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BMC Cancer


Title:Accuracy of volatile urine biomarkers for the detection and characterization of lung cancer
Author(s):Mazzone PJ; Wang XF; Lim S; Choi H; Jett J; Vachani A; Zhang Q; Beukemann M; Seeley M; Martino R; Rhodes P;
Address:"Respiratory Institute, Cleveland Clinic, 9500 Euclid Ave., A90, Cleveland, OH, 44195, USA. mazzonp@ccf.org. Respiratory Institute, Cleveland Clinic, 9500 Euclid Ave., A90, Cleveland, OH, 44195, USA. wangx6@ccf.org. Metabolomx, Mountainview, CA, USA. slim@isensesystems.com. Respiratory Institute, Cleveland Clinic, 9500 Euclid Ave., A90, Cleveland, OH, 44195, USA. choih@ccf.org. National Jewish Health, Denver, CO, USA. JettJ@NJHealth.org. University of Pennsylvania, Philadelphia, PA, USA. avachani@mail.med.upenn.edu. Respiratory Institute, Cleveland Clinic, 9500 Euclid Ave., A90, Cleveland, OH, 44195, USA. zhangq@ccf.org. Respiratory Institute, Cleveland Clinic, 9500 Euclid Ave., A90, Cleveland, OH, 44195, USA. beukemm@ccf.org. Respiratory Institute, Cleveland Clinic, 9500 Euclid Ave., A90, Cleveland, OH, 44195, USA. seeleym@ccf.org. Metabolomx, Mountainview, CA, USA. rmartino@isensesystems.com. Metabolomx, Mountainview, CA, USA. prhodes@isensesystems.com"
Journal Title:BMC Cancer
Year:2015
Volume:20151223
Issue:
Page Number:1001 -
DOI: 10.1186/s12885-015-1996-0
ISSN/ISBN:1471-2407 (Electronic) 1471-2407 (Linking)
Abstract:"BACKGROUND: The mixture of volatile organic compounds in the headspace gas of urine may be able to distinguish lung cancer patients from relevant control populations. METHODS: Subjects with biopsy confirmed untreated lung cancer, and others at risk for developing lung cancer, provided a urine sample. A colorimetric sensor array was exposed to the headspace gas of neat and pre-treated urine samples. Random forest models were trained from the sensor output of 70% of the study subjects and were tested against the remaining 30%. Models were developed to separate cancer and cancer subgroups from control, and to characterize the cancer. An additional model was developed on the largest clinical subgroup. RESULTS: 90 subjects with lung cancer and 55 control subjects participated. The accuracies, reported as C-statistics, for models of cancer or cancer subgroups vs. control ranged from 0.795 - 0.917. A model of lung cancer vs. control built using only subjects from the largest available clinical subgroup (30 subjects) had a C-statistic of 0.970. Models developed and tested to characterize cancer histology, and to compare early to late stage cancer, had C-statistics of 0.849 and 0.922 respectively. CONCLUSIONS: The colorimetric sensor array signature of volatile organic compounds in the urine headspace may be capable of distinguishing lung cancer patients from clinically relevant controls. The incorporation of clinical phenotypes into the development of this biomarker may optimize its accuracy"
Keywords:"Adult Aged Biomarkers, Tumor/*urine Case-Control Studies Colorimetry/methods Early Detection of Cancer/*methods/standards Female Humans Lung Neoplasms/diagnosis/*urine Male Middle Aged Predictive Value of Tests Sensitivity and Specificity Volatile Organic;"
Notes:"MedlineMazzone, Peter J Wang, Xiao-Feng Lim, Sung Choi, Humberto Jett, James Vachani, Anil Zhang, Qi Beukemann, Mary Seeley, Meredith Martino, Ray Rhodes, Paul eng P30 ES013508/ES/NIEHS NIH HHS/ R43 CA177023/CA/NCI NIH HHS/ UL1 TR000439/TR/NCATS NIH HHS/ 1R43CA177023-01/CA/NCI NIH HHS/ Research Support, N.I.H., Extramural England 2015/12/25 BMC Cancer. 2015 Dec 23; 15:1001. doi: 10.1186/s12885-015-1996-0"

 
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