Influence of study features and methods on overdiagnosis estimates in breast and prostate cancer screening

Abstract

Knowledge of the likelihood that a screening-detected case of cancer has been overdiagnosed is vitally important to make treatment decisions and develop screening policy. An overdiagnosed case is an excess case detected by screening. Estimates of the frequency of overdiagnosis in breast and prostate cancer screening vary greatly across studies. This article identifies features of overdiagnosis studies that influence results and shows their effect by using published research. First, different ways to define and measure overdiagnosis are considered. Second, contextual features and how they affect overdiagnosis estimates are examined. Third, the effect of estimation approach is discussed. Many studies use excess incidence under screening as a proxy for overdiagnosis. Others use statistical models to make inferences about lead time or natural history and then derive the corresponding fraction of cases that are overdiagnosed. This article concludes with questions that readers of overdiagnosis studies can use to evaluate the validity and relevance of published estimates and recommends that authors of studies quantifying overdiagnosis provide information about these features.

Figure 1

Link between overdiagnosis and lead time. A non-overdiagnosed case (upper panel) is a screen-detected case who would have presented clinically before dying of non-cancer causes. An overdiagnosed case (lower panel) is a screen-detected case who would have died of non-cancer causes before presenting clinically, i.e., a screen-detected case who would not have been diagnosed without screening. The lead time is the time from screen detection to clinical diagnosis. The longer the lead time, the greater the chance of overdiagnosis. Similarly, the higher the risk of other-cause death, the greater the chance of overdiagnosis.

Figure 2

Incidence trends following the introduction of screening in three scenarios with the same baseline incidence (constant 100 cases per 100,000 individuals per year), disease prevalence, test sensitivity, and screening test dissemination. (1) Lead time equals 1 year, no overdiagnosis. (B) Lead time equals 2 years, no overdiagnosis (c) Lead time (among non-overdiagnosed cases) equals 2 years, 3 screen-detected cases overdiagnosed per 13 screen-detected cases (23%). In each panel, the number of cases per 100,000 screen-detected each year is preceded by a plus sign. The number of deficits in incidence each year, due to earlier detection by screening, is preceded by a minus sign.