Using decision analysis to model cancer surveillance
Cancer management includes surveillance of patients after treatment. Such programs become increasingly important since chances of survival after cancer treatment and, thus, disease-free survival rates are continuing to increase. Surveillance programs are also time-consuming and, in addition, a very expensive component of clinical activity since frequent testing is often involved. The choice of a surveillance program is complex and should ideally consider aspects of survival, quality of life, the burden of surveillance tests, and financial costs. As for all clinical decisions, the choice involves a condition of uncertainty. This uncertainty originates from relationships between diagnostic information and the presence of disease, uncertainty about the effects of early treatment, and ambiguity in clinical information.
|Keywords||Analysis, CEA, Decision node, Models, Surveillance strategies|
|Persistent URL||dx.doi.org/10.1007/978-1-60327-969-7_3, hdl.handle.net/1765/101775|
van Kessel, K.E.M, Geurts, S.M.E. (Sandra M.E.), Verbeek, A.L.M, & Steyerberg, E.W. (2013). Using decision analysis to model cancer surveillance. In Patient Surveillance After Cancer Treatment (pp. 15–29). doi:10.1007/978-1-60327-969-7_3