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A Rulefit-based prognostic analysis using structured MRI report to select potential beneficiaries from induction chemotherapy in advanced nasopharyngeal carcinoma: A dual-centre study.

Authors :
Li, Shuqi
Zhang, Weijing
Liang, Baodan
Huang, Wenjie
Luo, Chao
Zhu, Yuliang
Kou, Kit Ian
Ruan, Guangying
Liu, Lizhi
Zhang, Guoyi
Li, Haojiang
Source :
Radiotherapy & Oncology. Dec2023, Vol. 189, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

• Rulefit enables the utilization of logical associations behind structured MRI report for nasopharyngeal carcinoma in the forms of prognostic rules. • The Rules model using Rulefit achieved a better accuracy and generalizability than common models for the prediction of overall survival among advanced nasopharyngeal carcinoma, with the highest C-index of 0.711 in external testing cohort. • Significant survival benefit was achieved in high-risk group stratified by Rules model with additional induction chemotherapy treatment. Structured MRI report facilitate prognostic prediction for nasopharyngeal carcinoma (NPC). However, the intrinsic association among structured variables is not fully utilised. This study aimed to investigate the performance of a Rulefit-based model in feature integration behind structured MRI report and prognostic prediction in advanced NPC. We retrospectively enrolled 1207 patients diagnosed with non-metastatic advanced NPC from two centres, and divided into training (N = 544), internal testing (N = 367), and external testing (N = 296) cohorts. Machine learning algorithms including multivariate analysis, deep learning, Lasso, and Rulefit were used to establish corresponding prognostic models. The concordance indices (C- indices) of three clinical and six combined models with different algorithms for overall survival (OS) prediction were compared. Survival benefits of induction chemotherapy (IC) were calculated among risk groups stratified by different models. A website was established for individualised survival visualisation. Incorporating structured variables into Stage model significantly improved the prognostic prediction performance. Six prognostic rules with structured variables were identified by Rulefit. OS prediction of Rules model was comparable to Lasso model in internal testing cohort (C-index: 0.720 vs. 0.713, P = 0.100) and achieved the highest C-index of 0.711 in external testing cohort, indicating better generalisability. The Rules model stratified patients into risk groups with significant 5-year OS differences in each cohort, and revealed significant survival benefits from additional IC in high-risk group. The Rulefit-based Rules model, with the revelation of intrinsic associations behind structured variables, is promising in risk stratification and guiding individualised IC treatment for advanced NPC. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01678140
Volume :
189
Database :
Academic Search Index
Journal :
Radiotherapy & Oncology
Publication Type :
Academic Journal
Accession number :
173853371
Full Text :
https://doi.org/10.1016/j.radonc.2023.109943