Literature DB >> 31683314

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

Steven D Criss1, Pianpian Cao2, Mehrad Bastani3, Kevin Ten Haaf4, Yufan Chen1, Deirdre F Sheehan5, Erik F Blom4, Iakovos Toumazis3, Jihyoun Jeon2, Harry J de Koning4, Sylvia K Plevritis3, Rafael Meza2, Chung Yin Kong6.   

Abstract

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.

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Year:  2019        PMID: 31683314     DOI: 10.7326/M19-0322

Source DB:  PubMed          Journal:  Ann Intern Med        ISSN: 0003-4819            Impact factor:   25.391


  24 in total

1.  Potential Impact of Cessation Interventions at the Point of Lung Cancer Screening on Lung Cancer and Overall Mortality in the United States.

Authors:  Pianpian Cao; Jihyoun Jeon; David T Levy; Jinani C Jayasekera; Christopher J Cadham; Jeanne S Mandelblatt; Kathryn L Taylor; Rafael Meza
Journal:  J Thorac Oncol       Date:  2020-03-08       Impact factor: 15.609

Review 2.  Lung cancer LDCT screening and mortality reduction - evidence, pitfalls and future perspectives.

Authors:  Matthijs Oudkerk; ShiYuan Liu; Marjolein A Heuvelmans; Joan E Walter; John K Field
Journal:  Nat Rev Clin Oncol       Date:  2020-10-12       Impact factor: 66.675

3.  A History of Health Economics and Healthcare Delivery Research at the National Cancer Institute.

Authors:  V Paul Doria-Rose; Nancy Breen; Martin L Brown; Eric J Feuer; Ann M Geiger; Larry Kessler; Joseph Lipscomb; Joan L Warren; K Robin Yabroff
Journal:  J Natl Cancer Inst Monogr       Date:  2022-07-05

4.  Evaluation of benefits and harms of adaptive screening schedules for lung cancer: A microsimulation study.

Authors:  Pianpian Cao; Jihyoun Jeon; Rafael Meza
Journal:  J Med Screen       Date:  2022-08-22       Impact factor: 1.687

5.  Optimizing the use of adjuvant chemotherapy in non-small cell lung cancer patients with comorbidities.

Authors:  Stacyann Bailey; Qian Wang; Chung Yin Kong; Kimberly Stone; Rajwanth Veluswamy; Susan E Bates; Cardinale B Smith; Juan P Wisnivesky; Keith Sigel
Journal:  Curr Probl Cancer       Date:  2022-05-21       Impact factor: 2.367

6.  Cost-Effectiveness Analyses of Lung Cancer Screening Using Low-Dose Computed Tomography: A Systematic Review Assessing Strategy Comparison and Risk Stratification.

Authors:  Matthew Fabbro; Kirah Hahn; Olivia Novaes; Mícheál Ó'Grálaigh; James F O'Mahony
Journal:  Pharmacoecon Open       Date:  2022-08-30

7.  Factors Influencing the False Positive Rate in CT Lung Cancer Screening.

Authors:  Mark M Hammer; Suzanne C Byrne; Chung Yin Kong
Journal:  Acad Radiol       Date:  2020-09-03       Impact factor: 5.482

8.  Cost-effectiveness Evaluation of the 2021 US Preventive Services Task Force Recommendation for Lung Cancer Screening.

Authors:  Iakovos Toumazis; Koen de Nijs; Pianpian Cao; Mehrad Bastani; Vidit Munshi; Kevin Ten Haaf; Jihyoun Jeon; G Scott Gazelle; Eric J Feuer; Harry J de Koning; Rafael Meza; Chung Yin Kong; Summer S Han; Sylvia K Plevritis
Journal:  JAMA Oncol       Date:  2021-12-01       Impact factor: 33.006

9.  Impact of Joint Lung Cancer Screening and Cessation Interventions Under the New Recommendations of the U.S. Preventive Services Task Force.

Authors:  Rafael Meza; Pianpian Cao; Jihyoun Jeon; Kathryn L Taylor; Jeanne S Mandelblatt; Eric J Feuer; Douglas R Lowy
Journal:  J Thorac Oncol       Date:  2021-10-12       Impact factor: 20.121

10.  Cost-Effectiveness of Smoking Cessation Interventions in the Lung Cancer Screening Setting: A Simulation Study.

Authors:  Christopher J Cadham; Pianpian Cao; Jinani Jayasekera; Kathryn L Taylor; David T Levy; Jihyoun Jeon; Elena B Elkin; Kristie L Foley; Anne Joseph; Chung Yin Kong; Jennifer A Minnix; Nancy A Rigotti; Benjamin A Toll; Steven B Zeliadt; Rafael Meza; Jeanne Mandelblatt
Journal:  J Natl Cancer Inst       Date:  2021-08-02       Impact factor: 11.816

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