Tailored care: Breast cancer screening models earn Alagoz CAREER award
Tailoring clothing to fit a woman is a straightforward process: take measurements and alter accordingly. Similarly, tailoring breast cancer screening to fit a woman involves taking into account individual risk factors, like age and family history, and altering a mammogram schedule accordingly.
Industrial and Systems Engineering Assistant Professor Oguzhan Alagoz is developing innovative techniques to fit mammogram schedules to individual women, and his research has earned a prestigious 2009 National Science Foundation Faculty Early Career Development Award (CAREER) and $430,000 grant. CAREER awards recognize faculty members who are at the beginning of their academic careers and have developed creative projects that effectively integrate advanced research and education.
Alagoz is working to optimize breast cancer screening policies for various populations of women and optimize follow-up decisions, such as recommendations for biopsies or additional mammograms. He will explore whether a dynamic screening interval, such as testing younger women every six months (since breast cancer is more aggressive in younger women) and testing older women every two years, is a better strategy than the current static strategy that tests every woman every year after age 40. Alagoz will also examine the effects of using sensitive but expensive technologies like MRI.
In addressing these issues, Alagoz may answer complex questions about why certain demographics of women suffer from higher breast cancer mortality rates.
Alagoz’s work is the first study to use stochastic optimization techniques and clinical data to find cost-effective strategies for personalized breast cancer screening, which could reduce the number of unnecessary biopsies and short-term follow-up mammograms conducted in the United States each year. His models could also provide a framework to develop appropriate screening schedules for other cancers and diseases, such as prostate and colorectal cancers.
The larger objective of Alagoz’s work is to introduce medical researchers to engineering tools and techniques in order to solve complex problems. He frequently collaborates with medical researchers in order to explain his models and how engineering can tackle health-related problems.
An example is Alagoz’s work with Radiology Associate Professor Elizabeth Burnside to develop a breast cancer prediction model. The model relies on sequential decision techniques, which account for decisions that are made multiple times and have a cascading effect, such as an abnormal mammogram prompting a woman to have another mammogram in six months. Using this model, a radiologist could tell a woman that a mammogram abnormality has, for example, a 10 percent chance of being cancerous, so if the woman is advised to undergo a biopsy, she will understand the realistic likelihood of cancer.
The National Institutes of Health originally funded the model, and Alagoz will now expand it as part of his CAREER award.
The work has been a success, Alagoz says, because he collaborated closely with Burnside. “You must involve healthcare professionals in research like this because the math won’t work without their help, and you must use real data when it comes to health-related issues,” says Alagoz.
In addition to collaborating with healthcare professionals and researchers, Alagoz is also working to bring more engineers into healthcare by training PhD students and involving undergraduate students in his research.
“We have to remove inefficiencies from the healthcare system, and I think industrial engineering can play a big role in that,” he says. “We can truly make a difference.”