A monte carlo simulation approach to the characterization of uncertainties in cancer staging and radiation treatment decisions
2007
J Oper Res Soc
2
58
177-185
Journal_Article
Medical_Oncology||Medical_Errors
Simulation_Monte_carlo_methods
Operational_Online
No
No
Article Link
Ekaette, E. L., R. C.; Kelly, K. L.; Dunscombe, P. (2007). A Monte Carlo simulation approach to the characterization of uncertainties in cancer staging and radiation treatment decisions. [Journal Article]. J Oper Res Soc, 58(2), 177-185.
Radiation treatment (RT) for cancer is a critical medical procedure that occurs in a complex environment that is subject to uncertainties and errors. We employed a simulation (a variant of Monte Carlo) model that followed a cohort of hypothetical breast cancer patients to estimate the probability of incorrect staging and treatment decisions. As inputs, we used a combination of literature information and expert judgement. Input variables were defined as probability distributions within the model. Uncertainties were propagated via simulation. Sensitivity and value-of-information analyses were then conducted to quantify the effect of variable uncertainty on the model outputs. We found a small but non-trivial probability that patients would be incorrectly staged and thus be subjected to inappropriate treatment. Some routinely used tests for staging and metastasis detection have very limited informational value. This work has implications for the methods used in cancer staging and subsequent risk assessment of treatment errors.