| Literature DB >> 27553002 |
Hong-Fei Zhang1,2, Jie-Jie Qin1,2, Peng-Fei Ren1,2, Jian-Xiang Shi1,2, Jun-Fen Xia1,2, Hua Ye1,2, Peng Wang1,2, Chun-Hua Song1,2, Kai-Juan Wang1,2, Jian-Ying Zhang3,4,5.
Abstract
Esophageal squamous cell carcinoma (ESCC) is one of the most common cancers in China with very low 5-year survival rate mostly due to the paucity of effective early diagnostic methods. Serum autoantibodies against 9 tumor-associated antigens (TAAs) from ESCC patients and healthy controls were detected by enzyme-linked immunosorbent assay to evaluate their performances in the immunodiagnosis of ESCC. Logistic regression models were generated to predict the probability of individuals being diagnosed with ESCC in training cohort (648 participants) and further validated in another independent cohort (372 participants). Finally, a panel of four TAAs showed high diagnostic accuracy with areas under the receiver operating characteristic curve of 0.838 in training cohort and 0.872 in validation cohort, respectively. The percentages of individuals correctly classified were 77.01 % in training cohort and 78.49 % in validation cohort, respectively. This model could discriminate early-stage (AJCC stage 0, I and II) ESCC patients from normal controls, with true-positive rate (TPR) of 67.57 % in training cohort and TPR of 63.33 % in validation cohort, and the overall TPR for early-stage ESCC was 66.85 % when the two cohorts were combined. The diagnostic performance of this model showed no significant difference between early-stage and late-stage (AJCC stage III and IV) ESCC patients. In summary, the optimized model with 4 TAAs has a high diagnostic performance for ESCC detection, especially for early-stage ESCC.Entities:
Keywords: Autoantibody; Early diagnosis; Esophageal squamous cell carcinoma; Logistic regression model; Tumor-associated antigen
Mesh:
Substances:
Year: 2016 PMID: 27553002 DOI: 10.1007/s00262-016-1886-6
Source DB: PubMed Journal: Cancer Immunol Immunother ISSN: 0340-7004 Impact factor: 6.968