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Cost-effectiveness of low-dose computed tomography for lung cancer screening in India: A Markov modelling study
Gowthaman Thangavel1, Stany Mathew1, Praveen Pujar1
1Indian Council of Medical Research, National Centre for Disease Informatics and Research, Bengaluru, India.
Abstract:
BackgroundLung cancer is a leading cause of cancer-related mortality in India, with most cases diagnosed at advanced stages. Low-dose computed tomography (LDCT) screening has been shown to enhance early detection and improve survival rates, but its cost-effectiveness in India remains unclear.ObjectiveTo evaluate the cost-effectiveness of LDCT screening for lung cancer compared to chest X-ray (CXR) and no screening in India using a Markov model.MethodsA Markov model simulated the natural progression of lung cancer, comparing LDCT, CXR, and no screening in a high-risk hypothetical population in the age group of 30 to 65 years. The model incorporated transition probabilities, costs, and quality-adjusted life years (QALYs) with data from published literature, cancer registries, and Global Cancer Observatory. Cost-effectiveness was assessed using the incremental cost-effectiveness ratio (ICER) and net monetary benefit (NMB). Sensitivity analyses, including probabilistic sensitivity analysis, threshold analysis, and budget impact, were conducted to evaluate model robustness.ResultsLDCT screening yielded the highest effectiveness (23.71 QALYs), compared to 19.82 for CXR and 13.43 for no screening. Although LDCT incurred the highest cost (₹380064.75), it also provided the highest NMB (₹5232241.18), making it the most cost-effective option. The ICER for LDCT (₹36429.44) remained below the willingness-to-pay threshold, confirming its economic viability. Sensitivity analyses further validated LDCT's robustness across scenarios.ConclusionLDCT is a cost-effective strategy for lung cancer screening in India, offering significant health benefits despite higher costs. Policymakers should consider integrating LDCT into national cancer screening programs, with further research needed to optimise screening intervals and target populations.
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