Literature DB >> 28073150

The impact of overdiagnosis on the selection of efficient lung cancer screening strategies.

Summer S Han1,2, Kevin Ten Haaf3, William D Hazelton4, Vidit N Munshi5, Jihyoun Jeon6, Saadet A Erdogan1, Colden Johanson5, Pamela M McMahon5, Rafael Meza6, Chung Yin Kong5, Eric J Feuer7, Harry J de Koning3, Sylvia K Plevritis2.   

Abstract

The U.S. Preventive Services Task Force (USPSTF) recently updated their national lung screening guidelines and recommended low-dose computed tomography (LDCT) for lung cancer (LC) screening through age 80. However, the risk of overdiagnosis among older populations is a concern. Using four comparative models from the Cancer Intervention and Surveillance Modeling Network, we evaluate the overdiagnosis of the screening program recommended by USPSTF in the U.S. 1950 birth cohort. We estimate the number of LC deaths averted by screening (D) per overdiagnosed case (O), yielding the ratio D/O, to quantify the trade-off between the harms and benefits of LDCT. We analyze 576 hypothetical screening strategies that vary by age, smoking, and screening frequency and evaluate efficient screening strategies that maximize the D/O ratio and other metrics including D and life-years gained (LYG) per overdiagnosed case. The estimated D/O ratio for the USPSTF screening program is 2.85 (model range: 1.5-4.5) in the 1950 birth cohort, implying LDCT can prevent ∼3 LC deaths per overdiagnosed case. This D/O ratio increases by 22% when the program stops screening at an earlier age 75 instead of 80. Efficiency frontier analysis shows that while the most efficient screening strategies that maximize the mortality reduction (D) irrespective of overdiagnosis screen through age 80, screening strategies that stop at age 75 versus 80 produce greater efficiency in increasing life-years gained per overdiagnosed case. Given the risk of overdiagnosis with LC screening, the stopping age of screening merits further consideration when balancing benefits and harms.
© 2017 UICC.

Entities:  

Keywords:  USPSTF; computed tomography; health policy; lung cancer; lung cancer screening; microsimulation; overdiagnosis; simulation model

Mesh:

Year:  2017        PMID: 28073150      PMCID: PMC5516788          DOI: 10.1002/ijc.30602

Source DB:  PubMed          Journal:  Int J Cancer        ISSN: 0020-7136            Impact factor:   7.396


  20 in total

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