Breast cancer screening has increased among women of a certain age, therefore; breast screening is subjected to overdiagnosis. With the overdiagnosis of cancer, the mammographic detection of cancer that may not be clinically evident is not reported and without an effective method of accurately diagnosing breast cancer unneeded preventative measures, which can be invasive are taken. There are disadvantages associated with mammographic screening which includes the adverse outcomes of unnecessary cancer treatments. There is a level of uncertainty in estimating the risk of overdiagnoses in cancer screening programs and percentages can vary between 0% - 54%. This is due to several factors including different definitions of overdiagnosis, study settings, and estimation methods. For example, previous studies have estimated the frequency of overdiagnosis among all cases of diagnosed cancer and some have estimated overdiagnosis among cases of screen-detected cancer. Also, several studies evaluate overdiagnosis after the introduction of population screening. Although there are two prominent methods for estimating frequency of overdiagnosis, Dr. Ruth Etzioni and colleagues, from the Division of Public Health Sciences, utilized the lead time method to estimate the frequency of overdiagnosis. In their recent publication, the researchers estimated the frequency of breast cancer overdiagnosis using the lead-time method, accounting for progressive and nonprogressive cancer and assessing model identifiability from previous methodological work. This work was published in the Annals of Internal Medicine.
According to the authors, “the lead-time method applies a mechanistic understanding of how overdiagnosis happens because of the early detection process. It uses statistical modeling to estimate the underlying disease latency and life tables to calculate the risk for death from other causes between screen detection and the end of the latent preclinical period (before symptoms or signs).” The data utilized in this study is from the Breast Cancer Surveillance Consortium (BCSC), which is a highly respected data source for breast cancer screening and outcomes in the US. The analysis included 35,986 women who had mammographic screenings. A bayesian learning algorithm was utilized to identify parameter values that matched observed data patterns. The Etzioni Group defined the outcome (rate of breast cancer diagnosis) as the proportion of screen-detected cases that were nonprogressive or progressive but would not have progressed to clinical disease before death.
The researchers found that 1 in 7 screen-detected cases would be overdiagnosed. Higher numbers of mammographic screenings women received had a minimal effect on the number of screen-detected cancers, this is because the estimated tumor latency was greater than 2 years. Among the over diagnosed cancers who underwent biennial screenings, one third of the overdiagnosed cases occurred because of the detection of nonprogressive cancer and two thirds were because of to the detection of progressive cancer that would not have progressed to clinical disease before death.
The Etzioni group explained the importance of their work, “Our work adds to the collection of modeling studies that have augmented the purely progressive disease model by adding nonprogressive cases.” The Etzioni group concluded, “we find that the rate of overdiagnosis in U.S. population-based mammography screening is unlikely to be as high as suggested by prominent excess-incident studies. We hope that our findings will bring the field closer to a consensus estimate and facilitate decision making about mammography screening. Our estimates of the frequency and the age dependence of overdiagnosis [50-74 years old] can be provided along with information about false-positive rates to balance estimates of mammography screening benefits as a part of a process of shard and informed decision making.”
This research was supported by the National Institutes of Health, the National Cancer Institute, and the Patient Centered Outcomes Research Institute.
Fred Hutch/UW Cancer Consortium members Lurdes Inoue and Ruth Etzioni contributed to this work.
Ryser MD, Lange J, Inoue LY, O’Meara ES, Gard C, Miglioretti DL, Bulliard JL, Brouwer AF, Hwang ES, Etzioni RB. 2022. Estimation of breast cancer overdiagnosis in a US breast screening cohort. Annals of Internal Medicine. Online ahead of print.