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      Topical analgesics for acute and chronic pain in adults - an overview of Cochrane Reviews

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          Abstract

          Topical analgesic drugs are used for a variety of painful conditions. Some are acute, typically strains or sprains, tendinopathy, or muscle aches. Others are chronic, typically osteoarthritis of hand or knee, or neuropathic pain.

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          Most cited references 39

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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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            The coxibs, selective inhibitors of cyclooxygenase-2.

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              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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                Author and article information

                Journal
                Cochrane Database of Systematic Reviews
                Wiley
                14651858
                May 12 2017
                Affiliations
                [1 ]Oxford Oxfordshire UK
                [2 ]Thame UK
                [3 ]Helsinki University and Helsinki University Hospital; Department of Anaesthesia, Intensive Care and Pain Medicine; Helsinki Finland
                [4 ]Haukeland University Hospital; Regional Centre of Excellence in Palliative Care; Bergen Norway
                [5 ]Royal Hampshire County Hospital; Winchester UK SO22 5DG
                [6 ]University of Oxford; Pain Research and Nuffield Department of Clinical Neurosciences (Nuffield Division of Anaesthetics); Churchill Hospital Oxford UK OX3 7LJ
                [7 ]Plymouth UK
                Article
                10.1002/14651858.CD008609.pub2
                28497473
                © 2017
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