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USPSTF s new lung cancer screening guidance lowers starting age
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The Centers for Medicare & Medicaid Services Requirement for Shared Decision-making for Lung Cancer Screening | Cancer Screening, Prevention, Control | JAMA
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Screening non-smokers for lung cancer just as important & effective, finds Taiwan study
Study by National Taiwan University College of Medicine which screened never-smokers based on family history, other risk factors identified a high baseline prevalence of lung cancer.
Chinmay Haridas 7 March, 2021 10:00 am IST
A+
Nagpur: Lung cancer in ‘never-smokers’ or people who have never smoked is a rising threat, and a new study from Taiwan has emphasised the importance of screening among certain risk groups to identify the disease early.
According to researchers from the National Taiwan University College of Medicine, Taipei, low-dose computed tomography (LDCT) screening currently the only recommended test for lung cancer screening may be “feasible” in never-smokers exposed to certain risk factors, such as a family history of lung cancer and exposure to second-hand smoke.
IN Malaysia, lung cancer is one of the most prevalent cancers and a leading cause of cancer-related mortality among men.
As with all cancers, the survival or prognosis for lung cancer depends very much on the stage of the disease. Poor outcomes here are largely due to late-stage presentation and hence delayed diagnosis in almost 95% of cases.
Traditionally a male smokers’ disease, an emerging global trend in recent years is the alarming rise in cases among non-smokers, particularly women of East Asian ethnicity.
Findings of a landmark study from Taiwan (TALENT study) presented at the virtual congress of the World Conference on Lung Cancer (WCLC) in Singapore last month demonstrated the feasibility and value of screening high-risk non-smokers for early detection of lung cancer.
Novel deep learning system can predict cardiovascular risk from CT scans
Coronary artery calcification the buildup of calcified plaque in the walls of the heart s arteries is an important predictor of adverse cardiovascular events like heart attacks. Coronary calcium can be detected by computed tomography (CT) scans, but quantifying the amount of plaque requires radiological expertise, time and specialized equipment.
In practice, even though chest CT scans are fairly common, calcium score CTs are not. Investigators from Brigham and Women s Hospital s Artificial Intelligence in Medicine (AIM) Program and the Massachusetts General Hospital s Cardiovascular Imaging Research Center (CIRC) teamed up to develop and evaluate a deep learning system that may help change this.
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