ArticleFrontiers in surgery2025
Work smart, not hard: analysis of delays faced by clinical trials investigating spinal fusion using Protocol AI.
Article in Frontiers in surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Degenerative diseases of the spine are increasingly prevalent with age. Spinal fusion is a common treatment if non-invasive or less-invasive treatment approaches have not been successful. Numerous clinical trials on spinal fusion are started every year to investigate novel technologies worldwide. However, a substiantial amount of trials are terminated prior to completion. Research question: In this study, we analyzed the historical performance of all clinical trials on spinal fusion since 2010. Material and methods: The identification of related trials was carried out using Protocol AI, which is the Risklick's software. It collects and updates clinical trial data from various sources, including clinical trial registries and datasets from the World Health Organization. Protocol AI has automatically extracted the data on trial, categorized them, and clustered them in trial phases. Results: The historical probability of early termination for a clinical trial investigating spinal fusion was approximately 25%. The average trial delay for completed trials was 10.6 months. With an average anticipated trial duration approaching 40 months, the observed delay represents an extension of 25% of the anticipated trial duration for completed trials. Trials facing delay and failure predominantly reported critical issues with patient recruitment. Dicsussion and conclusion: This study emphasizes the importance of implementing a strict risk management plan and recruitment plans, while suggesting professionals to implement standardized enrollment monitoring analyzes during the course of the trial. The amelioration of recruitment policies could substantially maximize the performance of trials within the field, benefiting patients and all stakeholders involved.
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