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False or flawed clinical trial data is a significant problem in medicine: some experts believe that up to a quarter of trails contain false or flawed data, spread throughout different medical fields. A July 2023 news feature from Nature reported findings from anesthetist John Carlisle, who reviewed more than 500 manuscripts from randomized controlled trials (RCTs).
We summarize the article here, and encourage our readers to check out the full piece at Nature (Link: https://www.nature.com/articles/d41586-023-02299-w)
Carlisle found that 44% of the trials he surveyed contained some flawed data, and 26% were impossible to trust due to incompetence or data falsification. As these trials seemed to be real research but were empty of trustful content, Carlisle calls them “zombie” trials. Although the prevalence is unclear, Carlisle’s data show editors, reviewers, and readers should be wary of untrustworthy trial data, especially when conducting systematic reviews and meta-analyses, which influence medical guidelines and clinical decision-making.
There are several efforts to address this issue. Some suggest that reliably excluding zombie data from systematic reviews requires the implementation of checks when examining RCTs, using criteria such as registration, study methods, funding, and statistical validity. Others propose journals should routinely request authors to share individual participant data (IPD) to verify the authenticity of trials. However this solution raises privacy concerns and requires considerable resources to properly archive the data. Increasing the transparency in institutional investigations, completing computational checks to examine data, and managing retractions after a systematic review are also important factors.
Untrustworthy clinical trials are an urgent issue in medicine. “Zombie" reports can lead to harmful consequences for patients when false or unreliable information influences clinical decision-making. Addressing this issue requires a multi-disciplinary approach. The medical community can defend the trust and reliability of clinical trials data by working collaboratively and with rigorous standards.