title: Serum cytokine biomarker panels for discriminating pancreatic cancer from benign pancreatic disease.
abstract: BACKGROUND
  We investigated whether combinations of serum cytokines, used with logistic disease predictor models, could facilitate the detection of pancreatic ductal adenocarcinoma (PDAC).
  
  
  METHODS
  The serum levels of 27 cytokines were measured in 241 subjects, 127 with PDAC, 49 with chronic pancreatitis, 20 with benign biliary obstruction and 45 healthy controls. Samples were split randomly into independent training and test sets. Cytokine biomarker panels were selected by identifying the top performing cytokines in best fit logistic regression models during multiple rounds of resampling from the training dataset. Disease prediction by logistic models, built using the resulting cytokine panels, was evaluated with training and test sets and further examined using resampled performance evaluation.
  
  
  RESULTS
  For the discrimination of PDAC patients from patients with benign disease, a panel of IP-10, IL-6, PDGF plus CA19-9 offered improved diagnostic performance over CA19-9 alone in the training (AUC 0.838 vs. 0.678) and independent test set (AUC 0.884 vs. 0.798). For the discrimination of PDAC from CP, a panel of IL-8, CA19-9, IL-6 and IP-10 offered improved diagnostic performance over CA19-9 alone with the training (AUC 0.880 vs. 0.758) and test set (AUC 0.912 vs. 0.848). Finally, for the discrimination of PDAC in the presence of jaundice from benign controls with jaundice, a panel of IP-10, IL-8, IL-1b and PDGF demonstrated improvement over CA19-9 in the training (AUC 0.810 vs. 0.614) and test set (AUC 0.857 vs. 0.659).
  
  
  CONCLUSIONS
  These findings support the potential role for cytokine panels in the discrimination of PDAC from patients with benign pancreatic diseases and warrant additional study.
authors.forename: Victoria E
authors.initials: VE
authors.lastname: Shaw
authors.forename: Brian
authors.initials: B
authors.lastname: Lane
authors.forename: Claire
authors.initials: C
authors.lastname: Jenkinson
authors.forename: Trevor
authors.initials: T
authors.lastname: Cox
authors.forename: William
authors.initials: W
authors.lastname: Greenhalf
authors.forename: Christopher M
authors.initials: CM
authors.lastname: Halloran
authors.forename: Joseph
authors.initials: J
authors.lastname: Tang
authors.forename: Robert
authors.initials: R
authors.lastname: Sutton
authors.forename: John P
authors.initials: JP
authors.lastname: Neoptolemos
authors.affiliation: NIHR Liverpool Pancreas Biomedical Research Unit, Royal Liverpool and Broadgreen University Hospital NHS Trust, Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool L69 3GA, UK. ecostell@liverpool.ac.uk.
authors.forename: Eithne
authors.initials: E
authors.lastname: Costello
mesh_terms: D000328:Adult; D000368:Aged; D015295:Antigens, Tumor-Associated, Carbohydrate / Q000097:blood* / Q000235:genetics; D015415:Biomarkers / Q000097:blood; D021441:Carcinoma, Pancreatic Ductal / Q000097:blood / Q000175:diagnosis* / Q000235:genetics / Q000473:pathology; D016022:Case-Control Studies; D002779:Cholestasis / Q000097:blood / Q000175:diagnosis / Q000235:genetics / Q000473:pathology; D016207:Cytokines / Q000097:blood* / Q000235:genetics; D003937:Diagnosis, Differential; D005260:Female; D015870:Gene Expression; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D010179:Pancreas / Q000378:metabolism / Q000473:pathology; D010190:Pancreatic Neoplasms / Q000097:blood / Q000175:diagnosis* / Q000235:genetics / Q000473:pathology; D050500:Pancreatitis, Chronic / Q000097:blood / Q000175:diagnosis / Q000235:genetics / Q000473:pathology; D010982:Platelet-Derived Growth Factor / Q000235:genetics / Q000378:metabolism*
chemical_list: D015295:Antigens, Tumor-Associated, Carbohydrate; D015415:Biomarkers; D016207:Cytokines; D010982:Platelet-Derived Growth Factor; C578959:carbohydrate antigen 199, human; C075278:platelet-derived growth factor A