Wenqiang Guan1,2, Kang Xie1,3, Yixin Fan1, Stefan Lin4,5, Rui Huang1, Qianlong Tang1, Ailin Chen1, Yanqiong Song1, Jinyi Lang1, Peng Zhang1. 1. Department of Radiation Oncology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Radiation Oncology Key Laboratory of Sichuan Province, Chengdu, China. 2. Department of Oncology, The Second People's Hospital of Yibin, Yibin, China. 3. The Second Department of Oncology, Chengdu First People's Hospital, Chengdu, China. 4. Department of Computer Science and Engineering, Office for Student Affairs, School of Statistics, Economics Institute, University of Minnesota-Twin Cities, Minneapolis, MN, United States. 5. Viterbi School of Engineering Applied Data Science, University of Southern California, Los Angeles, CA, United States.
Abstract
BACKGROUND: The purpose was to develop and validate a nomogram for prediction on radiation-induced temporal lobe injury (TLI) in patients with nasopharyngeal carcinoma (NPC). METHODS: The prediction model was developed based on a primary cohort that consisted of 194 patients. The data was gathered from January 2008 to December 2010. Clinical factors associated with TLI and dose-volume histograms for 388 evaluable temporal lobes were analyzed. Multivariable logistic regression analysis was used to develop the predicting model, which was conducted by R software. The performance of the nomogram was assessed with calibration and discrimination. An external validation cohort contained 197 patients from January 2011 to December 2013. RESULTS: Among the 391 patients, 77 patients had TLI. Prognostic factors contained in the nomogram were Dmax (the maximum point dose) of temporal lobe, D1cc (the maximum dose delivered to a volume of 1 ml), T stage, and neutrophil-to-lymphocyte ratios (NLRs). The Internal validation showed good discrimination, with a C-index of 0.847 [95%CI 0.800 to 0.893], and good calibration. Application of the nomogram in the external validation cohort still obtained good discrimination (C-index, 0.811 [95% CI, 0.751 to 0.870]) and acceptable calibration. CONCLUSIONS: This study developed and validated a nomogram, which may be conveniently applied for the individualized prediction of TLI.
BACKGROUND: The purpose was to develop and validate a nomogram for prediction on radiation-induced temporal lobe injury (TLI) in patients with nasopharyngeal carcinoma (NPC). METHODS: The prediction model was developed based on a primary cohort that consisted of 194 patients. The data was gathered from January 2008 to December 2010. Clinical factors associated with TLI and dose-volume histograms for 388 evaluable temporal lobes were analyzed. Multivariable logistic regression analysis was used to develop the predicting model, which was conducted by R software. The performance of the nomogram was assessed with calibration and discrimination. An external validation cohort contained 197 patients from January 2011 to December 2013. RESULTS: Among the 391 patients, 77 patients had TLI. Prognostic factors contained in the nomogram were Dmax (the maximum point dose) of temporal lobe, D1cc (the maximum dose delivered to a volume of 1 ml), T stage, and neutrophil-to-lymphocyte ratios (NLRs). The Internal validation showed good discrimination, with a C-index of 0.847 [95%CI 0.800 to 0.893], and good calibration. Application of the nomogram in the external validation cohort still obtained good discrimination (C-index, 0.811 [95% CI, 0.751 to 0.870]) and acceptable calibration. CONCLUSIONS: This study developed and validated a nomogram, which may be conveniently applied for the individualized prediction of TLI.
Authors: Ying Sun; Xiao-Li Yu; Wei Luo; Anne W M Lee; Joseph Tien Seng Wee; Nancy Lee; Guan-Qun Zhou; Ling-Long Tang; Chang-Juan Tao; Rui Guo; Yan-Ping Mao; Rong Zhang; Ying Guo; Jun Ma Journal: Radiother Oncol Date: 2014-04-07 Impact factor: 6.280
Authors: James C H Chow; Ka-Man Cheung; Kwok-Hung Au; Benny C Y Zee; Jack Lee; Roger K C Ngan; Anne W M Lee; Harry H Y Yiu; Kenneth W S Li; Alex K C Leung; Jeffrey C H Chan; Francis K H Lee; Kam-Hung Wong Journal: Radiother Oncol Date: 2019-06-25 Impact factor: 6.280