title: Establishment of an integrated model incorporating standardised uptake value and N-classification for predicting metastasis in nasopharyngeal carcinoma.
abstract: BACKGROUND
  Previous studies reported a correlation between the maximum standardised uptake value (SUVmax) obtained by 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) and distant metastasis in nasopharyngeal carcinoma (NPC). However, an integrated model incorporating SUVmax and anatomic staging for stratifying metastasis risk has not been reported.
  
  
  RESULTS
  The median SUVmax for primary tumour (SUV-T) and cervical lymph nodes (SUV-N) was 13.6 (range, 2.2 to 39.3) and 8.4 (range, 2.6 to 40.9), respectively. SUV-T (HR, 3.396; 95% CI, 1.451-7.947; P = 0.005), SUV-N (HR, 2.688; 95%CI, 1.250-5.781; P = 0.011) and N-classification (HR, 2.570; 95%CI, 1.422-4.579; P = 0.001) were identified as independent predictors for DMFS from multivariate analysis. Three valid risk groups were derived by RPA: low risk (N0-1 + SUV-T <10.45), medium risk (N0-1 + SUV-T >10.45) and high risk (N2-3). The three risk groups contained 100 (22.3%), 226 (50.3%), and 123 (27.4%) patients, respectively, with corresponding 3-year DMFS rates of 99.0%, 91.5%, and 77.5% (P <0.001). Moreover, multivariate analysis confirmed the RPA-based prognostic grouping as the only significant prognostic indicator for DMFS (HR, 3.090; 95%CI, 1.975-4.835; P <0.001).
  
  
  METHODS
  Data from 449 patients with with histologically-confirmed, stage I-IVB NPC treated with radiotherapy or chemoradiotherapy were retrospectively analysed. A prognostic model for distant metastasis-free survival (DMFS) was derived by recursive partitioning analysis (RPA) combining independent predictors identified by multivariate analysis.
  
  
  CONCLUSIONS
  SUV-T, SUV-N and N-classification were identified as independent predictors for DMFS. An integrated RPA-based prognostic model for DMFS incorporating SUV-N and N-classification was proposed.
authors.affiliation: Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Canton, Guangdong, China.
authors.forename: Yuan
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Canton, Guangdong, China.
authors.forename: Wen-Fei
authors.initials: WF
authors.lastname: Li
authors.affiliation: Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Canton, Guangdong, China.
authors.forename: Yan-Ping
authors.initials: YP
authors.lastname: Mao
authors.affiliation: Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Canton, Guangdong, China.
authors.forename: Guan-Qun
authors.initials: GQ
authors.lastname: Zhou
authors.affiliation: Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Canton, Guangdong, China.
authors.forename: Hao
authors.initials: H
authors.lastname: Peng
authors.affiliation: Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Canton, Guangdong, China.
authors.forename: Ying
authors.initials: Y
authors.lastname: Sun
authors.affiliation: Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Canton, Guangdong, China.
authors.forename: Qing
authors.initials: Q
authors.lastname: Liu
authors.affiliation: Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Canton, Guangdong, China.
authors.forename: Lei
authors.initials: L
authors.lastname: Chen
authors.affiliation: Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Canton, Guangdong, China.
authors.forename: Jun
authors.initials: J
authors.lastname: Ma
mesh_terms: D000328:Adult; D000368:Aged; D002277:Carcinoma / Q000000981:diagnostic imaging / Q000378:metabolism / Q000473:pathology* / Q000628:therapy; D002294:Carcinoma, Squamous Cell / Q000000981:diagnostic imaging / Q000378:metabolism / Q000556:secondary* / Q000628:therapy; D003131:Combined Modality Therapy; D005260:Female; D019788:Fluorodeoxyglucose F18 / Q000378:metabolism*; D005500:Follow-Up Studies; D006801:Humans; D008207:Lymphatic Metastasis; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D064847:Multimodal Imaging / Q000379:methods*; D000077274:Nasopharyngeal Carcinoma; D009303:Nasopharyngeal Neoplasms / Q000000981:diagnostic imaging / Q000378:metabolism / Q000473:pathology* / Q000628:therapy; D009361:Neoplasm Invasiveness; D009367:Neoplasm Staging; D049268:Positron-Emission Tomography / Q000379:methods*; D011379:Prognosis; D019275:Radiopharmaceuticals / Q000378:metabolism; D012189:Retrospective Studies; D015996:Survival Rate; D014057:Tomography, X-Ray Computed / Q000379:methods*; D055815:Young Adult
chemical_list: D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18
keywords: TNM staging; maximum standardized uptake value; metastasis; nasopharyngeal neoplasms; recursive partitioning analysis