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      When and how should multiple imputation be used for handling missing data in randomised clinical trials – a practical guide with flowcharts

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          Abstract

          Background

          Missing data may seriously compromise inferences from randomised clinical trials, especially if missing data are not handled appropriately. The potential bias due to missing data depends on the mechanism causing the data to be missing, and the analytical methods applied to amend the missingness. Therefore, the analysis of trial data with missing values requires careful planning and attention.

          Methods

          The authors had several meetings and discussions considering optimal ways of handling missing data to minimise the bias potential. We also searched PubMed (key words: missing data; randomi*; statistical analysis) and reference lists of known studies for papers (theoretical papers; empirical studies; simulation studies; etc.) on how to deal with missing data when analysing randomised clinical trials.

          Results

          Handling missing data is an important, yet difficult and complex task when analysing results of randomised clinical trials. We consider how to optimise the handling of missing data during the planning stage of a randomised clinical trial and recommend analytical approaches which may prevent bias caused by unavoidable missing data. We consider the strengths and limitations of using of best-worst and worst-best sensitivity analyses, multiple imputation, and full information maximum likelihood. We also present practical flowcharts on how to deal with missing data and an overview of the steps that always need to be considered during the analysis stage of a trial.

          Conclusions

          We present a practical guide and flowcharts describing when and how multiple imputation should be used to handle missing data in randomised clinical.

          Electronic supplementary material

          The online version of this article (10.1186/s12874-017-0442-1) contains supplementary material, which is available to authorized users.

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          Most cited references30

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          Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls

          Most studies have some missing data. Jonathan Sterne and colleagues describe the appropriate use and reporting of the multiple imputation approach to dealing with them
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            The prevention and treatment of missing data in clinical trials.

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              Hydroxyethyl starch 130/0.42 versus Ringer's acetate in severe sepsis.

              Hydroxyethyl starch (HES) [corrected] is widely used for fluid resuscitation in intensive care units (ICUs), but its safety and efficacy have not been established in patients with severe sepsis. In this multicenter, parallel-group, blinded trial, we randomly assigned patients with severe sepsis to fluid resuscitation in the ICU with either 6% HES 130/0.42 (Tetraspan) or Ringer's acetate at a dose of up to 33 ml per kilogram of ideal body weight per day. The primary outcome measure was either death or end-stage kidney failure (dependence on dialysis) at 90 days after randomization. Of the 804 patients who underwent randomization, 798 were included in the modified intention-to-treat population. The two intervention groups had similar baseline characteristics. At 90 days after randomization, 201 of 398 patients (51%) assigned to HES 130/0.42 had died, as compared with 172 of 400 patients (43%) assigned to Ringer's acetate (relative risk, 1.17; 95% confidence interval [CI], 1.01 to 1.36; P=0.03); 1 patient in each group had end-stage kidney failure. In the 90-day period, 87 patients (22%) assigned to HES 130/0.42 were treated with renal-replacement therapy versus 65 patients (16%) assigned to Ringer's acetate (relative risk, 1.35; 95% CI, 1.01 to 1.80; P=0.04), and 38 patients (10%) and 25 patients (6%), respectively, had severe bleeding (relative risk, 1.52; 95% CI, 0.94 to 2.48; P=0.09). The results were supported by multivariate analyses, with adjustment for known risk factors for death or acute kidney injury at baseline. Patients with severe sepsis assigned to fluid resuscitation with HES 130/0.42 had an increased risk of death at day 90 and were more likely to require renal-replacement therapy, as compared with those receiving Ringer's acetate. (Funded by the Danish Research Council and others; 6S ClinicalTrials.gov number, NCT00962156.).
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                Author and article information

                Contributors
                jcj@ctu.dk
                cgluud@ctu.dk
                wetterslev@ctu.dk
                pwinkel@ctu.dk
                Journal
                BMC Med Res Methodol
                BMC Med Res Methodol
                BMC Medical Research Methodology
                BioMed Central (London )
                1471-2288
                6 December 2017
                6 December 2017
                2017
                : 17
                : 162
                Affiliations
                [1 ]The Copenhagen Trial Unit, Centre for Clinical Intervention Research, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
                [2 ]ISNI 0000 0004 0646 8763, GRID grid.414289.2, Department of Cardiology, Holbæk Hospital, ; Holbæk, Denmark
                Article
                442
                10.1186/s12874-017-0442-1
                5717805
                29207961
                2d7aa46b-170e-4e4c-8be8-f8f8ef95b175
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 30 May 2017
                : 24 November 2017
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2017

                Medicine
                missing data,randomised clinical trials,multiple imputation
                Medicine
                missing data, randomised clinical trials, multiple imputation

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