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Meta-Analysis
. 2009 Aug 13;4(8):e6624.
doi: 10.1371/journal.pone.0006624.

Missing data in randomized clinical trials for weight loss: scope of the problem, state of the field, and performance of statistical methods

Mai A Elobeid  1 , Miguel A Padilla, Theresa McVie, Olivia Thomas, David W Brock, Bret Musser, Kaifeng Lu, Christopher S Coffey, Renee A Desmond, Marie-Pierre St-Onge, Kishore M Gadde, Steven B Heymsfield, David B Allison
Affiliations
Meta-Analysis

Missing data in randomized clinical trials for weight loss: scope of the problem, state of the field, and performance of statistical methods

Mai A Elobeid et al. PLoS One. .

Abstract

Background: Dropouts and missing data are nearly-ubiquitous in obesity randomized controlled trails, threatening validity and generalizability of conclusions. Herein, we meta-analytically evaluate the extent of missing data, the frequency with which various analytic methods are employed to accommodate dropouts, and the performance of multiple statistical methods.

Methodology/principal findings: We searched PubMed and Cochrane databases (2000-2006) for articles published in English and manually searched bibliographic references. Articles of pharmaceutical randomized controlled trials with weight loss or weight gain prevention as major endpoints were included. Two authors independently reviewed each publication for inclusion. 121 articles met the inclusion criteria. Two authors independently extracted treatment, sample size, drop-out rates, study duration, and statistical method used to handle missing data from all articles and resolved disagreements by consensus. In the meta-analysis, drop-out rates were substantial with the survival (non-dropout) rates being approximated by an exponential decay curve (e(-lambdat)) where lambda was estimated to be .0088 (95% bootstrap confidence interval: .0076 to .0100) and t represents time in weeks. The estimated drop-out rate at 1 year was 37%. Most studies used last observation carried forward as the primary analytic method to handle missing data. We also obtained 12 raw obesity randomized controlled trial datasets for empirical analyses. Analyses of raw randomized controlled trial data suggested that both mixed models and multiple imputation performed well, but that multiple imputation may be more robust when missing data are extensive.

Conclusion/significance: Our analysis offers an equation for predictions of dropout rates useful for future study planning. Our raw data analyses suggests that multiple imputation is better than other methods for handling missing data in obesity randomized controlled trials, followed closely by mixed models. We suggest these methods supplant last observation carried forward as the primary method of analysis.

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Conflict of interest statement

Competing Interests: Allison, Gadde, Coffey, and St-Onge have received grants, honoraria, consulting fees, or donations from multiple food, pharmaceutical, dietary supplement, and other companies, government agencies, and litigators with interests in obesity randomized controlled trials. Drs. Musser, Liu, and Heymsfield are employees of Merck & Co. None of the remaining authors reported financial disclosures.

Figures

Figure 1
Figure 1. Scatter plot of dropouts over time with fitted exponential decay curve.
Drop-out rates for six small (N = 18 to 60) studies that reported zero drop-outs were set to 1% to allow the analyses to proceed.
Figure 2
Figure 2. Percent of published studies using methods to accommodate drop-outs.
For this chart, when an article reported using more than one analytic procedure, it was coded as having used the ‘best’ of the procedures it employed where the ranking was in ascending order: Completers only, LOCF (any variation on last observation carried forward); an unspecified intent to treat (ITT) analysis; any of several mixed model analyses (mixed), or multiple imputation (MI). ‘Completers’ denotes completer only analysis, ITT-NOS, ITT not otherwise specified, ‘No Drop Outs’, no dropouts reported, and NS, not specified.
Figure 3
Figure 3. Mean power level averaged across all 12 RCT plasmode situations with 95% confidence intervals.
See this image and copyright information in PMC

References

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