Identifying patients for whom lung cancer screening is preference-sensitive a microsimulation study

Annals of Internal Medicine

Volumn 169, Issue 1, 2018, Pages 1-9

  Caverly, Tanner J ^a   Cao, Pianpian ^b   Hayward, Rodney A ^a   Meza, Rafael ^b  

^a UNIVERSITY OF MICHIGAN MEDICAL SCHOOL   (United States)

^b UNIVERSITY OF MICHIGAN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; AGED; ARTICLE; CANCER INCIDENCE; CANCER MORTALITY; CANCER PATIENT; CANCER REGISTRY; CANCER RISK; CANCER SCREENING; CANCER SURVIVAL; CIGARETTE; CLINICAL ARTICLE; CLINICAL OUTCOME; COHORT ANALYSIS; COMPUTER ASSISTED TOMOGRAPHY; DISEASE ASSOCIATION; FEMALE; FOLLOW UP; HEALTH PROGRAM; HEALTH STATUS; HEALTH SURVEY; HUMAN; LIFE EXPECTANCY; LUNG CANCER; MALE; MORTALITY RISK; OUTCOME ASSESSMENT; PREDICTION; PRIORITY JOURNAL; QUALITY ADJUSTED LIFE YEAR; RADIATION DOSE; RISK REDUCTION; SMOKING; COMPUTER SIMULATION; DIAGNOSTIC IMAGING; EARLY CANCER DIAGNOSIS; LUNG; LUNG TUMOR; MARKOV CHAIN; MIDDLE AGED; MORTALITY; PROCEDURES; RISK ASSESSMENT; RISK FACTOR; TREATMENT OUTCOME; VERY ELDERLY; X-RAY COMPUTED TOMOGRAPHY;

AGED; AGED, 80 AND OVER; COMPUTER SIMULATION; EARLY DETECTION OF CANCER; FEMALE; HUMANS; LUNG; LUNG NEOPLASMS; MALE; MARKOV CHAINS; MIDDLE AGED; OUTCOME AND PROCESS ASSESSMENT (HEALTH CARE); QUALITY-ADJUSTED LIFE YEARS; RISK ASSESSMENT; RISK FACTORS; SEER PROGRAM; TOMOGRAPHY, X-RAY COMPUTED;

EID: 85049737802     PISSN: 00034819     EISSN: 15393704     Source Type: Journal    
DOI: 10.7326/M17-2561     Document Type: Article

References (50)

1. Aberle DR, Adams AM, Berg CD, Black WC, Clapp JD, Fager-strom RM, et al; National Lung Screening Trial Research Team. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med. 2011;365:395-409. [PMID: 21714641] doi:10.1056/NEJMoa1102873
2. National Cancer Institute. Cancer Stat Facts: Lung and Bronchus Cancer. Bethesda, MD: National Cancer Institute. Accessed at http://seer.cancer.gov/statfacts/html/lungb.html on 11 March 2018.
3. Kinsinger LS, Anderson C, Kim J, Larson M, Chan SH, King HA, et al. Implementation of lung cancer screening in the Veterans Health Administration. JAMA Intern Med. 2017;177:399-406. [PMID: 28135352] doi:10.1001/jamainternmed.2016.9022
4. Kovalchik SA, Tammemagi M, Berg CD, Caporaso NE, Riley TL, Korch M, et al. Targeting of low-dose CT screening according to the risk of lung-cancer death. N Engl J Med. 2013;369:245-54. [PMID: 23863051] doi:10.1056/NEJMoa1301851
5. Black WC, Gareen IF, Soneji SS, Sicks JD, Keeler EB, Aberle DR, et al; National Lung Screening Trial Research Team. Cost-effectiveness of CT screening in the National Lung Screening Trial. N Engl J Med. 2014;371:1793-802. [PMID: 25372087] doi:10.1056/NEJMoa1312547
6. Moyer VA; U.S. Preventive Services Task Force. Screening for lung cancer: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med. 2014;160:330-8. [PMID: 24378917] doi:10 .7326/M13-2771
7. Sox HC. Implementing lung cancer screening under Medicare: the last chance to get it right? [Editorial]. JAMA. 2014;312:1206-7. [PMID: 25247515] doi:10.1001/jama.2014.12921
8. Volk RJ, Hawk E, Bevers TB. Should CMS cover lung cancer screening for the fully informed patient? JAMA. 2014;312:1193-4. [PMID: 25247511] doi:10.1001/jama.2014.12709
9. Centers for Medicare & Medicaid Services. Beneficiary Engagement and Incentives Models: Shared Decision Making Model. 8 December 2016. Accessed at www.cms.gov/Newsroom/MediaReleaseDatabase/Fact-sheets/2016-Fact-sheets-items/2016-12-08-2.html on 11 March 2018.
10. Tammemägi MC, Katki HA, Hocking WG, Church TR, Caporaso N, Kvale PA, et al. Selection criteria for lung-cancer screening. N Engl J Med. 2013;368:728-36. [PMID: 23425165] doi:10.1056/NEJMoa1211776
11. Katki HA, Kovalchik SA, Berg CD, Cheung LC, Chaturvedi AK. Development and validation of risk models to select ever-smokers for CT lung cancer screening. JAMA. 2016;315:2300-11. [PMID: 27179989] doi:10.1001/jama.2016.6255
12. Tammemägi MC, Church TR, Hocking WG, Silvestri GA, Kvale PA, Riley TL, et al. 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;11:e1001764. [PMID: 25460915] doi:10.1371/journal.pmed.1001764
13. Ten Haaf K, Tammemägi MC, Bondy SJ, van der Aalst CM, Gu S, McGregor SE, et al. Performance and cost-effectiveness of computed tomography lung cancer screening scenarios in a population-based setting: a microsimulation modeling analysis in Ontario, Canada. PLoS Med. 2017;14:e1002225. [PMID: 28170394] doi:10.1371/journal.pmed.1002225
14. Kumar V, Cohen JT, van Klaveren D, Soeteman DI, Wong JB, Neumann PJ, et al. Risk-targeted lung cancer screening: a cost-effectiveness analysis. Ann Intern Med. 2018;168:161-9. [PMID: 29297005] doi:10.7326/M17-1401
15. Caverly TJ, Fagerlin A, Wiener RS, Slatore CG, Tanner NT, Yun S, et al. Comparison of observed harms and expected mortality benefit for persons in the Veterans Health Affairs Lung Cancer Screening Demonstration Project. JAMA Intern Med. 2018;178:426-8. [PMID: 29356812] doi:10.1001/jamainternmed.2017.8170
16. Yarnall KS, Pollak KI, Østbye T, Krause KM, Michener JL. Primary care: is there enough time for prevention? Am J Public Health. 2003; 93:635-41. [PMID: 12660210]
17. Aberle DR, DeMello S, Berg CD, Black WC, Brewer B, Church TR, et al; National Lung Screening Trial Research Team. Results of the two incidence screenings in the National Lung Screening Trial. N Engl J Med. 2013;369:920-31. [PMID: 24004119] doi:10.1056/NEJMoa1208962
18. Oken MM, Hocking WG, Kvale PA, Andriole GL, Buys SS, Church TR, et al; PLCO Project Team. Screening by chest radiograph and lung cancer mortality: the Prostate, Lung, Colorectal, and Ovarian (PLCO) randomized trial. JAMA. 2011;306:1865-73. [PMID: 22031728] doi:10.1001/jama.2011.1591
19. Siebert U, Alagoz O, Bayoumi AM, Jahn B, Owens DK, Cohen DJ, et al. State-transition modeling: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force-3. Med Decis Making. 2012;32:690-700. [PMID: 22990084]
20. Mahadevia PJ, Fleisher LA, Frick KD, Eng J, Goodman SN, Powe NR. Lung cancer screening with helical computed tomography in older adult smokers: a decision and cost-effectiveness analysis. JAMA. 2003;289:313-22. [PMID: 12525232]
21. National Center for Health Statistics. NHIS: National Health Interview Survey. 2018. Accessed at www.cdc.gov/nchs/nhis on 11 March 2018.
22. The R Project for Statistical Computing. R-3.3.1 for Windows (32/64 bit). Updated 31 June 2016. Accessed at https://cran.r-project.org/bin/windows/base/old/3.3.1 on 11 March 2018.
23. Bach PB, Kattan MW, Thornquist MD, Kris MG, Tate RC, Barnett MJ, et al. Variations in lung cancer risk among smokers. J Natl Cancer Inst. 2003;95:470-8. [PMID: 12644540]
24. Ten Haaf K, Jeon J, Tammemägi MC, Han SS, Kong CY, Plevritis SK, et al. Risk prediction models for selection of lung cancer screening candidates: a retrospective validation study. PLoS Med. 2017;14: e1002277. [PMID: 28376113] doi:10.1371/journal.pmed.1002277.
25. Fritz AG, ed. International Classification of Diseases for Oncology: ICD-O. 3rd ed. Geneva: World Health Organization; 2013
26. American Joint Committee on Cancer. AJCC Cancer Staging Manual. 8th ed. 2018. Accessed at https://cancerstaging.org/references-tools/deskreferences/Pages/default.aspx on 11 March 2018.
27. National Cancer Institute. Cancer Survival Analysis Software (CanSurv). Updated 31 January 2017. Accessed at https://surveillance.cancer.gov/cansurv on 11 March 2018.
28. Othus M, Barlogie B, Leblanc ML, Crowley JJ. Cure models as a useful statistical tool for analyzing survival. Clin Cancer Res. 2012;18: 3731-6. [PMID: 22675175] doi:10.1158/1078-0432.CCR-11-2859
29. Meza R, ten Haaf K, Kong CY, Erdogan A, Black WC, Tammemagi MC, et al. Comparative analysis of 5 lung cancer natural history and screening models that reproduce outcomes of the NLST and PLCO trials. Cancer. 2014;120:1713-24. [PMID: 24577803] doi:10 .1002/cncr.28623
30. de Koning HJ, Meza R, Plevritis SK, ten Haaf K, Munshi VN, Jeon J, et al. Benefits and harms of computed tomography lung cancer screening strategies: a comparative modeling study for the U.S. Preventive Services Task Force. Ann Intern Med. 2014;160:311-20. [PMID: 24379002] doi:10.7326/M13-2316
31. Wever EM, Draisma G, Heijnsdijk EA, de Koning HJ. How does early detection by screening affect disease progression? Modeling estimated benefits in prostate cancer screening. Med Decis Making. 2011;31:550-8. [PMID: 21406620] doi:10.1177/0272989X10396717
32. National Cancer Institute. NCI Dictionary of Cancer Terms. Bethesda, MD: National Cancer Institute. Accessed at www.cancer.gov/publications/dictionaries/cancer-terms on 11 March 2018.
33. Ten Haaf K, van Rosmalen J, de Koning HJ. Lung cancer detectability by test, histology, stage, and gender: estimates from the NLST and the PLCO trials. Cancer Epidemiol Biomarkers Prev. 2015;24: 154-61. [PMID: 25312998] doi:10.1158/1055-9965.EPI-14-0745
34. Patz EF Jr, Pinsky P, Gatsonis C, Sicks JD, Kramer BS, Tammemägi MC, et al; NLST Overdiagnosis Manuscript Writing Team. Overdiagnosis in low-dose computed tomography screening for lung cancer. JAMA Intern Med. 2014;174:269-74. [PMID: 24322569] doi:10.1001/jamainternmed.2013.12738
35. Han SS, Ten Haaf K, Hazelton WD, Munshi VN, Jeon J, Erdogan SA, et al. The impact of overdiagnosis on the selection of efficient lung cancer screening strategies. Int J Cancer. 2017;140:2436-43. [PMID: 28073150] doi:10.1002/ijc.30602
36. Tramontano AC, Schrag DL, Malin JK, Miller MC, Weeks JC, Swan JS, et al. Catalog and comparison of societal preferences (utilities) for lung cancer health states: results from the Cancer Care Outcomes Research and Surveillance (CanCORS) study. Med Decis Making. 2015;35:371-87. [PMID: 25670839] doi:10.1177/0272989 X15570364
37. Pinsky PF, Gierada DS, Black W, Munden R, Nath H, Aberle D, et al. Performance of Lung-RADS in the National Lung Screening Trial: a retrospective assessment. Ann Intern Med. 2015;162:485-91. [PMID: 25664444] doi:10.7326/M14-2086
38. Bibbins-Domingo K, Grossman DC, Curry SJ, Davidson KW, Epling JW Jr, García FAR, et al; US Preventive Services Task Force. Screening for colorectal cancer: US Preventive Services Task Force recommendation statement. JAMA. 2016;315:2564-75. [PMID: 27304597] doi:10.1001/jama.2016.5989
39. Siu AL; U.S. Preventive Services Task Force. Screening for breast cancer: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med. 2016;164:279-96. [PMID: 26757170] doi:10 .7326/M15-2886
40. Center for Clinical Management Research; Ann Arbor Veterans Health Administration Medical Center; The Regents of the University of Michigan. Lung Cancer Screening. Accessed at https://share.lungdecisionprecision.com on 11 March 2018.
41. University of Michigan. Should I Screen: Lung Cancer Screening Decision Aid. 2018. Accessed at www.shouldiscreen.com on 11 March 2018.
42. ePrognosis Web site. Accessed at http://eprognosis.ucsf.edu on 11 March 2018.
43. Hayward RA, Kent DM, Vijan S, Hofer TP. Multivariable risk prediction can greatly enhance the statistical power of clinical trial subgroup analysis. BMC Med Res Methodol. 2006;6:18. [PMID: 16613605]
44. Kent DM, Hayward RA. Limitations of applying summary results of clinical trials to individual patients: the need for risk stratification. JAMA. 2007;298:1209-12. [PMID: 17848656]
45. Cheung LC, Katki HA, Chaturvedi AK, Jemal A, Berg CD. Preventing lung cancer mortality by computed tomography screening: the effect of risk-based versus U.S. Preventive Services Task Force eligibility criteria, 2005–2015. Ann Intern Med. 2018;168:229-32. [PMID: 29297008] doi:10.7326/M17-2067
46. Memorial Sloan Kettering Cancer Center. Lung Cancer Screening Decision Tool. 2014. Accessed at http://nomograms.mskcc.org/Lung/Screening.aspx on 11 March 2018.
47. Brock University. Lung Cancer Risk Calculators. St. Catharines, Ontario, Canada: Brock University; 2018. Accessed at https://brocku.ca/lung-cancer-screening-and-risk-prediction/risk-calculators on 11 March 2018.
48. National Cancer Institute. Risk-based NLST Outcomes Tool (RNOT). Bethesda, MD: National Cancer Institute. Accessed at https://analysistools.nci.nih.gov/lungCancerScreening/# on 11 March 2018.
49. National Cancer Institute. SEER Data & Software for Researchers. Bethesda, MD: National Cancer Institute. Accessed at https://seer.cancer.gov/resources on 12 April 2017.
50. Earle CC, Chapman RH, Baker CS, Bell CM, Stone PW, Sandberg EA, et al. Systematic overview of cost-utility assessments in oncology. J Clin Oncol. 2000;18:3302-17. [PMID: 10986064]