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Oleg Kshivets
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P2.11 - Screening and Early Detection (Not CME Accredited Session) (ID 960)
- Event: WCLC 2018
- Type: Poster Viewing in the Exhibit Hall
- Track:
- Presentations: 1
- Moderators:
- Coordinates: 9/25/2018, 16:45 - 18:00, Exhibit Hall
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P2.11-13 - Precise Early Detection of Lung Cancer and Blood Cell Circuit (ID 11122)
16:45 - 18:00 | Presenting Author(s): Oleg Kshivets
- Abstract
Background
Significance of blood cell circuit in terms of early detection of lung cancer (LC) was investigated.
a9ded1e5ce5d75814730bb4caaf49419 Method
In trial (1987-2018) consecutive cases after surgery, monitored 115 LC patients (LCP) (m=100, f=15; lobectomies=115) with pathologic stage IA (tumor size=1.86±0.30 cm; squamous=51, adenocarcinoma=59, large cell=5; T1N0M0=115; G1=39, G2=42, G3=34, 5-year survival=100%) and 120 healthy donors (HD) (m=69, f=51) were reviewed. Variables selected for study were input levels of blood cell circuit, sex, age, TNMG. Differences between groups were evaluated using discriminant analysis, clustering, nonlinear estimation, structural equation modeling, Monte Carlo, bootstrap simulation and neural networks computing.
4c3880bb027f159e801041b1021e88e8 Result
It was revealed that early detection of LC from HD (n=235) significantly depended on: leucocytes (abs, total), segmented neutrophils (%, abs, total), lymphocytes (%), monocytes (abs, total) (P=0.012-0.000). Neural networks computing, genetic algorithm selection and bootstrap simulation revealed relationships of early detection of LC and lymphocytes (rank=1), stick neutrophils (rank=2), monocytes (3), segmented neutrophils (4), leucocytes (5), eosinophils (6). Correct detection of early LCP was 100% by neural networks computing (error=0.000; area under ROC curve=1.0).
8eea62084ca7e541d918e823422bd82e Conclusion
Early detection of LC from HD significantly depended on blood cell circuit.
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