AB1387 Acknowledged biostatistical help and the quality of statistical analyses in randomised controlled trials in rheumatology
Authors: G. Guzelant, E. Dincses, G. Hatemi, H. Yazici
Journal: Annals of the Rheumatic Diseases (2018)

<h3>Background</h3> The quality of statistical analysis and reporting are wanting even in our most prestigious journals.<sup>1</sup> It stands to reason that active participation of biostatisticians in data analysis and reporting would improve the situation. <h3>Objectives</h3> We aimed to test the hypothesis that more close cooperation with biostatisticians would improve the quality of reporting randomised clinical trials in rheumatology. We defined a <i>close cooperation</i> as the inclusion of a formal biostatistician among the co-authors and/or a declaration of formal statistical help in the study reports. <h3>Methods</h3> Two independent observers screened both by reading and, when applicable, electronic scanning the texts of all randomised controlled trials (RCT) in Annals of the Rheumatic Diseases, Arthritis Care and Research, Arthritis and Rheumatology, Rheumatology Oxford published in 2015 and 2016. Using a prepared worksheet, the observers specifically tabulated, the presence of a biostatistician among the co-authors and/or formal acknowledgement of statistical help in the methods, the inclusion of effect sizes (whether they were specifically indicated as such, could be calculated or not given at all) and the corresponding confidence intervals. The instances in which an effect size was given as a number needed to treat (NNT) and number needed to harm (NNH) were separately sought. In addition at the number of times separate p values were reported for interdependent comparisons (like DAS28-CRP and DAS28-ESR), and the presence of a Bayesian analysis in the methods. <h3>Results</h3> The total RCT number in these four journals was 134. In 26 trials, there was a biostatistician or an epidemiologist as a co-author and in 3, statistical help was acknowledged in the text. In the remaining 105 papers (78%) no statistical help was declared. The tabulation of effect sizes, confidence intervals and giving separate p values for interdependent variables are given in the table 1. In giving the effect sizes it is to be noted that the presence of a statistician made did not improve the explicit announcement of an effect size but made it more calculable. None of the trials used Bayesian methods for analysis. Only in one trial NNT and in another NNH (both with no acknowledged biostatistical help) were given. <h3>Conclusions</h3> The inclusion of a biostatistician improved the reporting of effect sizes, at least rendering them calculable. The same cannot be said for reporting confidence intervals and separate p values for interdependent variables. It was interesting that Bayesian analyses and giving NNT and NNH, rather intuitive ways of expressing effect sizes, were not popular. There were 2 main limitations. The sample size was relatively small and many authors could have obtained statistical help without acknowledging it. <h3>Reference</h3> [1] Chavalarias D, et al. JAMA. 2016,315(11):1141–8 <h3>Disclosure of Interest</h3> None declared