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Risk model-based screening for lung cancer accounting for personal risk may be more cost-effective than age- and smoking history-based screening recommended by the U.S. Preventive Services Task Force (USPSTF), according to a cost-effectiveness analysis.

Use of the Prostate, Lung, Colorectal, Ovarian Cancer Screening Trial risk prediction model modified in 2012 (PLCOm2012) with a 6-year risk threshold of ≥1.2% had an incremental cost-effectiveness ratio (ICER) of $94,659 per quality-adjusted life-year (QALY) gained, and yielded a higher reduction in lung cancer mortality compared with the USPSTF recommendation (12.4% vs 11.7%), with a similar level of screening coverage (person ever-screened 21.7% vs 22.6%, respectively), reported Summer S. Han, PhD, of Stanford University in California, and co-authors.

Use of the Lung Cancer Death Risk Assessment Tool (LCDRAT) model, which predicts the risk for 6-year lung cancer mortality -- compared with a 6-year lung cancer incidence as in PLCOm2012 -- yielded similar findings, but this strategy used a 1.1% 6-year risk threshold, with an ICER of $97,284 per QALY gained, they noted in the .

Sex-specific analyses showed that both risk model-based and categorical age-smoking strategies were more cost-effective for women versus men, in line with previous studies.

The USPSTF updated the guidelines for annual lung cancer screening with low-dose CT in 2021, lowering the minimum cumulative smoking exposure from 30 to 20 pack-years and the starting age from 55 to 50 among high-risk individuals until age 80, including those who have quit smoking within the past 15 years.

"Interim findings from the International Lung Screening Trial demonstrated that risk model-based lung cancer screening programs improve sensitivity versus categorical age-smoking strategies," Han and colleagues wrote. "Despite the potential for risk model-based screening to improve screening performance, comprehensive evaluations of the cost-effectiveness of risk model-based screening programs have been largely lacking."

In a press release, co-author Iakovos Toumazis, PhD, of the University of Texas MD Anderson Cancer Center in Houston, noted that "findings from this study could be considered as a potential guide for the development of cost-effective risk model-based lung cancer screening under various settings and availability of healthcare resources. While the current recommendations are cost effective, our findings suggest that we can improve on these guidelines and provide more flexibility to include those most likely to benefit from lung cancer screening."

Despite risk-based strategies being more cost-effective, some experts have doubts about the real-world impact and practicality of these methods.

"Selection criteria aside, the biggest crisis facing LCS [lung cancer screening] implementation is the slow uptake in practice, with only 10% to 20% of LCS-eligible Americans screened to date," noted Renda Soylemez Wiener, MD, MPH, of the Boston University Chobanian & Avedisian School of Medicine, and Michael K. Gould, MD, MS, of the Kaiser Permanente Bernard J. Tyson School of Medicine in Pasadena, California, in an .

"Smoking history is often missing or inaccurate in electronic health records (EHRs), creating challenges for clinicians and health systems to identify LCS candidates by categorical age-smoking criteria; incorporating even simple prediction models adds further complexity," they wrote.

"Integrating risk models into EHRs to autopopulate clinical reminders with personalized information would substantially advance the likelihood of adoption of risk model-based LCS," they continued. "However, it would require a major investment of time and resources to update EHRs, reassess workflows to ensure necessary data are collected, and educate clinicians on how to use and discuss results of prediction models with patients. Such an overhaul would doubtless slow LCS implementation, negatively impacting the timeliness of getting eligible persons screened."

For this analysis, Han and colleagues used a comparative modeling approach involving four validated microsimulation models of the Cancer Intervention and Surveillance Modeling Network (CISNET) Lung Working Group that informed the USPSTF 2013 and 2021 recommendations on lung cancer screening, including the Microsimulation Screening Analysis-Lung Model from Erasmus University Medical Center, the Lung Cancer Policy Model from Massachusetts General Hospital, the Lung Cancer Outcomes Simulation from Stanford University, and the model from University of Michigan.

Lung cancer-related events for 1 million men and women were simulated separately, using smoking patterns from a 1960 U.S. birth cohort that is representative of the U.S. population targeted by screening. Simulated individuals entered the study at age 45 and were followed until age 90 or death, whichever occurred first, corresponding to a study horizon of 2005 to 2050.

Screening was considered to be cost-effective if the strategy had an ICER of less than $100,000 and fell on the cost-effectiveness efficiency frontier, which connects "strategies that yield the highest health benefit at a given level of cost."

The study had several limitations, Han and team said. Models used for analysis were simplified in regards to risk prediction, and could not incorporate information such as availability of resources or smoking cessation interventions for the patient present at the lung cancer screening.

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