Use Data for Personalized Cancer Care

Women Leading Research: Margrét Bjarnadóttir

SMITH BRAIN TRUST – A new predictive app that culls through medical data can offer a better answer to many cancer patients’ top question: “What’s my prognosis?” Having an accurate answer helps patients choose the treatment or care that will work best for them, and it helps doctors and hospitals make better recommendations and plans.

Professor Margrét Bjarnadóttir, at the University of Maryland’s Robert H. Smith School of Business, and a team of researchers developed the app and patient-specific prediction method. They used a comprehensive dataset from all colorectal cancer patients in California, choosing that disease because of its prevalence – the third most common cancer in the U.S. – and its varying treatment options and outcomes. Bjarnadóttir and her co-authors used the data to create predictive models to estimate short-term and medium-term survival probabilities for patients based on their clinical and demographic information.

Currently, almost half of colorectal cancer patients receive no prognosis information from their doctors, and the predictions they do receive are often inaccurate or biased, according to the researchers. They contend that using predictive modeling and visualization tools makes prognosis information easier for doctors to present and patients to understand. They say having accurate information about their prognosis helps patients make better decisions about their course of care, lessens uncertainty, and increases their satisfaction with their doctors.

The researchers also say using predictive tools can save health care dollars by reducing the tendency many doctors have to overprescribe and over treat conditions that won’t see any benefit to those actions. Typical colorectal treatments include surgery, chemotherapy and radiation, which have risks and often-severe side effects, but may not improve outcomes for a patient. Hospitals can also use the predictions to anticipate loads on their systems and adjust staffing levels accordingly and make better resource allocations for things like surgical facilities, beds and equipment. 

The researchers say their app is a user-friendly tool to help doctors and patients have better conversations about treatment options and outcomes, and a solution that could be applied to many other types of cancer and medical diagnoses. The app takes a patient’s information and displays both predicted survival curves and the actual survival data for the 20 most similar patients in the database to help the patient understand the possible range of outcomes to make better treatment decisions.

“We have provided a roadmap for modeling disease outcomes based on existing data,” write the researchers in a working paper detailing their study. “These models provide an unbiased view of the likely trajectory of a patient’s disease, offering patients and providers a base for data-driven decision making that personalizes treatment and improves quality of care.”

Margrét Bjarnadóttir is an Assistant Professor of Management Science and Statistics in the Department of Decisions, Operations and Information Technologies at the University of Maryland's Robert H. Smith School of Business.

Research interests: Operations research methods using large-scale data. Her work spans applications ranging from analyzing nationwide cross-ownership patterns and systemic risk in finance to drug surveillance and practice patterns in health care.

Selected accomplishments: Winner of the Smith School’s Top 15 Percent Teaching Award in 2013; papers published in Operations Research, The European Journal of Operations Research, IIE transactions on Health Care Systems, Pharmaco Economics and more.

About this series: The Smith School faculty is celebrating Women’s History Month 2018 in partnership with ADVANCE, an initiative to transform the University of Maryland by investing in a culture of inclusive excellence. Daily faculty spotlights support activities from the school’s Office of Diversity Initiatives, starting with the seventh annual Women Leading Women forum on March 1, 2018.

Other fearless ideas from:  Rajshree Agarwal  |  Ritu Agarwal  |  T. Leigh Anenson  |  Kathryn M. Bartol  |  Christine Beckman  |  Margrét Bjarnadóttir  |  M. Cecilia Bustamante  |  Jessica M. Clark  |  Rellie Derfler-Rozin  |  Waverly Ding  |  Wedad J. Elmaghraby  |  Rosellina Ferraro  |  Rebecca Hann  | Amna Kirmani  |  Hanna Lee  |  Hui Liao  |  Jennifer Carson Marr  |  Wendy W. Moe  |  Courtney Paulson  |  Louiqa Raschid  |  Rebecca Ratner  |  Debra L. Shapiro  |  M. Susan Taylor  |  Niratcha (Grace) Tungtisanont  |  Vijaya Venkataramani  |  Janet Wagner  |  Yajin Wang  |  Yajun Wang  |  Liu Yang  |  Jie Zhang  |  Lingling Zhang

Photo credit: Makistock