A leading killer with an early-detection solution. Lung cancer is the top cause of cancer-related death globally, responsible for roughly 2 million new cases and 1.76 million deaths each year. Critically, about 75% of patients are diagnosed only at advanced stages, when treatment is far less effective - making earlier detection strategies essential.
Proven mortality benefit from LDCT. Two landmark randomized controlled trials - the National Lung Screening Trial (NLST) and the NELSON trial - demonstrated that low-dose computed tomography (LDCT) screening reduces lung cancer mortality by 20-24% compared to chest X-ray or no screening at all. This level of benefit is substantial enough to justify wider implementation.
The economic question that follows clinical benefit. Even when a screening strategy works clinically, healthcare systems must evaluate whether it represents good value for money. With limited budgets and competing priorities, cost-effectiveness analysis helps policymakers decide which populations should be screened, how often, and with which technology.
Filling a gap in the evidence base. Prior systematic reviews focused only on LDCT screening and used literature searches that ended in 2022. This new review is the first to include data through early 2025 and to incorporate emerging tools such as AI-assisted screening and polygenic risk scores alongside traditional LDCT and chest X-ray approaches.
A rigorous PRISMA-compliant search. The authors searched four major databases - PubMed, EMBASE, Web of Science, and Cochrane Library - from their inception through March 18, 2025, using the terms 'Lung Cancer,' 'Screening,' and 'Economic Evaluations.' From an initial pool of 15,610 records, 3,348 duplicates were removed, and after stepwise screening, 79 studies from 21 countries were ultimately included.
Both full and partial economic analyses were eligible. The review accepted comprehensive economic analyses (cost-effectiveness, cost-utility, and cost-benefit studies) as well as partial analyses (cost-only studies). Both trial-based and model-based designs were included, without restrictions on language, publication date, or country of origin.
Rigorous quality scoring was applied. Model-based studies (87% of the total) were evaluated using the BMJ checklist by Drummond and Jefferson, assessing model transparency, data sources, simulation components, and sensitivity analysis. An impressive 89.9% of model-based studies rated as high quality. Trial-based studies were assessed with standard tools including the Cochrane Risk of Bias Tool and Newcastle-Ottawa Scale.
Costs were standardized for comparability. Because studies came from many countries and different years, all reported costs were converted to 2022 US dollars using Consumer Price Index (CPI) adjustments and Purchasing Power Parity (PPP) conversion factors from the OECD database. This allowed meaningful side-by-side comparison of incremental cost-effectiveness ratios (ICERs) across diverse settings.
LDCT is the clear frontrunner in study volume and cost-effectiveness. The vast majority of included studies evaluated LDCT, and 90.3% of LDCT screening strategies were found to be cost-effective within their national thresholds. ICERs for LDCT versus no screening ranged widely - from $8,376 to $200,921 per quality-adjusted life-year (QALY) gained - reflecting genuine variation in populations, health systems, and screening protocols.
Older adults and heavier smokers derive the greatest benefit. Studies consistently show that lung cancer screening is most cost-effective among people with the highest risk: those who are older, have longer or heavier smoking histories, or have additional risk factors like COPD. For example, in China, starting screening at age 55-76 had a lower ICER ($15,217/QALY) than starting at 40-76 ($18,340/QALY), since older populations carry more concentrated cancer risk.
Biennial screening often beats annual in economic terms. While annual screening finds cancers sooner, biennial screening typically achieves a lower ICER across many age groups and risk profiles. However, the optimal frequency is not one-size-fits-all: for daily smokers aged 50-74, annual screening ($12,613/QALY) was actually more cost-effective than biennial ($23,374/QALY), illustrating that screening interval should be tailored to individual risk.
Men tend to show more favorable economics than women - with important exceptions. Multiple studies reported lower ICERs (i.e., better cost-effectiveness) for men compared to women with equivalent smoking histories, likely because of men's higher baseline lung cancer risk. However, in East Asia - where lung cancer among non-smoking women is notably prevalent - some analyses have found lower ICERs for female non-smokers, underscoring the need for population-specific guidelines.
Guideline choice strongly influences cost-effectiveness outcomes. Four studies directly compared the ICERs of screening protocols recommended by different guidelines. ICERs across guidelines ranged from $8,328 to $112,700 per QALY. Notably, the NELSON and China guidelines consistently showed the most favorable cost-effectiveness, while the U.S. Preventive Services Task Force (USPSTF) guideline had the highest ICER.
Why NELSON outperforms NLST economically. The NELSON trial's superior cost-effectiveness stems largely from its use of volume doubling time (VDT) for nodule management. This approach produces a dramatically lower false-positive rate: just 1.2% in NELSON versus 23.3% in NLST. Fewer false positives means fewer unnecessary diagnostic procedures, reducing both costs and patient burden while preserving health outcomes.
NELSON also identified more early-stage cancers. Because NELSON's nodule management was more precise, it captured a higher proportion of early-stage lung cancers than NLST - leading to greater projected gains in QALYs and life-years. Both Australian and Dutch modeling studies confirmed that NELSON-based screening is more cost-effective than NLST-based screening in their respective populations.
Risk prediction models add another layer of targeting. Only 10 of the 79 studies incorporated formal risk prediction models (such as PLCOM2012) to identify the highest-risk individuals for screening. Risk-stratified approaches hold promise for improving cost-effectiveness further - but the external validity of these models across diverse populations, particularly in East Asia, remains to be established.
AI integration in lung cancer screening is still emerging. The review found that economic evidence for AI-assisted screening is very limited - only two of the 79 included studies examined AI combined with LDCT. The integration of AI with LDCT first appeared in cost-effectiveness literature in 2022, reflecting how recently this technology has entered clinical and research discussions.
One study found AI-plus-LDCT was actually cost-saving. In a striking finding, one study reported that combining AI with LDCT produced a negative ICER of -$68 per QALY compared to LDCT alone - meaning the AI-enhanced approach was both clinically superior and less expensive overall. This suggests AI could improve screening accuracy enough to reduce downstream costs by cutting unnecessary follow-up tests.
How AI could improve the economics of screening. AI can contribute to cost-effectiveness in several ways: reducing radiation dose through ultra-low-dose CT imaging (potentially improving patient adherence), improving nodule detection sensitivity (catching more true cancers), reducing false positives (decreasing unnecessary procedures), and even detecting incidental findings like coronary artery calcification that add health value beyond lung cancer alone.
Key uncertainties remain for AI adoption. Current economic analyses rarely account for the equipment purchase and ongoing maintenance costs of AI systems, which could be substantial. Additionally, since AI has not yet been widely deployed in real clinical screening programs, its actual impact in practice remains uncertain. The authors call for comprehensive economic analyses before broad AI-assisted screening programs are implemented.
Blood-based biomarker tests offer a different path. The EarlyCDT-Lung blood test, studied in Scotland's ECLS trial, was found to be cost-effective as a complement to LDCT. Blood-based screening emerged as the most cost-effective alternative compared to either no screening or LDCT alone in economic models, and reducing its cost would further enhance its value - making it particularly interesting for resource-limited settings.
Polygenic risk scores have not proven cost-effective. One study evaluated using polygenic risk scores (PRS) - genetic markers that capture inherited cancer risk - to guide LDCT screening decisions. The PRS-based strategy was not found to be cost-effective, primarily because it may restrict screening to a smaller high-risk subgroup and therefore fails to generate sufficient additional life-years gained over standard LDCT screening alone.
The potential role of biomarkers in low-resource settings. In regions where LDCT infrastructure is unavailable or prohibitively expensive, blood-based biomarker tests could represent a more practical first-line screening tool. Mobile LDCT units combined with AI diagnostics have also been explored in underserved populations, showing promising feasibility and cost-effectiveness data in one recent study.
Both technologies require more rigorous study. The authors emphasize that evidence on blood biomarkers and PRS remains thin - just a handful of studies each - and that robust, population-specific economic analyses are needed before these approaches can be recommended as policy-level screening tools.
How much does adherence actually affect cost-effectiveness? Nine of the 79 studies investigated the impact of patient participation and adherence on screening cost-effectiveness - and their findings are inconsistent. Most modeling studies suggest that reduced participation rates have only limited influence on the ICER, because when participation falls, both costs and health gains tend to fall together, leaving the ratio relatively stable.
Fixed infrastructure costs complicate the picture. When programs have substantial fixed costs - for equipment, administration, and facility operation - reduced uptake can genuinely harm cost-effectiveness by spreading those fixed costs across fewer participants. This dynamic underscores the importance of maximizing enrollment and minimizing overhead to make real-world screening programs economically viable.
Pairing screening with smoking cessation adds complexity. Several studies incorporated smoking cessation interventions alongside LDCT screening, given their potential to improve health outcomes and cost-effectiveness simultaneously. However, the added costs of cessation programs require careful accounting in economic models, and evidence on whether the combination is reliably cost-effective compared to screening alone remains limited.
Risk-stratified intervals as an emerging optimization strategy. Moving beyond fixed annual or biennial schedules, some researchers are exploring personalized screening intervals based on individual risk profiles. This approach holds promise for improving cost-effectiveness by increasing screening frequency for those at highest risk while reducing it for those at lower risk - but the real-world generalizability of risk models needs further validation.
Low- and middle-income countries are largely absent from the literature. The overwhelming majority of studies were conducted in high-income countries - China and the US together account for 43% of all included studies. Lung cancer screening programs are virtually absent from low- and middle-income countries (LMICs), yet these settings carry a significant and growing share of the global lung cancer burden.
Methodological heterogeneity limits cross-study comparisons. Despite standardizing costs to 2022 US dollars, the review notes that differences in model types, analytic perspectives, cost-effectiveness thresholds, and study populations make direct comparison difficult. Each country's willingness-to-pay threshold varies with its economic context, meaning a strategy that looks cost-effective in the UK may not appear so in Hungary or New Zealand.
Three priority areas for future research. The authors identify the most urgent needs: first, comprehensive economic analyses of AI-assisted screening and biomarker-based approaches; second, evaluation of risk-stratified screening programs in real-world clinical settings; and third, generation of robust, country-specific economic evidence for LMICs. Without data from these settings, global implementation of equitable lung cancer screening cannot be effectively guided.
The field is rapidly evolving. With AI integration, new biomarkers, and refining risk models all advancing simultaneously, the cost-effectiveness landscape is changing quickly. The authors acknowledge that continued updated reviews will be essential to keep policy-relevant evidence current as new technologies enter practice.
LDCT screening is generally cost-effective - but not universally. Across 79 studies and 21 countries, LDCT emerged as the dominant and most cost-effective lung cancer screening modality, with 90.3% of strategies meeting national cost-effectiveness thresholds. However, the economics depend heavily on who is being screened: older adults and heavy smokers derive the clearest benefit, while the value of screening younger or lower-risk individuals is less certain.
Protocol and guideline choice matters as much as technology choice. The choice between NELSON-based and NLST-based protocols, and between annual and biennial screening, can shift cost-effectiveness dramatically. Adopting more precise nodule management strategies - as exemplified by NELSON's volume doubling time approach - can simultaneously improve clinical outcomes and reduce economic costs.
Emerging technologies need urgent economic evaluation. AI-assisted LDCT shows early economic promise but has been formally evaluated in only two studies. Blood-based biomarkers show potential for LMICs and resource-limited settings. Neither technology has sufficient evidence to guide broad policy adoption, making targeted investment in economic research a clear priority.
Equitable global implementation requires locally-generated evidence. Because healthcare costs, population risk profiles, and willingness-to-pay thresholds vary enormously between countries, economic analyses from high-income countries cannot simply be transplanted to LMIC settings. Generating local evidence - and designing context-appropriate screening programs - is essential for ensuring that the life-saving benefits of lung cancer screening are accessible worldwide.