Dynamic probabilistic model for determination of optimal timing of surveillance chest radiography in pediatric Hodgkin disease

A dynamic probabilistic model based on hazard rate analysis, Monte Carlo modeling, and lead-time estimation techniques was developed to determine the optimal timing and frequency of chest radiography in the monitoring for relapse of children with treated Hodgkin disease. The analysis incorporates the performance characteristics of chest radiography, the natural history of the disease process, and therapeutic efficacy as a function of earliness of detection in the determination of optimal strategy. Examples of the model applied to the experiences of Stanford Medical Center and St. Jude Children's Research Hospital illustrate the utility of such a model in customizing an optimal monitoring strategy for a specific institution and clinical experience. The results suggest that monitoring protocols significantly overutilize chest radiography in the evaluation for recurrent Hodgkin disease in children.