Optimal breast biopsy decision-making based on mammographic features and demographic factors

Jagpreet Chhatwal*, Oguzhan Alagoz, Elizabeth S. Burnside

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

78 Scopus citations

Abstract

Breast cancer is the most common non-skin cancer affecting women in the United States, where every year more than 20 million mammograms are performed. Breast biopsy is commonly performed on the suspicious findings on mammograms to confirm the presence of cancer. Currently, 700,000 biopsies are performed annually in the U.S.; 55%-85% of these biopsies ultimately are found to be benign breast lesions, resulting in unnecessary treatments, patient anxiety, and expenditures. This paper addresses the decision problem faced by radiologists: When should a woman be sent for biopsy based on her mammographic features and demographic factors? This problem is formulated as a finite-horizon discrete-time Markov decision process. The optimal policy of our model shows that the decision to biopsy should take the age of patient into account; particularly, an older patient's risk threshold for biopsy should be higher than that of a younger patient. When applied to the clinical data, our model outperforms radiologists in the biopsy decision-making problem. This study also derives structural properties of the model, including sufficiency conditions that ensure the existence of a control-limit type policy and nondecreasing control-limits with age.

Original languageEnglish (US)
Pages (from-to)1577-1591
Number of pages15
JournalOperations Research
Volume58
Issue number6
DOIs
StatePublished - Nov 2010
Externally publishedYes

ASJC Scopus subject areas

  • Computer Science Applications
  • Management Science and Operations Research

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