Screening for Prostate and Breast Cancer: It’s More Complex Than You May Think

Felipe Nogueira

“Pink October” and “Blue November” are campaigns to promote awareness for breast and prostate cancer, respectively. In Brazil, as well as in other countries, the population is encouraged to do tests such as the prostate-specific antigen (PSA) for prostate cancer and mammography for breast cancer.

  The main idea is screening: to perform tests in healthy persons to detect and to treat diseases before their symptoms appear to increase the chances of cure and even to offer a less aggressive treatment. A good example of cancer screening is for cervical cancer, where incidence of the advanced cases decreased after the Papanicolaou test was introduced (Adegoke et al. 2012). However, studies that assess the efficacy of screening for prostate or breast cancer show that in reality things are more complicated than usually advertised by those campaigns.

In May 2018, the U.S. Preventive Services Task Force (USPSTF) reviewed studies of PSA screening for prostate cancer (Fenton et al. 2018). Only two randomized controlled trials were of sufficient quality to assess impact on mortality. One, called the PLCO,1 did not show differences in mortality. The second trial, called ERSPC,2 showed that screening reduced prostate cancer mortality in men aged fifty-five to sixty-nine. Even in that case, it’s far from simple. In order to avoid one prostate cancer death and three cases of metastatic prostate cancer, 1,000 men aged fifty-five to sixty-nine have to be screened every four years during thirteen years. Of those, twenty-seven men received treatment—prostate surgery and/or radiation therapy. More important, the majority of those who were treated, twenty-four patients, received aggressive treatment with no benefits, only the harms caused by the treatment itself. Regardless of screening, five men died from prostate cancer. See Table 1 for complete estimates.

A careful analysis of cancer screening must consider harms of treatment. The USPSTF review found that of those who undergo complete prostate surgery, one in five men develop urinary incontinence and two in three experience impotence. More than half of those who receive radiation therapy develop impotence and one in six men develop bowel symptoms, including bowel urgency and fecal incontinence (Fenton et al. 2018).

The overall view that prostate cancer screening might cause more harm than good is far from new. A 2013 Cochrane meta-analysis (Ilic et al. 2013) of five studies showed no reduction in mortality, and in 2012 USPSTF recommended against screening regardless of age. At present, the USPSTF concludes the benefits and harms of screening for men aged fifty-five to sixty-nine are balanced, recommending an individualized decision after a careful consideration of potential benefits and harms. For men aged seventy and older, the USPSTF recommends against screening. See Figure 1 for USPSTF decision aid. 

Regarding breast cancer, the evidence might look more favorable to screening with mammography, but again it’s not as crystal clear as the campaign messages suggest. A 2018 JAMA article (Keating and Pace 2018) estimated that ten out of 10,000 women in their fifties screened annually with mammography during ten years would avoid breast cancer death. But 940 women would have unnecessary biopsies and forty-four would be treated needlessly with surgery, radiation, chemotherapy, or hormonal therapy. Despite screening, sixty-two women would still die from breast cancer. Since breast cancer treatment improved dramatically as trials were conducted, screening benefits might be even smaller today than those reported in trials (Keating and Pace 2018). To offer benefits while reducing the possible harms, the USPSTF recommends mammography every two years for women aged fifty to seventy-four and recommends against teaching breast self-examination.

This situation is not restricted to breast and prostate cancer. Between 1975 and 2009, the incidence of thyroid cancer in the United Stated tripled from 4.9 to 14.4 in 100,000. But the mortality rate remained constant: 0.56 in 100,000 (Esserman et al. 2014). A study in Finland detected thyroid cancers in autopsies of 36 percent of patients who had died from other causes (Esserman et al. 2014).

Autopsy studies in prostates in patients who died from other causes also show a great disease reservoir (Sandhu and Adriole 2012). In autopsied men aged sixty to seventy-nine, the incidence of prostate cancer varied between 14 and 77 percent. Astonishingly, prostate cancer was found even in autopsied men in their twenties, with an incidence of 8–11 percent (Sandhu and Adriole 2012).

Figure 1. USPSTF illustration of benefits and harms of prostate cancer screening. Note the estimate of benefits is from the ERSPC trial, but harms are derived from three other treatment studies combined. Available at https://screeningforprostatecancer.org/get-the-facts/.

What these data are describing is overdiagnosis (Welch and Black 2010; Carter and Barrat 2017). Screening detects mainly nonlethal or harmless cases of cancers; if it weren’t for screening we would die from other causes not even realizing that we also had cancer. Overdiagnosis is not a false-positive result, which is a positive test that subsequent evaluation shows no signs of cancer. In overdiagnosis, the lesion detected actually meets the diagnostic criteria for cancer but would not have caused symptoms (i.e., it would not have been diagnosed in the absence of screening) (Welch and Black 2010; Carter and Barrat 2017).

Overdiagnosis and its consequence are the main harms of screening. Since at the time of diagnosis it is impossible to differentiate harmless lesions from lethal ones, almost all cases are treated (Welch and Black 2010). Estimates suggest that between 20 percent and 60 percent (Fenton et al. 2018; Carter et al. 2015) of screen-detected prostate cancers were overdiagnosed. Of screen-detected breast cancers, the estimate of overdiagnosis from trials is 19 percent (Keating and Pace 2018), while an analysis of screening programs reported 52 percent (Jørgensen and Gøtzsche 2009). Then, a few might benefit from prostate and breast cancer screening, but more patients face harms of aggressive treatment they didn’t even need in the first place.

One of the premises of screening is that cancer has a linear progression, which would always allow detection before it’s lethal. But this premise is outdated. Cancers are heterogeneous, with different progression rates (Figure 2) (Carter and Barrat 2017). Screening is more likely to detect cancers that grow slowly or would have regressed. Critically, most lethal cancers, those that grow fast, are less likely to be detected by screening because they tend to cause symptoms between screening rounds (Carter and Barrat 2017).

Figure 2. Heterogenity of cancer. Not all cancers have the same progression rate (Carter and Barrat 2017; adapted from Welch and Black 2010).

While the messages encouraging screening tests rarely mention overdiagnosis, they often come with claims such as: “If it is early diagnosed, the chances of cure are 95%, but it’s 20% if detected in advanced stage.” However, when overdiagnosis exists, the rate of cured patients is biased, as the number of patients who survived cancer increases “automatically” because those patients with new harmless cases are now classified as “cured,” even when screening offers no benefits. Ironically, the rise in cancer incidence and inflated rates of cure due to overdiagnosis might reinforce the efforts to do screening, leading to even more overdiagnosis3 (Brodersen et al. 2018).

Another way the survival metric is biased relates to how many years the patient has lived after the diagnosis. Screening is effective only if it can detect diseases earlier. Consider, for instance, that without screening, patients are diagnosed due to symptoms at seventy years of age and die at seventy-five. Consider also that these patients would be diagnosed by screening at sixty-five and die due to cancer ten years later. With these descriptions, screening looks beneficial since whoever undergoes screening has a survival of ten years, and those who don’t survive only five years after the diagnosis. In both cases, the patient died at the same time; screening only made the diagnosis earlier, without actually increasing the life expectancy. This is called the lead time bias (Raffle and Gray 2007).

Figure 3. Incidence of different stages of breast cancer standardized by age in the United States White. SEER 9, 1975–2011 (Narod et al. 2015)

Due to biases, survival statistics do not show the efficacy of screening. If screening works, the incidence of advanced cases must go down. After the introduction of breast and prostate cancer screenings, an increase was expected in the incidence of early cancers. That should be followed by, as the population ages, a compensatory decrease in advanced cancers, while overall incidence remains unchanged (Esserman et al. 2009). Note in Figure 3 that the incidence of early breast cancers increased significantly, while the incidence of regional cancers decreased very little and the rate of metastases to other parts of the body remained stable. Interestingly, although breast cancer mortality is falling, the decrease was larger in young women who were not invited to screening (Gøtzsche et al. 2012; Narod et al. 2015). In addition, breast cancer mortality decreased in a similar way over the world, but the start of screening differs between countries (Gøtzsche 2015a). Similar observations could be made for prostate cancer. After screening, there was not a significant decrease in invasive cases as expected, and different rates of screening and treatment in different regions were unrelated to prostate cancer mortality (Esserman et al. 2009). These trend analyses, while not showing causality, indicate that screening leads to considerable overdiagnosis of early disease and that its impact on breast and prostate cancer mortality is small at best.

The best approach to measure screening efficacy is using randomized controlled trials, like PLCO and ERSPC. Trials compare a screened group with a control group, looking for a reduction in deaths caused by the cancer being screened forwhat’s called cancer-specific mortality. It is, for instance, the reduction in breast cancer mortality that prompts the claim that mammography screening “save lives.” But as women overdiagnosed with breast cancer might receive radiotherapy, which increases mortality due to lung cancer (Gøtzsche 2015b), screening could cause more deaths than breast cancer deaths averted. Since deaths by treatment are usually classified as other causes, cancer-specific mortality is biased in favor of screening. This bias is avoided by using overall mortality. What might be shocking is that cancer screening trials do not show overall mortality reduction. As Vinay Prasad and colleagues wrote in the BMJ (Prasad et al. 2016), “cancer screening has never been shown to save lives.”4 Does screening increase deaths from other causes? We don’t knowmaybe it’s just chance, since millions of people are required in a trial to look for a difference in overall mortality. Prasad and colleagues argued that those large trials are needed to know screening effects. In contrast, researcher Peter Gøtzsche thinks such trials are not an ethical thing to do, since a large number of people would have to be screened without knowing whether this will lengthen their lives, while it will make them less happy due to psychological distress caused by false-positive results and overdiagnosis (Gøtzsche 2015a). Due to small, if any, benefit in mortality but documented harms, Gøtzsche has stated that mammography screening would have been withdrawn from the market had it been a drug (Gøtzsche 2015b).

Other scientists, such as Laura Esserman, think that we should focus on ways to make screening better. For example, she and colleagues suggest not calling those indolent cases that are usually detected by screening “cancer” (Esserman et al. 2009). Since a cancer diagnosis is associated with a lethal disease that causes suffering in the minds of patients and physicians, renaming those as indolent lesions might reduce needless treatment. This was first proposed almost ten years ago, but as late as August 2018 other scientists are still asking for those changes (Nickel et al. 2018). Esserman has also proposed to move to a risk-based screening, which targets people at high risk of cancer. Testing whether risk-based screening can reduce mammography use without increasing advanced cancers is the objective of the Wisdom Study (Esserman et al. 2017).

Meanwhile, the public needs to be properly informed. The prostate and breast cancer awareness campaigns must be used to clearly tell the population the complexities regarding screening. This is very important. According to surveys, women overestimate the benefits of mammography screening by a factor of between ten and 200 (Wegwarth and Gigerenzer 2018). Also, as screening is often promoted as prevention, 68 percent of women in a survey wrongly believed that mammography reduces their chance of developing breast cancer (Domenighetti et al. 2003). As a perspective article in the New England Journal of Medicine (Biller-Andorno 2014) pointed out, “How can women make an informed decision if they overestimate the benefit of mammography so grossly?” This might be explained by doctors’ failure to communicate screening risk: in a survey of 300 U.S. screening patients, 90 percent of them had not received information from their doctors about the possible harms of screening (Esserman et al. 2009).

That’s not the whole story. A 2017 systematic review showed that doctors usually overestimate screening and treatment benefits while they underestimate its harms (Hoffman and Del Mar 2017).  A survey with primary care physicians in the United States suggests that doctors misunderstand screening statistics: 76 percent of doctor participants were misguided by the survival metric discussed earlier (Wegwarth et al. 2012). They wrongly thought patients diagnosed by screening with better five-year survival rates than patients diagnosed by symptoms means that the screening test saved lives. In an article Wegwarth and Gigerenzer (2018) asked, “Why is risk literacy so scarce in health care?” The authors discussed how the difficulty to understand risks and benefits in health likely lies with how statistical information is presented, from biased reports in medical journals to the use of relative risk and misleading statistics by the media. And research shows that decision aids help patients be more informed regarding screening decisions (Stacey et al. 2014). The researchers beautifully concluded: “A critical mass of informed citizens will not resolve all healthcare problems, but it can constitute a major triggering factor for better care” (Wegwarth and Gigerenzer 2018).


Notes

  1. PLCO: Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial
  2. ERSPC: European Randomized Study of Screening for Prostate Cancer
  3. This has been called the popularity paradox: “The greater the harm through overdiagnosis and overtreatment from screening, the more people there are who believe they owe their health, or even their life, to the programme” (Raffle and Gray 2007, 68).
  4. Lung cancer screening with CT in heavy smokers in a 2011 trial reduced lung cancer and overall mortality. Even though this is a case of screening in a high-risk group, Prasad and colleagues considered it the best evidence for overall mortality reduction in a cancer screening trial. However, as discussed by the authors, a 2013 meta-analysis for the USPSTF has not shown overall mortality reduction (Prasad et al. 2016).

Further Reading

Overdiagnosed: Making People Sick in the Pursuit of Health by H. Gilbert Welch, Lisa Schwartz, and‎ Steve Woloshin (2012).

Mammography Screening: Truth, Lies and Controversy by Peter C. Gøtzsche (2012).


References

  • Adegoke, O., S. Kulasingam, and B. Virnig. 2012. Cervical cancer trends in the United States: A 35-year population-based analysis. Journal of Women’s Health (Larchmt) 21(10):1031–37. doi: 10.1089/jwh.2011.3385.
  • Biller-Andorno, N. 2014. Abolishing mammography screening programs?  A view from the Swiss Medical Board. New England Journal of Medicine 370(21): 1965–1967.
  • Brodersen, J., B.S. Kramer, H. Macdonald, et al. 2018. Focusing on overdiagnosis as a driver of too much medicine. BMJ 362: k3494. doi: 10.1136/bmj.k3494.
  • Carter, J.L., R.J. Colett, and R.P. Harri. 2015. Quantifying and monitoring overdiagnosis in cancer screening: A systematic review of methods. BMJ 350: g7773. doi: 10.1136/bmj.g7773.
  • Carter, S.M., and A. Barratt. 2017. What is overdiagnosis and why should we take it seriously in cancer screening? Public Health Research and Practice 27(3): e2731722. doi: https://doi.org/1017061/phrp2731722.
  • Domenighetti, G., B. D’Avanzo, M. Egger, et al. 2003. Women’s perception of the benefits of mammography screening: Population-based survey in four countries. International Journal of Epidemiology 32: 816–21.
  • Esserman, L.J., H. Anton-Culver, A. Borowsky, et al. 2017. The WISDOM Study: Breaking the deadlock in the breast cancer screening debate. npj Breast Cancer 3: 34. doi:10.1038/s41523-017-0035-5.
  • Esserman, L.J., I.M. Thompson, B. Reid, et al. 2014. Addressing overdiagnosis and overtreatment in cancer: A prescription for change. The Lancet Oncology 15: e234–e242. doi: 10.1016/S1470-2045(13)70598-9.
  • Esserman, L., Y. Shieh, and I. Thompson. 2009. Rethinking screening for breast cancer and prostate cancer. JAMA 302(15):1685–92. doi: 10.1001/jama.2009.1498.
  • Fenton, J.J., M.S. Weyrich, S. Durbin, et al. 2018. Prostate-specific antigen–based screening for prostate cancer: A systematic evidence review for the U.S. Preventive Services Task Force. Agency for Healthcare Research and Quality, Evidence Synthesis No. 154. AHRQ Publication No. 17-05229-EF-1.
  • Gøtzsche, P.C. 2015a. Commentary: Screening: A seductive paradigm that has generally failed us. International Journal of Epidemiology 244(1): 278–80. doi: 10.1093/ije/dyu267.
  • ———. 2015b. Mammography screening is harmful and should be abandoned. Journal of the Royal Society of Medicine 108(9): 341–345. doi:10.1177/0141076815602452.
  • Gøtzsche, P.C., K.L. Jørgensen, P.H. Zahl, et al. 2012. Why mammography screening has not lived up to expectations from the randomised trials. Cancer Causes Control 23:15–21 doi: 10.1007/s10552-011-9867-8.
  • Hoffman, T.C., and C. Del Mar. 2017. Clinicians’ expectations of the benefits and harms of treatments, screening, and tests: A systematic review. JAMA Internal Medicine 177(3):407–419. doi: 10.1001/jamainternmed.2016.8254.
  • Ilic, D., M.M. Neuberger, M. Djulbegovic, et al. 2013. Screening for prostate cancer. Cochrane Database of Systematic Reviews, Issue 1. Art. No.: CD004720. doi: 10.1002/14651858.CD004720.pub3.
  • Jørgensen, K.J., and P.C. Gøtzsche. 2009. Overdiagnosis in publicly organised mammography screening programmes: Systematic review of incidence trends. BMJ 339: b2587. doi: 10.1136/bmj.b2587.
  • Keating, N.L., and L.E. Pace. 2018. Breast cancer screening in 2018: Time for shared decision making. JAMA. doi:10.1001/jama.2018.3388.
  • Narod, S.A., J. Iqbal, and A.B. Miller. 2015. Why have breast cancer mortality rates declined? Journal of Cancer Policy 5: 8–17. Available online at  https://doi.org/10.1016/j.jcpo.2015.03.002.
  • Nickel, B., R. Moynihan, A. Barratt, et al. 2018. Renaming low risk conditions labelled as cancer. BMJ 362: k3322 doi: 10.1136/bmj.k3322.
  • Prasad, V., J. Lenzer, and D.H. Newman. 2016. Why cancer screening has never been shown to “save lives”—and what we can do about it. BMJ 352: h6080 doi: 10.1136/bmj.h6080.
  • Raffle, A.E., and J.A.M. Gray. 2007. Screening: Evidence and Practice. Oxford University Press.
  • Sandhu, G.S., and G.L Adriole. 2012. Overdiagnosis of prostate cancer. Journal of the National Cancer Institute Monographs (45): 146–151.
  • Stacey, D., F. Légaré, K. Lewis, et al. 2014. Decision aids for people facing health treatment or screening decisions. Cochrane Database of Systematic Reviews CD001431.doi: 10.1002/14651858.CD001431.pub5.
  • Wegwarth, O., and G. Gigerenzer. 2018. The barrier to informed choice in cancer screening: Statistical illiteracy in physicians and patients. Recent Results in Cancer Research 210: 207–221. doi: 10.1007/978-3-319-64310-6_13.
  • Wegwarth, O., L.M. Schwartz, S. Woloshin, et al. 2012. Do physicians understand cancer screening statistics? A national survey of primary care physicians in the United States. Annals of Internal Medicine 156: 340–49. doi: 10.7326/0003-4819-156-5-201203060-00005.
  • Welch, H.G., and W.C. Black. 2010. Overdiagnosis in cancer. Journal of the National Cancer Institute 102: 605–613.

Felipe Nogueira

Felipe Nogueira received his PhD in medical science from Rio Janeiro State University (UERJ). He has a master’s degree in computer science. As a science writer, Nogueira was a regular columnist for Skeptical Briefs—the newsletter of the Committee for Skeptical Inquiry. He has also made contributions to Skeptic magazine. His articles can be found at https://skepticalinquirer.org/authors/felipe-nogueira/ and http://skepticismandscience.blogspot.com/.


“Pink October” and “Blue November” are campaigns to promote awareness for breast and prostate cancer, respectively. In Brazil, as well as in other countries, the population is encouraged to do tests such as the prostate-specific antigen (PSA) for prostate cancer and mammography for breast cancer.   The main idea is screening: to perform tests in …

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