Screening Study Provides Edge in Lung Cancer

Screening Study Examines New Strategy for Lung Cancer Treatment

Kathleen Raven |  18-05-2016

When the National Lung Screening Trial (NLST) launched in the U.S. in 2002, neither American nor European medical organizations endorsed specific lung cancer screening guidelines. Furthermore, the existing strategies missed crucial lung cancer diagnoses because the disease can be asymptomatic until the advanced stages.

About Siemens Healthineers

Our new name expresses our mission and what we stand for: Helping healthcare providers become more successful in caring for their patients.  

Our new name is unique. It embodies our pioneering spirit and our engineering expertise in the healthcare industry. It reflects the fact that this industry is increasingly driven by the skills of individuals. It also contains a commitment and a promise to our customers that we will use our pioneering spirit and our engineering expertise to help drive their success.

Share this page: (Accessed 3 July 2015)

2American Lung Association (2015) Lung Cancer Screening: Coverage in health insurance.

3Goulart BH, Bensink ME, Mummy DG, et al. (2012) Lung Cancer Screening With Low-Dose Computed Tomography: Costs, National Expenditures, and Cost-Effectiveness. J Natl Compr Canc Netw. 10:267-75


5Kauczor HU, Bonomo L, Gaga M et al (2015) ESR/ERS white paper on lung cancer screening. Eur Radiol, May 1, 2015 [Epub ahead of print]

6Frauenfelder T, Puhan MA, Lazor R et al (2014) Early Detection of Lung Cancer: A Statement from an Expert Panel of the Swiss University Hospitals on Lung Cancer Screening. Respiration 87:254-64

7Black WC, Gareen IF, Soneji SS, et al. (2014) Cost-effectiveness of CT screening in the National Lung Screening Trial. N Engl J Med 371:1793-802

8The National Lung Screening Trial Research Team (2011) Reduced Lung-Cancer Mortality with Low-Dose Computed Tomographic Screening. N Engl J Med 365:395-409

The statements by Siemens’ customers described herein are based on results that were achieved in the customer's unique setting. Since there is no "typical" hospital and many variables exist (e.g., hospital size, case mix, level of IT adoption) there can be no guarantee that other customers will achieve the same results.