Accurately assessing the risk of recurrence in patients with locally advanced rectal cancer (LARC) before treatment is important for the development of treatment strategies. The purpose of this study is to develop an MRI-based scoring system to predict the risk of recurrence in patients with LARC.
This was a multicenter observational study that enrolled participants who underwent neoadjuvant chemoradiotherapy. To evaluate the risk of recurrence in these patients, we developed the mrDEC scoring system and assessed inter-reader agreement. Additionally, we plotted Kaplan–Meier curves to compare the 3-year disease-free survival (DFS) and 5-year overall survival (OS) rates among patients with different mrDEC scores.
A total of 1287 patients with LARC were included in this study. We observed substantial inter-reader agreement for mrDEC. Based on the mrDEC scores ranging from 0 to 3, the patients were categorized into four groups. The 3-year DFS rates for the groups were 91.0%, 79.5%, 65.5%, and 44.0% (P < 0.0001), respectively, and the 5-year OS rates were 92.9%, 87.1%, 74.8%, and 44.5%, respectively (P < 0.0001).
The mrDEC scoring system proved to be an effective tool for predicting the prognosis of patients with LARC and can assist clinicians in clinical decision-making.
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All data supporting the findings in this study are presented in the manuscript and the supplementary information, and additional raw data can be made available by the corresponding author upon reasonable request.
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This work was supported by the National Postdoctoral Program for Innovative Talents of China (No.BX20220359), Science Foundation of Yunnan Basic Research (202201AT070010), NSFC Incubation Project of Guangdong Provincial People’s Hospital (KY0120220037), National Science Foundation for Young Scientists of China (82202267), National Natural Science Foundation of China (No. 82001789), National Science Fund for Distinguished Young Scholars , Regional Innovation and Development Joint Fund of National Natural Science Foundation of China (No.U22A20345), and Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application [2022B1212010011].
Funding sources can be found in “Acknowledgements” section.
The authors declare no competing interests.
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Zhao, M., Feng, L., Zhao, K. et al. An MRI-based scoring system for pretreatment risk stratification in locally advanced rectal cancer. Br J Cancer 129, 1095–1104 (2023). https://doi.org/10.1038/s41416-023-02384-x