Predicting disease progression from the rate of bodyweight change in nasopharyngeal carcinoma patient during radiotherapy

• Published in: Scientific reports Vol. 15; no. 1; pp. 7490 - 12
• Main Authors: Sun, Jiachen, Lam, Sai kit Edmond, Teng, Xinzhi, Zhang, Jiang, Lee, Francis Kar-ho, Yip, Celia Wai-yi, Chow, James Chung-hang, Lee, Victor Ho-fun, Sun, Ying, Cai, Jing
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 03.03.2025; Nature Publishing Group; Nature Portfolio
• Subjects: 631/114/1305; 631/553/2701; 631/67/1536; 692/53/2422; 692/53/2423; Adjuvant chemotherapy; Adult; Aged; Body height; Body Weight - radiation effects; Chemotherapy; Concurrent chemoradiotherapy; Deep learning; Differential equations; Disease Progression; Female; Humanities and Social Sciences; Humans; Male; Middle Aged; multidisciplinary; Multivariate analysis; Nasopharyngeal carcinoma; Nasopharyngeal Carcinoma - pathology; Nasopharyngeal Carcinoma - radiotherapy; Nasopharyngeal Neoplasms - pathology; Nasopharyngeal Neoplasms - radiotherapy; Patients; Prognosis; Radiation therapy; Retrospective Studies; Science; Science (multidisciplinary); Throat cancer; Weight loss; Weight Loss - radiation effects; Nasopharyngeal carcinoma; Deep learning; Adjuvant chemotherapy; Concurrent chemoradiotherapy; Weight loss; Differential equations
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-025-88810-x

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.