How to impute study-specific standard deviations in meta-analyses of skewed continuous endpoints?

AIM: To compare four methods to approximate mean and standard deviation (SD) when only medians and interquartile ranges are provided. METHODS: We performed simulated meta-analyses on six datasets of 15, 30, 50, 100, 500, and 1000 trials, respectively. Subjects were iteratively generated from one of the following seven scenarios: five theoretical continuous distributions [Normal, Normal (0, 1), Gamma, Exponential, and Bimodal] and two real-life distributions of intensive care unit stay and hospital stay. For each simulation, we calculated the pooled estimates assembling the study-specific medians and SD approximations: Conservative SD, less conservative SD, mean SD, or interquartile range. We provided a graphical evaluation of the standardized differences. To show which imputation method produced the best estimate, we ranked those differences and calculated the rate at which each estimate appeared as the best, second-best, third-best, or fourth-best. RESULTS: Our results demonstrated that the best pooled estimate for the overall mean and SD was provided by the median and interquartile range (mean standardized estimates: 4.5 +/- 2.2, P = 0.14) or by the median and the SD conservative estimate (mean standardized estimates: 4.5 +/- 3.5, P = 0.13). The less conservative approximation of SD appeared to be the worst method, exhibiting a significant difference from the reference method at the 90% confidence level. The method that ranked first most frequently is the interquartile range method (23/42 = 55%), particularly when data were generated according to the Standard Normal, Gamma, and Exponential distributions. The second-best is the conservative SD method (15/42 = 36%), particularly for data from a bimodal distribution and for the intensive care unit stay variable. CONCLUSION: Meta-analytic estimates are not significantly affected by approximating the missing values of mean and SD with the correspondent values for median and interquartile range.