TY - JOUR
T1 - Influence of study features and methods on overdiagnosis estimates in breast and prostate cancer screening
AU - Etzioni, Ruth
AU - Gulati, Roman
AU - Mallinger, Leslie
AU - Mandelblatt, Jeanne
PY - 2013/6/4
Y1 - 2013/6/4
N2 - 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.
AB - 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.
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U2 - 10.7326/0003-4819-158-11-201306040-00008
DO - 10.7326/0003-4819-158-11-201306040-00008
M3 - Article
C2 - 23732716
AN - SCOPUS:84878716848
SN - 0003-4819
VL - 158
SP - 831
EP - 838
JO - Annals of internal medicine
JF - Annals of internal medicine
IS - 11
ER -