Tian-Tian Zhai1, Lisanne V van Dijk2, Bao-Tian Huang3, Zhi-Xiong Lin4, Cássia O Ribeiro2, Charlotte L Brouwer2, Sjoukje F Oosting5, Gyorgy B Halmos6, Max J H Witjes7, Johannes A Langendijk2, Roel J H M Steenbakkers2, Nanna M Sijtsema2. 1. Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, The Netherlands; Department of Radiation Oncology, Cancer Hospital of Shantou University Medical College, China. Electronic address: t.zhai@umcg.nl. 2. Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, The Netherlands. 3. Department of Radiation Oncology, Cancer Hospital of Shantou University Medical College, China. 4. Department of Radiation Oncology, Cancer Hospital of Shantou University Medical College, China. Electronic address: zxlin5@qq.com. 5. Department of Medical Oncology, University Medical Center Groningen, University of Groningen, The Netherlands. 6. Department of Otolaryngology, University Medical Center Groningen, University of Groningen, The Netherlands. 7. Department of Maxillofacial Surgery, University Medical Center Groningen, University of Groningen, The Netherlands.
Abstract
PURPOSE: To develop and validate prediction models of overall survival (OS) for head and neck cancer (HNC) patients based on image biomarkers (IBMs) of the primary tumor and positive lymph nodes (Ln) in combination with clinical parameters. MATERIAL AND METHODS: The study cohort was composed of 289 nasopharyngeal cancer (NPC) patients from China and 298 HNC patients from the Netherlands. Multivariable Cox-regression analysis was performed to select clinical parameters from the NPC and HNC datasets, and IBMs from the NPC dataset. Final prediction models were based on both IBMs and clinical parameters. RESULTS: Multivariable Cox-regression analysis identified three independent IBMs (tumor Volume-density, Run Length Non-uniformity and Ln Major-axis-length). This IBM model showed a concordance(c)-index of 0.72 (95%CI: 0.65-0.79) for the NPC dataset, which performed reasonably with a c-index of 0.67 (95%CI: 0.62-0.72) in the external validation HNC dataset. When IBMs were added in clinical models, the c-index of the NPC and HNC datasets improved to 0.75 (95%CI: 0.68-0.82; p=0.019) and 0.75 (95%CI: 0.70-0.81; p<0.001), respectively. CONCLUSION: The addition of IBMs from the primary tumor and Ln improved the prognostic performance of the models containing clinical factors only. These combined models may improve pre-treatment individualized prediction of OS for HNC patients.
PURPOSE: To develop and validate prediction models of overall survival (OS) for head and neck cancer (HNC) patients based on image biomarkers (IBMs) of the primary tumor and positive lymph nodes (Ln) in combination with clinical parameters. MATERIAL AND METHODS: The study cohort was composed of 289 nasopharyngeal cancer (NPC) patients from China and 298 HNC patients from the Netherlands. Multivariable Cox-regression analysis was performed to select clinical parameters from the NPC and HNC datasets, and IBMs from the NPC dataset. Final prediction models were based on both IBMs and clinical parameters. RESULTS: Multivariable Cox-regression analysis identified three independent IBMs (tumor Volume-density, Run Length Non-uniformity and Ln Major-axis-length). This IBM model showed a concordance(c)-index of 0.72 (95%CI: 0.65-0.79) for the NPC dataset, which performed reasonably with a c-index of 0.67 (95%CI: 0.62-0.72) in the external validation HNC dataset. When IBMs were added in clinical models, the c-index of the NPC and HNC datasets improved to 0.75 (95%CI: 0.68-0.82; p=0.019) and 0.75 (95%CI: 0.70-0.81; p<0.001), respectively. CONCLUSION: The addition of IBMs from the primary tumor and Ln improved the prognostic performance of the models containing clinical factors only. These combined models may improve pre-treatment individualized prediction of OS for HNC patients.
Authors: Jong Yeob Kim; Andreas Kronbichler; Michael Eisenhut; Sung Hwi Hong; Hans J van der Vliet; Jeonghyun Kang; Jae Il Shin; Gabriele Gamerith Journal: Cancers (Basel) Date: 2019-11-15 Impact factor: 6.639
Authors: Lisanne V van Dijk; Steven J Frank; Ying Yuan; Brandon Gunn; Amy C Moreno; Abdallah S R Mohamed; Kathryn E Preston; Yun Qing; Michael T Spiotto; William H Morrison; Anna Lee; Jack Phan; Adam S Garden; David I Rosenthal; Johannes A Langendijk; Clifton D Fuller Journal: Clin Transl Radiat Oncol Date: 2021-11-11