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Cost-effectiveness of lung MRI in lung cancer screening

  • Magnetic Resonance
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European Radiology Aims and scope Submit manuscript

Abstract

Objectives

Recent studies with lung MRI (MRI) have shown high sensitivity (Sn) and specificity (Sp) for lung nodule detection and characterization relative to low-dose CT (LDCT). Using this background data, we sought to compare the potential screening performance of MRI vs. LDCT using a Markov model of lung cancer screening.

Methods

We created a Markov cohort model of lung cancer screening which incorporated lung cancer incidence, progression, and mortality based on gender, age, and smoking burden. Sensitivity (Sn) and Sp for LDCT were taken from the MISCAN Lung Microsimulation and Sn/Sp for MRI was estimated from a published substudy of the German Lung Cancer Screening and Intervention Trial. Screening, work-up, and treatment costs were estimated from published data. Screening with MRI and LDCT was simulated for a cohort of male and female smokers (2 packs per day; 36 pack/years of smoking history) starting at age 60. We calculated the screening performance and cost-effectiveness of MRI screening and performed a sensitivity analysis on MRI Sn/Sp and cost.

Results

There was no difference in life expectancy between MRI and LDCT screening (males 13.28 vs. 13.29 life-years; females 14.22 vs. 14.22 life-years). MRI had a favorable cost-effectiveness ratio of $258,169 in men and $403,888 in women driven by fewer false-positive screens. On sensitivity analysis, MRI remained cost effective at screening costs < $396 dollars and Sp > 81%.

Conclusions

In this Markov model of lung cancer screening, MRI has a near-equivalent life expectancy benefit and has superior cost-effectiveness relative to LDCT.

Key Points

In this Markov model of lung cancer screening, there is no difference in mortality between yearly screening with MRI and low-dose CT.

Compared to low-dose CT, screening with MRI led to a reduction in false-positive studies from 26 to 2.8% in men and 26 to 2.6% in women.

Due to similar life-expectancy and reduced false-positive rate, we found a favorable cost-effectiveness ratio of $258,169 in men and $403,888 in women of MRI relative to low-dose CT.

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Abbreviations

LDCT:

Low-dose computed tomography for lung cancer screening

LUSI :

German Lung Cancer Screening Trial

MISCAN:

Microsimulation screening analysis lung simulation

MRI:

Lung magnetic resonance imaging for lung cancer screening

NLST:

National Lung Cancer Screening Trial

PLCO:

Prostate, lung, colon, and ovarian cancer screening trial

SEER:

Surveillance, epidemiology, and end result

Sn:

Sensitivity

Sp:

Specificity

References

  1. Aberle DR, Adams AM, Berg CD et al (2011) Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med 365:395–409

    Article  Google Scholar 

  2. Tanoue LT, Tanner NT, Gould MK, Silvestri GA (2015) Lung cancer screening. Am J Respir Crit Care Med 191:19–33

    Article  Google Scholar 

  3. Bach PB, Mirkin JN, Oliver TK et al (2012) Benefits and harms of CT screening for lung cancer: a systematic review. JAMA 307:2418–2429

    Article  CAS  Google Scholar 

  4. Croswell JM, Baker SG, Marcus PM, Clapp JD, Kramer BS (2010) Cumulative incidence of false-positive test results in lung cancer screening: a randomized trial. Ann Intern Med 152(505-512):W176–W580

    Google Scholar 

  5. Pinsky PF (2014) Assessing the benefits and harms of low-dose computed tomography screening for lung cancer. Lung Cancer Manag 3:491–498

    Article  Google Scholar 

  6. Biederer J, Ohno Y, Hatabu H et al (2017) Screening for lung cancer: does MRI have a role? Eur J Radiol 86:353–360

    Article  Google Scholar 

  7. Meier-Schroers M, Homsi R, Skowasch D et al (2018) Lung cancer screening with MRI: results of the first screening round. J Cancer Res Clin Oncol 144:117–125

    Article  Google Scholar 

  8. Sommer G, Tremper J, Koenigkam-Santos M et al (2014) Lung nodule detection in a high-risk population: comparison of magnetic resonance imaging and low-dose computed tomography. Eur J Radiol 83:600–605

    Article  Google Scholar 

  9. Sonnenberg FA, Beck JR (1993) Markov models in medical decision making. Med Decis Making 13:322–338

    Article  CAS  Google Scholar 

  10. Meza R, Hazelton WD, Colditz GA, Moolgavkar SH (2008) Analysis of lung cancer incidence in the Nurses’ Health and the Health Professionals’ Follow-Up Studies using a multistage carcinogenesis model. Cancer Causes Control 19:317–328

    Article  Google Scholar 

  11. Ten Haaf K, van Rosmalen J, de Koning HJ (2015) Lung cancer detectability by test, histology, stage, and gender: estimates from the NLST and the PLCO trials. Cancer Epidemiol Biomarkers Prev 24:154–161

    Article  Google Scholar 

  12. Rosenberg MA, Feuer EJ, Yu B et al (2012) Chapter 3: Cohort life tables by smoking status, removing lung cancer as a cause of death. Risk Anal 32(Suppl 1):S25–S38

    Article  Google Scholar 

  13. Ten Haaf K, Jeon J, Tammemagi MC et al (2017) Risk prediction models for selection of lung cancer screening candidates: a retrospective validation study. PLoS Med 14:e1002277

    Article  Google Scholar 

  14. Black WC, Gareen IF, Soneji SS et al (2014) Cost-effectiveness of CT screening in the National Lung Screening Trial. N Engl J Med 371:1793–1802

    Article  CAS  Google Scholar 

  15. Yabroff KR, Lamont EB, Mariotto A et al (2008) Cost of care for elderly cancer patients in the United States. J Natl Cancer Inst 100:630–641

    Article  Google Scholar 

  16. Johnson KM, Fain SB, Schiebler ML, Nagle S (2013) Optimized 3D ultrashort echo time pulmonary MRI. Magn Reson Med 70:1241–1250

    Article  Google Scholar 

  17. Burris NS, Johnson KM, Larson PE et al (2015) Detection of small pulmonary nodules with ultrashort echo time sequences in oncology patients by using a PET/MR system. Radiology 278:239–246

    Article  Google Scholar 

  18. Menezes GL, Knuttel FM, Stehouwer BL, Pijnappel RM, van den Bosch M (2014) Magnetic resonance imaging in breast cancer: a literature review and future perspectives. World J Clin Oncol 5:61–70

  19. Pisano ED, Gatsonis C, Hendrick E et al (2005) Diagnostic performance of digital versus film mammography for breast-cancer screening. N Engl J Med 353:1773–1783

    Article  CAS  Google Scholar 

  20. Pinsky PF, Gierada DS, Black W et al (2015) Performance of lung-rads in the national lung screening trial: a retrospective assessment. Ann Intern Med 162:485–491

    Article  Google Scholar 

  21. Kinsinger LS, Anderson C, Kim J et al (2017) Implementation of lung cancer screening in the veterans health administration. JAMA Intern Med 177:399–406

    Article  Google Scholar 

  22. van Klaveren RJ, Oudkerk M, Prokop M et al (2009) Management of lung nodules detected by volume ct scanning. N Engl J Med 361:2221–2229

    Article  Google Scholar 

  23. De Koning H (2017) ES 02.01 The Dutch-Belgian Lung Cancer Screening Trial (NELSON). J Thorac Oncol 12:S1611

    Article  Google Scholar 

  24. Pastorino U, Silva M, Sestini S et al (2019) Prolonged lung cancer screening reduced 10-year mortality in the MILD Trial: new confirmation of lung cancer screening efficacy. Ann Oncol 30:1162–1169

  25. MacMahon H, Naidich DP, Goo JM et al (2017) Guidelines for management of incidental pulmonary nodules detected on ct images: from the Fleischner Society 2017. Radiology 284:228–243

    Article  Google Scholar 

  26. Pyenson BS, Henschke CI, Yankelevitz DF, Yip R, Dec E (2014) Offering lung cancer screening to high-risk medicare beneficiaries saves lives and is cost-effective: an actuarial analysis. Am Health Drug Benefits 7:272–282

    PubMed  PubMed Central  Google Scholar 

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Acknowledgments

The authors wish to recognize Joey Kong, PhD, and Pari Pandharipande, M.D., M.P.H., for their contributions to this manuscript.

Funding

The authors state that this work has not received any funding.

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Correspondence to Bradley D. Allen.

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The scientific guarantor of this publication is Bradley Allen, MD, MS.

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The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

One of the authors (GBH) has significant statistical expertise.

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Written informed consent was not required for this study because analysis was based on previously published results available in the literature.

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Institutional Review Board approval was not required because of the statistical/mathematical nature of this work.

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Allen, B.D., Schiebler, M.L., Sommer, G. et al. Cost-effectiveness of lung MRI in lung cancer screening. Eur Radiol 30, 1738–1746 (2020). https://doi.org/10.1007/s00330-019-06453-9

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  • DOI: https://doi.org/10.1007/s00330-019-06453-9

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