Introduction A randomized trial has demonstrated that lung cancer screening reduces mortality. Identifying participant and program characteristics that influence the cost-effectiveness of screening will help translate trial results into benefits at the population level. Methods Six U.S. cohorts (males and females aged 50, 60, or 70) were simulated in an existing patient-level lung cancer model. Smoking histories reflected observed U.S. patterns. We simulated lifetime histories of 500,000 identical individuals per cohort in each scenario. Costs per quality-adjusted life-year gained ($/QALY) were estimated for each program: CT screening; stand-alone smoking cessation therapies (4–30% 1-year abstinence); and combined programs. Results Annual screening of current and former smokers aged 50–74 cost between $126,000–$169,000/QALY (minimum 20 pack-years of smoking) or $110,000–$166,000/QALY (40 pack-year minimum), compared to no screening and assuming background quit rates. Screening was beneficial but had a higher cost per QALY when the model included radiation-induced lung cancers. If screen participation doubled background quit rates, the cost of annual screening (at age 50, 20 pack-year minimum) was below $75,000/QALY. If screen participation halved background quit rates, benefits from screening were nearly erased. If screening had no effect on quit rates, annual screening cost more but provided fewer QALYs than annual cessation therapies. Annual combined screening/cessation therapy programs at age 50 cost $130,500–$159,700/QALY, compared to annual stand-alone cessation. Conclusions The cost-effectiveness of CT screening will likely be strongly linked to achievable smoking cessation rates. Trials and further modeling should explore the consequences of relationships between smoking behaviors and screen participation.

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The significant increase in the detection and treatment of ductal carcinoma in situ (DCIS) since the introduction of screening mammography has not been accompanied by the anticipated reduction in invasive breast cancer (IBC) incidence. The prevalence of DCIS requires a reexamination of the population level effects of detecting and treating DCIS. To further our understanding of the possible impact of DCIS diagnosis and treatment on IBC incidence in the U.S., we simulated breast cancer incidence over 25 years under various assumptions regarding the baseline incidence of IBC and the progression of DCIS to IBC. The simulations demonstrate a tradeoff between the expected increased incidence of IBC absent any DCIS detection and treatment and the rate of progression of DCIS to IBC. Our analyses indicate that a high progression of DCIS to IBC implies a significant increase in incidence of IBC over what is observed had we not detected and treated DCIS. Conversely, if we assume that there would not have been a significant increase over and above the observed incidence evident in SEER, then our model indicates that the rate of DCIS progression to clinically significant IBC is low. Given the tradeoff illustrated by our model, we must reevaluate the assumption that DCIS is a short-term obligate precursor of invasive cancer and instead focus on further exploration of the true natural history of DCIS.

Drop out needs to be reduced to ensure effective treatment.