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      Using evidence from different sources: an example using paracetamol 1000 mg plus codeine 60 mg

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          Abstract

          Background

          Meta-analysis usually restricts the information pooled, for instance using only randomised, double-blind, placebo-controlled trials. This neglects other types of high quality information. This review explores using different information for the combination of paracetamol 1000 mg and codeine 60 mg in acute postoperative pain.

          Results

          Randomised, double-blind, placebo-controlled trials of paracetamol 1000 mg and codeine 60 mg had an NNT of 2.2 (95% confidence interval 1.7 to 2.9) for at least 50% pain relief over four to six hours in three trials with 197 patients. Computer simulation of randomised trials demonstrated 92% confidence that the simulated NNT was within ± 0.5 of the underlying value of 2.2 with this number of patients. The result was supported a rational dose-response relationship for different doses of paracetamol and codeine in 17 additional trials with 1,195 patients. Three controlled trials lacking a placebo and with 117 patients treated with of paracetamol 1000 mg and codeine 60 mg had 73% (95%CI 56% to 81%) of patients with at least 50% pain relief, compared with 57% (48% to 66%) in placebo controlled trials. Six trials in acute pain were omitted because of design issues, like the use of different pain measures or multiple dosing regimens. In each paracetamol 1000 mg and codeine 60 mg was shown to be better than placebo or comparators for at least one measure.

          Conclusions

          Different designs of high quality trials can be used to support limited information used in meta-analysis without recourse to low quality trials that might be biased.

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          Most cited references51

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          Randomized, Controlled Trials, Observational Studies, and the Hierarchy of Research Designs

          New England Journal of Medicine, 342(25), 1887-1892
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            Confidence intervals rather than P values: estimation rather than hypothesis testing.

            Overemphasis on hypothesis testing--and the use of P values to dichotomise significant or non-significant results--has detracted from more useful approaches to interpreting study results, such as estimation and confidence intervals. In medical studies investigators are usually interested in determining the size of difference of a measured outcome between groups, rather than a simple indication of whether or not it is statistically significant. Confidence intervals present a range of values, on the basis of the sample data, in which the population value for such a difference may lie. Some methods of calculating confidence intervals for means and differences between means are given, with similar information for proportions. The paper also gives suggestions for graphical display. Confidence intervals, if appropriate to the type of study, should be used for major findings in both the main text of a paper and its abstract.
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              The number needed to treat: a clinically useful measure of treatment effect.

              The relative benefit of an active treatment over a control is usually expressed as the relative risk, the relative risk reduction, or the odds ratio. These measures are used extensively in both clinical and epidemiological investigations. For clinical decision making, however, it is more meaningful to use the measure "number needed to treat." This measure is calculated on the inverse of the absolute risk reduction. It has the advantage that it conveys both statistical and clinical significance to the doctor. Furthermore, it can be used to extrapolate published findings to a patient at an arbitrary specified baseline risk when the relative risk reduction associated with treatment is constant for all levels of risk.
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                Author and article information

                Journal
                BMC Med Res Methodol
                BMC Medical Research Methodology
                BioMed Central (London )
                1471-2288
                2001
                10 January 2001
                : 1
                : 1
                Affiliations
                [1 ] Pain Research & Nuffield Department of Anaesthetics, University of Oxford, Oxford, UK
                [2 ] Oxford University Computing Laboratory, Oxford, UK
                Article
                1471-2288-1-1
                10.1186/1471-2288-1-1
                32200
                11231885
                252df9ba-8f7b-46c3-880b-028b55c1d916
                Copyright © 2001 Smith et al; licensee BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL.
                History
                : 25 October 2000
                : 10 January 2001
                Categories
                Research Article

                Medicine
                Medicine

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