Development and Validation of Risk Models to Select Ever-Smokers for CT Lung Cancer Screening
- PMID: 27179989
- PMCID: PMC4899131
- DOI: 10.1001/jama.2016.6255
Development and Validation of Risk Models to Select Ever-Smokers for CT Lung Cancer Screening
Abstract
Importance: The US Preventive Services Task Force (USPSTF) recommends computed tomography (CT) lung cancer screening for ever-smokers aged 55 to 80 years who have smoked at least 30 pack-years with no more than 15 years since quitting. However, selecting ever-smokers for screening using individualized lung cancer risk calculations may be more effective and efficient than current USPSTF recommendations.
Objective: Comparison of modeled outcomes from risk-based CT lung-screening strategies vs USPSTF recommendations.
Design, setting, and participants: Empirical risk models for lung cancer incidence and death in the absence of CT screening using data on ever-smokers from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO; 1993-2009) control group. Covariates included age; education; sex; race; smoking intensity, duration, and quit-years; body mass index; family history of lung cancer; and self-reported emphysema. Model validation in the chest radiography groups of the PLCO and the National Lung Screening Trial (NLST; 2002-2009), with additional validation of the death model in the National Health Interview Survey (NHIS; 1997-2001), a representative sample of the United States. Models were applied to US ever-smokers aged 50 to 80 years (NHIS 2010-2012) to estimate outcomes of risk-based selection for CT lung screening, assuming screening for all ever-smokers, yield the percent changes in lung cancer detection and death observed in the NLST.
Exposures: Annual CT lung screening for 3 years beginning at age 50 years.
Main outcomes and measures: For model validity: calibration (number of model-predicted cases divided by number of observed cases [estimated/observed]) and discrimination (area under curve [AUC]). For modeled screening outcomes: estimated number of screen-avertable lung cancer deaths and estimated screening effectiveness (number needed to screen [NNS] to prevent 1 lung cancer death).
Results: Lung cancer incidence and death risk models were well calibrated in PLCO and NLST. The lung cancer death model calibrated and discriminated well for US ever-smokers aged 50 to 80 years (NHIS 1997-2001: estimated/observed = 0.94 [95%CI, 0.84-1.05]; AUC, 0.78 [95%CI, 0.76-0.80]). Under USPSTF recommendations, the models estimated 9.0 million US ever-smokers would qualify for lung cancer screening and 46,488 (95% CI, 43,924-49,053) lung cancer deaths were estimated as screen-avertable over 5 years (estimated NNS, 194 [95% CI, 187-201]). In contrast, risk-based selection screening of the same number of ever-smokers (9.0 million) at highest 5-year lung cancer risk (≥1.9%) was estimated to avert 20% more deaths (55,717 [95% CI, 53,033-58,400]) and was estimated to reduce the estimated NNS by 17% (NNS, 162 [95% CI, 157-166]).
Conclusions and relevance: Among a cohort of US ever-smokers aged 50 to 80 years, application of a risk-based model for CT screening for lung cancer compared with a model based on USPSTF recommendations was estimated to be associated with a greater number of lung cancer deaths prevented over 5 years, along with a lower NNS to prevent 1 lung cancer death.
Figures
Comment in
-
Who Should Be Screened for Lung Cancer? And Who Gets to Decide?JAMA. 2016 Jun 7;315(21):2279-81. doi: 10.1001/jama.2016.5986. JAMA. 2016. PMID: 27179674 No abstract available.
Similar articles
-
Evaluation of the lung cancer risks at which to screen ever- and never-smokers: screening rules applied to the PLCO and NLST cohorts.PLoS Med. 2014 Dec 2;11(12):e1001764. doi: 10.1371/journal.pmed.1001764. eCollection 2014 Dec. PLoS Med. 2014. PMID: 25460915 Free PMC article.
-
Assessing eligibility for lung cancer screening using parsimonious ensemble machine learning models: A development and validation study.PLoS Med. 2023 Oct 3;20(10):e1004287. doi: 10.1371/journal.pmed.1004287. eCollection 2023 Oct. PLoS Med. 2023. PMID: 37788223 Free PMC article.
-
Risk prediction models for selection of lung cancer screening candidates: A retrospective validation study.PLoS Med. 2017 Apr 4;14(4):e1002277. doi: 10.1371/journal.pmed.1002277. eCollection 2017 Apr. PLoS Med. 2017. PMID: 28376113 Free PMC article.
-
Screening for Lung Cancer With Low-Dose Computed Tomography: An Evidence Review for the U.S. Preventive Services Task Force [Internet].Rockville (MD): Agency for Healthcare Research and Quality (US); 2021 Mar. Report No.: 20-05266-EF-1. Rockville (MD): Agency for Healthcare Research and Quality (US); 2021 Mar. Report No.: 20-05266-EF-1. PMID: 33750087 Free Books & Documents. Review.
-
Evaluation of the Benefits and Harms of Lung Cancer Screening With Low-Dose Computed Tomography: A Collaborative Modeling Study for the U.S. Preventive Services Task Force [Internet].Rockville (MD): Agency for Healthcare Research and Quality (US); 2021 Mar. Report No.: 20-05266-EF-2. Rockville (MD): Agency for Healthcare Research and Quality (US); 2021 Mar. Report No.: 20-05266-EF-2. PMID: 33750088 Free Books & Documents. Review.
Cited by
-
Adaptation of a Tailored Lung Cancer Screening Decision Aid for People With HIV.CHEST Pulm. 2024 Sep;2(3):100044. doi: 10.1016/j.chpulm.2024.100044. Epub 2024 Feb 19. CHEST Pulm. 2024. PMID: 39391570 Free PMC article.
-
Lung cancer screening: where do we stand?Breathe (Sheff). 2024 Aug 27;20(2):230190. doi: 10.1183/20734735.0190-2023. eCollection 2024 Jun. Breathe (Sheff). 2024. PMID: 39193459 Free PMC article. Review.
-
Evaluation of risk prediction models to select lung cancer screening participants in Europe: a prospective cohort consortium analysis.Lancet Digit Health. 2024 Sep;6(9):e614-e624. doi: 10.1016/S2589-7500(24)00123-7. Lancet Digit Health. 2024. PMID: 39179310 Free PMC article.
-
Identifying Populations at Risk for Lung Cancer Mortality from the National Health and Nutrition Examination Survey (2001-2018) Using the 2021 USPSTF Screening Guidelines.Int J Environ Res Public Health. 2024 Jun 15;21(6):781. doi: 10.3390/ijerph21060781. Int J Environ Res Public Health. 2024. PMID: 38929027 Free PMC article.
-
How will lung cancer screening and lung nodule management change the diagnostic and surgical lung cancer landscape?Eur Respir Rev. 2024 Jun 26;33(172):230232. doi: 10.1183/16000617.0232-2023. Print 2024 Apr. Eur Respir Rev. 2024. PMID: 38925794 Free PMC article. Review.
References
-
- Moyer VA, Force USPST Screening for lung cancer: U.S. Preventive Services Task Force recommendation statement. Annals of internal medicine. 2014;160(5):330–338. - PubMed
-
- Syrek Jensen T, Chin J, Ashby L, Hermansen J, Hutter JD. [Accessed April 23, 2016];Decision Memo for Screening for Lung Cancer with Low Dose Computed Tomography (LDCT) (CAG-00439N) Centers for Medicare and Medicaid Services. 2015 https://www.cms.gov/medicare-coverage-database/details/nca-decision-memo....
Publication types
MeSH terms
Grants and funding
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical
