title: Diagnostic Value of Combining Tumor and Inflammatory Markers in Lung Cancer.
abstract: BACKGROUND
  Despite major advances in lung cancer treatment, early detection remains the most promising way of improving outcomes. To detect lung cancer in earlier stages, many serum biomarkers have been tested. Unfortunately, no single biomarker can reliably detect lung cancer. We combined a set of 2 tumor markers and 4 inflammatory or metabolic markers and tried to validate the diagnostic performance in lung cancer.
  
  
  METHODS
  We collected serum samples from 355 lung cancer patients and 590 control subjects and divided them into training and validation datasets. After measuring serum levels of 6 biomarkers (human epididymis secretory protein 4 [HE4], carcinoembryonic antigen [CEA], regulated on activation, normal T cell expressed and secreted [RANTES], apolipoprotein A2 [ApoA2], transthyretin [TTR], and secretory vascular cell adhesion molecule-1 [sVCAM-1]), we tested various sets of biomarkers for their diagnostic performance in lung cancer.
  
  
  RESULTS
  In a training dataset, the area under the curve (AUC) values were 0.821 for HE4, 0.753 for CEA, 0.858 for RANTES, 0.867 for ApoA2, 0.830 for TTR, and 0.552 for sVCAM-1. A model using all 6 biomarkers and age yielded an AUC value of 0.986 and sensitivity of 93.2% (cutoff at specificity 94%). Applying this model to the validation dataset showed similar results. The AUC value of the model was 0.988, with sensitivity of 93.33% and specificity of 92.00% at the same cutoff point used in the validation dataset. Analyses by stages and histologic subtypes all yielded similar results.
  
  
  CONCLUSIONS
  Combining multiple tumor and systemic inflammatory markers proved to be a valid strategy in the diagnosis of lung cancer.
authors.affiliation: Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea.
authors.forename: Ho Il
authors.initials: HI
authors.lastname: Yoon
authors.affiliation: BioInfra, Inc., Seoul, Korea.
authors.forename: Oh-Ran
authors.initials: OR
authors.lastname: Kwon
authors.affiliation: BioInfra, Inc., Seoul, Korea.
authors.forename: Kyung Nam
authors.initials: KN
authors.lastname: Kang
authors.affiliation: BioInfra, Inc., Seoul, Korea.
authors.forename: Yong Sung
authors.initials: YS
authors.lastname: Shin
authors.affiliation: BioInfra, Inc., Seoul, Korea.
authors.forename: Ho Sang
authors.initials: HS
authors.lastname: Shin
authors.affiliation: BioInfra, Inc., Seoul, Korea.
authors.forename: Eun Hee
authors.initials: EH
authors.lastname: Yeon
authors.affiliation: Department of Pathology, Korea Regional Bank, Keimyung University School of Medicine, Daegu, Korea.
authors.forename: Keon Young
authors.initials: KY
authors.lastname: Kwon
authors.affiliation: Department of Pathology, Korea Regional Bank, Keimyung University School of Medicine, Daegu, Korea.
authors.forename: Ilseon
authors.initials: I
authors.lastname: Hwang
authors.affiliation: Department of Pathology, Seoul National University College of Medicine, Seoul, Korea.
authors.forename: Yoon Kyung
authors.initials: YK
authors.lastname: Jeon
authors.affiliation: Department of Statistics, College of Natural Science, Seoul National University, Seoul, Korea.
authors.forename: Yongdai
authors.initials: Y
authors.lastname: Kim
authors.affiliation: BioInfra, Inc., Seoul, Korea; Department of Pathology, Seoul National University College of Medicine, Seoul, Korea.
authors.forename: Chul Woo
authors.initials: CW
authors.lastname: Kim
keywords: Biomarkers; Lung neoplasms