title: Automated detection of genetic abnormalities combined with cytology in sputum is a sensitive predictor of lung cancer.
abstract: Detection of lung cancer by sputum cytology has low sensitivity but is noninvasive and, if improved, could be a powerful tool for early lung cancer detection. To evaluate whether the accuracy of diagnosing lung cancer by evaluating sputa for cytologic atypia and genetic abnormalities is greater than that of conventional cytology alone, automated scoring of genetic abnormalities for 3p22.1 and 10q22.3 (SP-A) by fluorescence in situ hybridization (FISH) and conventional cytology was done on sputa from 35 subjects with lung cancer, 25 high-risk smokers, and 6 healthy control subjects. Multivariate analysis was performed to select variables that most accurately predicted lung cancer. A model of probability for the presence of lung cancer was derived for each subject. Cells exfoliated from patients with lung cancer contained genetic aberrations and cytologic atypias at significantly higher levels than in those from control subjects. When combined with cytologic atypia, a model of risk for lung cancer was derived that had 74% sensitivity and 82% specificity to predict the presence of lung cancer, whereas conventional cytology achieved only 37% sensitivity and 87% specificity. For diagnosing lung cancer in sputum, a combination of molecular and cytologic variables was superior to using conventional cytology alone.
authors.affiliation: Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030-4009, USA. rkatz@mdanderson.org
authors.forename: Ruth L
authors.initials: RL
authors.lastname: Katz
authors.forename: Tanweer M
authors.initials: TM
authors.lastname: Zaidi
authors.forename: Ricardo L
authors.initials: RL
authors.lastname: Fernandez
authors.forename: Jingpin
authors.initials: J
authors.lastname: Zhang
authors.forename: Weigong
authors.initials: W
authors.lastname: He
authors.forename: Charisse
authors.initials: C
authors.lastname: Acosta
authors.forename: Michal
authors.initials: M
authors.lastname: Daniely
authors.forename: Lea
authors.initials: L
authors.lastname: Madi
authors.forename: Mary A
authors.initials: MA
authors.lastname: Vargas
authors.forename: Qiong
authors.initials: Q
authors.lastname: Dong
authors.forename: Xiaoying
authors.initials: X
authors.lastname: Gao
authors.forename: Xiaoying Gao Feng
authors.initials: XG
authors.lastname: Jiang
authors.forename: Feng
authors.initials: F
authors.lastname: Jiang
authors.forename: Nancy P
authors.initials: NP
authors.lastname: Caraway
authors.forename: Ara A
authors.initials: AA
authors.lastname: Vaporciyan
authors.forename: Jack A
authors.initials: JA
authors.lastname: Roth
authors.forename: Margaret R
authors.initials: MR
authors.lastname: Spitz
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D018278:Carcinoma, Neuroendocrine / Q000175:diagnosis / Q000235:genetics*; D002294:Carcinoma, Squamous Cell / Q000175:diagnosis / Q000235:genetics*; D002869:Chromosome Aberrations; D002880:Chromosomes, Human, Pair 11; D002893:Chromosomes, Human, Pair 3; D003581:Cytodiagnosis / Q000379:methods; D005260:Female; D006801:Humans; D019044:Image Cytometry / Q000379:methods; D017404:In Situ Hybridization, Fluorescence / Q000379:methods; D008175:Lung Neoplasms; D008297:Male; D008875:Middle Aged; D009367:Neoplasm Staging; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012372:ROC Curve; D013183:Sputum / Q000166:cytology