  Identifying patient characteristics that influence the rate of colorectal
polyp recurrence can provide important insights into which patients are at
higher risk for recurrence. We used natural language processing to extract
polyp morphological characteristics from 953 polyp-presenting patients'
electronic medical records. We used subsequent colonoscopy reports to examine
how the time to polyp recurrence (731 patients experienced recurrence) is
influenced by these characteristics as well as anthropometric features using
Kaplan-Meier curves, Cox proportional hazards modeling, and random survival
forest models. We found that the rate of recurrence differed significantly by
polyp size, number, and location and patient smoking status. Additionally,
right-sided colon polyps increased recurrence risk by 30% compared to
left-sided polyps. History of tobacco use increased polyp recurrence risk by
20% compared to never-users. A random survival forest model showed an AUC of
0.65 and identified several other predictive variables, which can inform
development of personalized polyp surveillance plans.
