Data Sharing Failures Limit Accuracy of Neuroimaging Meta-Analyses

The integrity of evidence based medicine and the data sharing gap

Modern clinical practice relies on the synthesis of vast amounts of data to guide interventions, such as the management of atrial fibrillation or the use of intraarterial treatment within 6 hours for acute ischemic stroke [1, 2]. Systematic reviews and meta-analyses (statistical methods that combine results from multiple independent studies to reach a single conclusion) serve as the primary tools for aggregating disparate findings, including the identification of neuroimaging biomarkers for social cognitive impairments or the prediction of outcomes in neurodegenerative diseases [3, 4, 5]. However, the utility of these syntheses depends entirely on data transparency, as evidenced by meta-analyses of resting-state functional magnetic resonance imaging where findings in anxiety disorders were not robust to file-drawer effects (the statistical bias where negative or non-significant results remain unpublished, leading to an overestimation of treatment efficacy) [6]. When critical information remains inaccessible or reporting is non-standardized, the resulting evidence base may be incomplete, potentially skewing the clinical guidelines that physicians use for daily decision-making [7, 8]. A new analysis now quantifies the extent of this information gap and its impact on the reliability of medical literature.

Quantifying the communication gap in neuroimaging research

To evaluate the accessibility of the evidence base supporting clinical neuroimaging, researchers conducted a retrospective quantitative analysis of research data requests ( a study design that looks back at historical records to measure specific outcomes) sent to authors of neuroimaging studies. This investigation tracked the outcomes of inquiries made during the preparation of a series of meta-analyses, focusing on the responsiveness of primary investigators and the actual availability of the data required for clinical synthesis. The researchers sought to determine how often the scientific community could successfully retrieve the underlying metrics necessary to validate or aggregate findings across different patient populations. This process is vital for clinicians because the strength of a recommendation often depends on the raw data underlying published p-values.

Predictors of data inaccessibility and author non-responsiveness

The researchers identified several specific variables that predicted whether a data request would be ignored or denied, revealing systemic vulnerabilities in how clinical evidence is maintained. Paradoxically, the analysis found that obtaining a response was less likely if the request was sent to the contact e-mail address provided in the publication. This suggests that the primary point of contact listed in medical journals often becomes obsolete or unmonitored, creating a significant barrier for clinicians who may need to contact authors for clarification on patient protocols or specific imaging parameters. Furthermore, the type of information sought influenced the success of the inquiry; the study found that obtaining a response was less likely if behavioral data was requested. These measures, which include patient performance metrics or symptom severity scores, are essential for correlating neuroanatomical findings with clinical presentation, yet they appear to be less accessible than raw imaging files. The study also highlighted counterintuitive social and temporal barriers that hinder the synthesis of medical evidence. While persistence is often encouraged in professional communication, the data showed that obtaining a response was less likely if reminders had to be sent, indicating that initial non-responsiveness is a strong predictor of a permanent lack of data availability. Even more surprising was the finding that obtaining a response was less likely if there was personal acquaintance with the contacted author, suggesting that informal professional networks do not reliably facilitate the formal data-sharing required for rigorous clinical review. Finally, the age of the research played a critical role in the ability to verify findings. The researchers reported that obtaining unpublished data or information from older publications was significantly more difficult than for more recent ones, a trend that threatens the long-term stability of the evidence base as older, foundational studies effectively become closed to further scrutiny or meta-analysis.

Systemic requirements for reproducible clinical evidence

The integrity of evidence-based medicine depends on the ability of the clinical community to verify and build upon published findings. According to the researchers, crucial aspects of reproducible, replicable, and reusable science include the responsiveness of study authors for clarifications and the availability of research data and analysis results. When authors fail to provide these components, the resulting evidence gap prevents the synthesis of data necessary to form reliable clinical guidelines. The study highlights that the current failure rate, where only 29% of requests yielded usable information, stems from a lack of infrastructure and accountability. This lack of transparency means that the neuroimaging findings used to understand disease pathology or treatment response may rest on data that cannot be independently scrutinized or combined into larger, more statistically powerful cohorts. In their evaluation of why so much clinical data remains inaccessible, the authors discuss possible reasons for the observed low response rates and limited sharing of information. These factors include the absence of standardized data archiving protocols and a lack of professional incentives for maintaining data sets after a study is published. To mitigate these barriers, the study concludes by providing suggestions to improve open-science practices, such as the mandatory use of public repositories and the adoption of standardized metadata (structured information that describes the content, quality, and condition of a dataset) that ensure clinical findings remain accessible for future meta-analyses. Ultimately, the study points to a need for change in the academic system to foster better research data management for transparency and efficient reuse of results. For the practicing physician, these systemic changes are necessary to ensure that the diagnostic and therapeutic recommendations they follow are derived from a complete and verifiable body of medical evidence.

References

1. Hindricks G, Potpara T, Dagres N, et al. 2020 ESC Guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS). European Heart Journal. 2020. doi:10.1093/eurheartj/ehaa612

2. Berkhemer OA, Fransen P, Beumer D, et al. A Randomized Trial of Intraarterial Treatment for Acute Ischemic Stroke. New England Journal of Medicine. 2014. doi:10.1056/nejmoa1411587

3. Hung HK, Kranz G, Zheng Y, Hsiao J, Chan S. Efficacy of non-invasive brain stimulation on theory of mind and emotion processing in neuropsychiatric disorders: a systematic review and meta-analysis.. Neuroscience and Biobehavioral Reviews. 2025. doi:10.1016/j.neubiorev.2025.106380

4. Kiani I, Mohammadzadeh S, Mozaffari S, et al. Neuroimaging Predictors of Futile Recanalization in Anterior Circulation Stroke: A Systematic Review and Meta-Analysis.. AJNR. American journal of neuroradiology. 2025. doi:10.3174/ajnr.A9095

5. Horton M, Whiley D, Mayhew M, McLean S. Association between spirochaetal infection and neurodegenerative diseases: a systematic review and quantitative synthesis of observational studies.. Journal of Medical Microbiology. 2026. doi:10.1099/jmm.0.002136

6. Zugman A, Jett L, Antonacci C, Winkler AM, Pine DS. A systematic review and meta-analysis of resting-state fMRI in anxiety disorders: Need for data sharing to move the field forward.. Journal of anxiety disorders. 2023. doi:10.1016/j.janxdis.2023.102773

7. Jauch EC, Saver JL, Adams HP, et al. Guidelines for the Early Management of Patients With Acute Ischemic Stroke. Stroke. 2013. doi:10.1161/str.0b013e318284056a

8. Safadieh GH, Majzoub RE, Abbas LA. Neuroimaging findings in children with COVID-19 infection: a systematic review and meta-analysis.. Scientific reports. 2024. doi:10.1038/s41598-024-55597-2