title: Integrating epidermal growth factor receptor assay with clinical parameters improves risk classification for relapse and survival in head-and-neck squamous cell carcinoma.
abstract: OBJECTIVE
  Epidermal growth factor receptor (EGFR) overexpression has been consistently found to be an independent predictor of local-regional relapse (LRR) after radiotherapy. We assessed the extent by which it can refine risk classification for overall survival (OS) and LRR in patients with head-and-neck squamous cell carcinoma (HNSCC).
  
  
  METHODS
  EGFR expression in locally advanced HNSCC was measured by immunohistochemistry in a series of patients randomized to receive accelerated or conventional radiation regimens in a Phase III trial. Subsequently, data of the two series were pooled (N = 533) for conducting a recursive partitioning analysis that incorporated clinical parameters (e.g., performance status, primary site, T and N categories) and four molecular markers (EGFR, p53, Ki-67, and microvessel density).
  
  
  RESULTS
  This study confirmed that patients with higher than median levels of tumor EGFR expression had a lower OS (relative risk [RR]: 1.90, p = 0.0010) and a higher LRR (RR: 1.91, p = 0.0163). Of the four markers analyzed, only EGFR was found to contribute to refining classification of patients into three risk classes with distinct OS and LRR outcomes. The addition of EGFR to three clinical parameters could identify patients having up to a fivefold difference in the risk of LRR.
  
  
  CONCLUSIONS
  Adding pretreatment EGFR expression data to known robust clinical prognostic variables improved the estimation of the probability for OS and LRR after radiotherapy. Its use for stratifying or selecting patients with defined tumor feature and pattern of relapse for enrollment into clinical trials testing specific therapeutic strategy warrants further investigation.
authors: Division of Hematology/Oncology, Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA. cchung11@jhmi.edu
authors: Christine H
authors: CH
authors: Chung
authors: Qiang
authors: Q
authors: Zhang
authors: Elizabeth M
authors: EM
authors: Hammond
authors: Andy M
authors: AM
authors: Trotti
authors: Huijun
authors: H
authors: Wang
authors: Sharon
authors: S
authors: Spencer
authors: Hua-Zhong
authors: HZ
authors: Zhang
authors: Jay
authors: J
authors: Cooper
authors: Richard
authors: R
authors: Jordan
authors: Marvin H
authors: MH
authors: Rotman
authors: K Kian
authors: KK
authors: Ang
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D014408:Biomarkers, Tumor / Q000378:metabolism*; D002294:Carcinoma, Squamous Cell / Q000098:blood supply / Q000378:metabolism* / Q000401:mortality / Q000473:pathology; D018572:Disease-Free Survival; D019583:Dose Fractionation, Radiation; D066246:ErbB Receptors / Q000378:metabolism*; D005260:Female; D006258:Head and Neck Neoplasms / Q000098:blood supply / Q000378:metabolism* / Q000401:mortality / Q000473:pathology; D006801:Humans; D017567:Karnofsky Performance Status; D019394:Ki-67 Antigen / Q000378:metabolism; D008297:Male; D055806:Microvessels / Q000473:pathology; D008875:Middle Aged; D009364:Neoplasm Recurrence, Local / Q000401:mortality; D016016:Proportional Hazards Models; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000145:classification; D016159:Tumor Suppressor Protein p53 / Q000378:metabolism
chemical_list: D014408:Biomarkers, Tumor; D019394:Ki-67 Antigen; D016159:Tumor Suppressor Protein p53; D066246:ErbB Receptors