X. Zhou, W. Zhao, Y. Chen, and Z. Zhang, “Chapter Six - Patient-derived tumor models for human nasopharyngeal carcinoma,” in Chick Chorioallantoic Membrane Model and Precision Cancer Therapy, vol. 46, F. B. T.-T. E. Tamanoi, Ed., Academic Press, 2019, pp. 81–96. https://doi.org/10.1016/bs.enz.2019.08.007.

L.-X. Peng and C.-N. Qian, “Chapter 17 - Nasopharyngeal Cancer,” S. G. B. T.-E. C. T. Gray, Ed., Boston: Academic Press, 2015, pp. 373–389. https://doi.org/10.1016/B978-0-12-800206-3.00017-3.

P. J. Slootweg and A. K. El-Naggar, “World Health Organization 4th edition of head and neck tumor classification: insight into the consequential modifications.” Virchows Archiv: an international journal of pathology, vol. 472, no. 3. Germany, pp. 311–313, Mar. 2018. https://doi.org/10.1007/s00428-018-2320-6.

Y. Wang, Y. Zhang, and S. Ma, “Racial differences in nasopharyngeal carcinoma in the United States.,” Cancer Epidemiol, vol. 37, no. 6, pp. 793–802, Dec. 2013. https://doi.org/10.1016/j.canep.2013.08.008.

Article  PubMed  Google Scholar 

H. Peng et al., “Prognostic value of deep learning PET/CT-based radiomics: Potential role for future individual induction chemotherapy in advanced nasopharyngeal carcinoma,” Clinical Cancer Research, vol. 25, no. 14, pp. 4271–4279, 2019. https://doi.org/10.1158/1078-0432.CCR-18-3065.

Article  CAS  PubMed  Google Scholar 

J. Yi et al., “Nasopharyngeal carcinoma treated by radical radiotherapy alone: Ten-year experience of a single institution.,” Int J Radiat Oncol Biol Phys, vol. 65, no. 1, pp. 161–168, May 2006. https://doi.org/10.1016/j.ijrobp.2005.12.003.

Article  PubMed  Google Scholar 

M. Kang et al., “Validation of the 8th edition of the UICC/AJCC staging system for nasopharyngeal carcinoma treated with intensity-modulated radiotherapy.,” Oncotarget, vol. 8, no. 41, pp. 70586–70594, Sep. 2017. https://doi.org/10.18632/oncotarget.19829.

S. Li, Y. Deng, Z. Zhu, H. Hua, and Z. Tao, A Comprehensive Review on Radiomics and Deep Learning for Nasopharyngeal Carcinoma Imaging. 2021.

P. Bossi et al., “Nasopharyngeal carcinoma: ESMO-EURACAN Clinical Practice Guidelines for diagnosis, treatment and follow-up,” Annals of Oncology, vol. 32, no. 4, pp. 452–465, 2021. https://doi.org/10.1016/j.annonc.2020.12.007.

Article  CAS  PubMed  Google Scholar 

Y.-P. Chen, A. T. C. Chan, Q.-T. Le, P. Blanchard, Y. Sun, and J. Ma, “Nasopharyngeal carcinoma,” The Lancet, vol. 394, no. 10192, pp. 64–80, Jul. 2019. https://doi.org/10.1016/S0140-6736(19)30956-0.

Article  Google Scholar 

S. Wang, S. Chen, Q. Zhong, and Y. Liu, “Immunotherapy for the treatment of advanced nasopharyngeal carcinoma: a promising new era,” J Cancer Res Clin Oncol, 2022. https://doi.org/10.1007/s00432-022-04214-8.

Article  PubMed  PubMed Central  Google Scholar 

V. Kaartemo and A. Helkkula, “A Systematic Review of Artificial Intelligence and Robots in Value Co-creation: Current Status and Future Research Avenues,” Journal of Creating Value, vol. 4, Oct. 2018. https://doi.org/10.1177/2394964318805625.

W. M. Yu and S. S. M. Hussain, “Incidence of nasopharyngeal carcinoma in Chinese immigrants, compared with Chinese in China and South East Asia: review.,” J Laryngol Otol, vol. 123, no. 10, pp. 1067–1074, Oct. 2009. https://doi.org/10.1017/S0022215109005623.

Article  CAS  PubMed  Google Scholar 

S. Li et al., “Deep learning for locally advanced nasopharyngeal carcinoma prognostication based on pre- and post-treatment MRI,” Comput Methods Programs Biomed, vol. 219, p. 106785, 2022. https://doi.org/10.1016/j.cmpb.2022.106785.

Article  PubMed  Google Scholar 

S. Jiang, L. Han, L. Liang, and L. Long, “Development and validation of an MRI-based radiomic model for predicting overall survival in nasopharyngeal carcinoma patients with local residual tumors after intensity-modulated radiotherapy,” BMC Med Imaging, vol. 22, no. 1, Dec. 2022. https://doi.org/10.1186/s12880-022-00902-6.

Y. Xi et al., “Early prediction of long-term survival of patients with nasopharyngeal carcinoma by multi-parameter MRI radiomics,” Eur J Radiol Open, vol. 12, Jun. 2024. https://doi.org/10.1016/j.ejro.2023.100543.

D. Bao et al., “Prognostic and predictive value of radiomics features at MRI in nasopharyngeal carcinoma,” Discover Oncology, vol. 12, no. 1, Dec. 2021. https://doi.org/10.1007/s12672-021-00460-3.

M. X. Sun, M. J. Zhao, L. H. Zhao, H. R. Jiang, Y. X. Duan, and G. Li, “A nomogram model based on pre-treatment and post-treatment MR imaging radiomics signatures: application to predict progression-free survival for nasopharyngeal carcinoma,” Radiation Oncology, vol. 18, no. 1, Dec. 2023. https://doi.org/10.1186/s13014-023-02257-w.

X. Yang, J. Wu, and X. Chen, “Application of Artificial Intelligence to the Diagnosis and Therapy of Nasopharyngeal Carcinoma,” Journal of Clinical Medicine, vol. 12, no. 9. Multidisciplinary Digital Publishing Institute (MDPI), May 01, 2023. https://doi.org/10.3390/jcm12093077.

Z. Lin, X. Zhang, Y. Luo, Y. Chen, and Y. Yuan, “The value of hemoglobin-to-red blood cell distribution width ratio (Hb/RDW), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) for the diagnosis of nasopharyngeal cancer,” Medicine (United States), vol. 100, no. 28, p. E26537, Jul. 2021. https://doi.org/10.1097/MD.0000000000026537.

Article  CAS  Google Scholar 

E. Kifle, M. Hussein, J. Alemu, and W. Tigeneh, “Prevalence of Anemia and Associated Factors among Newly Diagnosed Patients with Solid Malignancy at Tikur Anbessa Specialized Hospital, Radiotherapy Center, Addis Ababa, Ethiopia,” Adv Hematol, vol. 2019, p. 8279789, 2019. https://doi.org/10.1155/2019/8279789.

Article  CAS  PubMed  PubMed Central  Google Scholar 

J. Zhu, R. Fang, Z. Pan, and X. Qian, “Circulating lymphocyte subsets are prognostic factors in patients with nasopharyngeal carcinoma,” BMC Cancer, vol. 22, no. 1, Dec. 2022. https://doi.org/10.1186/s12885-022-09438-y.

Y. Dai et al., “The effect of hispidulin, a flavonoid from salvia plebeia, on human nasopharyngeal carcinoma cne-2z cell proliferation, migration, invasion, and apoptosis,” Molecules, vol. 26, no. 6, Mar. 2021. https://doi.org/10.3390/molecules26061604.

M. Zhang, S. Wei, L. Su, W. Lv, and J. Hong, “Prognostic significance of pretreated serum lactate dehydrogenase level in nasopharyngeal carcinoma among Chinese population: A meta-analysis.,” Medicine, vol. 95, no. 35, p. e4494, Aug. 2016. https://doi.org/10.1097/MD.0000000000004494.

L. Huang et al., “Lactate dehydrogenase kinetics predict chemotherapy response in recurrent metastatic nasopharyngeal carcinoma.,” Ther Adv Med Oncol, vol. 12, p. 1758835920970050, 2020. https://doi.org/10.1177/1758835920970050.

Article  CAS  PubMed  PubMed Central  Google Scholar 

J. Li et al., “Prognostic nomogram for patients with Nasopharyngeal Carcinoma incorporating hematological biomarkers and clinical characteristics.,” Int J Biol Sci, vol. 14, no. 5, pp. 549–556, 2018. https://doi.org/10.7150/ijbs.24374.

Article  CAS  PubMed  PubMed Central  Google Scholar 

N. Lee et al., “Intensity-modulated radiation therapy with or without chemotherapy for nasopharyngeal carcinoma: Radiation therapy oncology group phase II trial 0225,” Journal of Clinical Oncology, vol. 27, no. 22, pp. 3684–3690, Aug. 2009. https://doi.org/10.1200/JCO.2008.19.9109.

Article  PubMed  PubMed Central  Google Scholar 

M. B. Amin et al., “ The Eighth Edition AJCC Cancer Staging Manual: Continuing to build a bridge from a population‐based to a more ‘personalized’ approach to cancer staging ,” CA Cancer J Clin, vol. 67, no. 2, pp. 93–99, Mar. 2017. https://doi.org/10.3322/caac.21388.

C. C. Lee, J. C. Lee, W. Y. Huang, C. J. Juan, Y. M. Jen, and L. F. Lin, “Image-based diagnosis of residual or recurrent nasopharyngeal carcinoma may be a phantom tumor phenomenon,” Medicine (United States), vol. 100, no. 8, p. E24555, Feb. 2021. https://doi.org/10.1097/MD.0000000000024555.

Article  CAS  Google Scholar 

A. A. K. Abdel Razek and A. King, “MRI and CT of nasopharyngeal carcinoma,” American Journal of Roentgenology, vol. 198, no. 1. pp. 11–18, Jan. 2012. https://doi.org/10.2214/AJR.11.6954.

M. W. van den Brekel et al., “Cervical lymph node metastasis: assessment of radiologic criteria.,” Radiology, vol. 177, no. 2, pp. 379–384, Nov. 1990. https://doi.org/10.1148/radiology.177.2.2217772.

Article  PubMed  Google Scholar 

T. Liu et al., “Radiomic signatures reveal multiscale intratumor heterogeneity associated with tissue tolerance and survival in re-irradiated nasopharyngeal carcinoma: a multicenter study,” BMC Med, vol. 21, no. 1, Dec. 2023. https://doi.org/10.1186/s12916-023-03164-3.

S. F. Su et al., “Treatment outcomes for different subgroups of nasopharyngeal carcinoma patients treated with intensity-modulated radiation therapy,” Chin J Cancer, vol. 30, no. 8, pp. 565–573, 2011. https://doi.org/10.5732/cjc.010.10547.

Article  PubMed  PubMed Central  Google Scholar 

D. P. Shedd, C. F. von Essen, and H. Eisenberg, “Cancer of the nasopharynx in connecticut. 1935 through 1959,” Cancer, vol. 20, no. 4, pp. 508–511, Jan. 1967. https://doi.org/10.1002/1097-0142(1967)20:4<508::AID-CNCR2820200407>3.0.CO;2-I.

Article  CAS  PubMed  Google Scholar 

M.-C. Chen et al., “The incidence and risk of second primary cancers in patients with nasopharyngeal carcinoma: a population-based study in Taiwan over a 25-year period (1979&#x2013;2003),” Annals of Oncology, vol. 19, no. 6, pp. 1180–1186, Jun. 2008. https://doi.org/10.1093/annonc/mdn003.

Article  PubMed  Google Scholar 

J. Friborg, J. Wohlfahrt, A. Koch, H. Storm, O. R. Olsen, and M. Melbye, “Cancer Susceptibility in Nasopharyngeal Carcinoma Families—A Population-Based Cohort Study,” Cancer Res, vol. 65, no. 18, pp. 8567–8572, Sep. 2005. https://doi.org/10.1158/0008-5472.CAN-04-4208.

Article  CAS  PubMed  Google Scholar 

T. S. De Silva, D. MacDonald, G. Paterson, K. C. Sikdar, and B. Cochrane, “Systematized nomenclature of medicine clinical terms (SNOMED CT) to represent computed tomography procedures,” Comput Methods Programs Biomed, vol. 101, no. 3, pp. 324–329, 2011. https://doi.org/10.1016/j.cmpb.2011.01.002.

Article  PubMed  Google Scholar 

S. Miao et al., “Development and validation of a risk prediction model for overall survival in patients with nasopharyngeal carcinoma: a prospective cohort study in China,” Cancer Cell Int, vol. 22, no. 1, Dec. 2022. https://doi.org/10.1186/s12935-022-02776-8.

B. Zhang, T. Zhang, L. Jin, Y. Zhang, and Q. Wei, “Treatment Strategy of Metastatic Nasopharyngeal Carcinoma With Bone Marrow Involvement—A Case Report,” Front Oncol, vol. 12, Jun. 2022. https://doi.org/10.3389/fonc.2022.877451.

J. Liu, C. Wei, H. Tang, Y. Liu, W. Liu, and C. Lin, “The prognostic value of the ratio of neutrophils to lymphocytes before and after intensity modulated radiotherapy for patients with nasopharyngeal carcinoma,” Medicine (United States), vol. 99, no. 2, Jan. 2020. https://doi.org/10.1097/MD.0000000000018545.

X. Zhong et al., “Cervical spine osteoradionecrosis or bone metastasis after radiotherapy for nasopharyngeal carcinoma? The MRI-based radiomics for characterization,” BMC Med Imaging, vol. 20, no. 1, p. 104, 2020. https://doi.org/10.1186/s12880-020-00502-2.

Article  PubMed  PubMed Central  Google Scholar 

M. Bologna et al., “Baseline mri-radiomics can predict overall survival in non-endemic ebv-related nasopharyngeal carcinoma patients,” Cancers (Basel), vol. 12, no. 10, pp. 1–20, Oct. 2020. https://doi.org/10.3390/cancers12102958.

Article  CAS  Google Scholar 

H. Shen et al., “Predicting Progression-Free Survival Using MRI-Based Radiomics for Patients With Nonmetastatic Nasopharyngeal Carcinoma,” Front Oncol, vol. 10, no. May, pp. 1–7, 2020. https://doi.org/10.3389/fonc.2020.00618.

Article  CAS  Google Scholar 

S. D. McGarry et al., “Magnetic Resonance Imaging-Based Radiomic Profiles Predict Patient Prognosis in Newly Diagnosed Glioblastoma Before Therapy.,” Tomography, vol. 2, no. 3, pp. 223–228, Sep. 2016. https://doi.org/10.18383/j.tom.2016.00250.

Article  PubMed  PubMed Central  Google Scholar 

R. Tibshirani, “Regression Shrinkage and Selection Via the Lasso,” Journal of the Royal Statistical Society: Series B (Methodological), vol. 58, no. 1, pp. 267–288, Jan. 1996. https://doi.org/10.1111/j.2517-6161.1996.tb02080.x.

Article  Google Scholar 

J. Weng et al., “Clinical outcomes of residual or recurrent nasopharyngeal carcinoma treated with endoscopic nasopharyngectomy plus chemoradiotherapy or with chemoradiotherapy alone: A retrospective study,” PeerJ, vol. 2017, no. 10, 2017. https://doi.org/10.7717/peerj.3912.

Article  CAS  Google Scholar 

H. L. Hua et al., “Deep learning for the prediction of residual tumor after radiotherapy and treatment decision-making in patients with nasopharyngeal carcinoma based on magnetic resonance imaging,” Quant Imaging Med Surg, vol. 13, no. 6, Jun. 2023. https://doi.org/10.21037/qims-22-1226.

J. L. Mi, M. Xu, C. Liu, and R. S. Wang, “Prognostic nomogram to predict the distant metastasis after intensity-modulated radiation therapy for patients with nasopharyngeal carcinoma,” Medicine (United States), vol. 100, no. 47, Nov. 2021. https://doi.org/10.1097/MD.0000000000027947.

L. Zhang et al., “Development and validation of a magnetic resonance imaging-based model for the prediction of distant metastasis before initial treatment of nasopharyngeal carcinoma: A retrospective cohort study,” EBioMedicine, vol. 40, pp. 327–335, Feb. 2019. https://doi.org/10.1016/j.ebiom.2019.01.013.

Article  PubMed  PubM