Risk Prediction Model for Lung Cancer Screening
نویسندگان
چکیده
منابع مشابه
Individualized Risk Prediction Model for Lung Cancer in Korean Men
PURPOSE Lung cancer is the leading cause of cancer deaths in Korea. The objective of the present study was to develop an individualized risk prediction model for lung cancer in Korean men using population-based cohort data. METHODS From a population-based cohort study of 1,324,804 Korean men free of cancer at baseline, the individualized absolute risk of developing lung cancer was estimated u...
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BACKGROUND Reliable risk prediction tools for estimating individual probability of lung cancer have important public health implications. We constructed and validated a comprehensive clinical tool for lung cancer risk prediction by smoking status. METHODS Epidemiologic data from 1851 lung cancer patients and 2001 matched control subjects were randomly divided into separate training (75% of th...
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Risk prediction models are useful in clinical decision making. We have published an internally validated prediction tool for lung cancer based on easily obtainable epidemiologic and clinical data. Because the precision of the model was modest, we now estimate the improvement obtained by adding two markers of DNA repair capacity. Assay data (host-cell reactivation and mutagen sensitivity) were a...
متن کاملLLPi: Liverpool Lung Project Risk Prediction Model for Lung Cancer Incidence.
Identification of high-risk individuals will facilitate early diagnosis, reduce overall costs, and also improve the current poor survival from lung cancer. The Liverpool Lung Project prospective cohort of 8,760 participants ages 45 to 79 years, recruited between 1998 and 2008, was followed annually through the hospital episode statistics until January 31, 2013. Cox proportional hazards models w...
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BACKGROUND Selection of candidates for lung cancer screening based on individual risk has been proposed as an alternative to criteria based on age and cumulative smoking exposure (pack-years). Nine previously established risk models were assessed for their ability to identify those most likely to develop or die from lung cancer. All models considered age and various aspects of smoking exposure ...
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ژورنال
عنوان ژورنال: Journal of the Korean Society of Radiology
سال: 2019
ISSN: 1738-2637,2288-2928
DOI: 10.3348/jksr.2019.80.5.860