Investigation of Combining Serum Tumor Biomarkers and Clinical Features for Elderly Lung Cancer Diagnosis and Classification

Yingxuan Tian, Min Yu, Li Sun, Xiaoping Ren, Weifeng Liang, Wenli Shang, Shufen Huo, Linghua Liu, Yajuan Ren, Hongxia Wen, Zhuo Yang, Shenghong Wei, Cairong Wang

Department of Geriatrics Oncology Medicine, Shaanxi Provincial People’s Hospital, Xi’an, China.
Department of Geriatrics Respiratory, Shaanxi Provincial People’s Hospital, Xi’an, China.
School of Public Health, Medical College of Xi’an Jiao Tong University, Xi’an, China.

DOI: 10.4236/jct.2014.52016                

Abstract

To evaluate the diagnosis model of serum tumor biomarker and several clinical features diagnose and classification for lung cancer, the solid protein chip technology (C-12) was used to detect the biomarkers of SF, CEA, CA242, NSE, CA125, CA19-9 and CA15-3 in serum and several clinical features of tumors and benign disease in elderly lung cancer patients were collected. Set up a discriminating analysis as a function diagnostic model in clinical elderly lung cancer diagnosis and sub-type discrimination. In combination of 2 obvious clinical indicators and 2 serum markers, it is possible to provide a diagnosis tool for lung cancer. With the help of mathematic model, it is promising to reduce the misjudgment risk based on the previous experience and therefore establish a reliable diagnosing function. This model is simple, cost-effective and easy to adapt in practice, and can also be used in screening of large population.

Keywords

Lung Cancer; Tumor Biomarkers; Diagnostic Models

Conflicts of Interest

The authors declare no conflicts of interest.

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