In Estimating Overdiagnosis, Details Matter

Academic Radiology, Vol 23, No 1, January 2016

and better risk stratification using clinical (6) and genomic data (12). Naturally, as screening is implemented in the general population in the United States, continued monitoring and analysis of the clinical data will determine whether the benefits outweigh the costs and risks, and can be used to arrive at better estimates of overdiagnosis and to further refine the strategies for diagnosis and management of screen-detected nodules, to achieve maximal societal benefit at minimum costs and harms.

REFERENCES 1. Mortani Barbosa EJ, Jr. Lung cancer screening overdiagnosis: reports of overdiagnosis in screening for lung cancer are grossly exaggerated. Acad Radiol 2015; 22:976–982. 2. ACR. Lung cancer screening resources. Available at: http://www.acr.org/Quality-Safety/Resources/Lung-Imaging-Resources. Accessed August 14, 2015. 3. McKee BJ, Regis SM, McKee AB, et al. Performance of ACR lungRADS in a clinical CT lung screening program. J Am Coll Radiol 2015; 12:273–276. 4. Manser R, Lethaby A, Lb I, et al. Screening for lung cancer. Cochrane Database Syst Rev 2013; (6):CD001991. 5. Heuvelmans MA, Vliegenthart R, Oudkerk M. Contributions of the European trials (European Randomized Screening Group) in Computed tomography lung cancer screening. J Thorac Imaging 2015; 30:101– 107. 6. Young RP, Duan F, Chiles C, et al. Airflow limitation and histology-shift in the National Lung Screening Trial: the NLST-ACRIN Cohort substudy (N=18, 714). Am J Respir Crit Care Med 2015; [Epub Jul 22, 2015]. DOI: 10.1164/rccm.201505-0894OC 7. Louie AV, Palma D, Dahele M, et al. Management of early-stage nonsmall cell lung cancer using stereotactic ablative radiotherapy: controversies, insights, and changing horizons. Radiother Oncol 2015; 114:138–147. 8. Chang JY, Senan S, Paul M, et al. Stereotactic ablative radiotherapy versus lobectomy for operable stage I non-small-cell lung cancer: a pooled analysis of two randomised trials. Lancet Oncol 2015; 16:630–637. 9. Haaf K, de Koning HJ. Overdiagnosis in lung cancer screening: why modelling is essential. J Epidemiol Community Health 2015; doi:10.1136/jech2014-20407; [Epub Jun 12, 2015]. 10. Esserman LJ, Thompson IM, Reid B, et al. Addressing overdiagnosis and overtreatment in cancer: a prescription for change. Lancet Oncol 2014; 15:e234–e242. 11. Prokop M. Lung cancer screening: the radiologist’s perspective. Semin Respir Crit Care Med 2014; 35:91–98. 12. Boeri M, Sestini S, Fortunato O, et al. Recent advances of microRNAbased molecular diagnostics to reduce false-positive lung cancer imaging. Expert Rev Mol Diagn 2015; 6:801–813. http://dx.doi.org/10.1016/j.acra.2015.09.006

In Estimating Overdiagnosis, Details Matter From: Jay A. Baker, MD From the Duke University Medical Center, Box 3808, Durham, NC 27710. I am deeply concerned about the recently published article by Dr. Archie Bleyer regarding screening mammography and the question of overdiagnosis (1). Dr. Bleyer offers a review of the literature and update of his prior work, but he has not

LETTER TO THE EDITOR

updated his puzzling approach and conclusions. My concerns are many, and I will address only some of them here. Dr. Bleyer’s review relies on modeling based on the author’s “best guess” about fundamental inputs such as the likely incidence rate of breast cancer in the absence of screening (2). The author estimated that the background growth in breast cancer incidence without screening would be 0.25% per year. Through careful analysis of multiple databases including the Surveillance, Epidemiology, and End Results database, the Connecticut Tumor Registry, and the United Kingdom female cancer registry data, Helvie et al. (3) established that the annual percentage change in breast cancer incidence ranged from at least 0.8% up to 2.3% with a central estimate of 1.3% growth in breast cancer incidence per year in the absence of screening. This matches well with the median of seven models from the Cancer Intervention and Surveillance Modeling Network, which sets the increase in background incidence at 1.2% (4). Although disagreements over assumptions may appear banal, in fact, accurate estimation of the annual percentage change in breast cancer incidence is crucial when attempting to estimate overdiagnosis. Dr. Bleyer’s marked underestimation of the upward trend in the incidence of breast cancer leads him to severely overestimate the difference between early- and latestage cancers. As a result, he markedly overestimates overdiagnosis. Since the actual background incidence is significantly higher—just as Helvie et al. and the Cancer Intervention and Surveillance Modeling Network models predict—Dr. Bleyer assumes that the difference between reality and his best guess must be due to cancers that would only be detected by screening (i.e., overdiagnosis). Instead, the difference is due, in large part, to changes in the underlying risk of breast cancer in the population. In addition to perpetuating his flawed modeling in this review, Dr. Bleyer also perpetuates several other discredited notions. Most notably, he rejects randomized controlled trials that show a significant decrease in breast cancer mortality because they do not also show a statistically significant decrease in all-cause mortality. This is simply a matter of resources. Tabár et al. demonstrated that to have sufficient power to demonstrate an improvement in all-cause mortality, a trial would require over 20 times as many subjects as the largest randomized controlled trial to date (5). Instead, Tabár et al. demonstrate that, among all women who develop breast cancer, there was a statistically significant 19% reduction in all-cause mortality for women who were invited to screening versus those in the control group. Finally, Dr. Bleyer suggests that many breast cancers are not real and that, despite histologic evidence, we do not know “who really has cancer.” He again suggests that many invasive breast cancers develop and then regress spontaneously, although there are only a small number of anecdotal accounts of spontaneous regression (6). Also, he strongly recommends that screening regimens be matched to a patient’s personal risk profile, a strategy that sounds logical on the face of it but for which there are also no empirical data demonstrating that such a strategy would be effective. There are 115

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existing data that definitively demonstrate that screening mammography significantly reduces mortality due to breast cancer in women exposed to screening and reduces all-cause mortality among women who develop breast cancer. I would urge Dr. Bleyer and others who are particularly focused on the possibility of overdiagnosis to test alternatives that will save as many lives as the screening strategies that have already been proven. REFERENCES 1. Bleyer A. Screening mammography: update and review of publications since our report in the New England Journal of Medicine on the magnitude of the problem in the United States. Acad Radiol 2015; 22:949– 960. 2. Bleyer A, Welch G. Effect of three decades of screening mammography on breast-cancer incidence. NEJM 2012; 367:1998–2005. 3. Helvie MA, Chang JT, Hendrick E, et al. Reduction in late-stage breast cancer incidence in the mammography era. Cancer 2014; 120:2649– 2656. 4. Cronin KA, Feuer EJ, Clarke LD, et al. Impact of adjuvant therapy and mammography on U.S. mortality from 1975 to 2000: comparison of mortality results from the CISNET breast cancer base case analysis. J Natl Cancer Inst Mongr 2006; 112–121. 5. Tabár L, Duffy SW, Yen M-F, et al. All-cause mortality among breast cancer patients in a screening trial: support for breast cancer mortality as an end point. J Med Screen 2002; 9:159–162. 6. Larsen SU, Rose C. [Spontaneous remission of breast cancer. A literature review]. Ugeskr Laeger 1999; 161:4001–4004. http://dx.doi.org/10.1016/j.acra.2015.08.034

The Faulty Analysis of Breast Cancer Screening Data From: Daniel B. Kopans, MD From the Harvard Medical School, Boston, Massachusetts 02115; Breast Imaging Division, Department of Radiology, Avon Comprehensive Breast Evaluation Center, Massachusetts General Hospital, 55 Fruit Street, Boston, Massachusetts 02114. In this limited space I cannot possibly address all the errors in the Bleyer analysis so I will concentrate on the fundamental issue. In his paper with Dr. Welch, in the prestigious New England Journal of Medicine (NEJM) (1), Dr. Bleyer sought to use Surveillance, Epidemiology, and End Results (SEER) data to show that there is massive overdiagnosis of breast cancer because of mammography screening. Their fundamental claim was that, in 2008 alone, there were more than 70,000 cases of breast cancer that would have disappeared on their own had they not been detected by screening (78,000 as he now claims in 2011). In fact, there is not a single credible report of an invasive cancer disappearing on its own. One would think that if there were 70,000 cases of 116

disappearing breast cancer in a single year, someone would have published a credible report. As Dr. Bleyer has, subsequently, written (2) in response to my review of their analysis and my concerns (3), they actually had no data to permit them to, scientifically, blame anything on screening because they had no data on who had mammograms and they had no data on which cancers were detected by mammography. Despite this fundamental fact, Bleyer and Welch’s analysis is being used by guidelines panels to reduce access to screening. Their paper was based on (as Dr. Bleyer has written) their “best guess” as to what the incidence of breast cancer would have been in 2008 (now up to 2011) had there not been any screening (which began in the mid-1980s). The authors chose to ignore 40 years of data from the Connecticut Tumor Registry (CTR), which has been used by every other author that I have been able to find who has evaluated breast cancer incidence prior to SEER. The CTR showed that the incidence of invasive cancers had been increasing by at least 1% per year dating back to at least 1940 (4). As I wrote in rebuttal to their paper (3), had they used the data-backed rate of increase and not their guess, there was no evidence of any “overdiagnosis” of invasive breast cancer. In fact, there were fewer invasive cancers than would have been expected. In this latest analysis by Dr. Bleyer, he confirms my analysis as well as that by Helvie et al. (6) (which he incorrectly disparaged). It is all there in his figure 4. I will go through it step by step. In their analysis, Bleyer and Welch did what no expert in breast cancer would do. They combined the Ductal Carcinoma in Situ (DCIS) data with small invasive cancers and called them “earlystage cancer.” Virtually everyone agrees that DCIS lesions are a major conundrum, but this is nothing new (5). There have been numerous efforts over the past decades to try to better tailor therapy for DCIS lesions knowing that some, but not all, will progress to invasive cancers. If Bleyer and Welch had written that we need better management of DCIS, the paper would not have been published because this is very old news. If you look at figure 4, the black lines are based on Drs. Bleyer and Welch’s “best guess” as to the rate of overdiagnosis of early-stage breast cancer (small invasive cancers + DCIS). This is based on the SEER incidence (actual cancers diagnosed) of the two combined (DCIS + small invasive cancers) minus what they “guessed” the rate would have been in the absence of screening. The difference between the two is their claim of “overdiagnosed” cancers (ones that would have never appeared in the absence of screening). The pink curves are Dr. Bleyer’s calculations, but based on 40 years of actual data (not guesses) from the CTR (back to 1940), which show a steady 1% increase in invasive cancers each year prior to the start of screening and what would result had this 40-year rate continued. Note that he calculates that there would still be 31,000 more “early-stage cancers” even with this data-based scenario. What Dr. Bleyer has forgotten or left out is that in 2011, the SEER data show that there were 57,650 in situ cancers that are included in his graphic