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About this Publication
Title
Risk Model-Based Lung Cancer Screening : A Cost-Effectiveness Analysis.
Pubmed ID
36745885 (View this publication on the PubMed website)
Digital Object Identifier
Publication
Ann Intern Med. 2023 Feb 7
Authors
Toumazis I, Cao P, de Nijs K, Bastani M, Munshi V, Hemmati M, Ten Haaf K, Jeon J, Tammemägi M, Gazelle GS, Feuer EJ, Kong CY, Meza R, de Koning HJ, Plevritis SK, Han SS
Affiliations
  • Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas (I.T., M.H.).
  • Department of Epidemiology, University of Michigan, Ann Arbor, Michigan (P.C., J.J.).
  • Erasmus MC-University Medical Center, Rotterdam, the Netherlands (K. de N., K. ten H., H.J. de K.).
  • Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York (M.B.).
  • Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts (V.M., G.S.G.).
  • Department of Health Sciences, Brock University, St. Catharines, Ontario, Canada (M.T.).
  • Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland (E.J.F.).
  • Division of General Internal Medicine, Department of Medicine, Mount Sinai Hospital, New York, New York (C.Y.K.).
  • Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, and Department of Integrative Oncology, BC Cancer Research Institute, British Columbia, Canada (R.M.).
  • Department of Biomedical Data Sciences, Stanford University, Stanford, California (S.K.P.).
...show more
  • Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, California (S.S.H.).
Abstract

BACKGROUND: In their 2021 lung cancer screening recommendation update, the U.S. Preventive Services Task Force (USPSTF) evaluated strategies that select people based on their personal lung cancer risk (risk model-based strategies), highlighting the need for further research on the benefits and harms of risk model-based screening.

OBJECTIVE: To evaluate and compare the cost-effectiveness of risk model-based lung cancer screening strategies versus the USPSTF recommendation and to explore optimal risk thresholds.

DESIGN: Comparative modeling analysis.

DATA SOURCES: National Lung Screening Trial; Surveillance, Epidemiology, and End Results program; U.S. Smoking History Generator.

TARGET POPULATION: 1960 U.S. birth cohort.

TIME HORIZON: 45 years.

PERSPECTIVE: U.S. health care sector.

INTERVENTION: Annual low-dose computed tomography in risk model-based strategies that start screening at age 50 or 55 years, stop screening at age 80 years, with 6-year risk thresholds between 0.5% and 2.2% using the PLCOm2012 model.

OUTCOME MEASURES: Incremental cost-effectiveness ratio (ICER) and cost-effectiveness efficiency frontier connecting strategies with the highest health benefit at a given cost.

RESULTS OF BASE-CASE ANALYSIS: Risk model-based screening strategies were more cost-effective than the USPSTF recommendation and exclusively comprised the cost-effectiveness efficiency frontier. Among the strategies on the efficiency frontier, those with a 6-year risk threshold of 1.2% or greater were cost-effective with an ICER less than $100 000 per quality-adjusted life-year (QALY). Specifically, the strategy with a 1.2% risk threshold had an ICER of $94 659 (model range, $72 639 to $156 774), yielding more QALYs for less cost than the USPSTF recommendation, while having a similar level of screening coverage (person ever-screened 21.7% vs. USPSTF's 22.6%).

RESULTS OF SENSITIVITY ANALYSES: Risk model-based strategies were robustly more cost-effective than the 2021 USPSTF recommendation under varying modeling assumptions.

LIMITATION: Risk models were restricted to age, sex, and smoking-related risk predictors.

CONCLUSION: Risk model-based screening is more cost-effective than the USPSTF recommendation, thus warranting further consideration.

PRIMARY FUNDING SOURCE: National Cancer Institute (NCI).

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