Journal
ANNALS OF NEUROLOGY
Volume 79, Issue 2, Pages 169-177Publisher
WILEY-BLACKWELL
DOI: 10.1002/ana.24569
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Funding
- Czech Duck research fellowship in Neurosurgery at the University of California San Diego
- ONR Multidisciplinary University Research Initiative [N000140811186]
- Center for Computational Analysis of Social and Organizational Systems (CASOS)
- Clinical and Translational Research Institute
- National Institutes of Health of CTSA [UL1TR001442]
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Academic genealogy refers to the linking of scientists and scholars based on their dissertation supervisors. We propose that this concept can be applied to medical training and that this medical academic genealogy may influence the landscape of the peer-reviewed literature. We performed a comprehensive PubMed search to identify US authors who have contributed peer-reviewed articles on a neurosurgery topic that remains controversial: the value of maximal resection for high-grade gliomas (HGGs). Training information for each key author (defined as the first or last author of an article) was collected (eg, author's medical school, residency, and fellowship training). Authors were recursively linked to faculty mentors to form genealogies. Correlations between genealogy and publication result were examined. Our search identified 108 articles with 160 unique key authors. Authors who were members of 2 genealogies (14% of key authors) contributed to 38% of all articles. If an article contained an authorship contribution from the first genealogy, its results were more likely to support maximal resection (log odds ratio=2.74, p<0.028) relative to articles without such contribution. In contrast, if an article contained an authorship contribution from the second genealogy, it was less likely to support maximal resection (log odds ratio=-1.74, p<0.026). We conclude that the literature on surgical resection for HGGs is influenced by medical academic genealogies, and that articles contributed by authors of select genealogies share common results. These findings have important implications for the interpretation of scientific literature, design of medical training, and health care policy. Ann Neurol 2016;79:169-177
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