Abstract
BackgroundPreoperative chemoradiotherapy (CRT) is a standard treatment for locally advanced rectal cancer (LARC). However, individual responses to preoperative CRT vary from patient to patient. The aim of this study is to develop a scoring system for the response of preoperative CRT in LARC using blood features derived from machine learning.MethodsPatients who underwent total mesorectal excision after preoperative CRT were included in this study. The performance of machine learning models using blood features before CRT (pre-CRT) and from 1 to 2 weeks after CRT (early-CRT) was evaluated. Based on the best model, important features were selected. The scoring system was developed from the selected model and features. The performance of the new scoring system was compared with those of systemic inflammatory indicators: neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, and the prognostic nutritional index.ResultsThe models using early-CRT blood features had better performances than those using pre-CRT blood features. Based on the ridge regression model, which showed the best performance among the machine learning models (AUROC 0.6322 and AUPRC 0.5965), a novel scoring system for the response of preoperative CRT, named Response Prediction Score (RPS), was developed. The RPS system showed higher predictive power (AUROC 0.6747) than single blood features and systemic inflammatory indicators and stratified the tumor regression grade and overall downstaging clearly.ConclusionWe discovered that we can more accurately predict CRT response by using early-treatment blood data. With larger data, we can develop a more accurate and reliable indicator that can be used in real daily practices. In the future, we urge the collection of early-treatment blood data and pre-treatment blood data.
Highlights
Rectal cancer represents approximately one-third of all colorectal cancer with the third highest incidence [1]
Total leukocyte, neutrophil, and monocyte counts at two weeks after initiating CRT were related to the response of CRT
PreCRT immune cell compositions were not related to the response of CRT (Supplementary Tables 1 and 2) These results suggest that blood features during CRT can more reflect the reaction to CRT than pre-treatment blood features
Summary
Rectal cancer represents approximately one-third of all colorectal cancer with the third highest incidence [1]. A considerable proportion (about 30–40%) of rectal cancer is locally advanced rectal cancer (LARC) [2, 3]. Local recurrence rates of rectal cancer are relatively higher than those of colon cancer. To reduce local recurrence in rectal cancer, radiotherapy has been performed in locally advanced rectal cancer (LARC). Preoperative radiotherapy or chemoradiotherapy (CRT) is accepted as a standard of care for rectal cancer [5]. Individual response to CRT is variable across patients. Preoperative chemoradiotherapy (CRT) is a standard treatment for locally advanced rectal cancer (LARC). Individual responses to preoperative CRT vary from patient to patient. The aim of this study is to develop a scoring system for the response of preoperative CRT in LARC using blood features derived from machine learning
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
