Using Semi-Markov Processes to Study Timeliness and Tests used in the Diagnostic Evaluation of Suspected Breast Cancer
Rebecca A. Hubbard, Jane Lange, Yue Zhang, Bob A. Salim, Jonathan R. Stroud and Lurdes Y. T. Inoue
University of Pennsylvania, Fred Hutchinson Cancer Center, University of Utah, University of Washington, Georgetown University and University of Washington
November 2016
Diagnostic evaluation of suspected breast cancer due to abnormal screening mammography results is common,
creates anxiety for women and is costly for the healthcare system. Timely evaluation with minimal use of
additional diagnostic testing is key to minimizing anxiety and cost. In this paper, we propose a Bayesian
semi-Markov model that allows for flexible, semi-parametric specification of the sojourn time distributions
and apply our model to an investigation of the process of diagnostic evaluation with mammography,
ultrasound and biopsy following an abnormal screening mammogram. We also investigate risk factors
associated with the sojourn time between diagnostic tests. By utilizing semi-Markov processes, we expand
on prior work that described the timing of the first test received by providing additional information such
as the mean time to resolution and proportion of women with unresolved mammograms after 90 days for women
requiring different sequences of tests in order to reach a definitive diagnosis. Overall, we found that
older women were more likely to have unresolved positive mammograms after 90 days. Differences in the
timing of imaging evaluation and biopsy were generally on the order of days and thus did not represent
clinically important differences in diagnostic delay.
The manuscript is available in PDF format.