Description of the condition
Fibromyalgia (FM) is a condition resulting in excessive somatic hyperalgesia and allodynia, and also bowel complaints (Triadafilopoulos 1991). These intestinal symptoms are often attributable to Irritable bowel syndrome (IBS). Up to 32% of patients with fibromyalgia are diagnosed with IBS, and 81% report irregular bowel habits (Sperber 1999; Triadafilopoulos 1991; Veale 1991). In the 1996 consensus report, Wolfe provides an overarching description of FM as a syndrome of widespread pain, decreased pain threshold, and characteristic symptoms, including non-restorative sleep, fatigue, stiffness, mood disturbance, IBS, headache, paraesthesias, and other less common features (Wolfe 1996).The prevalence of FM varies between 2% and 6% in patients attending general practitioners, 5% to 8% in hospitalised patients and 14% to 20% in rheumatology consultations (Branco 2010; Doherty 1995; Wolfe 1995).
FM interventions are usually largely focused on pain. Several medications such as pregabalin, duloxetine and milnacipran have been licensed in the United States of America for treating FM (Derry 2012). These pharmacological interventions have been found to have a very limited to moderate effect on reducing chronic pain among people with FM (Gill 2011; Häuser 2013; Hearn 2012; Moore 2012; Tort 2012). Other forms of therapy that appear to be beneficial are cognitive behavioural therapy (Bernardy 2012), exercise (Busch 2007), or a combination of the two (Theadom 2009), and acupuncture (Deare 2009). However diet and, more recently, probiotics have been suggested to have an effect on FM, in particular for those with gastrointestinal symptoms. Due to the multifaceted care that is needed among patients with FM, a multidisciplinary approach consisting of all the therapies has been recommended, because no single therapy is universally superior (Arnold 2006).
Description of the intervention
Probiotics are "live microorganisms which when administered in adequate amount confer a health benefit on the host" (FAO 2001). Probiotics have been shown to be effective in varied clinical conditions - ranging from infantile diarrhoea, necrotizing enterocolitis, antibiotic-associated diarrhoea, relapsing Clostridium difficile colitis, to cancer and inflammatory bowel disease (Gupta 2009).
The bacterial genera most commonly used in probiotic preparations are Lactobacillus, Bifidobacterium, Escherichia, Enterococcus, Bacillus and Streptococcus. Lactobacillus rhamnosus strain GG, one of the most common probiotics, has proven effects on intestinal immunity (Perdigón 1999). It increases the number of IgA and other immunoglobulin secreting cells in the intestinal mucosa, stimulates local release of interferons, and facilitates antigen transport to underlying lymphoid cells, which serves to increase antigen uptake in Peyer's patches (Reid 2003).
How the intervention might work
Bacterial overgrowth of the small intestine has been suggested as a trigger for FM and chronic fatigue syndrome (Pimentel 2003). Pimentel et al (Pimentel 2004) found that 42/42 (100%) patients with FM had an abnormal lactulose hydrogen breath test compared to patients with IBS (93/111, 84%) and healthy controls (3/15, 20%). Patients with FM had a higher hydrogenic profile that correlated with somatic pain (Pimentel 2004). Probiotics may have beneficial effects by reversing bacterial overgrowth, strengthening the barrier function of the gut, inhibiting several pathogens, modifying the inflammatory response of the bowel, and/or reducing visceral hypersensitivity (Preidis 2009; Quigley 2006; Quigley 2007; Spiller 2008). Studies reporting on the therapeutic effect of probiotics on intestinal bacterial overgrowth which may exacerbate symptoms of IBS, common in patients with FM, are however limited (Gabrielli 2009; Schiffrin 2009; Stotzer 1996).
Probiotics also stimulate local release of alpha interferons (Reid 2003), a potent regulatory cytokine involved in immunologic responses (Durand 1992; Middleton 1994). A clinical trial evaluating the efficacy of alpha interferon in the treatment of deep palpation tenderness (TPI) in FM failed to show a significant mean change in TPI over six weeks in the treatment group compared to placebo. However, there was significant improvement for global severity of morning stiffness and physical function ability averaged over time, as assessed by the Health Assessment Questionnaire (HAQ) in the interferon group as opposed to the placebo group (Russell 1999).
Why it is important to do this review
FM has been treated primarily with pharmocotherapy, routinely focused on a symptom management approach. The most frequently prescribed medications are tricyclic antidepressants (TCAs), selective serotonin uptake inhibitors (SSRIs), simple analgesics and serotonin norepinephrine reuptake inhibitors (SNRIs), which have demonstrated efficacy for reducing pain and improving sleep (Dworkin 2003; Häuser 2013; Moore 2009). However, a recent systematic review of guidelines for the management of FM (Hauser 2010) highlights the importance of a multidimensional approach, including a combination of non-pharmacological and pharmacological therapies.
This Cochrane review concentrates on providing relevant and up-to-date evidence on the effects of probiotics on major FM clinical outcomes (pain, function, IBS, etc.) and potential adverse effects. There appear to be no other systematic reviews that assess the evidence on probiotics for FM.
To assess the benefits and harm of probiotics for reducing pain and improving function in people with fibromyalgia and its major complications.
Criteria for considering studies for this review
Types of studies
We will include randomised controlled trials (RCTs) or cluster-RCTs. We will also include controlled clinical trials (CCTs) but conduct a sensitivity analysis including only RCTs.
Types of participants
All persons 18 years of age or older having a clinical diagnosis of fibromyalgia, as defined by the 1990 American College of Rheumatology (ACR) guidelines (Wolfe 1990).
Types of interventions
We will include studies with at least one treatment group in which any probiotic intervention as a mono- or mixed culture of live micro-organisms was applied to humans with fibromyalgia. We will compare the intervention with placebo, usual diet and other mind and body therapies.
Types of outcome measures
The primary outcome measures will be:
- Pain (to include self-reported levels of pain measured by validated pain assessment)
- Functional status (ability to complete everyday tasks, e.g. scores on the Fibromyalgia Impact Questionnaire) (Bennett 2005)
We will assess all outcome measures at the beginning (baseline), three and six months for short and medium term studies respectively, and at the end of the studies, ranging from one to twelve months.
Secondary outcome measures will include:
- Quality of life
- Tender point score (measured by dolorimetry or digital palpation)
- Sleep quality
- Mood (depression, anxiety)
- Number of withdrawals due to adverse events
- Serious adverse events
In order to improve endpoint outcome measurements, we will use the OMERACT 9 (Choy 2009) core set of outcome measures (pain, physical function, patient global assessment, joint imaging, health-related quality of life measure, physician global assessment, tenderness).
Search methods for identification of studies
We report the search strategy developed for MEDLINE in Appendix 1. We will search the following electronic databases:
- The Cochrane Central Register of Controlled Trials (CENTRAL) via OVID (The Cochrane Library, current issue)
- MEDLINE via OVID (1948 to present)
- CINAHL via EBSCOhost (1982 to present)
- AGRICOLA via OVID (1970 to present)
- Food Science Technology Abstracts via OVID (1969 to present)
Searching other resources
We will search the reference lists of all the included studies for additional articles. We will contact experts in the field to identify any other unpublished or published studies. We will identify unpublished or ongoing trials by searching clinical trials registers.
Data collection and analysis
Selection of studies
Two review authors (DKF and IP) will independently carry out selection of papers and decisions about eligibility. DKF is a nutritionist. If the relevance of a report is unclear, the full text will be reviewed, and all disagreements will be resolved by discussion and consensus with the review author team. Study authors will be contacted for clarification and to obtain additional data in order to perform the systematic review, whenever necessary. Studies will be translated into English when necessary.
Data extraction and management
At least two independent authors will extract relevant data from selected studies according to inclusion criteria. Disagreements will be resolved by discussion and consensus. Any issue which cannot be resolved by the review authors will be discussed by the entire review team. In the case of missing data or ambiguity, we will contact the authors of the original article for clarification. We will consult a statistician in cases of doubt about data extraction and analysis.
For each study, we will extract the patient and study characteristics (diagnosis), intervention and outcomes data. We will extract the raw data (means and standard deviations for continuous outcomes and number of events and participants for dichotomous outcomes) for outcomes of interest. We will pilot test and use predefined data extraction forms to collect data.
We will extract and enter the following data into a customised collection form:
1. Study ID number
2. Study design, date and duration of study; setting of the study
a) sample size
b) inclusion and exclusion criteria
c) demographic characteristics of participants: age, sex, country of origin, gender, co-morbidities
4. Intervention - details of the experimental and comparison interventions
Other data that we will extract include:
- ethical approval
- sample size calculation (yes/no)
- funding sources
- key conclusions of the included studies as reported by their authors.
Assessment of risk of bias in included studies
Two independent authors will assess and record the risk of bias of included studies using the Cochrane Collaboration's tool for assessing risk of bias. The tool addresses six specific domains of bias:
- Selection bias (random sequence generation, allocation concealment);
- Performance bias (blinding of participants and personnel);
- Detection bias (blinding of outcome assessment);
- Attrition bias (incomplete outcome data);
- Reporting bias (selective outcome reporting); and
- Other bias.
For other bias, we will consider specifically contamination where control or placebo group intentionally or unintentionally received the intervention probiotics. Two review authors will independently assess the risk of bias for all included studies. In case of lack of important study information, we will contact authors using open-ended questions to obtain the information needed. To determine the risk of bias of each study, for each criterion we will evaluate the presence of sufficient information and the likelihood of potential bias. The judgement for each criterion will be assessed as 'Low risk', High risk', or 'Unclear risk' of bias. In a consensus meeting, disagreements among the review authors will be discussed and resolved. If consensus cannot be reached, a third review author will make the final decision.
Measures of treatment effect
The data extracted from the studies will be entered into Review Manager 5 (Review Manager 2011). We will complete a summary table describing the study characteristics. For continuous data, we will calculate the mean difference in end point scores between groups using the same self-report questionnaires (such as the Fibromyalgia Impact Questionnaire) with 95% confidence intervals. We will calculate standardised mean differences when different scales are used to measure end point scores. For dichotomous data, we will compile a 2x2 contingency table including the number of participants with each outcome event and risk ratios (RR) with 95% confidence intervals.
Unit of analysis issues
For cluster-randomised trials (cluster-RCTs) we will follow the methods for adjusting for clustering as described in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). If a cluster-RCT has properly accounted for the cluster design it can be included in a meta-analysis by simply using the effect estimate and its standard error (SE) and using the generic inverse variance method in Review Manager 5. If an appropriate analysis has not been performed, we will incorporate the cluster-RCT into a meta-analysis (if relevant) by using an 'approximate method'.
The approximately correct analyses will only be performed if the following information can be extracted:
- the number of clusters (or groups) randomised to each intervention group; or the average (mean) size of each cluster;
- the outcome data ignoring the cluster design for the total number of individuals (for example, number or proportion of individuals with events, or means and standard deviations); and
- an estimate of the intracluster (or intraclass) correlation coefficient (ICC).
The aim of the approximately correct analysis is to reduce the size of each trial to its "effective sample size" (Rao 1992). The effective sample size of a single intervention group in a cluster-randomised trial is its original sample size divided by a quantity called the ‘design effect’. The design effect is: 1 + (M – 1) ICC, where M is the average cluster size and ICC is the intracluster correlation coefficient. A common design effect is usually assumed across intervention groups. For dichotomous data both the number of participants and the number experiencing the event will be divided by the same design effect. We will use the generic inverse variance method (that uses the effect estimates and standard error). For continuous data only the sample size need be reduced; means and standard deviations should remain unchanged.
Studies with multiple treatment groups
For studies where there are multiple treatment groups, we will combine groups to create a single pairwise comparison as recommended by the Cochrane Handbook (16.5.4) (Higgins 2011). We will combine all relevant experimental intervention groups (probiotics or probiotics and food) of the study into a single group, and all relevant control intervention groups (placebo or treatment as usual) into a single control group. For dichotomous outcomes, both the sample sizes and the numbers of people with events will be summed across groups. For continuous outcomes, we will combine means and standard deviations using the formula specified in Appendix 2, according to the Cochrane Handbook (220.127.116.11) (Higgins 2011).
Multiple time points
We will report data at all collection time points during and after the intervention period (follow-up). Where data allow, we plan to group time points as follows: ≤ 3 months of probiotic treatment, 3 to 6 months of probiotic treatment and > 6 months of probiotics treatment.
Dealing with missing data
Where change scores are not available we will seek them from the authors. Failing that, we will use imputation methods recommended in the Cochrane Handbook (16.1.2) (Higgins 2011). We will be imputing the missing data with replacement values, and treating these as if they were observed. For dichotomous data we will use last observation carried forward and for continuous data we will account for missing data by imputing the mean.
We will request further details from authors in cases where published data are incomplete, perform sensitivity analyses to assess how sensitive results are to reasonable changes in assumptions made, and address the potential impact of missing data on the findings of the review in the Discussion section.
Assessment of heterogeneity
Where appropriate, we will assess heterogeneity of the data using the I
Assessment of reporting biases
We will assess publication bias using the funnel plot or other corrective analytical methods depending on the number of included trials of this review. We will explore reasons for any asymmetry in the funnel plot.
We will use a fixed-effect model unless statistically significant heterogeneity exists between studies. If heterogeneity is found a sensitivity analysis will be completed and followed by a random-effects model for meta-analysis if appropriate.
Subgroup analysis and investigation of heterogeneity
Conducting a large number of subgroup analyses increases the likelihood of false positive results and therefore it is important to carefully select the relevant characteristics to be investigated in advance (Higgins 2011). We plan to conduct the following subgroup analyses a priori in order to explore possible effect size differences:
- Intervention - duration of treatment.
- Characteristics of participants - severity of baseline disease; age; disease duration; sex.
For this review, we will assess results separately at three, six and 12 months, by duration of disease (as determined by average duration upon analysis), and by study eligibility criteria (probiotics).
Data will be analysed by different types of probiotic agents and how they effect on subgroup analyses.
- Intervention – different types of probiotic agents in intervention group, and different control;
- Different doses of probiotic agents;
- Different preparations of probiotic agents;
- Different duration of treatment;
- Different follow-up period; and
- Study design - inclusion of RCTs only and inclusion of CCTs as well.
Sensitivity analyses will be carried out to assess the robustness of results to inclusion of only studies at low risk of bias and to assess the robustness of results to variations in any estimated values of ICC.
'Summary of findings' table
We will include a 'Summary of findings' table to present the main findings of our review using GRADEprofiler (GRADEpro). It will provide key information concerning the quality of evidence, the magnitude or the effect of probiotics versus placebo or other mind and body therapies, and the sum of the available data on main outcomes (pain, fatigue, quality of life etc.).
We will include the following outcomes in the 'Summary of findings' table:
- Tender point score
- Functional status
- Withdrawals due to adverse events
- Serious adverse events
The review authors thank the Cochrane Musculoskeletal editorial team for their comments and helpful editorial suggestions.
Appendix 1. MEDLINE search strategy
Preliminary search strategy for MEDLINE (via OVID):
3 exp Lactobacillus/
7 (bifido$ or bifidu$).tw.
8 exp Lactococcus/
12 exp Enterococcus/
14 streptococcus/ or streptococcus thermophilus/
17 exp Saccharomyces/
19 exp Bacteriocins/
20 (bacteriocin$ or lantibiotic$).tw.
21 (nisin or lacticin or lactococin or caseicin or lactobacilin or lactocin or acidophilin).tw,nm.
22 lactic acid bacteria.tw.
24 (ferment$ adj5 (food$ or milk or drink$ or beverage$ or product$)).tw.
25 exp Cultured Milk Products/
26 cultured milk.tw.
27 (buttermilk or yog?urt$ or kefir or kephir or doogh or filmjolk or kumis or lassi or matsoni or tibicos or viili or ayran).tw.
28 ((living or functional) adj3 food$).tw.
29 ((food$ adj3 specif$ adj3 health) or FOSHU).tw.
30 ((intestin$ or bowel) adj3 (microflora or flora or microbiota or bacteria$ or metabolism)).tw.
31 (SIBO or SBBO).tw.
32 (fecal adj3 (microorganism$ or microbiota)).tw.
36 Fatigue Syndrome, Chronic/
38 ((muscular or muscle or soft-tissue) adj3 rheumati$).tw.
40 myofascial pain.tw.
41 (pain adj3 (diffuse or widespread or chronic or syndrome)).tw.
42 chronic fatigue.tw.
43 (sleep adj3 (disturb$ or patholog$)).tw.
44 (tender$ adj3 point$1).tw.
45 Irritable Bowel Syndrome/
46 (irritable adj3 (bowel or colon)).tw.
48 33 and 47
Appendix 2. Formulae for combining multiple treatment groups
Contributions of authors
Ivancica Pavlicevic has been responsible for coordinating the development of the protocol.
Vjekoslava Supraha has provided methodological and content expertise to the development of the protocol.
Ana Utrobicic has been responsible for developing the search methods to identify studies.
Damian K. Francis has contributed his clinical and methodological expertise to the development of the protocol.
Marina Zoricic, Anton Kordic, Dana Tenzera helped write the protocol.
Ernest HS Choy contributed to the final version of the protocol
Declarations of interest