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ORIGINAL RESEARCH

RuleFit-Based Nomogram Using Inflammatory Indicators for Predicting Survival in Nasopharyngeal Carcinoma, a Bi-Center Study

, , , , , , , , & ORCID Icon show all
Pages 4803-4815 | Published online: 24 Aug 2022

References

  • Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394–424. doi:10.3322/caac.21492
  • Chen YP, Chan ATC, Le QT, Blanchard P, Sun Y, Ma J. Nasopharyngeal carcinoma. Lancet. 2019;394(10192):64–80. doi:10.1016/s0140-6736(19)30956-0
  • Tang LL, Chen YP, Mao YP, et al. Validation of the 8th Edition of the UICC/AJCC staging system for nasopharyngeal carcinoma from endemic areas in the intensity-modulated radiotherapy era. J Natl Compr Canc Netw. 2017;15(7):913–919. doi:10.6004/jnccn.2017.0121
  • Fang W, Zhang J, Hong S, et al. EBV-driven LMP1 and IFN-γ up-regulate PD-L1 in nasopharyngeal carcinoma: implications for oncotargeted therapy. Oncotarget. 2014;5(23):12189–12202. doi:10.18632/oncotarget.2608
  • Mo X, Wu X, Dong D, et al. Prognostic value of the radiomics-based model in progression-free survival of hypopharyngeal cancer treated with chemoradiation. Eur Radiol. 2020;30(2):833–843. doi:10.1007/s00330-019-06452-w
  • Tang LQ, Li CF, Li J, et al. Establishment and validation of prognostic nomograms for endemic nasopharyngeal carcinoma. J Natl Cancer Inst. 2016;108(1):djv291. doi:10.1093/jnci/djv291
  • Tu X, Ren J, Zhao Y. Prognostic value of prognostic nutritional index in nasopharyngeal carcinoma: a meta-analysis containing 4511 patients. Oral Oncol. 2020;110:104991. doi:10.1016/j.oraloncology.2020.104991
  • Li J, Chen S, Peng S, et al. Prognostic nomogram for patients with Nasopharyngeal Carcinoma incorporating hematological biomarkers and clinical characteristics. Int J Biol Sci. 2018;14(5):549–556. doi:10.7150/ijbs.24374
  • Forget P, Echeverria G, Giglioli S, et al. Biomarkers in immunonutrition programme, is there still a need for new ones? A brief review. Ecancermedicalscience. 2015;9:546. doi:10.3332/ecancer.2015.546
  • Ohno Y. Role of systemic inflammatory response markers in urological malignancy. Int J Urol. 2019;26(1):31–47. doi:10.1111/iju.13801
  • Balkwill F, Mantovani A. Inflammation and cancer: back to Virchow? Lancet. 2001;357(9255):539–545. doi:10.1016/s0140-6736(00)04046-0
  • Wilcox RA, Ristow K, Habermann TM, et al. The absolute monocyte and lymphocyte prognostic score predicts survival and identifies high-risk patients in diffuse large-B-cell lymphoma. Leukemia. 2011;25(9):1502–1509. doi:10.1038/leu.2011.112
  • Zhang Y, Zhou GQ, Liu X, et al. Exploration and validation of C-reactive protein/albumin ratio as a novel inflammation-based prognostic marker in nasopharyngeal carcinoma. J Cancer. 2016;7(11):1406–1412. doi:10.7150/jca.15401
  • Li X, Han Z, Cheng Z, Yu J, Yu X, Liang P. Prognostic value of preoperative absolute lymphocyte count in recurrent hepatocellular carcinoma following thermal ablation: a retrospective analysis. Onco Targets Ther. 2014;7:1829–1835. doi:10.2147/ott.S69227
  • Su L, Zhang M, Zhang W, Cai C, Hong J. Pretreatment hematologic markers as prognostic factors in patients with nasopharyngeal carcinoma: a systematic review and meta-analysis. Medicine. 2017;96(11):e6364. doi:10.1097/md.0000000000006364
  • Friedman JH, Popescu BE. Predictive learning via rule ensembles. Ann Appl Stat. 2008;2(3):916–954. doi:10.1214/07-aoas148
  • Fokkema M, Smits N, Kelderman H, Penninx B. Connecting clinical and actuarial prediction with rule-based methods. Psychol Assess. 2015;27(2):636–644. doi:10.1037/pas0000072
  • Lin Y, Huang S, Simon GE, Liu S. Data-based decision rules to personalize depression follow-up. Sci Rep. 2018;8(1):5064. doi:10.1038/s41598-018-23326-1
  • Sun YV, Bielak LF, Peyser PA, et al. Application of machine learning algorithms to predict coronary artery calcification with a sibship-based design. Genet Epidemiol. 2008;32(4):350–360. doi:10.1002/gepi.20309
  • Lin Y, Qian X, Krischer J, Vehik K, Lee HS, Huang S. A rule-based prognostic model for type 1 diabetes by identifying and synthesizing baseline profile patterns. PLoS One. 2014;9(6):e91095. doi:10.1371/journal.pone.0091095
  • Yang L, Hong S, Wang Y, et al. Development and external validation of nomograms for predicting survival in nasopharyngeal carcinoma patients after definitive radiotherapy. Sci Rep. 2015;5:15638. doi:10.1038/srep15638
  • Peng RR, Liang ZG, Chen KH, Li L, Qu S, Zhu XD. Nomogram based on lactate dehydrogenase-to-albumin ratio (LAR) and platelet-to-lymphocyte ratio (PLR) for predicting survival in nasopharyngeal carcinoma. J Inflamm Res. 2021;14:4019–4033. doi:10.2147/jir.S322475
  • Liu LT, Chen QY, Tang LQ, et al. The prognostic value of treatment-related lymphopenia in nasopharyngeal carcinoma patients. Cancer Res Treat. 2018;50(1):19–29. doi:10.4143/crt.2016.595
  • Jiang R, Cai XY, Yang ZH, et al. Elevated peripheral blood lymphocyte-to-monocyte ratio predicts a favorable prognosis in the patients with metastatic nasopharyngeal carcinoma. Chin J Cancer. 2015;34(6):237–246. doi:10.1186/s40880-015-0025-7
  • He J, Shen G, Ren Z, et al. Pretreatment levels of peripheral neutrophils and lymphocytes as independent prognostic factors in patients with nasopharyngeal carcinoma. Head Neck. 2012;34(12):1769–1776. doi:10.1002/hed.22008
  • Gooden MJ, de Bock GH, Leffers N, Daemen T, Nijman HW. The prognostic influence of tumour-infiltrating lymphocytes in cancer: a systematic review with meta-analysis. Br J Cancer. 2011;105(1):93–103. doi:10.1038/bjc.2011.189
  • So YK, Byeon SJ, Ku BM, et al. An increase of CD8(+) T cell infiltration following recurrence is a good prognosticator in HNSCC. Sci Rep. 2020;10(1):20059. doi:10.1038/s41598-020-77036-8
  • Lin W, Cao D, Dong A, et al. Systematic construction and external validation of an immune-related prognostic model for nasopharyngeal carcinoma. Head Neck. 2022;44:1086–1098. doi:10.1002/hed.26996
  • Gay LJ, Felding-Habermann B. Contribution of platelets to tumour metastasis. Nat Rev Cancer. 2011;11(2):123–134. doi:10.1038/nrc3004
  • Haemmerle M, Stone RL, Menter DG, Afshar-Kharghan V, Sood AK. The platelet lifeline to cancer: challenges and opportunities. Cancer Cell. 2018;33(6):965–983. doi:10.1016/j.ccell.2018.03.002
  • Yamagata K, Fukuzawa S, Ishibashi-Kanno N, Uchida F, Bukawa H. Association between the C-reactive protein/albumin ratio and prognosis in patients with oral squamous cell carcinoma. Sci Rep. 2021;11(1):5446. doi:10.1038/s41598-021-83362-2