{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T05:59:00Z","timestamp":1788328740286,"version":"build-2803163510"},"reference-count":61,"publisher":"American Medical Association (AMA)","issue":"7","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Netw Open"],"abstract":"\n Importance<\/jats:title>\n Lung cancer is the leading cause of cancer death in Singapore, with approximately 48% of cases occurring in individuals who have never smoked (never smokers) and 82% diagnosed at late stages (stage III or IV). Current screening guidelines exclude never smokers entirely.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n To determine whether low-dose computed tomography (LDCT) lung cancer screening including never smokers is cost-effective in Singapore and to identify the minimum risk model performance for targeted never smoker screening.<\/jats:p>\n <\/jats:sec>\n \n Design, Setting, and Participants<\/jats:title>\n This economic evaluation from the perspective of the Singapore health care system used a 9-state Markov cohort model with annual cycles. The model was parameterized with 2023-2024 national life tables, cancer registry incidence from 2019 to 2023, and 2024 smoking prevalence data, simulating adults from 30 to 100 years of age stratified by sex and smoking status.<\/jats:p>\n <\/jats:sec>\n \n Exposures<\/jats:title>\n Four LDCT screening strategies included no screening, US Preventive Services Task Force (USPSTF) 2021 (annual screening of eligible ever smokers aged 50-80 years), a universal program (annual screening of all adults aged 50-74 years), and Singapore expanded (biennial screening of all adults aged 50-75 years).<\/jats:p>\n <\/jats:sec>\n \n Main Outcomes and Measures<\/jats:title>\n Quality-adjusted life-years (QALYs), lifetime costs in 2024 Singapore dollars (SGD), and incremental cost-effectiveness ratios (ICERs). Probabilistic sensitivity analysis used 1\u202f000\u202f000 iterations. Risk threshold analysis identified the minimum area under the receiver operating characteristics curve (AUROC) for targeted never smoker screening.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n The model reproduced registry-reported late-stage diagnosis (79% modeled vs 82% observed). The USPSTF strategy achieved the lowest ICER (SGD 8741\/QALY [US $6523\/QALY] for males and SGD 6480\/QALY [US $4836\/QALY] for females) but screened approximately 8% of males and 2% of females only. Sequential ICERs for extending from the USPSTF strategy to Singapore expanded biennial screening were SGD 86\u202f312\/QALY (US $64 412\/QALY) for males and SGD 80\u202f881\/QALY (US $60\u202f359\/QALY) for females, below the SGD 100\u202f000 (US $74\u202f627) benchmark. At SGD 100\u202f000\/QALY (US $74\u202f627\/QALY) willingness to pay, the Singapore expanded strategy had the highest probability of being cost-effective (61.1% for males and 72.1% for females). A risk prediction model with AUROC of 0.82 or higher for males or 0.81 or higher for females would make targeted never smoker screening as cost-effective as smoking-based criteria.<\/jats:p>\n <\/jats:sec>\n \n Conclusions and Relevance<\/jats:title>\n In this economic evaluation of LDCT lung cancer screening including never smokers in Singapore, targeted ever smoker screening was highly cost-effective but left approximately 37% of lung cancers unaddressed. Universal biennial screening fell below conventional cost-effectiveness thresholds. Extending screening to never smokers warrants consideration as risk prediction models are validated for Asian populations of never smokers.<\/jats:p>\n <\/jats:sec>","DOI":"10.1001\/jamanetworkopen.2026.22042","type":"journal-article","created":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T15:00:29Z","timestamp":1783522829000},"page":"e2622042","source":"Crossref","is-referenced-by-count":1,"title":["Cost-Effectiveness of Universal Low-Dose Computed Tomographic Lung Cancer Screening in Singapore"],"prefix":"10.1001","volume":"9","author":[{"given":"Ruijie","family":"Li","sequence":"first","affiliation":[{"name":"Health Services and Outcomes Research, National Healthcare Group, Singapore"},{"name":"Health Empowered by AI, Centre for Health Innovation, National Healthcare Group, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John","family":"Abisheganaden","sequence":"additional","affiliation":[{"name":"Health Services and Outcomes Research, National 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