Risk Model-Based Lung Cancer Screening : A Cost-Effectiveness Analysis

Abstract

Background: In their 2021 lung cancer screening recommendation update, the U.S. Preventive Services Task Force (USPSTF) evaluated strategies that select people based on their personal lung cancer risk (risk model-based strategies), highlighting the need for further research on the benefits and harms of risk model-based screening.

Objective: To evaluate and compare the cost-effectiveness of risk model-based lung cancer screening strategies versus the USPSTF recommendation and to explore optimal risk thresholds.

Design: Comparative modeling analysis.

Data sources: National Lung Screening Trial; Surveillance, Epidemiology, and End Results program; U.S. Smoking History Generator.

Target population: 1960 U.S. birth cohort.

Time horizon: 45 years.

Perspective: U.S. health care sector.

Intervention: Annual low-dose computed tomography in risk model-based strategies that start screening at age 50 or 55 years, stop screening at age 80 years, with 6-year risk thresholds between 0.5% and 2.2% using the PLCOm2012 model.

Outcome measures: Incremental cost-effectiveness ratio (ICER) and cost-effectiveness efficiency frontier connecting strategies with the highest health benefit at a given cost.

Results of base-case analysis: Risk model-based screening strategies were more cost-effective than the USPSTF recommendation and exclusively comprised the cost-effectiveness efficiency frontier. Among the strategies on the efficiency frontier, those with a 6-year risk threshold of 1.2% or greater were cost-effective with an ICER less than $100 000 per quality-adjusted life-year (QALY). Specifically, the strategy with a 1.2% risk threshold had an ICER of $94 659 (model range, $72 639 to $156 774), yielding more QALYs for less cost than the USPSTF recommendation, while having a similar level of screening coverage (person ever-screened 21.7% vs. USPSTF's 22.6%).

Results of sensitivity analyses: Risk model-based strategies were robustly more cost-effective than the 2021 USPSTF recommendation under varying modeling assumptions.

Limitation: Risk models were restricted to age, sex, and smoking-related risk predictors.

Conclusion: Risk model-based screening is more cost-effective than the USPSTF recommendation, thus warranting further consideration.

Primary funding source: National Cancer Institute (NCI).

Figure 1.

Additional Total Health Benefits (Measured Using QALY) Gained and Costs Incurred Associated With Categorical Age-Smoking and Risk Model-Based Screening Strategies Relative to the No Screening Strategy Based on the Mean Values Across the 4 CISNET Models under the base-case analysis Using (A) the PLCOm2012 Risk Prediction Model and (B) the Lung Cancer Death Risk Assessment Tool (LCDRAT) Risk Prediction Model. ^¶The screening strategies are labeled as follows: For categorical age-smoking strategies, frequency (A–annual)–age start–age stop–minimum pack-years–maximum years since quitting; For risk model-based strategies, frequency (A–annual)–age start–age stop–6-year lung cancer risk threshold per the risk prediction model specified *Strategies in bold text are the cost-effective strategies (defined as those strategies with an ICER lower than $100,000) relative to the strategy that precedes it on the efficiency frontier. ^†All outcomes are discounted at a 3% annual rate. Abbreviations: QALY, quality-adjusted life-years; USPSTF, U.S. Preventive Services Task Force; WTP, willingness-to-pay threshold; CISNET, Cancer Intervention and Surveillance Modeling Network.

Figure 2.

Univariate Sensitivity Analyses (±25% of their base-case value unless otherwise indicated) of the 1.2% 6-year PLCOm2012 risk strategies that start screening at age 50 years relative to their preceding strategy on the efficiency frontier (1.3% 6-year PLCOm2012 risk strategy) from the base-case analysis. ^‡minimum utility was −1 day per LDCT exam; maximum utility was 0 days per LDCT exam ^†minimum utility was −0.02 per indeterminate finding; maximum utility was −0.005 per indeterminate finding *minimum discounting factor was 1%; maximum discounting factor was 5% The screening strategies are labeled as follows: frequency (A–annual)–age start–age stop–6-year lung cancer risk threshold per the risk prediction model specified Abbreviations: ICER, incremental cost-effectiveness ratio; PLCO, Prostate, Lung, Colorectal and Ovarian Screening Trial, LDCT, low-dose computed tomography; NSCLC, non-small cell lung cancer; Tx, treatment; LC, lung cancer; SCLC, small cell lung cancer; OCM, other causes of mortality.