Predicting disease progression from the rate of bodyweight change in nasopharyngeal carcinoma patient during radiotherapy
Abstract Bodyweight loss is a common occurrence in Nasopharyngeal Carcinoma (NPC) patients during Radiotherapy (RT). Previous studies found that the prognostic value of percentage weight loss (pWL) during RT is not credible. We aimed to develop a novel progression predictor surrogated to pWL by mode...
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Nature Portfolio
2025-03-01
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| Online Access: | https://doi.org/10.1038/s41598-025-88810-x |
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| author | Jiachen Sun Sai kit Edmond Lam Xinzhi Teng Jiang Zhang Francis Kar-ho Lee Celia Wai-yi Yip James Chung-hang Chow Victor Ho-fun Lee Ying Sun Jing Cai |
| author_facet | Jiachen Sun Sai kit Edmond Lam Xinzhi Teng Jiang Zhang Francis Kar-ho Lee Celia Wai-yi Yip James Chung-hang Chow Victor Ho-fun Lee Ying Sun Jing Cai |
| author_sort | Jiachen Sun |
| collection | DOAJ |
| description | Abstract Bodyweight loss is a common occurrence in Nasopharyngeal Carcinoma (NPC) patients during Radiotherapy (RT). Previous studies found that the prognostic value of percentage weight loss (pWL) during RT is not credible. We aimed to develop a novel progression predictor surrogated to pWL by modelling all bodyweight records measured during the treatment interval. This retrospective study included two independent hospitals of 624 patients. The Predicted Progression Probability (PPP) was obtained from deep learning-guided differential equation solution, model by the patient’s age, sex, body height, and the weekly measured bodyweight records. The performance of PPP in predicting disease progression was assessed, its association with prognosis and adjuvant chemotherapy response was evaluated. The PPP was learnt from the training cohort (N = 257) with 7 weeks of bodyweight records. The prediction performance was validated with 367 patients of the testing cohort sub-divided according to the number of bodyweight records found. The area under of curve for patients with 7 weeks (N = 155), 6 weeks (N = 176), and 5 weeks bodyweight records (N = 32) were 0.76, 0.73, and 0.95 respectively. PPP was significantly associated with progression-free and remained an independent prognostic factor adjusting for clinicopathologic variables in multivariate analysis in all study cohort (adjusted hazard ratio [HR] range: 2.50–7.04, all p < 0.001). Patients with high-PPP derived progression benefit from adjuvant chemotherapy (HR: 0.41–0.54, all p < 0.03), whereas those with low-PPP did not for both cohorts. The trajectory of bodyweight change during RT is more robust than the pWL to give a progression prediction after RT. The PPP is a reliable predictor for estimating the risk of residual diseases after RT course, which also helps to predict adjuvant chemotherapy response in locally advanced NPC patients. |
| format | Article |
| id | doaj-art-0462f7e7a57c44f7890fe8051c6074b3 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-0462f7e7a57c44f7890fe8051c6074b32025-08-20T03:06:01ZengNature PortfolioScientific Reports2045-23222025-03-0115111210.1038/s41598-025-88810-xPredicting disease progression from the rate of bodyweight change in nasopharyngeal carcinoma patient during radiotherapyJiachen Sun0Sai kit Edmond Lam1Xinzhi Teng2Jiang Zhang3Francis Kar-ho Lee4Celia Wai-yi Yip5James Chung-hang Chow6Victor Ho-fun Lee7Ying Sun8Jing Cai9Department of Health Technology and Informatics, The Hong Kong Polytechnic UniversityDepartment of Biomedical Engineering, The Hong Kong Polytechnic UniversityDepartment of Health Technology and Informatics, The Hong Kong Polytechnic UniversityDepartment of Health Technology and Informatics, The Hong Kong Polytechnic UniversityDepartment of Clinical Oncology, Queen Elizabeth HospitalDepartment of Clinical Oncology, Queen Elizabeth HospitalDepartment of Clinical Oncology, Queen Elizabeth HospitalDepartment of Clinical Oncology, The University of Hong KongState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnostics and Therapy, Department of Radiation Oncology, Sun Yat-Sen University Cancer CenterDepartment of Health Technology and Informatics, The Hong Kong Polytechnic UniversityAbstract Bodyweight loss is a common occurrence in Nasopharyngeal Carcinoma (NPC) patients during Radiotherapy (RT). Previous studies found that the prognostic value of percentage weight loss (pWL) during RT is not credible. We aimed to develop a novel progression predictor surrogated to pWL by modelling all bodyweight records measured during the treatment interval. This retrospective study included two independent hospitals of 624 patients. The Predicted Progression Probability (PPP) was obtained from deep learning-guided differential equation solution, model by the patient’s age, sex, body height, and the weekly measured bodyweight records. The performance of PPP in predicting disease progression was assessed, its association with prognosis and adjuvant chemotherapy response was evaluated. The PPP was learnt from the training cohort (N = 257) with 7 weeks of bodyweight records. The prediction performance was validated with 367 patients of the testing cohort sub-divided according to the number of bodyweight records found. The area under of curve for patients with 7 weeks (N = 155), 6 weeks (N = 176), and 5 weeks bodyweight records (N = 32) were 0.76, 0.73, and 0.95 respectively. PPP was significantly associated with progression-free and remained an independent prognostic factor adjusting for clinicopathologic variables in multivariate analysis in all study cohort (adjusted hazard ratio [HR] range: 2.50–7.04, all p < 0.001). Patients with high-PPP derived progression benefit from adjuvant chemotherapy (HR: 0.41–0.54, all p < 0.03), whereas those with low-PPP did not for both cohorts. The trajectory of bodyweight change during RT is more robust than the pWL to give a progression prediction after RT. The PPP is a reliable predictor for estimating the risk of residual diseases after RT course, which also helps to predict adjuvant chemotherapy response in locally advanced NPC patients.https://doi.org/10.1038/s41598-025-88810-xNasopharyngeal carcinomaConcurrent chemoradiotherapyAdjuvant chemotherapyWeight lossDeep learningDifferential equations |
| spellingShingle | Jiachen Sun Sai kit Edmond Lam Xinzhi Teng Jiang Zhang Francis Kar-ho Lee Celia Wai-yi Yip James Chung-hang Chow Victor Ho-fun Lee Ying Sun Jing Cai Predicting disease progression from the rate of bodyweight change in nasopharyngeal carcinoma patient during radiotherapy Scientific Reports Nasopharyngeal carcinoma Concurrent chemoradiotherapy Adjuvant chemotherapy Weight loss Deep learning Differential equations |
| title | Predicting disease progression from the rate of bodyweight change in nasopharyngeal carcinoma patient during radiotherapy |
| title_full | Predicting disease progression from the rate of bodyweight change in nasopharyngeal carcinoma patient during radiotherapy |
| title_fullStr | Predicting disease progression from the rate of bodyweight change in nasopharyngeal carcinoma patient during radiotherapy |
| title_full_unstemmed | Predicting disease progression from the rate of bodyweight change in nasopharyngeal carcinoma patient during radiotherapy |
| title_short | Predicting disease progression from the rate of bodyweight change in nasopharyngeal carcinoma patient during radiotherapy |
| title_sort | predicting disease progression from the rate of bodyweight change in nasopharyngeal carcinoma patient during radiotherapy |
| topic | Nasopharyngeal carcinoma Concurrent chemoradiotherapy Adjuvant chemotherapy Weight loss Deep learning Differential equations |
| url | https://doi.org/10.1038/s41598-025-88810-x |
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