A Comparative Modeling Analysis of Risk-Based Lung Cancer Screening Strategies

Author:

ten Haaf Kevin1ORCID,Bastani Mehrad2,Cao Pianpian3ORCID,Jeon Jihyoun3ORCID,Toumazis Iakovos2ORCID,Han Summer S24,Plevritis Sylvia K2,Blom Erik F1,Kong Chung Yin56ORCID,Tammemägi Martin C7,Feuer Eric J8ORCID,Meza Rafael3ORCID,de Koning Harry J1ORCID

Affiliation:

1. Department of Public Health, Erasmus MC-University Medical Center Rotterdam, Rotterdam, Zuid-Holland, the Netherlands

2. Department of Radiology, Stanford University, Palo Alto, CA

3. Department of Epidemiology, University of Michigan, Ann Arbor, MI

4. Department of Medicine, Stanford University, Palo Alto, CA (SSH)

5. Harvard Medical School, Boston, MA

6. Department of Radiology, Massachusetts General Hospital, Boston, MA

7. Department of Health Sciences, Brock University, St. Catharines, ON, Canada

8. Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD

Abstract

Abstract Background Risk-prediction models have been proposed to select individuals for lung cancer screening. However, their long-term effects are uncertain. This study evaluates long-term benefits and harms of risk-based screening compared with current United States Preventive Services Task Force (USPSTF) recommendations. Methods Four independent natural history models were used to perform a comparative modeling study evaluating long-term benefits and harms of selecting individuals for lung cancer screening through risk-prediction models. In total, 363 risk-based screening strategies varying by screening starting and stopping age, risk-prediction model used for eligibility (Bach, PLCOm2012, or Lung Cancer Death Risk Assessment Tool [LCDRAT]), and risk threshold were evaluated for a 1950 US birth cohort. Among the evaluated outcomes were percentage of individuals ever screened, screens required, lung cancer deaths averted, life-years gained, and overdiagnosis. Results Risk-based screening strategies requiring similar screens among individuals ages 55–80 years as the USPSTF criteria (corresponding risk thresholds: Bach = 2.8%; PLCOm2012 = 1.7%; LCDRAT = 1.7%) averted considerably more lung cancer deaths (Bach = 693; PLCOm2012 = 698; LCDRAT = 696; USPSTF = 613). However, life-years gained were only modestly higher (Bach = 8660; PLCOm2012 = 8862; LCDRAT = 8631; USPSTF = 8590), and risk-based strategies had more overdiagnosed cases (Bach = 149; PLCOm2012 = 147; LCDRAT = 150; USPSTF = 115). Sensitivity analyses suggest excluding individuals with limited life expectancies (<5 years) from screening retains the life-years gained by risk-based screening, while reducing overdiagnosis by more than 65.3%. Conclusions Risk-based lung cancer screening strategies prevent considerably more lung cancer deaths than current recommendations do. However, they yield modest additional life-years and increased overdiagnosis because of predominantly selecting older individuals. Efficient implementation of risk-based lung cancer screening requires careful consideration of life expectancy for determining optimal individual stopping ages.

Funder

National Cancer Institute’s (NCI's) CISNET Lung Consortium

Publisher

Oxford University Press (OUP)

Subject

Cancer Research,Oncology

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