Abstract

Since the 1960s, there have been revolutionary developments in imaging technology. Undoubtedly, these advances in imaging technology have made it possible to detect most cancers much earlier than they would have presented with clinical signs or symptoms. However, there are harms from screening, including false-positive results and overdiagnosis, and the costs of screening can be substantial. Therefore, screening for cancer must be rigorously evaluated to ensure that it provides more benefit than harm at an acceptable cost. Unfortunately, the evaluation of cancer screening is difficult and susceptible to several forms of bias. Randomized clinical trials are the most valid study design for cancer screening, but they cannot be expected to answer all the questions that arise with the implementation of screening. Decision modeling can be used to extrapolate the results of randomized clinical trials to help inform public policy and individual decision making.

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