation among patients as a continuum of diseases rather than a single disease contributes to the challenges of diagnosis and treatment. The purpose of this analysis was to distinguish and characterize classes of FM within the continuum using data from chronic pain patients.MethodsFM patients were identified from administrative claims data from the ProCare Systems’ network of Michigan pain clinics between January 1999 and February 2015. Identification was based on either use of traditional criteria (ie, ICD-9 codes) or a predictive model indicative of patients having FM. Patients were classified based on similarity of comorbidities (symptom severity), region of pain (widespread pain), and type and number of procedures (treatment intensity) using unsupervised learning. Text mining and a review of physician notes were conducted to assist in understanding the FM continuum.ResultsA total of 2,529 FM patients with 79,570 observations or clinical visits were evaluated. Four main classes of FM patients were identified: Class 1) regional FM with classic symptoms; Class 2) generalized FM with increasing widespread pain and some additional symptoms; Class 3) FM with advanced and associated conditions, increasing widespread pain, increased sleep disturbance, and chemical sensitivity; and Class 4) FM secondary to other conditions.ConclusionFM is a disease continuum characterized by progressive and identifiable classifications. Four classes of FM can be differentiated by pain and symptom severity, specific comorbidities, and use of clinical procedures.

BackgroundAn academic, community medicine partnership was established to build a phenotype-to-outcome model targeting chronic pain. This model will be used to drive clinical decision support for pain medicine in the community setting. The first step in this effort is an examination of the electronic health records (EHR) from clinics that treat chronic pain. The biopsychosocial components provided by both patients and care providers must be of sufficient scope to populate the spectrum of patient types, treatment modalities, and possible outcomes.MethodsThe patient health records from a large Midwest pain medicine practice (Michigan Pain Consultants, PC) contains physician notes, administrative codes, and patient-reported outcomes (PRO) on over 30,000 patients during the study period spanning 2010 to mid-2014. The PRO consists of a regularly administered Pain Health Assessment (PHA), a biopsychosocial, demographic, and symptomology questionnaire containing 163 items, which is completed approximately every six months with a compliance rate of over 95 %. The biopsychosocial items (74 items with Likert scales of 0–10) were examined by exploratory factor analysis and descriptive statistics to determine the number of independent constructs available for phenotypes and outcomes. Pain outcomes were examined both in the aggregate and the mean of longitudinal changes in each patient.ResultsExploratory factor analysis of the intake PHA revealed 15 orthogonal factors representing pain levels; physical, social, and emotional functions; the effects of pain on these functions; vitality and health; and measures of outcomes and satisfaction. Seven items were independent of the factors, offering unique information. As an exemplar of outcomes from the follow-up PHAs, patients reported approximately 60 % relief in their pain. When examined in the aggregate, patients showed both a decrease in pain levels and an increase in coping skills with an increased number of visits. When examined individually, 80-85 % of patients presenting with the highest pain levels reported improvement by approximately two points on an 11-point pain scale.ConclusionsWe conclude that the data available in a community practice can be a rich source of biopsychosocial information relevant to the phenotypes of chronic pain. It is anticipated that phenotype linkages to best treatments and outcomes can be constructed from this set of records.

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Objective: To evaluate the effectiveness of opioids and/or pregabalin on patient-reported outcomes among fibromyalgia (FM) patients based on levels of improvement. Methods: A total of 1,421 FM patients were identified, with 3,082 observational periods of opioids with or without pregabalin use between April 2008 and February 2015. Patients were categorized by opioids, and pregabalin with and without opioids; opioids were designated by morphine equivalent dose (MED) of ≤ 20 (low MED), > 20 to < 100 (moderate MED), ≥ 100 (high MED), and pregabalin doses of ≤ 150 mg, 151 to 300 mg, and 301 to 450 mg. Proportions of patients meeting clinically relevant thresholds of ≥ 30% and ≥ 50% improvement for pain interference (ability to enjoy life; activity; mood; relationships; sleep), pain severity, and fatigue were compared among treatments, and area under the curve (AUC) for improvement and worsening of effects was determined, enabling ranking of treatments. Further analysis compared pregabalin doses. Results: Pregabalin without opioids resulted in the highest proportions of patients with ≥ 30% improvement on all pain items and pain interference with "ability to enjoy life," "activity" "mood," and "sleep." For the ≥ 50% threshold, pregabalin alone was highest for all pain interference items and for "average pain" and "worst pain." Pregabalin was consistently lowest across thresholds for fatigue, but showed better results combined with moderate MED opioids. Pregabalin doses recommended for treatment of FM (151 to 450 mg) generally resulted in the highest proportion of patients achieving thresholds relative to opioids. The AUC results were consistent with thresholds; pregabalin without opioids resulted in the greatest benefits with regard to improvement, with the highest ranking for overall improvement and overall effects. Conclusion: Pregabalin without opioids provided the most favorable outcomes overall based on ≥ 30% and ≥ 50% improvement thresholds and AUC, with support for moderate MED opioids + pregabalin in patients suffering from fatigue. While most patients took less than recommended pregabalin doses, higher doses may lead to improved outcomes. &

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