A protocol for chronic pain outcome measurement enhancement by linking PROMIS-29 scale to legacy measures and improving chronic pain stratification

Predictors of Pain Management Strategies in Adults with Low-Back Pain: A Secondary Analysis of Amazon Mechanical Turk Survey Data

Objective: To evaluate the associations between baseline demographics, health conditions, pain management strategies, and health-related quality-of-life (HRQoL) measures with pain management strategies at 3-month follow-up in respondents reporting current low-back pain (LBP). Study design: Cohort study of survey data collected from adults with LBP sampled from Amazon Mechanical Turk crowdsourcing panel. Methods: Demographics, health conditions, and the Patient-Reported Outcomes Measurement Information System (PROMIS)-10 were included in the baseline survey. Respondents reporting LBP completed a more comprehensive survey inquiring about pain management strategies and several HRQoL measures. Bivariate then multivariate logistic regression estimated odds ratios (ORs) with 95% confidence intervals (CIs) for the association between baseline characteristics and pain management utilization at 3-month follow-up. Model fit statistics were evaluated to assess the predictive value. Results: The final cohort included 717 respondents with completed surveys. The most prevalent pain management strategy at follow-up was other care (n = 474), followed by no care (n = 94), conservative care only (n = 76), medical care only (n = 51), and medical and conservative care combined (n = 22). The conservative care only group had higher (better) mental and physical health PROMIS-10 scores as opposed to the medical care only and combination care groups, which had lower (worse) physical health scores. In multivariate models, estimated ORs (95% CIs) for the association between baseline and follow-up pain management ranged from 4.6 (2.7-7.8) for conservative care only to 16.8 (6.9-40.7) for medical care only. Additional significant baseline predictors included age, income, education, workman's compensation claim, Oswestry Disability Index score, and Global Chronic Pain Scale grade. Conclusions: This study provides important information regarding the association between patient characteristics, HRQoL measures, and LBP-related pain management utilization.

Dietary fatty acids improve perceived sleep quality, stress, and health in migraine: a secondary analysis of a randomized controlled trial

Background

Migraine is a prevalent disabling condition often associated with comorbid physical and psychological symptoms that contribute to impaired quality of life and disability. Studies suggest that increasing dietary omega-3 fatty acid is associated with headache reduction, but less is known about the effects on quality of life in migraine.

Methods

After a 4-week run-in, 182 adults with 5-20 migraine days per month were randomized to one of the 3 arms for sixteen weeks. Dietary arms included: H3L6 (a high omega-3, low omega-6 diet), H3 (a high omega-3, an average omega-6 diet), or a control diet (average intakes of omega-3 and omega-6 fatty acids). Prespecified secondary endpoints included daily diary measures (stress perception, sleep quality, and perceived health), Patient-Reported Outcome Measurement Information System Version 1.0 ([PROMIS©) measures and the Migraine Disability Assessment (MIDAS). Analyses used linear mixed effects models to control for repeated measures.

Results

The H3L6 diet was associated with significant improvements in stress perception [adjusted mean difference (aMD): -1.5 (95% confidence interval: -1.7 to -1.2)], sleep quality [aMD: 0.2 (95% CI:0.1-0.2)], and perceived health [aMD: 0.2 (0.2-0.3)] compared to the control. Similarly, the H3 diet was associated with significant improvements in stress perception [aMD: -0.8 (-1.1 to -0.5)], sleep quality [aMD: 0.2 (0.1, 0.3)], and perceived health [aMD: 0.3 (0.2, 0.3)] compared to the control. MIDAS scores improved substantially in the intervention groups compared with the control (H3L6 aMD: -11.8 [-25.1, 1.5] and H3 aMD: -10.7 [-24.0, 2.7]). Among the PROMIS-29 assessments, the biggest impact was on pain interference [H3L6 MD: -1.8 (-4.4, 0.7) and H3 aMD: -3.2 (-5.9, -0.5)] and pain intensity [H3L6 MD: -0.6 (-1.3, 0.1) and H3 aMD: -0.6 (-1.4, 0.1)].

Discussion

The diary measures, with their increased power, supported our hypothesis that symptoms associated with migraine attacks could be responsive to specific dietary fatty acid manipulations. Changes in the PROMIS© measures reflected improvements in non-headache pain as well as physical and psychological function, largely in the expected directions. These findings suggest that increasing omega-3 with or without decreasing omega-6 in the diet may represent a reasonable adjunctive approach to reducing symptoms associated with migraine attacks. Trial Registration: ClinicalTrials.gov NCT02012790.

Pain Education and Knowledge (PEAK) Consensus Guidelines for Neuromodulation: A Proposal for Standardization in Fellowship and Training Programs

The need to be competent in neuromodulation is and should be a prerequisite prior to completing a fellowship in interventional pain medicine. Unfortunately, many programs lack acceptable candidates for these advanced therapies, and fellows may not receive adequate exposure to neuromodulation procedures. The American Society of Pain and Neuroscience (ASPN) desires to create a consensus of experts to set a minimum standard of competence for neurostimulation procedures, including spinal cord stimulation (SCS), dorsal root ganglion stimulation (DRG-S), and peripheral nerve stimulation (PNS). The executive board of ASPN accepted nominations for colleagues with excellence in the subject matter of neuromodulation and physician education. This diverse group used peer-reviewed literature and, based on grading of evidence and expert opinion, developed critical consensus guides for training that all accredited fellowship programs should adopt. For each consensus point, transparency and recusal were used to eliminate bias, and an author was nominated for evidence grading oversight and bias control. Pain Education and Knowledge (PEAK) Consensus Guidelines for Neuromodulation sets a standard for neuromodulation training in pain fellowship training programs. The consensus panel has determined several recommendations to improve care in the United States for patients undergoing neuromodulation. As neuromodulation training in the United States has evolved dramatically, these therapies have become ubiquitous in pain medicine. Unfortunately, fellowship programs and the Accreditation Council for Graduate Medical Education (ACGME) pain program requirements have not progressed training to match the demands of modern advancements. PEAK sets a new standard for fellowship training and presents thirteen practice areas vital for physician competence in neuromodulation.

Crosswalking the National Institutes of Health Impact Stratification Score to the PEG

OBJECTIVE

To crosswalk the National Institutes of Health (NIH) Pain Consortium's Research Task Force proposed Impact Stratification Score (ISS) to the PEG (Pain Intensity, Interference With Enjoyment of Life, Interference With General Activity) Scale.

DESIGN

Cross-sectional data collected in 2021. Ordinary least squares regression analyses of ISS and PEG.

SETTING

Amazon Mechanical Turk workers.

PARTICIPANTS

1931 adults with back pain with an average age of 41 (range, 19-77); 48% were female, 16% Hispanic, 7% non-Hispanic Black, 5% non-Hispanic Asian, and 71% non-Hispanic White (N=1931).

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

The Patient-Reported Outcomes Measurement Information System (PROMIS)-29+2 v2.1 survey that includes the ISS, and the 3-item PEG.

RESULTS

The ISS and PEG had a correlation coefficient of 0.74. The ISS accounted for 55% of the adjusted variance in the PEG and the standardized average deviation between observed and predicted scores (normalized mean absolute error) was 0.53. Likewise, the PEG explained 55% of the variance in the ISS with a normalized mean absolute error of 0.52.

CONCLUSIONS

This study provides a crosswalk between the ISS and PEG that can be used to predict one from the other. The regression equations can facilitate comparisons in studies that use different measures.

Analyses of Cross-Sectional Data to Link the PEG With the Patient Reported Outcomes Measurement and Information System (PROMIS) Global Physical Health Scale

It is challenging to synthesize findings across studies of pain impact. This study develops a link to estimate the Patient-Reported Outcomes Measurement Information System (PROMIS) global health measure from the 3-item Pain intensity, interference with Enjoyment of life, interference with General activity (PEG) scale. The PROMIS and PEG items were administered to 795 adults (average age = 51; 54% female, 79% White). We estimated correlations among the PEG and PROMIS items and conducted factor analysis to identify the best subset of PROMIS items for linking to the PEG. An item response theory graded response model was estimated to link the PEG with the 4-item PROMIS global physical health scale. A categorical single-factor model and a bifactor model provided support for a single dimension for the PEG and PROMIS global physical health items. The product-moment correlation between estimated PROMIS global physical health scale from the PEG and the actual global physical health score was .74. The mean difference between estimated PROMIS global physical health scale score from the PEG and the observed global physical health score was less than a T-score point. This study makes it possible to estimate the average global physical health for group-level comparisons in research that includes the PEG. PERSPECTIVE: This article describes an empirical link of the PEG to the PROMIS global physical health scale that makes it possible to estimate the average global physical health in studies that include the PEG. This link can facilitate comparisons among studies that have not administered the PEG or the PROMIS global health scale.

Crosswalking the Patient-Reported Outcomes Measurement Information System Physical Function, Pain Interference, and Pain Intensity Scores to the Roland-Morris Disability Questionnaire and the Oswestry Disability Index

OBJECTIVE

To link scores from 2 condition-specific measures for chronic low back pain (CLBP), the Oswestry Disability Index (ODI) and the Roland-Morris Disability Questionnaire (RMDQ), to Patient Reported Outcomes Measurement Information System (PROMIS) physical function, pain interference, and pain intensity scores.

DESIGN

Ordinary least squares regression analyses of existing data to link the PROMIS scores with the ODI and RMDQ.

SETTING

Not applicable.

PARTICIPANTS

Samples of adults with CLBP (N=2279) obtained from the Center for Excellence in Research for Complementary and Integrative Health (CERC) Study (n=1677), the Assessment of Chiropractic Treatment for Low Back Pain and Smoking Cessation in Military Active Duty Personnel (ACT) (n=384), and the pain subsample of the PROMIS 1 Wave 2 Pain and Depression study (PROMIS 1 W2) (n=218).

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

PROMIS physical function, pain interference, and pain intensity (CERC, ACT, and PROMIS 1 W2), ODI (CERC and PROMIS 1 W2), and RMDQ (ACT and PROMIS 1 W2).

RESULTS

In predicting PROMIS scores, the ODI model R² values ranged from 0.26-0.56 and the RMDQ model R² values ranged from 0.13-0.50. ODI and RMDQ models were the least precise in predicting the PROMIS pain intensity score (R² value range, 0.13-0.41) relative to the other PROMIS scores. Models with the 3 PROMIS scores as predictors yielded R² values ranging from 0.64-0.68 and 0.46-0.58 for the ODI and RMDQ, respectively. Models using combined data from 2 studies (ie, PROMIS 1 W2 and ACT, or PROMIS 1 W2 and CERC) tended to be more precise than models using only a single study sample.

CONCLUSIONS

Model results reported here can be used to translate PROMIS physical function, pain interference, and pain intensity scores to and from the ODI and RMDQ. The empirical linkages can facilitate comparisons across CLBP interventions and broaden interpretation of study results.