LAUSR

OBJECTIVE Determining factors that predict a career in academic neurosurgery can help to improve neurosurgical training and faculty mentoring efforts. Though many academic career predictors have been established in the literature, no method has yet been developed to allow for individualized predictions of an academic career trajectory. The objective of the present study was to develop a web-based calculator for predicting the probability of a career in academic neurosurgery. METHODS The present study utilized data from neurosurgeons listed in the American Association of Neurological Surgeons (AANS) database. A logistic regression model was used to predict probability of an academic career, and bootstrapping with 2000 samples was used to calculate an optimism-corrected c-statistic. p<0.05 was considered statistically significant. RESULTS A total of 1,818 neurosurgeons were included in our analysis. The majority of surgeons were male (89.7%) and employed in non-academic positions (60.2%). Factors independently associated with an academic career were female sex, attending a residency program affiliated with a top 10 U.S. News medical school, attaining a Doctor of Philosophy (Ph.D.) degree, attaining a Master of Science (M.S.) degree, higher h-index during residency, more months of protected research time during residency, and completing a clinical fellowship. Our final model had an optimism-corrected c-statistic of 0.74. This model was incorporated into a web-based calculator (https://neurooncsurgery.shinyapps.io/academic_calculator/). CONCLUSION The present study consolidates prior research investigating neurosurgery career predictors into a simple, open-access tool. Our work may serve to better clarify the many factors influencing trainees' likelihood of pursuing a career in academic neurosurgery.