Selecting the Best Candidates for Lung Cancer Screening Tanner Caverly, MD, MPH

The Center for Medicare and Medicaid Services (CMS) recently decided to reimburse for annual lung cancer screening with low-dose computed tomography (LDCT) among persons who meet the inclusion criteria for the National Lung Cancer Screening Trial (NLST).1 Those who have smoked for Related article more than 30 pack-years, continue to smoke, or quit within the past 15 years and are 55 to 77 years old will be eligible for free annual LDCT screening—roughly 6% of the US population older than 40 years.2 For the initial LDCT screening, a “lung cancer screening counseling and shared decision-making visit” will be required. Counseling visits will be reimbursed annually thereafter but will not be required. What considerations should be included in shared decision making? The Teachable Moment published in this issue by Schneider and Arenberg3 reminds us that lung cancer screening—like most medical decision-making—is a gamble; that there are good bets and bad bets—and that the odds are stacked against some people who will be eligible for LDCT screening. Thinking hard about how to optimally select people to screen is critically important as we move forward with populationbased lung cancer screening programs.

Patient Selection 101: Recognize When Screening Is a Bad Bet The goal of screening for lung cancer is to diagnose cancer in the early stages when it is potentially curable. But to achieve cure, a person must be able to tolerate and survive the necessary diagnostic and treatment procedures. In addition, screening is unlikely to help a person who is at high risk of dying from another cause before they have time to develop or die from lung cancer. Thus, people who are too sick to have surgery or likely to die of other causes may suffer more harm than benefit from screening. Moreover, the baseline risk of developing lung cancer varies substantially, even among those eligible for LDCT screening,4-6 and the benefit of screening those who meet eligibility criteria but are still at lower risk for lung cancer may not outweigh the harms of screening. 1. High Risk for Surgery Clinicians ordering LDCT screening need to understand the factors that increase risk for adverse outcomes from lung resection. As elegantly desc ribed by S chneider and Arenberg,3 the riskier surgery is for a person (all else being jamainternalmedicine.com

equal), the lower the likelihood that screening will be beneficial. Age alone is not a strong predictor of surgical risk.7 Underlying comorbidities, such as heart failure or severe chronic obstructive pulmonary disease, and functional status are much more important.7 The presence of multiple risk factors can result in very high risk for death related to surgery. A model developed to predict in-hospital death following thoracic surgery8,9 suggests that the risk of death in a healthy man older than 65 years undergoing an elective lobectomy for lung cancer is about 1%, which is similar to the 1.2% surgical mortality found in the NLST.10 However, if the patient has a high American Society of Anesthesiologists score, poor performance, dyspnea when walking on the level, and multiple comorbidities, the model suggests that the risk of death associated with elective lobectomy is about 17%.8 People at such a high risk for mortality are not likely to be considered good candidates for curative lung resection and are therefore poor candidates for screening. But even among patients who are somewhat less sick, a relatively high risk of surgical mortality (eg, 5%) could make lung cancer screening a bad bet for many patients. 2. High Risk for Non–Lung Cancer Death A person’s potential to benefit from lung cancer screening decreases as their risk for dying from causes other than lung cancer increases. This occurs for 2 reasons.11 First, the likelihood that lung cancer screening will actually prevent lung cancer death is lower because death from other causes is more likely to occur before the person develops and dies from lung cancer. Second, even if a person at high risk for non–lung cancer death is lucky enough to avoid dying from lung cancer due to screening, the survival gain is much smaller. Multiple models to predict overall mortality rates are available to guide decision-making and were recently summarized in a systematic review.12 3. Low Risk for Lung Cancer The lower a person’s baseline risk of lung cancer, the less benefit will be derived from lung cancer screening.5,6 Assuming all lung cancers will be fatal, a 55-year-old man with a history of smoking 1 pack per day for 30 years who quit smoking 10 years ago has about a 0.5% risk of dying from lung cancer in the next 6 years.16 In contrast, a 70-year-old man who has smoked 2 packs per day for 50 years and continues to smoke has about a 5% risk of dying from lung cancer in the next 6 years. On the one hand, given that 3 annual computed tomographic screenings reduced the risk of dying of lung cancer 20% (Reprinted) JAMA Internal Medicine Published online April 6, 2015

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after 6 years of follow-up in the NLST, 1000 people with the same overall risk as the 55-year-old man would need to be screened to avoid 1 lung cancer death. This also means that 999 out of the 1000 people in this risk group would be screened without benefit, but nonetheless exposed to the risks associated with screening, including overdiagnosis and the possible need for additional imaging and invasive procedures. Among a group of people with the same overall risk as the 70year-old man, on the other hand, only 100 would need to be screened to avoid 1 lung cancer death. 4. Putting It All Together Using prediction models for surgical risk, other-cause mortality, and lung cancer risk can help us better identify persons with the best chance of benefiting from lung cancer screening. On average, for every 10 lung cancer deaths avoided with screening in the NLST, there were 3 deaths due to invasive follow-up testing and surgical treatment of lung cancer.10 But persons enrolled in the NLST had, on average, low surgical risk (ie, 1.2% surgical mortality), modest risk for dying from lung cancer (ie, 1.7% cumulative incidence of dying from lung cancer over 6 years), and fewer comorbidities than heavy smokers in the general US population.10,13 Different combinations of risk factors will result in a more or less favorable riskbenefit profile and may lead to limited benefits for many persons who meet current eligibility criteria. Also, it is likely that risks are correlated: eligible persons at the highest risk for lung cancer are also likely to have more comorbidities, higher levels of surgical risk, and higher other-cause mortality. Clinicians should be able to recognize patients at very high risk for other causes of death or surgical mortality, and those at very low risk for lung cancer, and counsel these patients accordingly. But it is not reasonable to expect clinicians to be able to estimate benefits and risks accurately for all patients. Models that simultaneously take into account an individual person’s surgical risk, lung cancer risk, and other-cause mortality risk should be developed to help us more precisely determine the odds for individual patients.

ARTICLE INFORMATION Author Affiliations: Veterans Affairs Center for Clinical Management Research, Ann Arbor, Michigan; Department of Internal Medicine, University of Michigan Medical School, Ann Arbor. Corresponding Author: Tanner J. Caverly, MD, MPH, Veterans Affairs Center for Clinical Management Research, 2215 Fuller Rd, Ann Arbor, MI 48105 ([email protected]). Published Online: April 6, 2015. doi:10.1001/jamainternmed.2015.1235. Conflict of Interest Disclosures: None reported. Additional Contributions: The author would like to thank the following people for providing helpful input on the ideas presented herein: Deborah Grady, MD, MPH, Department of Medicine, University of California San Francisco School of Medicine; Rodney Hayward, MD, Department of Internal Medicine, University of Michigan Medical School and Ann Arbor VA Center for Clinical Management Research; Rafael Meza, PhD,


Patient Selection 201: Develop Tools That Help People Understand the Odds Guidelines endorse the importance of shared decision-making for lung cancer screening,14 and the Medicare coverage decision strongly promotes shared decision-making by explicitly specifying coverage for a shared decision-making visit.1 Despite this favorable policy environment and the strong ethical basis for promoting shared decision-making in this context, incorporating true shared decision-making into current clinical practice will be a challenge. While it is clear that decisions regarding lung cancer screening need to be individualized, it is not clear how best to communicate key risk information so that patients and their clinicians adequately understand the odds. Busy clinicians need support, such as risk prediction models and decision tools, to help them inform individual persons considering lung cancer screening. Developing a shared decisionmaking tool is complex and would best be done by an interdisciplinary group with expertise in multiple areas (eg, lung cancer, cancer screening, risk communication, behavioral health, graphic design, and modeling) with support from professional and policy-making organizations. Such tools could be used by ancillary clinical staff and would help document that satisfactory shared decision making occurred.

Patient Selection 301: Informed People Need to Like Their Odds The benefits of lung cancer screening can vary dramatically even among eligible heavy smokers, from a number needed to screen of 161 to avoid 1 lung cancer death in the highest-risk quintile to a number needed to screen of greater than 5000 in the lowest.4 Optimal patient selection will identify and discourage screening for those who have a limited chance to benefit. What about the rest of the eligible population? Should screening be encouraged for them or presented as an option? Unfortunately, it is currently unknown at what level of benefit most of informed persons would consider lung cancer screening to be a good bet. Given this uncertainty, it makes the most sense to present screening as an option, with both substantial benefits and substantial harms.15

Department of Epidemiology, University of Michigan School of Public Health; and Sameer Saini, MD, MS, Department of Internal Medicine, University of Michigan Medical School and Ann Arbor VA Center for Clinical Management Research. REFERENCES 1. CMS proposes coverage for lung cancer screening with low-dose CT. http://healthaffairs.org /blog/2014/12/09/cms-proposes-coverage-with -evidence-development-for-lung-cancer-screening -with-low-dose-ct/. Accessed December 29, 2014. 2. Pinsky PF, Berg CD. Applying the National Lung Screening Trial eligibility criteria to the US population: what percent of the population and of incident lung cancers would be covered? J Med Screen. 2012;19(3):154-156. 3. Schneider D, Arenberg D. Competing mortality in cancer screening: a teachable moment [published online April 6, 2015]. JAMA Intern Med. doi:10.1001 /jamainternmed.2015.1232.

4. Kovalchik SA, Tammemägi M, Berg CD, et al. Targeting of low-dose CT screening according to the risk of lung-cancer death. N Engl J Med. 2013; 369(3):245-254. 5. Tammemägi MC, Church TR, Hocking WG, 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(12):e1001764. 6. Bach PB, Gould MK. When the average applies to no one: personalized decision making about potential benefits of lung cancer screening. Ann Intern Med. 2012;157(8):571-573. 7. Brunelli A, Kim AW, Berger KI, Addrizzo-Harris DJ. Physiologic evaluation of the patient with lung cancer being considered for resectional surgery: Diagnosis and Management of Lung Cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines. Chest. 2013;143(5)(suppl):e166S-e190S. 8. Falcoz PE, Conti M, Brouchet L, et al. The Thoracic Surgery Scoring System (Thoracoscore):

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risk model for in-hospital death in 15,183 patients requiring thoracic surgery. J Thorac Cardiovasc Surg. 2007;133(2):325-332. 9. Société Française d’Anesthésie et de Réanimation. Scoring systems for ICU and surgical patients: Thoracoscore (the Thoracic Surgery Scoring System). http://www.sfar.org/scores2 /thoracoscore2.php. Accessed March 10, 2015. 10. Aberle DR, Adams AM, Berg CD, et al; National Lung Screening Trial Research Team. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med. 2011;365(5): 395-409.


11. van Hees F, Zauber AG, Klabunde CN, Goede SL, Lansdorp-Vogelaar I, van Ballegooijen M. The appropriateness of more intensive colonoscopy screening than recommended in Medicare beneficiaries: a modeling study. JAMA Intern Med. 2014;174(10):1568-1576. 12. Yourman LC, Lee SJ, Schonberg MA, Widera EW, Smith AK. Prognostic indices for older adults: a systematic review. JAMA. 2012;307(2):182-192. 13. Pinsky PF, Gierada DS, Hocking W, Patz EF Jr, Kramer BS. National Lung Screening Trial findings by age: Medicare-eligible versus under-65 population. Ann Intern Med. 2014;161(9):627-633.

14. Moyer VA; US Preventive Services Task Force. Screening for lung cancer: US Preventive Services Task Force recommendation statement. Ann Intern Med. 2014;160(5):330-338. 15. Eddy DM. Clinical decision making: from theory to practice: designing a practice policy: standards, guidelines, and options. JAMA. 1990;263(22):30773084. 16. Memorial Sloan Kettering Cancer Center. Lung Cancer Screening Decision Tool. http://nomograms .mskcc.org/Lung/Screening.aspx. Accessed March 10, 2015.

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Selecting the best candidates for lung cancer screening.

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