Reporting of statistical sample size calculations in publications of trials on age-related macular degeneration, glaucoma and cataract

Abstract

Background Transparent and complete publications of randomised controlled trials (RCT) ought to comply with the guidelines of the CONSORT Statement, which stipulates sample size calculation as an important aspect of trial planning. The objective of this study was to analyse and compare the reporting of statistical sample size calculations in RCT papers on the treatment of age-related macular degeneration (AMD), glaucoma and cataract published in 2018. Material and methods This study comprises a total of 113 RCT papers (RCT-P) published in 2018 (AMD: 14, glaucoma: 28, cataract: 71), in English or German, and identified through an internet-based literature search in PubMed and EMBASE. The primary outcome measure of the study was the number of trials providing a complete description of the underlying sample case calculation on the basis of the variables required (significance level, expected outcomes, power, and resulting sample size). Results Of the RCTs reviewed, 64% (AMD), 61% (glaucoma) and 31% (cataract) provided a justification of the number of patients included. A complete description of the described studies’ sample size calculation including all the necessary values (primary outcome measure of this study) was described by 21% of the AMD, 29% of the cataract and 18% of the glaucoma RCT publications (in total: 24 of 113 (21%) at a confidence interval of 95%: [13%; 29%]). Conclusion All three treatment areas analysed lacked reporting quality regarding the justification of the number of patients included in a clinical trial based on a sample size calculation required for ethical reasons. More than half of all RCT publications reviewed did not provide all of the required information on statistical sample size calculation, and thus lacked transparency and completeness. It is therefore urgently required to involve methodologists in a study’s planning and publishing processes to ensure that methodology descriptions are transparent and of high quality.