Brian R Hirshman1,2,3, Ali A Alattar4, Sanjay Dhawan5, Kathleen M Carley2,3, Clark C Chen6. 1. Department of Neurosurgery, University of California San Diego, San Diego, CA, USA. 2. Center for Computational Analysis of Social and Organizational Systems, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA. 3. Computation, Organizations and Society Program, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA. 4. School of Medicine, University of California San Diego, San Diego, CA, USA. 5. Department of Neurosurgery, University of Minnesota, Minneapolis, MN, USA. 6. Department of Neurosurgery, University of Minnesota, Minneapolis, MN, USA. ccchen@umn.edu.
Abstract
BACKGROUND: Our previous studies suggest that the training history of an investigator, termed "medical academic genealogy", influences the outcomes of that investigator's research. Here, we use meta-analysis and quantitative statistical modeling to determine whether such effects contribute to systematic bias in published conclusions. METHODS: A total of 108 articles were identified through a comprehensive search of the high-grade glioma (HGG) surgical resection literature. Analysis was performed on the 70 articles with sufficient data for meta-analysis. Pooled estimates were generated for key academic genealogies. Monte Carlo simulations were performed to determine whether the effects attributed to genealogy alone can arise due to chance alone. RESULTS: Meta-analysis of the HGG literature without consideration for academic medical genealogy revealed that gross total resection (GTR) was associated with a significant decrease in the odds ratio (OR) for the hazard of death after surgery for both anaplastic astrocytoma (AA) and glioblastoma (AA: log [OR] = - 0.04, 95% CI [- 0.07 to - 0.01]; glioblastoma log [OR] = - 0.36, 95% CI [- 0.44 to - 0.29]). For the glioblastoma literature, meta-analysis of articles contributed by members of a genealogy consisting of mostly radiation oncologists revealed no reduction in the hazard of death after GTR [log [OR] = - 0.16, 95% CI [- 0.41 to 0.09]. In contrast, meta-analysis of published articles contributed by members of a genealogy consisting of mostly neurosurgeons revealed that GTR was associated with a significant reduction in the hazard of death [log [OR] = - 0.29, 95% CI [- 0.40 to 0.18]. Monte Carlo simulation revealed that the observed discrepancy between the articles contributed by the members of these two genealogies was unlikely to arise by chance alone (p < 0.006). CONCLUSIONS: Meta-analysis of articles contributed by authors belonging to the different medical academic genealogies yielded distinct and contradictory pooled point-estimates, suggesting that genealogy contributes to systematic bias in the published literature.
BACKGROUND: Our previous studies suggest that the training history of an investigator, termed "medical academic genealogy", influences the outcomes of that investigator's research. Here, we use meta-analysis and quantitative statistical modeling to determine whether such effects contribute to systematic bias in published conclusions. METHODS: A total of 108 articles were identified through a comprehensive search of the high-grade glioma (HGG) surgical resection literature. Analysis was performed on the 70 articles with sufficient data for meta-analysis. Pooled estimates were generated for key academic genealogies. Monte Carlo simulations were performed to determine whether the effects attributed to genealogy alone can arise due to chance alone. RESULTS: Meta-analysis of the HGG literature without consideration for academic medical genealogy revealed that gross total resection (GTR) was associated with a significant decrease in the odds ratio (OR) for the hazard of death after surgery for both anaplastic astrocytoma (AA) and glioblastoma (AA: log [OR] = - 0.04, 95% CI [- 0.07 to - 0.01]; glioblastoma log [OR] = - 0.36, 95% CI [- 0.44 to - 0.29]). For the glioblastoma literature, meta-analysis of articles contributed by members of a genealogy consisting of mostly radiation oncologists revealed no reduction in the hazard of death after GTR [log [OR] = - 0.16, 95% CI [- 0.41 to 0.09]. In contrast, meta-analysis of published articles contributed by members of a genealogy consisting of mostly neurosurgeons revealed that GTR was associated with a significant reduction in the hazard of death [log [OR] = - 0.29, 95% CI [- 0.40 to 0.18]. Monte Carlo simulation revealed that the observed discrepancy between the articles contributed by the members of these two genealogies was unlikely to arise by chance alone (p < 0.006). CONCLUSIONS: Meta-analysis of articles contributed by authors belonging to the different medical academic genealogies yielded distinct and contradictory pooled point-estimates, suggesting that genealogy contributes to systematic bias in the published literature.
Entities:
Keywords:
Brain tumor; Medical academic genealogy; Meta-analysis; Scientific objectivity
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