OHSU

Focus on Research July 2014

NIH Task Force on Research Standards for Chronic Low Back Pain

By Rick Deyo
Kaiser Permanente Professor of Evidence-Based Familly Medicine

Richard Deyo, MD, MPHFor 2 years, Rick Deyo, MD,MPH, has co-chaired an NIH Task Force on Research Standards for Chronic Low Back Pain. The goal was to recommend more consistent ways of classifying patients and reporting research results. The NIH will require use of the standards in all grant applications dealing with chronic low back pain. The Task Force just published its report in the Journal of Pain(2014; 15: 569-85) with simultaneous publication in Spine, The Spine Journal, Clinical Journal of Pain, and the European Spine Journal.

Background: 

ChartChronic low-back pain (cLBP) is common and has a major societal impact. Despite rapidly increasing use of medications, injections, and surgery, functional disability has increased in recent decades [See figure]. Many patients who have procedures to correct putative causes continue to have pain. Further, we often cannot identify mechanisms to explain the major negative impact cLBP has on many patients. Such cLBP is often termed nonspecific, idiopathic, or mechanical, and may in fact be due to varied and multiple biologic and behavioral etiologies. 

In 2009-10, the NIH Pain Consortium convened two workshops on low-back pain, noting that researchers use varied inclusion criteria, definitions, baseline assessments, and outcome measures. This impedes comparing studies, replicating findings, pooling data, resolving conflicts, and achieving consensus. It was recommended that NIH establish research standards on cLBP.

Approach:

The Task Force had Co-chairs with complementary expertise and 14 additional members with varied scientific and clinical expertise. The group evolved a three-stage work plan, each with a 2-day meeting and intervening literature review. Between meetings, the co-chairs surveyed members regarding key elements. These principles emerged:

  • The process should be evidence-based and use a biopsychosocial model of chronic pain.
  • Data should be useful for patients with degenerative disorders (e.g., herniated disc, lumbar stenosis) as well as those without clear pathoanatomy.
  • Patients with no clear pathoanatomy should not be assumed to have “psychogenic” pain.
  • Classifying cLBP by impact is more feasible and potentially useful than classifying solely by pathophysiology. “Impact” includes pain intensity, interference, and physical function.
  • A brief minimal uniform dataset should be reported in all studies of chronic back pain.
  • The dataset should be relevant for population, observational, and interventional research.
  • An investigator could substitute more detailed and precise measures for a particular domain but should report all domains of the minimal dataset.
Recommendations:
  1. Definition of cLBP: A patient with pain on at least half the days in the past 6 months would have accumulated at least 3 months’ worth of pain days, and this was the recommended definition.
  2. Classification of cLBP by Impact: “Impact” was defined by pain intensity, pain interference with normal activities, and functional status, calculated from the Patient Reported Outcomes Measurement Information System (PROMIS) short form.
  3. Minimal Dataset: Key elements were demographics, involvement in workers’ compensation, work status, education, comorbidity, and previous treatment. Self-report domains were pain intensity, pain interference, physical function, depression, sleep disturbance, and catastrophizing. Short form PROMIS measures were recommended.
  4. Outcome Measures: The RTF did not recommend specific outcome measures, but did recommend reporting a “responder” analysis in addition to reporting group means of outcome measures
  5. Recommendations for Research on the Proposed Standards: The RTF recommended research to improve prognostic stratification; test composite outcome measures; assess patient stakeholders’ views of relevant outcomes; and further evaluate psychometric properties of the minimal dataset.
Conclusion:

The RTF believes these recommendations will advance the field, help resolve controversies, and facilitate future research on cLBP. We expect the recommendations will be dynamic and undergo continual improvement.