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Design and Rationale of the HANSE Study: A Holistic German Lung Cancer Screening Trial Using Low-Dose Computed Tomography

Jens Vogel‐Claussen, Florian Lasch, Benjamin‐Alexander Bollmann, Katharina May, Alexander Kuhlmann, Gerald Schmid‐Bindert, Rudolf Kaaks, Jörg Barkhausen, Sabine Bohnet, Martin Reck

2022RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren27 citationsDOIOpen Access PDF

Abstract

6-year risk ≥ 1.58 % or fulfilling NELSON risk inclusion criteria, will be screened by LDCT at baseline and after 12 months. Lung nodules are analyzed by a modified Lung-RADS 1.1 score of the HANSE study, and values of emphysema and coronary calcium are determined and randomly reported to the participants. 7100 low-risk participants serve as a control. All patients are followed-up for up to 10 years. The sensitivity and specificity of the two risk assessments and LDCT screening, effects of the randomized LDCT reporting, efficiency of lung nodule management, and several other factors are assessed to analyze the success and quality of the holistic screening program.The HANSE study is designed as a holistic lung cancer screening study in northern Germany to answer pressing questions for a successful implementation of an effective German lung cancer screening program. · HANSE is designed to address pressing questions for the implementation of lung cancer screening in Germany.. · HANSE compares NELSON and PLCOM2012 risk assessments for optimal definition of the high-risk group. . · HANSE integrates cardiac calcium and pulmonary emphysema scoring in a holistic screening approach.. CITATION FORMAT: · Vogel-Claussen J, Lasch F, Bollmann B et al. Design and Rationale of the HANSE Study: A Holistic German Lung Cancer Screening Trial Using Low-Dose Computed Tomography. Fortschr Röntgenstr 2022; 194: 1333 - 1345.

Topics & Concepts

Computed tomographyLung cancerLung cancer screeningMedicineGermanNuclear medicineRadiologyMedical physicsOncologyPhilosophyLinguisticsLung Cancer Diagnosis and TreatmentLung Cancer Treatments and MutationsRadiomics and Machine Learning in Medical Imaging
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