Economic impact of using risk models for eligibility selection to the International lung screening Trial

Sonya Cressman; Marianne F Weber; Preston J Ngo; Stephen Wade; Silvia Behar Harpaz; Michael Caruana; Alain Tremblay; Renee Manser; Emily Stone; Sukhinder Atkar-Khattra; Deme Karikios; Cheryl Ho; Aleisha Fernandes; Jing Yi Weng; Annette McWilliams; Renelle Myers; John Mayo; John Yee; Ren Yuan; Henry M Marshall; Kwun M Fong; Stephen Lam; Karen Canfell; Martin C Tammemägi

doi:10.1016/j.lungcan.2022.12.011

Economic impact of using risk models for eligibility selection to the International lung screening Trial

Lung Cancer. 2023 Feb:176:38-45. doi: 10.1016/j.lungcan.2022.12.011. Epub 2022 Dec 22.

Authors

Sonya Cressman¹, Marianne F Weber², Preston J Ngo², Stephen Wade², Silvia Behar Harpaz², Michael Caruana², Alain Tremblay³, Renee Manser⁴, Emily Stone⁵, Sukhinder Atkar-Khattra⁶, Deme Karikios⁷, Cheryl Ho⁸, Aleisha Fernandes⁹, Jing Yi Weng¹⁰, Annette McWilliams¹¹, Renelle Myers¹², John Mayo¹³, John Yee¹³, Ren Yuan⁸, Henry M Marshall¹⁴, Kwun M Fong¹⁴, Stephen Lam¹², Karen Canfell², Martin C Tammemägi¹⁵

Affiliations

¹ Faculty of Health Sciences, Simon Fraser University, Burnaby, British Columbia, Canada; The Centre for Clinical Epidemiology and Evaluation, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, Canada. Electronic address: [email protected].
² The Daffodil Centre, The University of Sydney, a joint venture with Cancer Council NSW, Sydney 2011, Australia.
³ Division of Respiratory Medicine and Arnie Charbonneau Cancer Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
⁴ Department of Respiratory and Sleep Medicine, Royal Melbourne Hospital, Parksville, Victoria, 3050, Australia; Department of Internal Medicine, Peter MacCallum Cancer Centre, Melbourne, Victoria 3000, Australia; University of Melbourne, Department of. Medicine, Royal Melbourne Hospital, Parksville, Victoria, 3010, Australia.
⁵ Department of Thoracic Medicine and Lung Transplantation, St Vincent Hospital, Sydney, Australia; School of Clinical Medicine; School of Public Health, University of Sydney, Australia.
⁶ BC Cancer Research Institute, Vancouver, BC, Canada.
⁷ Nepean Clinical School, The University of Sydney, NSW 2747, Australia.
⁸ BC Cancer, Vancouver, British Columbia, Australia; Faculty of Medicine, University of British Columbia, Vancouver, British Columbia.
⁹ Faculty of Health Sciences, Simon Fraser University, Burnaby, British Columbia, Canada; Department of Public Health Sciences, Queen's University, Kingston, Ontario, Canada.
¹⁰ Department of Primary Care and Population Health, University College London, London, United Kingdom.
¹¹ Department of Respiratory Medicine, Fiona Stanley Hospital, Murdoch, WA, Australia.
¹² BC Cancer Research Institute, Vancouver, BC, Canada; BC Cancer, Vancouver, British Columbia, Australia; Faculty of Medicine, University of British Columbia, Vancouver, British Columbia.
¹³ Faculty of Medicine, University of British Columbia, Vancouver, British Columbia.
¹⁴ The Prince Charles Hospital and University of Queensland Thoracic Research Centre, Brisbane, QLD, Australia.
¹⁵ Brock University, St. Catharines, Ontario, Canada.

PMID: 36592498
DOI: 10.1016/j.lungcan.2022.12.011

Abstract

Objectives: Using risk models as eligibility criteria for lung screening can reduce race and sex-based disparities. We used data from the International Lung Screening Trial(ILST; NCT02871856) to compare the economic impact of using the PLCOm2012 risk model or the US Preventative Services' categorical age-smoking history-based criteria (USPSTF-2013).

Materials and methods: The cost-effectiveness of using PLCOm2012 versus USPSTF-2013 was evaluated with a decision analytic model based on the ILST and other screening trials. The primary outcomes were costs in 2020 International Dollars ($), quality-adjusted life-years (QALY) and incremental net benefit (INB, in $ per QALY). Secondary outcomes were selection characteristics and cancer detection rates (CDR).

Results: Compared with the USPSTF-2013 criteria, the PLCOm2012 risk model resulted in $355 of cost savings per 0.2 QALYs gained (INB=$4294 at a willingness-to-pay threshold of $20 000/QALY (95 %CI: $4205-$4383). Using the risk model was more cost-effective in females at both a 1.5 % and 1.7 % 6-year risk threshold (INB=$6616 and $6112, respectively), compared with males ($5221 and $695). The PLCOm2012 model selected more females, more individuals with fewer years of formal education, and more people with other respiratory illnesses in the ILST. The CDR with the risk model was higher in females compared with the USPSTF-2013 criteria (Risk Ratio = 7.67, 95 % CI: 1.87-31.38).

Conclusion: The PLCOm2012 model saved costs, increased QALYs and mitigated socioeconomic and sex-based disparities in access to screening.

Keywords: Cost-effectiveness; Economic impact; Eligibility criteria; Equity impact; Health equity; Lung cancer screening; Lung screening; PLCOm2012; Risk model; Screening selection; USPSTF2013.

Publication types

Clinical Trial
Research Support, Non-U.S. Gov't

MeSH terms

Cost-Benefit Analysis
Early Detection of Cancer / methods
Eligibility Determination
Female
Humans
Lung
Lung Neoplasms* / diagnosis
Lung Neoplasms* / epidemiology
Male
Mass Screening / methods
Quality-Adjusted Life Years

Associated data

ClinicalTrials.gov/NCT02871856