Analyzing the usage of standards in radiation therapy clinical studies

Standards for scoring adverse effects after radiation therapy (RT) is crucial for integrated, consistent, and accurate analysis of toxicity results at large scale and across multiple studies. This project aims to investigate the usage of the three most commonly used standards in published RT clinical studies by developing a text-mining based analysis method. We develop and compare two text-mining methods, one based on regular expressions and one based on Naïve Bayes Classifier, to analyze published full articles in terms of their adoption of standards in RT. The full dataset includes published articles identified in MEDLINE between January 2010 and August 2015. A radiation oncology physician reviewed all the articles in the training/validation subset and produced the usage trending data manually as gold standard for validation. The regular-expression based method reported classifications and overall usage trends that are comparable to those of the domain expert. The CTCAE standard is becoming the overall most commonly used standards over time, but the pace of adoption seems very slow. Further examination of the results indicates that the usage vary by disease type. It suggests that further efforts are needed to improve and harmonize the standards for adverse effects scoring in RT research community.