Assessing screening efficacy in the presence of cancer overdiagnosis

Abstract

Cancer screening facilitates the early detection of cancer at a stage when treatment is often most effective. However, it also brings the risk of overdiagnosis, where a diagnosis made through screening would not have led to symptoms or death during the patient’s lifetime. In this paper we tackle a significant unresolved issue in the evaluation of screening efficacy: selecting primary endpoints and inferential procedures that efficiently consider potential overdiagnosis in screening trials. This is motivated by the necessity to design and analyze a phase IV Early Detection Initiative (EDI) trial for evaluating a pancreatic cancer screening strategy. We introduce two novel approaches for assessing screening efficacy, grounded on cancer stage shift. These methods address potential overdiagnosis by: (i) borrowing information about clinical diagnosis from the control arm that hasn’t undergone screening (the BR approach) and (ii) performing sensitivity analysis, contingent upon a conservative bound of the overdiagnosis magnitude (the SEN-T approach). Analytical methods and extensive simulation studies underscore the superiority of our proposed methods, demonstrating enhanced efficiency in estimating and testing screening efficacy compared to existing methods. The latter either overlook overdiagnosis or adhere to a valid, yet conservative, cumulative incidence endpoint. We illustrate the practical application of these approaches using ovarian cancer data from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. The results affirm that our methods bolster an efficient and robust study design for cancer screening trials.