Analysis of the Frequency, Characteristics, and Reasons for Termination of Spine-related Clinical Trials.

STUDY DESIGN: Cross-sectional analysis of completed and terminated spine-related clinical trials in the ClinicalTrials.gov registry. OBJECTIVE: The aim was to quantify completed and terminated spine-related clinical trials, assess reasons for termination, and determine predictors of termination by comparing characteristics of completed and terminated trials. SUMMARY OF BACKGROUND DATA: Clinical trials are key to the advancement of products and procedures related to the spine. Unfortunately, trials may be terminated before completion. ClinicalTrials.gov is a registry and results database maintained by the National Library of Medicine that catalogs trial characteristics and tracks overall recruitment status (eg, ongoing, completed, terminated) for each study as well as reasons for termination. Reasons for trial termination have not been specifically evaluated for spine-related clinical trials. METHODS: The ClinicalTrials.gov database was queried on July 20, 2021 for all completed and terminated interventional studies registered to date using all available spine-related search terms. Trial characteristics and reason for termination, were abstracted. Univariate and multivariate analyses were performed determine predictors of trial termination. RESULTS: A total of 969 clinical trials were identified and characterized (833 completed, 136 terminated). Insufficient rate of participant accrual was the most frequently reported reason for trial termination, accounting for 33.8% of terminated trials.Multivariate analysis demonstrated increased odds of trial termination for industry-sponsorship [odds ratio (OR)=1.59] relative to sponsorship from local groups, device studies (OR=2.18) relative to investigations of drug or biological product(s), and phase II (OR=3.07) relative to phase III studies ( P <0.05 for each). CONCLUSIONS: Spine-related clinical trials were found to be terminated 14% of the time, with insufficient accrual being the most common reason for termination. With significant resources put into clinical studies and the need to advance scientific objectives, predictors, and reasons for trial termination should be considered and optimized to increase the completion rate of trials that are initiated.

Preresidency Publication Productivity of U.S. Neurosurgery Interns.

BACKGROUND: Research experience is believed to be an important component of the neurosurgery residency application process. One measure of research productivity is publication volume. The preresidency publication volume of U.S. neurosurgery interns and any potential association between applicant publication volume and the match results of top-ranked residency programs have not been well characterized. OBJECTIVE: In this study, we sought to characterize the preresidency publication volume of U.S. neurosurgery residents in the 2018-2019 intern class using the Scopus database. METHODS: For each intern, we recorded the total number of publications, total number of first or last author publications, total number of neuroscience-related publications, mean number of citations per publication, and mean impact factor of the journal per publication. Preresidency publication volumes of interns at the top-25 programs (based on a composite ranking score according to 4 different ranking metrics) were compared with those at all other programs. RESULTS: We found that 82% of neurosurgery interns included in the analysis (190 interns from 95 programs) had at least 1 publication. The average number of publications per intern among all programs was 6 ± 0.63 (mean ± standard error of the mean). We also found that interns at top-25 neurosurgery residency programs tended to have a higher number of publications (8.3 ± 1.2 vs. 4.8 ± 0.7, P = 0.0137), number of neuroscience-related publications (6.8 ± 1.1 vs. 4.1 ± 0.7, P = 0.0419), and mean number of citations per publication (9.8 ± 1.7 vs. 5.7 ± 0.8, P = 0.0267) compared with interns at all other programs. CONCLUSIONS: Our results provide a general estimate of the preresidency publication volume of U.S. neurosurgery interns and suggest a potential association between publication volume and matching in the top-25 neurosurgery residency programs.

Insights into Computational Drug Repurposing for Neurodegenerative Disease.

Computational drug repurposing has the ability to remarkably reduce drug development time and cost in an era where these factors are prohibitively high. Several examples of successful repurposed drugs exist in fields such as oncology, diabetes, leprosy, inflammatory bowel disease, among others, however computational drug repurposing in neurodegenerative disease has presented several unique challenges stemming from the lack of validation methods and difficulty in studying heterogenous diseases of aging. Here, we examine existing approaches to computational drug repurposing, including molecular, clinical, and biophysical methods, and propose data sources and methods to advance computational drug repurposing in neurodegenerative disease using Alzheimer's disease as an example.