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Comparative Study
. 2020 May 1;112(5):466-479.
doi: 10.1093/jnci/djz164.

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

Affiliations
Comparative Study

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

Kevin Ten Haaf et al. J Natl Cancer Inst. .

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.

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Figures

Figure 1.
Figure 1.
Number of CT screens and lung cancer deaths averted for risk-based screening strategies screening between ages 55 and 80 years compared with the USPSTF criteria (mean results across the four CISNET models). Risk thresholds corresponding to strategies that yield a similar number of lung cancer deaths averted as the USPSTF criteria: Bach model = 3.4%; PLCOm2012 model = 2.2%; LCDRAT model = 2.1%. CT = computed tomography; LCDRAT = Lung Cancer Death Risk Assessment Tool; USPSTF = United States Preventive Services Task Force.
Figure 2.
Figure 2.
Number of CT screens and life-years gained for risk-based screening strategies screening between ages 55 and 80 years compared with the USPSTF criteria (mean results across the four CISNET models). Risk thresholds corresponding to strategies that yield a similar number of life-years gained as the USPSTF criteria: Bach model = 2.8%; PLCOm2012 model = 1.83%; LCDRAT model = 1.7%. CT = computed tomography; LCDRAT = Lung Cancer Death Risk Assessment Tool; USPSTF = United States Preventive Services Task Force.

Comment in

References

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