Treatments for enhancing sleep quality in fibromyalgia: a systematic review and meta-analysis

Abstract

Objectives: Sleep disturbance is a key symptom of fibromyalgia and a risk factor for chronic widespread pain. This systematic review and meta-analysis aims to assess the effectiveness of pharmacological treatments and cognitive behavioural therapy (CBT) in improving sleep quality in fibromyalgia patients.

Methods: A systematic search of PubMed, MEDLINE, Embase, Cochrane CENTRAL and CINAHL was conducted for randomized controlled trials (RCTs) published up to April 2023. Studies assessing pharmacological or CBT interventions with sleep-related outcomes were included. Data were extracted, and meta-analyses were performed where applicable. Study quality and bias were evaluated using the Cochrane Risk of Bias tool.

Results: Forty-seven RCTs, including 11 094 participants, were reviewed. CBT for insomnia (CBT-I) showed a significant improvement in sleep quality (SMD -0.63, 95% CI -0.98 to -0.27), while CBT for pain (CBT-P) had no significant impact. Pharmacological agents such as pregabalin and sodium oxybate moderately improved sleep, but there was uncertainty around this evidence. Amitriptyline, milnacipran and duloxetine showed no significant benefit for sleep. Study heterogeneity was moderate, and no publication bias was detected.

Conclusion: CBT-I is a promising treatment for enhancing sleep quality in fibromyalgia. Pharmacological treatments like pregabalin may be beneficial but should be used cautiously due to potential risks. Future research should prioritize trials focusing on sleep as a primary outcome and explore the comparative effectiveness of pharmacological treatments and CBT-I in fibromyalgia. Understanding the mechanisms linking sleep and fibromyalgia will also help guide future therapies.

Keywords: cognitive behavioural therapy; fibromyalgia; pharmacological therapies; sleep.

Graphical abstract

Figure 1.

Flow diagram summarizing literature search presented according to PRISMA guidelines

Figure 2.

Risk of bias assessment for included studies. The figure summarizes the risk of bias across studies included in this systematic review, grouped by intervention type. Domains assessed include randomization process, deviations from intended interventions, missing outcome data, measurement of the outcome, selection of the reported result and overall risk of bias. Green circles represent ‘low risk’, yellow circles indicate ‘some concerns’, and red circles denote ‘high risk’ for each domain. The overall risk of bias for each study was determined by combining the judgements across all domains using the Cochrane Risk of Bias tool. Note, some studies evaluated multiple interventions. CBT-I: cognitive behavioural therapy for insomnia; CBT-P: cognitive behavioural therapy for pain; CBT-IP: combined CBT-I and CBT-P

Figure 3.

Forest plot of the effect of pharmacological interventions on sleep quality in fibromyalgia. The diamond at the bottom depicts the overall pooled effect, with its width representing the 95% CI. The size of each square corresponds to the weight of the study in the meta-analysis. For pregabalin (A), the pooled standardized mean differences (SMDs) and variances were calculated across all doses evaluated in each study, with crossover studies (e.g. Gilron et al. [40], Roth et al. [39]) appropriately handled using variance reduction techniques. Amitriptyline (B) utilized baseline-adjusted standardized mean difference (SMD) to account for pre-treatment differences between intervention and control groups. For Braz et al. [21], baseline means and SDs were estimated from medians and 95% CIs using the methods of Luo et al. [65] and Wan et al. [66]. Follow-up means were derived from reported percentage improvements, while follow-up SDs were imputed assuming a correlation of 0.7 between baseline and follow-up values. For sodium oxybate (C), SMDs for 4.5 and 6 g doses were combined using inverse variance weighting to produce a pooled effect. Milnacipran (D) SMDs were calculated based on the change scores from baseline to follow-up and pooled for studies with multiple doses. Hartung–Knapp (HK) adjustment was applied in all random-effects models to provide more accurate estimation of uncertainty

Figure 4.

Forest plot of the effect of cognitive behavioural therapy for insomnia (CBT-I) on sleep quality in fibromyalgia patients. The SMD for each study is presented with corresponding standard errors (SEs) and 95% CIs. Effect sizes were adjusted to account for baseline differences in sleep quality measures between control and intervention groups. The diamond at the bottom of the plot represents the overall pooled effect, with its width corresponding to the 95% CI. The size of each square is proportional to the weight of the study in the random-effects model. The random-effects model uses the restricted maximum likelihood (REML) method to estimate between-study variance, with Hartung–Knapp (HK) adjustment applied to provide more robust estimates of uncertainty. SMD: standardized mean difference