Optimal Timing for Cancer Screening and Adaptive Surveillance Using Mathematical Modeling.

ABSTRACT: Cancer screening and early detection efforts have been partially successful in reducing incidence and mortality, but many improvements are needed. Although current medical practice is informed by epidemiologic studies and experts, the decisions for guidelines are ultimately ad hoc. We propose here that quantitative optimization of protocols can potentially increase screening success and reduce overdiagnosis. Mathematical modeling of the stochastic process of cancer evolution can be used to derive and optimize the timing of clinical screens so that the probability is maximal that a patient is screened within a certain "window of opportunity" for intervention when early cancer development may be observable. Alternative to a strictly empirical approach or microsimulations of a multitud

SUBMITTER: Curtius K 

PROVIDER: S-EPMC7611607 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature