Cost-Effectiveness Analysis of Lung Cancer Screening in the United States: A Comparative Modeling Study.

Background: Recommendations vary regarding the maximum age at which to stop lung cancer screening: 80 years according to the U.S. Preventive Services Task Force (USPSTF), 77 years according to the Centers for Medicare & Medicaid Services (CMS), and 74 years according to the National Lung Screening Trial (NLST). Objective: To compare the cost-effectiveness of different stopping ages for lung cancer screening. Design: By using shared inputs for smoking behavior, costs, and quality of life, 4 independently developed microsimulation models evaluated the health and cost outcomes of annual lung cancer screening with low-dose computed tomography (LDCT). Data Sources: The NLST; Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial; SEER (Surveillance, Epidemiology, and End Results) program; Nurses' Health Study and Health Professionals Follow-up Study; and U.S. Smoking History Generator. Target Population: Current, former, and never-smokers aged 45 years from the 1960 U.S. birth cohort. Time Horizon: 45 years. Perspective: Health care sector. Intervention: Annual LDCT according to NLST, CMS, and USPSTF criteria. Outcome Measures: Incremental cost-effectiveness ratios (ICERs) with a willingness-to-pay threshold of $100 000 per quality-adjusted life-year (QALY). Results of Base-Case Analysis: The 4 models showed that the NLST, CMS, and USPSTF screening strategies were cost-effective, with ICERs averaging $49 200, $68 600, and $96 700 per QALY, respectively. Increasing the age at which to stop screening resulted in a greater reduction in mortality but also led to higher costs and overdiagnosis rates. Results of Sensitivity Analysis: Probabilistic sensitivity analysis showed that the NLST and CMS strategies had higher probabilities of being cost-effective (98% and 77%, respectively) than the USPSTF strategy (52%). Limitation: Scenarios assumed 100% screening adherence, and models extrapolated beyond clinical trial data. Conclusion: All 3 sets of lung cancer screening criteria represent cost-effective programs. Despite underlying uncertainty, the NLST and CMS screening strategies have high probabilities of being cost-effective. Primary Funding Source: CISNET (Cancer Intervention and Surveillance Modeling Network) Lung Group, National Cancer Institute.

Population impact of lung cancer screening in the United States: Projections from a microsimulation model.

BACKGROUND: Previous simulation studies estimating the impacts of lung cancer screening have ignored the changes in smoking prevalence over time in the United States. Our primary rationale was to perform, to our knowledge, the first simulation study that estimates the health outcomes of lung cancer screening with explicit modeling of smoking trends for the whole US population. METHODS/FINDINGS: Utilizing a well-validated microsimulation model, we estimated the benefits and harms of an annual low-dose computed tomography screening scenario with a realistic screening adherence rate versus a no-screening scenario for the US population from 2016-2030. The Centers for Medicare and Medicaid Services (CMS) eligibility criteria were applied: age 55-77 years at time of screening, history of at least 30 pack-years of smoking, and current smoker or former smoker with fewer than 15 years since quitting. In the screened population, cumulative mortality reduction was projected to reach 16.98% (95% CI 16.90%-17.07%). Cumulative mortality reduction was estimated to be 3.52% (95% CI 3.50%-3.53%) for the overall study population, with annual mortality reduction peaking at 4.38% (95% CI 4.36%-4.41%) in 2021 and falling to 3.53% (95% CI 3.50%-3.56%) by 2030. Lung cancer screening would save a projected 148,484 life-years (95% CI 147,429-149,540) across the total population through 2030. There were estimated to be 9,054 (95% CI 9,011-9,098) overdiagnosed cases among the 252,429 (95% CI 251,208-253,649) screen-detected lung cancer diagnoses, yielding an overdiagnosis rate of 3.59%. The limitations of our study are that we do not explicitly model race or socioeconomic status and our model was calibrated to data from studies performed in academic centers, both of which may impact the generalizability of our results. We also exclusively model the effects of the CMS guidelines for lung cancer screening and not any other screening strategies. CONCLUSIONS: The mortality reduction and life-years gained estimated by this study are lower than those of single birth cohort studies. Single cohort studies neglect the changing dynamics of smoking behavior across generations, whereas this study reflects the trend of decreasing smoking prevalence since the 1960s. Maximum benefit could be derived from lung cancer screening through 2021; in later years, mortality reduction due to screening will decline. If a comprehensive screening program is not implemented in the near future, the opportunity to achieve these benefits will have passed.

The Impact of a Prior Diagnosis of Barrett's Esophagus on Esophageal Adenocarcinoma Survival.

OBJECTIVES: Endoscopic surveillance of patients with Barrett's Esophagus (BE) is recommended to detect esophageal adenocarcinoma (EAC) and its dysplasia precursors, but survival benefits are unclear. Using Surveillance, Epidemiology, and End Results (SEER) and linked Medicare data, we sought to determine the impact of a prior BE diagnosis on survival in patients with EAC. METHODS: Our analysis focused on patients over age 65 with primary EAC diagnosed in a SEER region from 2000-2011 and enrolled in Medicare. We identified patients with preexisting BE prior to EAC diagnosis and compared this group to EAC patients without a prior BE diagnosis. A Cox Proportional Hazards model compared survival and included variables such as age, sex, cancer stage, treatment, and medical comorbidities. RESULTS: Among 4,978 SEER-Medicare patients identified with EAC, 577 (12%) had preexisting BE; 4,401 (88%) did not. BE patients had overall lower stage (28.5% stage I vs. 12.8% stage IV) than those without preexisting BE (16.4% stage I vs. 30.6% stage IV). Overall survival was better among patients in the BE group (hazard ratio (HR), 0.56; 95% confidence interval (CI), 0.50-0.61); this benefit persisted in the adjusted model (HR, 0.72; 95%, 0.65-0.80). After adjusting for lead-time bias, the HRs attenuated to the null, with an unadjusted HR of 0.96 (95% CI: 0.86-1.05, P=0.39) and adjusted HR of 0.99 (CI: 0.89-1.10, P=0.92). CONCLUSIONS: Survival outcomes in patients with a BE diagnosis prior to EAC were statistically better in both the unadjusted and adjusted Cox proportional hazards model. However, this benefit appears to be predominantly lead-time and length-time bias.

Disparities and Trends in Genetic Testing and Erlotinib Treatment among Metastatic Non-Small Cell Lung Cancer Patients.

BACKGROUND: Despite reports of socioeconomic disparities in rates of genetic testing and targeted therapy treatment for metastatic non-small cell lung cancer (NSCLC), little is known about whether such disparities are changing over time. METHODS: We performed a retrospective analysis to identify disparities and trends in genetic testing and treatment with erlotinib. Using the Surveillance, Epidemiology, and End Results (SEER)-Medicare database, we identified 9,900 patients with stage IV NSCLC diagnosed in 2007 to 2011 at age 65 or older. We performed logistic regression analyses to identify patient factors associated with odds of receiving a genetic test and erlotinib treatment, and to assess trends in these differences with respect to diagnosis year. RESULTS: Patients were more likely to receive genetic testing if they were under age 75 at diagnosis [odds ratio (OR), 1.55] independent of comorbidity level, and this age-based gap showed a decrease over time (OR, 0.93). For untested patients, erlotinib treatment was associated with race (OR, 0.58, black vs. white; OR, 2.45, Asian vs. white), and was more likely among female patients (OR, 1.45); for tested patients, erlotinib treatment was less likely among low-income patients (OR, 0.32). Most of these associations persisted or increased in magnitude. CONCLUSIONS: Race and sex are associated with rates of erlotinib treatment for patients who did not receive genetic testing, and low-income status is associated with treatment rates for those who did receive testing. The racial disparity remained stable over time, while the income-based disparity grew larger. IMPACT: Attention to reducing disparities is needed as precision cancer treatments continue to be developed.

A simulation study of the effect of lung cancer screening in China, Japan, Singapore, and South Korea.

More than 50% of the world's lung cancer cases occur in Asia and more than 20% of cancer deaths in Asia are attributable to lung cancer. The U.S. National Lung Screening Trial has shown that lung cancer screening with computed tomography (CT) can reduce lung cancer deaths. Using the Lung Cancer Policy Model-Asia (LCPM-Asia), we estimated the potential mortality reduction achievable through the implementation of CT-based lung cancer screening in China, Japan, Singapore, and South Korea. The LCPM-Asia was calibrated to the smoking prevalence of each of the aforementioned countries based on published national surveys and to lung cancer mortality rates from the World Health Organization. The calibrated LCPM-Asia was then used to simulate lung cancer deaths under screening and no-screening scenarios for the four countries. Using screening eligibility criteria recommended by the U.S. Centers for Medicare & Medicaid Services (CMS), which are based on age and smoking history, we estimated the lung cancer mortality reduction from screening through year 2040. By 2040, lung cancer screening would result in 91,362 life-years gained and 4.74% mortality reduction in South Korea; 290,325 life-years gained and 4.33% mortality reduction in Japan; 3,014,215 life-years gained and 4.22% mortality reduction in China; and 8,118 life-years gained and 3.76% mortality reduction in Singapore. As for mortality reduction by smoker type, current smokers would have the greatest mortality reduction in each country, ranging from 5.56% in Japan to 6.86% in Singapore. Among the four countries, lung cancer screening under CMS eligibility criteria was most effective in South Korea and least effective in Singapore. Singapore's low smoking prevalence and South Korea's aging population and higher smoking prevalence may partially explain the discrepancy in effectiveness. CT screening was shown to be promising as a means of reducing lung cancer mortality in the four countries.

Effect of PD-L1 testing on the cost-effectiveness and budget impact of pembrolizumab for advanced urothelial carcinoma of the bladder in the United States.

PURPOSE: Our purpose was to evaluate the effect of PD-L1 testing on the cost-effectiveness of pembrolizumab for second-line treatment of advanced urothelial carcinoma in the bladder from the U.S. societal perspective. MATERIALS AND METHODS: We developed a microsimulation model to compare 3 treatment strategies: (1) treat all patients with standard-of-care chemotherapy, (2) treat all patients with pembrolizumab, and (3) treat patients with PD-L1-positive tumors at a ≥1% expression threshold with pembrolizumab, and all others with standard-of-care chemotherapy. Additionally, we performed a budget impact analysis based on the projected number of urothelial carcinoma patients eligible for second-line pembrolizumab treatment. RESULTS: Treating all patients with chemotherapy resulted in a mean cost of $17,232 and mean effect of 0.43 quality-adjusted life-years. The PD-L1 test strategy was the most efficient strategy, with an incremental cost-effectiveness ratio of $122,933/quality-adjusted life-year. Treating all patients with pembrolizumab resulted in an incremental cost-effectiveness ratio of $197,383/quality-adjusted life-year compared to the PD-L1 test strategy. The PD-L1 test strategy would produce an incremental budget impact of $14.9 million in the first year of use compared to chemotherapy, increasing to $16.5 million in the fifth year of use. Treating all patients with pembrolizumab would produce an incremental budget impact of $19.6 million compared to the PD-L1 test strategy in its first year of use, increasing to $20.9 million by year 5. CONCLUSIONS: Pembrolizumab was not cost-effective in either strategy based on a $100,000/quality-adjusted life-year willingness-to-pay threshold. Using PD-L1 testing to select for patients who may have better associated outcomes may improve the affordability of pembrolizumab.

Pancreatic cancer treatment costs, including patient liability, by phase of care and treatment modality, 2000-2013.

OBJECTIVES: Our study provides phase-specific cost estimates for pancreatic cancer based on stage and treatment. We compare treatment costs between the different phases and within the stage and treatment modality subgroups. METHODS: Our cohort included 20,917 pancreatic cancer patients from the Surveillance, Epidemiology, and End Results (SEER)-Medicare database diagnosed between 2000 and 2011. We allocated costs into four phases of care-staging (or surgery), initial, continuing, and terminal- and calculated the total, cancer-attributable, and patient-liability costs in 2018 US dollars. We fit linear regression models using log transformation to determine whether costs were predicted by age and calendar year. RESULTS: Monthly cost estimates were high during the staging and surgery phases, decreased over the initial and continuing phases, and increased during the three-month terminal phase. Overall, the linear regression models showed that cancer-attributable costs either remained stable or increased by year, and either were unaffected by age or decreased with older age; continuing phase costs for stage II patients increased with age. CONCLUSIONS: Our estimates demonstrate that pancreatic cancer costs can vary widely by stage and treatment received. These cost estimates can serve as an important baseline foundation to guide resource allocation for cancer care and research in the future.

Cost-effectiveness and Budgetary Consequence Analysis of Durvalumab Consolidation Therapy vs No Consolidation Therapy After Chemoradiotherapy in Stage III Non-Small Cell Lung Cancer in the Context of the US Health Care System.

Importance: In early 2018, durvalumab became the first immunotherapy to be approved for adjuvant treatment of patients with unresectable stage III non-small cell lung cancer (NSCLC) whose cancer has not progressed after definitive chemoradiotherapy. However, the cost-effectiveness and potential economic implications of using this high-priced therapy in this indication are unknown to date. Objective: To explore the cost-effectiveness and potential budgetary consequences of durvalumab consolidation therapy vs no consolidation therapy after chemoradiotherapy in stage III NSCLC in the context of the US health care system. Design, Setting, and Participants: A decision analytic microsimulation model was developed in an academic medical setting to compare the following 2 postchemoradiotherapy strategies: all patients receive no consolidation therapy until progression vs all patients receive durvalumab consolidation therapy until progression or for a maximum of 1 year. The potential budgetary consequence was calculated by applying the proportion of patients with NSCLC who were diagnosed in stage III and received chemoradiotherapy to the projected number of annual new cases for 2018 to 2022 to find total eligible patients and then multiplied by the mean difference in annual cost between the strategies over this 5-year period. Simulated conditions were matched to those of the PACIFIC phase 3 randomized clinical trial and reasonable treatment strategies for metastatic NSCLC. All simulated patients begin disease free after having received radical treatment with chemoradiotherapy and are followed up as they progress to metastatic disease first-line treatment, metastatic disease second-line treatment, end-stage progressive disease, and death. Main Outcomes and Measures: The main outcome of this study was the incremental cost-effectiveness ratio of durvalumab consolidation therapy vs no consolidation therapy, given as aggregate cost of treatment per quality-adjusted life-year gained. Results: Among 2 million simulated patients, durvalumab consolidation therapy was cost-effective compared with no consolidation therapy at a $100 000 per quality-adjusted life-year willingness-to-pay threshold, with an estimated incremental cost-effectiveness ratio of $67 421 per quality-adjusted life-year, and would contribute an additional $768 million to national cancer spending in year 1. The annual budgetary consequence would then decrease to $241 million in year 5. Conclusions and Relevance: Durvalumab consolidation therapy represents an indication where expensive immunotherapies can be cost-effective. Treating with immunotherapy earlier in the course of cancer progression can provide significant value, despite having a substantial budgetary consequence.

Lung cancer costs by treatment strategy and phase of care among patients enrolled in Medicare.

BACKGROUND: We studied trends in lung cancer treatment cost over time by phase of care, treatment strategy, age, stage at diagnosis, and histology. METHODS: Using the Surveillance, Epidemiology, and End Results (SEER)-Medicare database for years 1998-2013, we allocated total and patient-liability costs into the following phases of care for 145 988 lung cancer patients: prediagnosis, staging, surgery, initial, continuing, and terminal. Patients served as self-controls to determine cancer-attributable costs based on individual precancer diagnosis healthcare costs. We fit linear regression models to determine cost by age and calendar year for each stage at diagnosis, histology, and treatment strategy and presented all costs in 2017 US dollars. RESULTS: Monthly healthcare costs prior to lung cancer diagnosis were $861 for a 70 years old in 2017 and rose by an average of $17 per year (P < 0.001). Surgery in 2017 cost $30 096, decreasing by $257 per year (P = 0.007). Chemotherapy and radiation costs remained stable or increased for most stage and histology groups, ranging from $4242 to $8287 per month during the initial six months of care. Costs during the final six months of life decreased for those who died of lung cancer or other causes. CONCLUSIONS: Cost-effectiveness analyses of lung cancer control interventions in the United States have been using outdated and incomplete treatment cost estimates. Our cost estimates enable updated cost-effectiveness analyses to determine the benefit of lung cancer control from a health economics point of view.

Benefits and harms of lung cancer screening in HIV-infected individuals with CD4+ cell count at least 500 cells/µl.

OBJECTIVE: Lung cancer is the leading cause of non-AIDS-defining cancer deaths among HIV-infected individuals. Although lung cancer screening with low-dose computed tomography (LDCT) is endorsed by multiple national organizations, whether HIV-infected individuals would have similar benefit as uninfected individuals from lung cancer screening is unknown. Our objective was to determine the benefits and harms of lung cancer screening among HIV-infected individuals. DESIGN: We modified an existing simulation model, the Lung Cancer Policy Model, for HIV-infected patients. DATA SOURCES: Veterans Aging Cohort Study, Kaiser Permanente Northern California HIV Cohort, and medical literature. TARGET POPULATION: HIV-infected current and former smokers. TIME HORIZON: Lifetime. PERSPECTIVE: Population. INTERVENTION: Annual LDCT screening from ages 45, 50, or 55 until ages 72 or 77 years. MAIN OUTCOME MEASURES: Benefits assessed included lung cancer mortality reduction and life-years gained; harms assessed included numbers of LDCT examinations, false-positive results, and overdiagnosed cases. RESULTS OF BASE-CASE ANALYSIS: For HIV-infected patients with CD4 cell count at least 500 cells/µl and 100% antiretroviral therapy adherence, screening using the Centers for Medicare & Medicaid Services criteria (age 55-77, 30 pack-years of smoking, current smoker or quit within 15 years of screening) would reduce lung cancer mortality by 18.9%, similar to the mortality reduction of uninfected individuals. Alternative screening strategies utilizing lower screening age and/or pack-years criteria increase mortality reduction, but require more LDCT examinations. LIMITATIONS: Strategies assumed 100% screening adherence. CONCLUSION: Lung cancer screening reduces mortality in HIV-infected patients with CD4 cell count at least 500 cells/µl, with a number of efficient strategies for eligibility, including the current Centers for Medicare & Medicaid Services criteria.

Evaluating lung cancer screening in China: Implications for eligibility criteria design from a microsimulation modeling approach.

More than half of males in China are current smokers and evidence from western countries tells us that an unprecedented number of smoking-attributable deaths will occur as the Chinese population ages. We used the China Lung Cancer Policy Model (LCPM) to simulate effects of computed tomography (CT)-based lung cancer screening in China, comparing the impact of a screening guideline published in 2015 by a Chinese expert group to a version developed for the United States by the U.S. Centers for Medicare & Medicaid Services (CMS). The China LCPM, built using an existing lung cancer microsimulation model, can project population outcomes associated with interventions for smoking-related diseases. After calibrating the model to published Chinese smoking prevalence and lung cancer mortality rates, we simulated screening from 2016 to 2050 based on eligibility criteria from the CMS and Chinese guidelines, which differ by age to begin and end screening, pack-years smoked, and years since quitting. Outcomes included number of screens, mortality reduction, and life-years saved for each strategy. We projected that in the absence of screening, 14.98 million lung cancer deaths would occur between 2016 and 2050. Screening with the CMS guideline would prevent 0.72 million deaths and 5.8 million life-years lost, resulting in 6.58% and 1.97% mortality reduction in males and females, respectively. Screening with the Chinese guideline would prevent 0.74 million deaths and 6.6 million life-years lost, resulting in 6.30% and 2.79% mortality reduction in males and females, respectively. Through 2050, 1.43 billion screens would be required using the Chinese screening strategy, compared to 988 million screens using the CMS guideline. In conclusion, CT-based lung cancer screening implemented in 2016 and based on the Chinese screening guideline would prevent about 20,000 (2.9%) more lung cancer deaths through 2050, but would require about 445 million (44.7%) more screens than the CMS guideline.

Combined Biomarker and Computed Tomography Screening Strategies for Lung Cancer: Projections of Health and Economic Tradeoffs in the US Population.

BACKGROUND: Lung cancer screening with computed tomography (CT) of individuals who meet certain age and smoking history criteria is the current standard-of-care. METHODS: Using a published simulation model, we compared outcomes associated with seven biomarker+CT screening strategies to CT screening alone using CMS eligibility criteria. We assumed that the biomarker: had conditionally independent performance; was used for first-line screening in some, or all, individuals screened; and could be extended to CMS-ineligible smokers. Strategies differed by inclusion criteria (e.g. pack-years) and proportion of individuals for whom CT remained the first-line test. Each model run simulated a combined cohort of one million men and one million women born in 1950. Primary outcomes were cancer-specific mortality reduction and screening costs; biomarker costs were measured relative to CT. Efficiency frontiers identified optimal health and economic trade-offs. Sensitivity analysis evaluated the stability of results. RESULTS: Standard-of-care screening yielded an 8.3% cancer-specific mortality reduction in the simulated U.S. population (screened+unscreened individuals). For a biomarker test with 75% sensitivity and 95% specificity, mortality reductions across biomarker+CT strategies ranged from 7.0% to 23.9%. If the biomarker's cost was >0.86× that of CT, standard-of-care screening remained on the efficiency frontier, indicating that health and economic trade-offs were equally (or more) efficient relative to all biomarker+CT strategies. Biomarker+CT strategy costs were principally driven by biomarker specificity; mortality reduction was driven by sensitivity. CONCLUSION: Combined biomarker+CT strategies have the potential to improve future lung cancer screening effectiveness in the U.S. and achieve economic efficiency that is greater than the current standard-of-care.

Evaluating the impacts of screening and smoking cessation programmes on lung cancer in a high-burden region of the USA: a simulation modelling study.

OBJECTIVE: While the US Preventive Services Task Force has issued recommendations for lung cancer screening, its effectiveness at reducing lung cancer burden may vary at local levels due to regional variations in smoking behaviour. Our objective was to use an existing model to determine the impacts of lung cancer screening alone or in addition to increased smoking cessation in a US region with a relatively high smoking prevalence and lung cancer incidence. SETTING: Computer-based simulation model. PARTICIPANTS: Simulated population of individuals 55 and older based on smoking prevalence and census data from Northeast Pennsylvania. INTERVENTIONS: Hypothetical lung cancer control from 2014 to 2050 through (1) screening with CT, (2) intensified smoking cessation or (3) a combination strategy. PRIMARY AND SECONDARY OUTCOME MEASURES: Primary outcomes were lung cancer mortality rates. Secondary outcomes included number of people eligible for screening and number of radiation-induced lung cancers. RESULTS: Combining lung cancer screening with increased smoking cessation would yield an estimated 8.1% reduction in cumulative lung cancer mortality by 2050. Our model estimated that the number of screening-eligible individuals would progressively decrease over time, indicating declining benefit of a screening-only programme. Lung cancer screening achieved a greater mortality reduction in earlier years, but was later surpassed by smoking cessation. CONCLUSIONS: Combining smoking cessation programmes with lung cancer screening would provide the most benefit to a population, especially considering the growing proportion of patients ineligible for screening based on current recommendations.