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      Combination pharmacotherapy for the treatment of fibromyalgia in adults

      1 , 1 , 2 , 2 , 3
      Cochrane Pain, Palliative and Supportive Care Group
      Cochrane Database of Systematic Reviews
      Wiley

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          Abstract

          Fibromyalgia is a chronic widespread pain condition affecting millions of people worldwide. Current pharmacotherapies are often ineffective and poorly tolerated. Combining different agents could provide superior pain relief and possibly also fewer side effects. To assess the efficacy, safety, and tolerability of combination pharmacotherapy compared to monotherapy or placebo, or both, for the treatment of fibromyalgia pain in adults. We searched CENTRAL, MEDLINE, and Embase to September 2017. We also searched reference lists of other reviews and trials registries. Double‐blind, randomised controlled trials comparing combinations of two or more drugs to placebo or other comparators, or both, for the treatment of fibromyalgia pain. From all studies, we extracted data on: participant‐reported pain relief of 30% or 50% or greater; patient global impression of clinical change (PGIC) much or very much improved or very much improved; any other pain‐related outcome of improvement; withdrawals (lack of efficacy, adverse events), participants experiencing any adverse event, serious adverse events, and specific adverse events (e.g. somnolence and dizziness). The primary comparison was between combination and one or all single‐agent comparators. We also assessed the evidence using GRADE and created a 'Summary of findings' table. We identified 16 studies with 1474 participants. Three studies combined a non‐steroidal anti‐inflammatory drug (NSAID) with a benzodiazepine (306 participants); two combined amitriptyline with fluoxetine (89 participants); two combined amitriptyline with a different agent (92 participants); two combined melatonin with an antidepressant (164 participants); one combined carisoprodol, paracetamol (acetaminophen), and caffeine (58 participants); one combined tramadol and paracetamol (acetaminophen) (315 participants); one combined malic acid and magnesium (24 participants); one combined a monoamine oxidase inhibitor with 5‐hydroxytryptophan (200 participants); and one combined pregabalin with duloxetine (41 participants). Six studies compared the combination of multiple agents with each component alone and with inactive placebo; three studies compared combination pharmacotherapy with each individual component but did not include an inactive placebo group; two studies compared the combination of two agents with only one of the agents alone; and three studies compared the combination of two or more agents only with inactive placebo. Heterogeneity among studies in terms of class of agents evaluated, specific combinations used, outcomes reported, and doses given prevented any meta‐analysis. None of the combinations of drugs found provided sufficient data for analysis compared with placebo or other comparators for our preferred outcomes. We therefore provide a narrative description of results. There was no or inadequate evidence in any comparison for primary and secondary outcomes. Two studies only reported any primary outcomes of interest (patient‐reported pain relief of 30%, or 50%, or greater). For each 'Risk of bias' item, only half or fewer of studies had unequivocal low risk of bias. Small size and selective reporting were common as high risk of bias. Our GRADE assessment was therefore very low for primary outcomes of pain relief of 30% or 50% or greater, PGIC much or very much improved or very much improved, any pain‐related outcome, participants experiencing any adverse event, any serious adverse event, or withdrawing because of an adverse event. Three studies found some evidence that combination pharmacotherapy reduced pain compared to monotherapy; these trials tested three different combinations: melatonin and amitriptyline, fluoxetine and amitriptyline, and pregabalin and duloxetine. Adverse events experienced by participants were not serious, and where they were reported (in 12 out of 16 studies), all participants experienced them, regardless of treatment. Common adverse events were nausea, dizziness, somnolence, and headache. There are few, large, high‐quality trials comparing combination pharmacotherapy with monotherapy for fibromyalgia, consequently limiting evidence to support or refute the use of combination pharmacotherapy for fibromyalgia. Combinations of drugs versus single drugs to treat fibromyalgia pain in adults Bottom line There is no good evidence to prove or disprove that combining drugs is better than using single drugs for fibromyalgia. Background People with fibromyalgia experience constant, widespread pain, sleep problems, and fatigue. Common drugs such as paracetamol (acetaminophen) and ibuprofen are not usually effective. Medicines used to treat epilepsy or depression can sometimes be effective for fibromyalgia and other forms of long‐lasting pain where there may be nerve damage. Many individuals with fibromyalgia take many different drugs to deal with pain. We did this review to find the evidence about using combinations of drugs compared to single drugs. Study characteristics In September 2017 we searched for clinical trials where combinations of medicines were used for fibromyalgia pain in adults. We found 16 studies evaluating combinations of drugs versus one drug for fibromyalgia pain. Key results These studies looked at combinations of all sorts of different drugs, but did not provide enough data to draw any conclusions. Many of the studies did not directly compare a combination of drugs with each single drug. They sometimes compared a combination of medicines with only one of the medicines in the combination, or with only placebo. This limited our ability to make any conclusions. Most studies did not report any of the outcomes important to people with fibromyalgia. Some studies showed that a combination of drugs is better at reducing pain than one drug alone, but other studies showed that one drug alone is better than a combination of drugs. Other studies did not find any difference between combinations of drugs and single drugs. Side effects were not severe, and generally were not different between combination therapy and monotherapy. Quality of the evidence We rated the quality of the evidence from studies using four levels: very low, low, moderate, or high. Very low‐quality evidence means that we are very uncertain about the results. High‐quality evidence means that we are very confident in the results. Overall, the quality of evidence for important outcomes was very low. None of the combinations of drugs provided enough information for our preferred outcomes. We think that new studies will be very likely to change any conclusions drawn from these studies.

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          Meta-analysis in clinical research.

          Meta-analysis is the process of combining study results that can be used to draw conclusions about therapeutic effectiveness or to plan new studies. We review important design and statistical issues of this process. The design issues include protocol development, objectives, literature search, publication bias, measures of study outcomes, and quality of the data. The statistical issues include consistency (homogeneity) of study outcomes, and techniques for pooling results from several studies. Guidelines are provided to assess the quality of meta-analyses based on our discussion of the design and statistical issues. Limitations and areas for further development of this approach are discussed; researchers should come to a general agreement on how to conduct meta-analysis. As an explicit strategy for summarizing results, meta-analysis may help clinicians and researchers better understand the findings of clinical studies.
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            Is Open Access

            Small study effects in meta-analyses of osteoarthritis trials: meta-epidemiological study

            Objective To examine the presence and extent of small study effects in clinical osteoarthritis research. Design Meta-epidemiological study. Data sources 13 meta-analyses including 153 randomised trials (41 605 patients) that compared therapeutic interventions with placebo or non-intervention control in patients with osteoarthritis of the hip or knee and used patients’ reported pain as an outcome. Methods We compared estimated benefits of treatment between large trials (at least 100 patients per arm) and small trials, explored funnel plots supplemented with lines of predicted effects and contours of significance, and used three approaches to estimate treatment effects: meta-analyses including all trials irrespective of sample size, meta-analyses restricted to large trials, and treatment effects predicted for large trials. Results On average, treatment effects were more beneficial in small than in large trials (difference in effect sizes −0.21, 95% confidence interval −0.34 to −0.08, P=0.001). Depending on criteria used, six to eight funnel plots indicated small study effects. In six of 13 meta-analyses, the overall pooled estimate suggested a clinically relevant, significant benefit of treatment, whereas analyses restricted to large trials and predicted effects in large trials yielded smaller non-significant estimates. Conclusions Small study effects can often distort results of meta-analyses. The influence of small trials on estimated treatment effects should be routinely assessed.
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              Size is everything--large amounts of information are needed to overcome random effects in estimating direction and magnitude of treatment effects.

              Variability in patients' response to interventions in pain and other clinical settings is large. Many explanations such as trial methods, environment or culture have been proposed, but this paper sets out to show that the main cause of the variability may be random chance, and that if trials are small their estimate of magnitude of effect may be incorrect, simply because of the random play of chance. This is highly relevant to the questions of 'How large do trials have to be for statistical accuracy?' and 'How large do trials have to be for their results to be clinically valid?' The true underlying control event rate (CER) and experimental event rate (EER) were determined from single-dose acute pain analgesic trials in over 5000 patients. Trial group size required to obtain statistically significant and clinically relevant (0.95 probability of number-needed-to-treat within -/+0.5 of its true value) results were computed using these values. Ten thousand trials using these CER and EER values were simulated using varying group sizes to investigate the variation due to random chance alone. Most common analgesics have EERs in the range 0.4-0.6 and CER of about 0.19. With such efficacy, to have a 90% chance of obtaining a statistically significant result in the correct direction requires group sizes in the range 30-60. For clinical relevance nearly 500 patients are required in each group. Only with an extremely effective drug (EER > 0.8) will we be reasonably sure of obtaining a clinically relevant NNT with commonly used group sizes of around 40 patients per treatment arm. The simulated trials showed substantial variation in CER and EER, with the probability of obtaining the correct values improving as group size increased. We contend that much of the variability in control and experimental event rates is due to random chance alone. Single small trials are unlikely to be correct. If we want to be sure of getting correct (clinically relevant) results in clinical trials we must study more patients. Credible estimates of clinical efficacy are only likely to come from large trials or from pooling multiple trials of conventional (small) size.
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                Author and article information

                Journal
                Cochrane Database of Systematic Reviews
                Wiley
                14651858
                February 19 2018
                Affiliations
                [1 ]Queen's University; Anesthesiology & Perioperative Medicine; Kingston ON Canada
                [2 ]University of Oxford; Pain Research and Nuffield Department of Clinical Neurosciences (Nuffield Division of Anaesthetics); Pain Research Unit Churchill Hospital Oxford Oxfordshire UK OX3 7LE
                [3 ]Queen's University; Departments of Anesthesiology & Perioperative Medicine & Biomedical & Molecular Sciences; 76 Stuart Street Victory 2 Pavillion Kingston ON Canada K7L 2V7
                Article
                10.1002/14651858.CD010585.pub2
                6491103
                29457627
                e481e4f0-bb52-42d0-b9ad-a6c421cc3ecf
                © 2018
                History

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