Cost-effectiveness of Lung Cancer Screening Combining with CVD and COPD Screening: A Microsimulation Study

Author:

Yuan Jingmin1,Xu Fenglin2,Sun Yan3,Fan Meng3,Ren Xiaoxiao4,Chen Mingwei3,Ren Hui3

Affiliation:

1. Yangtze University

2. Hubei College of Chinese Medicine

3. The First Affiliated Hospital of Xi’an Jiaotong University

4. The First Affiliated Hospital of Xi’an Jiaotong Univeristy

Abstract

Abstract Objective This study aims to estimate the cost-effectiveness of lung cancer (LC), cardiovascular disease (CVD), and chronic obstructive pulmonary disease (COPD), the so-called “big-3 diseases”, combining screening and identify the optimal target screening population in China. Methods A stage shift microsimulation model constructed and different screening strategies were set. Cost, quality-adjusted life years (QALYs), incremental cost-effectiveness ratios (ICER) and net health benefits (NHB) under different screening strategies were calculated. Strategies with a mean ICER less than $38,223 (3 times as much as China’s GDP per capita in 2022) were deemed to be cost-effective, and the optimal one in this case is the strategy with the largest NHB obtained at the same willingness to pay (WTP). One-way and probabilistic sensitivity analysis was conducted to estimate results’ stability. Results ICERs in all strategies ranged from $2,186.5 to 11,227.6 per QALY, which was less than China’s GDP per capita in 2022. This value was basically lower in combined screening for “big-3 diseases” than in screening for LC alone. The largest NHB and probability of cost-effectiveness were both obtained in the strategy with “big-3 diseases” screening for people over 45 years old with a smoking history of 20 pack-year at least. Conclusion The optimal target screening population should be current smokers or smoking quitters in the past 15 years, aged over 45 years old, with a smoking history of 20 pack-year at least. These findings may provide data support for the revision of lung cancer screening guidelines.

Publisher

Research Square Platform LLC

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