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Cost-Effectiveness of Screening in the National Lung Screening Trial

This study evaluates the cost-effectiveness of lung cancer screening methods - LDCT, CXR, and no screening - in the National Lung Screening Trial. It compares outcomes in terms of life-years and quality-adjusted life-years, incorporating costs and societal perspective. Direct medical costs, non-medical expenses, and opportunity costs are assessed to determine the Incremental Cost-Effectiveness Ratio (ICER) and inform decision-making. Sensitivity analyses address uncertainty in the findings to enhance the study's robustness.

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Cost-Effectiveness of Screening in the National Lung Screening Trial

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  1. Cost-Effectiveness of Screening in the National Lung Screening Trial William C. Black, MD Dartmouth-Hitchcock Medical Center

  2. Working Group

  3. NLST CEA • Comparison: LDCT vs CXR vs None • Effectiveness: LYs and QALYs • Costs: $US (reference 2009) • Perspective: Societal • Time horizon: Within-trial and lifetime • Discount rate: 3% .

  4. Effectiveness • Aggregate LYs from entry to death • Observed survival before 2009 • Projected survival after 2009 • age, sex, lung ca stage, smoking

  5. Effectiveness (cont) • Adjust LYs for QOL (0-1.0) • SF-6D utility scoring • Estimate missing scores • age, sex, scr, lung ca Brazier et al. JHE 2002; 21:271-92

  6. Costs • Direct medical (screening, dx, rx) • Non-medical (travel, lodging) • Opportunity (lost wages) • Projected beyond 2009 - age, sex, and lung ca stage

  7. Direct Medical Costs • Utilization based on med abstraction • Estimate/ impute missing utilization • Multiply by Medicare prices

  8. ICER = ∆COSTS ∆QALYS

  9. Baseline Results • LYs, QALYs & Costs • ICERs • Subset analyses • age, sex, smokhx, co-morbidity

  10. Hypothetical Baseline Results

  11. Uncertainty • Sensitivity analysis • Scatter plot of ICE • CE Acceptability curves

  12. Incremental Cost K II IB IA Incremental Effect IIIA IIIB IV Black WC. Med Decis Making 1990;10:212-4

  13. Developed analytic approach using R Completed analysis of “enriched” DHMC subset Developed plan for managing missing data Obtained approval to reuse Medicare data Developed algorithms for projecting survival Selected relevant CPT and DRG codes Accomplishments .

  14. Next Steps • Estimate Medicare payments for DRGs • Extract utilization and QOL from ACRIN dataset • Analyze Medicare data & adjust cost estimates • Impute and/or estimate missing data elements • Analyze completed NLST CEA dataset in R • Write up results and submit .

  15. Use this slide for graphics or images requiring a larger space

  16. Use this slide for text only Keep number of points to six of fewer per slide

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