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In clinical trials, missing outcome data can be problematic, potentially introducing bias and affecting internal and external study validity.1–7 These concerns are not new. Multiple guidelines for investigators emphasise the importance of first minimising the causes of missing data, such as loss to follow-up, and then using appropriate statistical strategies to account for missing values.5 ,8–11
In spite of the increased focus on addressing missing outcome data in the design and analysis phases of clinical trials, there continues to be significant variability in how the missing data—and the related statistical analyses—are reported in the medical literature.2 ,12 Systematic reviews of published studies have found that few clinical trial reports provide a complete description of the investigators’ strategy for addressing missing outcome data,2 ,12 which can significantly impact the interpretation of study findings.1 ,3 ,4 ,6 ,7 As the recommended statistical approaches to missing data grow increasingly complex,8 ,13–15 there is more need than ever to ensure that clinical trials are reported clearly and include sufficient detail to allow readers to critically assess the underlying assumptions made by investigators.
The CONSORT (Consolidated Standards of Reporting) statement,16 which was developed to improve the reporting of clinical trials, is widely used as the standard for the format and content of clinical trial reports. While the guidelines in the updated CONSORT 2010 statement only explicitly call for investigators to address missing outcome data in the …
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