Unreported summary statistics in trial publications and risk of bias in stroke rehabilitation systematic reviews: an international survey of review authors and examination of practical solutions

So we have no standardization of stroke research. A COMPLETE FAILURE  because we have NO STROKE LEADERSHIP.  We need to destroy all the

fucking failures of stroke associations

and replace them with survivor led ones.

Unreported summary statistics in trial publications and risk of bias in stroke rehabilitation systematic reviews: an international survey of review authors and examination of practical solutions

Introduction
Systematic reviews and meta-analyses of the effectiveness of stroke rehabilitation interventions
form a valuable resource for stroke survivors, carers, researchers, healthcare professionals, guideline developers and policymakers. The Cochrane Library1 contains over 200 stroke-related
systematic reviews co-ordinated by the Cochrane Stroke Review Group. The influential role of
systematic reviews as the primary route to readily accessible and rigorous summaries of stroke
trial findings confers a responsibility on reviewers to implement valid and robust methodology.
With the rapid and accelerating accumulation of new stroke trial data, systematic reviews must
summarise the evidence with minimal bias and the greatest possible precision to inform stroke
patients and healthcare professionals and to guide future stroke research. This depends
critically on avoiding bias in identifying trials, selecting trials for meta-analysis and extracting data;2 and on including as much of the available data as possible. 
Continuous outcome measures such as the Stroke Impact Scale3 and SS-QOL (Williams et al.,
1999) are highly relevant to stroke survivors, while continuous resource use measures such as
hospital length of stay are pivotal to evaluating the cost-effectiveness of a stroke intervention. Around one-third of stroke reviews in the Cochrane Database of Systematic Reviews1 include a
continuous primary outcome; three-quarters contain a continuous secondary outcome.  
Although some continuous outcomes have a “bell-shaped” normal distribution, many do not:
examples include hospital length of stay and measures of physical function and depression post-stroke.5  For such outcomes, analysis strategies and reporting vary:6 the clinical trial
publication often summarises the outcome using the median and either the minimum and
maximum values or the lower and upper quartiles. In contrast, standard meta-analysis requires information on the mean and either the standard deviation, variance or standard error7 for each
treatment group.  These may not be reported for outcomes that are not normally distributed.
Accessing original individual patient data or additional summary statistics not included in the original trial report is often difficult.8 
While the problem of incomplete reporting of trials9 has lessened in recent years thanks in part to reporting guidance such as the CONsolidated Standards Of Reporting Trials (CONSORT),10
in order to summarise the available literature fully stroke rehabilitation systematic reviewers still
need to deal with unreported standard deviation and mean values. One option is to exclude the
trial from the meta-analysis. The alternative is to apply statistical methods to recover the
unreported values, allowing the trial to be retained in the meta-analysis.  We recently reviewed methods to handle missing standard deviation and missing mean values.11  Here, we explore
the extent of the issue in stroke rehabilitation systematic reviewing and illustrate potential solutions by reanalysing individual patient data from a Cochrane stroke review.12    
We planned to establish, via a survey of Cochrane review authors, how often stroke
rehabilitation systematic reviewers encounter missing mean or standard deviation values in their
reviews and the methods they use to address this.  Secondly, we aimed to illustrate the use of
statistical methods for handling missing standard deviation and mean values in meta-analysis by reanalysing individual patient data from a Cochrane stroke review.12  We sought to identify
methods that would be straightforward for systematic reviewers to apply, while still avoiding bias
and giving the correct level of precision in the meta-analysis findings