Risk model-based lung cancer screening more economical than USPSTF recommendation

14 Feb 2023
Risk model-based lung cancer screening more economical than USPSTF recommendation

Lung cancer screening based on a risk model is more cost-effective than the 2021 recommendation by the US Preventive Services Task Force (USPSTF), meriting further consideration for the former, reports a recent study.

A group of researchers conducted a comparative modeling analysis in a 1960 US birth cohort using data from the National Lung Screening Trial; Surveillance, Epidemiology, and End Results program; and the US Smoking History Generator. They measured the incremental cost-effectiveness ratio (ICER) and cost-effectiveness efficiency frontier connecting strategies with the highest health benefit at a given cost.

On base-case analysis, risk model-based screening strategies were more cost-effective than the USPSTF recommendation, exclusively comprising the cost-effectiveness efficiency frontier. Among strategies on the efficiency frontier, those with a 6-year risk threshold of 1.2 percent were cost-effective with an ICER <USD 100,000 per quality-adjusted life year (QALY).

In particular, the strategy with a 1.2-percent risk threshold had an ICER of USD 94,659, which generated more QALYs for less cost compared with the USPSTF recommendation, while providing a similar level of screening coverage (person ever-screened 21.7 percent vs 22.6 percent, respectively).

Sensitivity analyses confirmed these findings, showing risk model-based strategies to be more cost-effective than the 2021 recommendation under varying modeling assumptions.

The study was limited by risk models that were restricted to age, sex, and smoking-related risk predictors.

In their 2021 lung cancer screening recommendation update, the 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, the researchers said.

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