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Báo cáo y học: "Identification of lung cancer with high sensitivity and specificity by blood testing"

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học 'Respiratory Research cung cấp cho các bạn kiến thức về ngành y đề tài:Identification of lung cancer with high sensitivity and specificity by blood testing. | Leidinger et al. Respiratory Research 2010 11 18 http respiratory-research.eom content 11 1 18 RESPIRATORY RESEARCH RESEARCH Open Access Identification of lung cancer with high sensitivity and specificity by blood testing Petra Leidinger1 Andreas Keller2 Sabrina Heisel1 Nicole Ludwig1 Stefanie Rheinheimer1 Veronika Klein1 I - I I I I A I r 2 A I r X CF- r- Ffz-biz-xl I 3 11 I zzx A I P4 c r I r kx c Fz-xz-x 1p ZM k5 r 1 Cf X k . kx k x6 I k x z Z X c Fz X kx I J 7 Claudia Andres Andrea Staratschek-Jox Jurgen vvolT trich Stoelben Bernhard Stephan Ingo Stehle 11 I r i I I -X kvx X z H z K8 I I -X k i k i Z X Ị ỊI IX A r x K9 I I -X k x c D xF x k I X k x H z xT2 c I kF h K f f r f 1 Jurg Hamacher Hanno Huwer Hans-Peter LenhoT tckart Meese Abstract Background Lung cancer is a very frequent and lethal tumor with an identifiable risk population. Cytological analysis and chest X-ray failed to reduce mortality and CT screenings are still controversially discussed. Recent studies provided first evidence for the potential usefulness of autoantigens as markers for lung cancer. Methods We used extended panels of arrayed antigens and determined autoantibody signatures of sera from patients with different kinds of lung cancer different common non-tumor lung pathologies and controls without any lung disease by a newly developed computer aided image analysis procedure. The resulting signatures were classified using linear kernel Support Vector Machines and 10-fold cross-validation. Results The novel approach allowed for discriminating lung cancer patients from controls without any lung disease with a specificity of 97.0 a sensitivity of 97.9 and an accuracy of 97.6 . The classification of stage IA IB tumors and controls yielded a specificity of 97.6 a sensitivity of 75.9 and an accuracy of 92.9 . The discrimination of lung cancer patients from patients with non-tumor lung pathologies reached an accuracy of 88.5 . Conclusion We were able to separate lung cancer patients from .