Medical decision making : an international journal of the Society for Medical Decision Making
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Simulation models are essential tools for estimating benefits of cancer screening programs. Such models include a screening-effect model that represents how early detection by screening followed by treatment affects disease-specific survival. Two commonly used screening-effect models are the stage-shift model, where mortality benefits are explained by the shift to more favorable stages, and the cure model, where early detection enhances the chances of cure from disease. ⋯ The differences in predicted mortality reductions show the importance of validating models to observed trial mortality data. The stage-shift models considerably overestimated the mortality reduction. Therefore, the stage-shift models should be used with care, especially when modeling the effect of screening for cancers with long lead times, such as prostate cancer.
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Guidelines with short-term harms and long-term benefits are often applied to chronically ill patients who may not benefit. The payoff time framework has been proposed (i.e., do not apply a guideline if a patient's life expectancy (LE) is shorter than when a guideline's cumulative incremental benefits first exceed its cumulative incremental harms), but its health impact is unclear. ⋯ The payoff time framework may indicate when withholding a guideline with short-term harms and long-term benefits may increase LE and/or QALY.