title: [Application of serum tumor markers and support vector machine in the diagnosis of oral squamous cell carcinoma].
abstract: OBJECTIVE
  To investigate the clinical application value of serum tumor markers detection combined with support vector machine (SVM) model in the diagnosis of oral squamous cell carcinoma.
  
  
  METHODS
  Serum levels of neuron-specific enolase (NSE), cancer antigen 242 (CA242), cancer antigen 19-9 (CA199), carcinoembryonic antigen (CEA), tissue polypeptide antigen (TPA), cancer antigen 72-4 (CA724), cancer antigen 21-1 (CA211) and alpha fetoprotein (AFP) were detected with enzyme-linked immunosorbent assay (ELISA) and time-resolved fluoroimmunoassay (TRFIA) in 163 oral squamous cell carcinoma patients and 160 healthy persons. All the data was analyzed with SVM; the SVM models for diagnosis of oral squamous cell carcinoma were created, trained and validated by cross validation.
  
  
  RESULTS
  Among the 163 oral squamous cell carcinoma patients, there were 128 males and 35 females with the male-to-female ratio of 3.66:1; the age ranged from 30 to 85 years old with a mean age of 59.3 years old; according to the primary site of tumor, 72 cases in tongue, 34 in gingiva, 22 in buccal mucosa, 15 in palatal mucosa, 13 in floor of mouth, 4 in lip and 3 in retromolar region; according to the TNM-UICC classification, there were 33 patients at stage T1, 72 at T2, 44 at T3, 14 at T4, 119 at N0, 42 at N1, 2 at N2, 159 at M0, 4 at M1, 27 at clinical stage I, 51 at stage II, 52 at III, and 33 at IV; according to the pathological differentiation grade, 109 tumors were well differentiated, 42 were moderately differentiated and 12 were poorly differentiated. Five serum tumor markers of CA211, CA199, TPA, CA724 and NSE were selected optimally to create the optimal SVM model for diagnosis of oral squamous cell carcinoma. The accuracy, specificity, sensitivity and positive predictive value of the optimal SVM model were 88.54%, 93.13%, 84.05% and 92.57%, respectively.
  
  
  CONCLUSIONS
  From the results, SVM model combined with 5 optimal serum tumor markers is suggested to be used in the diagnosis of oral squamous cell carcinoma. Supported by Shanghai Leading Academic Discipline Project (Grant No.Y0203).
authors.affiliation: Department of Oral and Maxillofacial Surgery, Ninth People's Hospital, College of Stomatology, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China.
authors.forename: Lai-Ping
authors.initials: LP
authors.lastname: Zhong
authors.forename: Xiao-Jian
authors.initials: XJ
authors.lastname: Zhou
authors.forename: Kui-Jie
authors.initials: KJ
authors.lastname: Wei
authors.forename: Xiao
authors.initials: X
authors.lastname: Yang
authors.forename: Chun-Yue
authors.initials: CY
authors.lastname: Ma
authors.forename: Chen-Ping
authors.initials: CP
authors.lastname: Zhang
authors.forename: Zhi-Yuan
authors.initials: ZY
authors.lastname: Zhang
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015295:Antigens, Tumor-Associated, Carbohydrate; D014408:Biomarkers, Tumor / Q000032:analysis*; D002272:Carcinoembryonic Antigen; D002294:Carcinoma, Squamous Cell / Q000175:diagnosis*; D005260:Female; D006801:Humans; D007633:Keratins; D008175:Lung Neoplasms; D008297:Male; D008875:Middle Aged; D009062:Mouth Neoplasms / Q000175:diagnosis*; D010751:Phosphopyruvate Hydratase; D012680:Sensitivity and Specificity; D060388:Support Vector Machine
chemical_list: D015295:Antigens, Tumor-Associated, Carbohydrate; D014408:Biomarkers, Tumor; C074601:CA 242 antigen; C083825:CA-72-4 antigen; D002272:Carcinoembryonic Antigen; D007633:Keratins; D010751:Phosphopyruvate Hydratase