Predictors of clinical pain in fibromyalgia: examining the role of sleep

Abstract

Understanding individual differences in the variability of fibromyalgia pain can help elucidate etiological mechanisms and treatment targets. Past research has shown that spatial extent of pain, negative mood, and aftersensation (pain ratings taken after experimental induction of pain) accounts for 40 to 50% of the variance in clinical pain. Poor sleep is hypothesized to have a reciprocal relationship with pain, and over 75% of individuals with fibromyalgia report disturbed sleep. We hypothesized that measures of sleep would increase the predictive ability of the clinical pain model. Measures of usual pain, spatial extent of pain, negative mood, and pain aftersensation were taken from 74 adults with fibromyalgia. Objective (actigraph) and subjective (diary) measures of sleep duration and nightly wake time were also obtained from the participants over 14 days. Hierarchical regression indicated that greater spatial extent (R(2) = .26), higher aftersensation ratings (R(2) = .06), and higher negative mood (R(2) = .04) accounted for 36% of the variance in clinical pain (average of 14 daily pain ratings). None of the sleep variables were significant predictors of clinical pain. Results replicate previous research and suggest that spatial extent of pain, pain aftersensation, and negative mood play important roles in clinical pain, but sleep disturbance did not aid in its prediction.

Perspective: This study suggests that measures of sleep duration and nightly wake time do not predict fibromyalgia pain at the group level. Fibromyalgia patients may benefit from a 3-pronged approach to pain management: reducing pain's spatial extent, normalization of central nervous system hypersensitivity, and psychobehavioral therapies for negative mood.

Copyright © 2012 American Pain Society. Published by Elsevier Inc. All rights reserved.

Figures

Figure 1

Body diagram used by participants to shade areas of current pain. Each shaded area was coded as 1. Each nonshaded area was coded as 0. A sum of shaded areas was calculated for each participant.