Meta-analysis Of Continuous Outcomes Research Articles

Meta-analysis of continuous outcomes: Using pseudo IPD created from aggregate data to adjust for baseline imbalance and assess treatment-by-baseline modification.

Meta‐analysis of individual participant data (IPD) is considered the “gold‐standard” for synthesizing clinical study evidence. However, gaining access to IPD can be a laborious task (if possible at all) and in practice only summary (aggregate) data are commonly available. In this work we focus on meta‐analytic approaches of comparative studies where aggregate data are available for continuous outcomes measured at baseline (pre‐treatment) and follow‐up (post‐treatment). We propose a method for constructing pseudo individual baselines and outcomes based on the aggregate data. These pseudo IPD can be subsequently analysed using standard analysis of covariance (ANCOVA) methods. Pseudo IPD for continuous outcomes reported at two timepoints can be generated using the sufficient statistics of an ANCOVA model, i.e., the mean and standard deviation at baseline and follow‐up per group, together with the correlation of the baseline and follow‐up measurements. Applying the ANCOVA approach, which crucially adjusts for baseline imbalances and accounts for the correlation between baseline and change scores, to the pseudo IPD, results in identical estimates to the ones obtained by an ANCOVA on the true IPD. In addition, an interaction term between baseline and treatment effect can be added. There are several modeling options available under this approach, which makes it very flexible. Methods are exemplified using reported data of a previously published IPD meta‐analysis of 10 trials investigating the effect of antihypertensive treatments on systolic blood pressure, leading to identical results compared with the true IPD analysis and of a meta‐analysis of fewer trials, where baseline imbalance occurred.

Dealing with missing standard deviation and mean values in meta-analysis of continuous outcomes: a systematic review

BackgroundRigorous, informative meta-analyses rely on availability of appropriate summary statistics or individual participant data. For continuous outcomes, especially those with naturally skewed distributions, summary information on the mean or variability often goes unreported. While full reporting of original trial data is the ideal, we sought to identify methods for handling unreported mean or variability summary statistics in meta-analysis.MethodsWe undertook two systematic literature reviews to identify methodological approaches used to deal with missing mean or variability summary statistics. Five electronic databases were searched, in addition to the Cochrane Colloquium abstract books and the Cochrane Statistics Methods Group mailing list archive. We also conducted cited reference searching and emailed topic experts to identify recent methodological developments. Details recorded included the description of the method, the information required to implement the method, any underlying assumptions and whether the method could be readily applied in standard statistical software. We provided a summary description of the methods identified, illustrating selected methods in example meta-analysis scenarios.ResultsFor missing standard deviations (SDs), following screening of 503 articles, fifteen methods were identified in addition to those reported in a previous review. These included Bayesian hierarchical modelling at the meta-analysis level; summary statistic level imputation based on observed SD values from other trials in the meta-analysis; a practical approximation based on the range; and algebraic estimation of the SD based on other summary statistics. Following screening of 1124 articles for methods estimating the mean, one approximate Bayesian computation approach and three papers based on alternative summary statistics were identified. Illustrative meta-analyses showed that when replacing a missing SD the approximation using the range minimised loss of precision and generally performed better than omitting trials. When estimating missing means, a formula using the median, lower quartile and upper quartile performed best in preserving the precision of the meta-analysis findings, although in some scenarios, omitting trials gave superior results.ConclusionsMethods based on summary statistics (minimum, maximum, lower quartile, upper quartile, median) reported in the literature facilitate more comprehensive inclusion of randomised controlled trials with missing mean or variability summary statistics within meta-analyses.

P234 Impact Of Inhaled Corticosteroids On Growth In Children With Asthma: Systematic Review And Meta-analysis

Background There are major concerns and uncertainty regarding a possible reduction in growth velocity and final height of children with asthma who are long-term users of inhaled corticosteroids (ICS). We aimed to evaluate the association between ICS use of >12 months and growth. Methods We initially searched MEDLINE and EMBASE in July 2013, followed by a PubMed search updated to June 2014. We used a combination of search terms involving drug names and adverse effects of interest (such as growth or height), and we also hand-searched reference lists of existing systematic reviews and trial reports. We selected RCTs and controlled observational studies of any ICS vs non-ICS control treatment in patients with asthma (treatment duration of at least 52 weeks). Meta-analysis of continuous outcomes (growth velocity in cm/year or final height in cm) was conducted using RevMan 5.3. We analysed mean differences using inverse variance method, random effects model. Heterogeneity was assessed using the I2 statistic. Results We found 21 relevant studies (seventeen RCTs and four observational studies) after screening 1876 hits from the search. Meta-analysis of 16 RCTs showed a significant association between ICS use and reduction in growth velocity compared to controls (pooled Mean Difference -0.35cm/year, 95% CI -0.54 to -0.18). No significant reduction in growth velocity with ICS was reported in two observational studies of lower quality (pooled Mean Difference 0.03cm/year, 95% CI -0.61 to 0.67). Analysis of final adult height showed a mean reduction of -1.20 cm (95% CI -1.90 cm to – 0.50 cm) with budesonide versus placebo in a high quality RCT. Meta-analysis of two lower quality observational studies found a non-statistically significant pooled mean reduction in final adult height of -0.85 cm (95% CI -3.35 to 1.65). Conclusion Use of ICS for 12 months or more in children with asthma has a limited impact on annual growth velocity, with a slight reduction in final adult height. When interpreted in the context of the typical final adult height in the UK, ICS users may experience less than 0.7% reduction in height compared to non-ICS users.