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      Effectiveness of non-benzodiazepine hypnotics in treatment of adult insomnia: meta-analysis of data submitted to the Food and Drug Administration

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          Abstract

          Objectives To investigate the effectiveness of non-benzodiazepine hypnotics (Z drugs) and associated placebo responses in adults and to evaluate potential moderators of effectiveness in a dataset used to approve these drugs.

          Design Systematic review and meta-analysis.

          Data source US Food and Drug Administration (FDA).

          Study selection Randomised double blind parallel placebo controlled trials of currently approved Z drugs (eszopiclone, zaleplon, and zolpidem).

          Data extraction Change score from baseline to post-test for drug and placebo groups; drug efficacy analysed as the difference of both change scores. Weighted raw and standardised mean differences with their confidence intervals under random effects assumptions for polysomnographic and subjective sleep latency, as primary outcomes. Secondary outcomes included waking after sleep onset, number of awakenings, total sleep time, sleep efficiency, and subjective sleep quality. Weighted least square regression analysis was used to explain heterogeneity of drug effects.

          Data synthesis 13 studies containing 65 separate drug-placebo comparisons by type of outcome, type of drug, and dose were included. Studies included 4378 participants from different countries and varying drug doses, lengths of treatment, and study years. Z drugs showed significant, albeit small, improvements (reductions) in our primary outcomes: polysomnographic sleep latency (weighted standardised mean difference, 95% confidence interval −0.57 to −0.16) and subjective sleep latency (−0.33, −0.62 to −0.04) compared with placebo. Analyses of weighted mean raw differences showed that Z drugs decreased polysomnographic sleep latency by 22 minutes (−33 to −11 minutes) compared with placebo. Although no significant effects were found in secondary outcomes, there were insufficient studies reporting these outcomes to allow firm conclusions. Moderator analyses indicated that sleep latency was more likely to be reduced in studies published earlier, with larger drug doses, with longer duration of treatment, with a greater proportion of younger and/or female patients, and with zolpidem.

          Conclusion Compared with placebo, Z drugs produce slight improvements in subjective and polysomnographic sleep latency, especially with larger doses and regardless of type of drug. Although the drug effect and the placebo response were rather small and of questionable clinical importance, the two together produced to a reasonably large clinical response.

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          Most cited references19

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          Sedative hypnotics in older people with insomnia: meta-analysis of risks and benefits.

          To quantify and compare potential benefits (subjective reports of sleep variables) and risks (adverse events and morning-after psychomotor impairment) of short term treatment with sedative hypnotics in older people with insomnia. Medline, Embase, the Cochrane clinical trials database, PubMed, and PsychLit, 1966 to 2003; bibliographies of published reviews and meta-analyses; manufacturers of newer sedative hypnotics (zaleplon, zolpidem, zopiclone) regarding unpublished studies. Randomised controlled trials of any pharmacological treatment for insomnia for at least five consecutive nights in people aged 60 or over with insomnia and otherwise free of psychiatric or psychological disorders. 24 studies (involving 2417 participants) with extractable data met inclusion and exclusion criteria. Sleep quality improved (effect size 0.14, P 0.05), and reports of daytime fatigue were 3.82 times more common (1.88 to 7.80, P < 0.001) in people using any sedative compared with placebo. Improvements in sleep with sedative use are statistically significant, but the magnitude of effect is small. The increased risk of adverse events is statistically significant and potentially clinically relevant in older people at risk of falls and cognitive impairment. In people over 60, the benefits of these drugs may not justify the increased risk, particularly if the patient has additional risk factors for cognitive or psychomotor adverse events.
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            Fixed- versus random-effects models in meta-analysis: model properties and an empirical comparison of differences in results.

            Today most conclusions about cumulative knowledge in psychology are based on meta-analysis. We first present an examination of the important statistical differences between fixed-effects (FE) and random-effects (RE) models in meta-analysis and between two different RE procedures, due to Hedges and Vevea, and to Hunter and Schmidt. The implications of these differences for the appropriate interpretation of published meta-analyses are explored by applying the two RE procedures to 68 meta-analyses from five large meta-analytic studies previously published in Psychological Bulletin. Under the assumption that the goal of research is generalizable knowledge, results indicated that the published FE confidence intervals (CIs) around mean effect sizes were on average 52% narrower than their actual width, with similar results being produced by the two RE procedures. These nominal 95% FE CIs were found to be on average 56% CIs. Because most meta-analyses in the literature use FE models, these findings suggest that the precision of meta-analysis findings in the literature has often been substantially overstated, with important consequences for research and practice.
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              The power of statistical tests for moderators in meta-analysis.

              Calculation of the statistical power of statistical tests is important in planning and interpreting the results of research studies, including meta-analyses. It is particularly important in moderator analyses in meta-analysis, which are often used as sensitivity analyses to rule out moderator effects but also may have low statistical power. This article describes how to compute statistical power of both fixed- and mixed-effects moderator tests in meta-analysis that are analogous to the analysis of variance and multiple regression analysis for effect sizes. It also shows how to compute power of tests for goodness of fit associated with these models. Examples from a published meta-analysis demonstrate that power of moderator tests and goodness-of-fit tests is not always high. ((c) 2004 APA, all rights reserved).
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                Author and article information

                Contributors
                Role: assistant professor
                Role: associate director of program in placebo studies (PiPS), lecturer in medicineRole: professor of psychology
                Role: research assistant
                Role: research fellow
                Role: professor of primary and prehospital health care
                Journal
                BMJ
                BMJ
                bmj
                BMJ : British Medical Journal
                BMJ Publishing Group Ltd.
                0959-8138
                1756-1833
                2012
                2012
                17 December 2012
                : 345
                : e8343
                Affiliations
                [1 ]Department of Allied Health Sciences, University of Connecticut, 358 Mansfield Road U-2101, Storrs, CT 06269-2101, USA
                [2 ]Harvard Medical School, Beth Israel Deaconess Medical Center, USA,
                [3 ]School of Psychology, Plymouth University, Plymouth, UK
                [4 ]Community and Health Research Unit, Lincoln School of Health and Social Care, University of Lincoln, Lincoln LN6 7TS, UK
                Author notes
                Correspondence to: A N Siriwardena nsiriwardena@ 123456lincoln.ac.uk
                Article
                huet004819
                10.1136/bmj.e8343
                3544552
                23248080
                d0a27a32-c639-445d-a196-4772f85770d1
                © Huedo-Medina et al 2012

                This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode.

                History
                : 30 November 2012
                Categories
                Research
                1779

                Medicine
                Medicine

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