[Not all published data are reliable: fabricated data in medical research]. / Niet alle gepubliceerde data zijn betrouwbaar.

For a long time, the reliability of medical-scientific research was, without further verification, based on real data. It is becoming increasingly clear that this assumption is unjustified and that probably at least 25% of published randomized clinical trials are based on unreliable and sometimes even fabricated data. After giving a number of examples, it is discussed what the reader can do about this problem. More importantly, editors and publishers should no longer rely on whistle-blowers but take action themselves. If this does not happen, external parties must intervene. Society cannot afford (medical) science that is based on unreliable data.

Data integrity of 14 randomised controlled trials.

BACKGROUND: A review of the literature on iron treatments for iron-deficient anaemia in pregnancy indicated duplication of baseline and outcome tables in two separate randomised controlled trials (RCTs) that share only a single author. AIM: To assess the integrity of randomised clinical trials from Dr A.M. Darwish, Assiut University, Egypt. DESIGN: Assessment of Research Integrity. METHODS: We tabulated the characteristics of studies, compared baseline and outcome tables between articles and looked for implausible findings. We used the distribution of baseline p-values to assess whether the summary statistics of baseline characteristics were consistent with properly conducted randomisation. RESULTS: We identified 14 RCTs (1,405 participants) published between October 2004 and September 2019. Two pairs of studies showed considerable similarities in baseline characteristics, while another pair of studies was plagiarized. The analysis of baseline p-values indicated a low probability that all the studies featured randomised treatment allocation. CONCLUSION: Our analysis of the RCTs of Dr Darwish suggests possible integrity problems. We recommend a critical investigation of the studies that have not been retracted. Until that has been completed, these studies should not be used to inform clinical practice.

A survey of experts to identify methods to detect problematic studies: Stage 1 of the INSPECT-SR Project.

Background: Randomised controlled trials (RCTs) inform healthcare decisions. Unfortunately, some published RCTs contain false data, and some appear to have been entirely fabricated. Systematic reviews are performed to identify and synthesise all RCTs which have been conducted on a given topic. This means that any of these 'problematic studies' are likely to be included, but there are no agreed methods for identifying them. The INSPECT-SR project is developing a tool to identify problematic RCTs in systematic reviews of healthcare-related interventions. The tool will guide the user through a series of 'checks' to determine a study's authenticity. The first objective in the development process is to assemble a comprehensive list of checks to consider for inclusion. Methods: We assembled an initial list of checks for assessing the authenticity of research studies, with no restriction to RCTs, and categorised these into five domains: Inspecting results in the paper; Inspecting the research team; Inspecting conduct, governance, and transparency; Inspecting text and publication details; Inspecting the individual participant data. We implemented this list as an online survey, and invited people with expertise and experience of assessing potentially problematic studies to participate through professional networks and online forums. Participants were invited to provide feedback on the checks on the list, and were asked to describe any additional checks they knew of, which were not featured in the list. Results: Extensive feedback on an initial list of 102 checks was provided by 71 participants based in 16 countries across five continents. Fourteen new checks were proposed across the five domains, and suggestions were made to reword checks on the initial list. An updated list of checks was constructed, comprising 116 checks. Many participants expressed a lack of familiarity with statistical checks, and emphasized the importance of feasibility of the tool. Conclusions: A comprehensive list of trustworthiness checks has been produced. The checks will be evaluated to determine which should be included in the INSPECT-SR tool.