Alexandra Urman, MPH Clinical Research Manager Clinical Development IBM Watson Health 

Watson for Clinical Trial Matching Increases Enrollment in Breast Cancer Trials Interview with:

Alexandra Urman, MPH Clinical Research Manager Clinical Development IBM Watson Health 

Alexandra Urman

Alexandra Urman, MPH
Clinical Research Manager
Clinical Development
IBM Watson Health What is the background for this study? 

Response: Cancer statistics show only 3-5% of cancer patients participate in clinical trials although up to 20% may be eligible.

Dr. Tufia Hadad, a medical Oncologist at the Mayo Clinic in Rochester, Minnesota sought to address this issue and spearheaded a project conducted at the Rochester facility in collaboration with IBM Watson Health. The objective was to determine if the use of cognitive computing increased clinical trial enrollment and screening efficiency in the breast cancer clinic.

Watson for Clinical Trial Matching (CTM) is a cognitive system which utilizes natural language processing to derive patient and tumor attributes from unstructured text in the electronic health record that can be further used to match a patient to complex eligibility criteria in trial protocols.  What are the main findings?

Response: The main finding for this study was an increase in the average monthly enrollment to breast cancer trials at the Mayo Clinic Rochester by 84%. Over the 18-month period following CTM implementation, an average of 6.4 patients per month were enrolled to breast cancer systemic therapy trials compared to 3.5 patients per month prior to CTM implementation. When including accruals to breast cancer cohorts of phase I trials within the experimental therapeutics program, enrollment rates increased further from 84% to 143%. This was an increase from baseline enrollment of 3.5 patients per month to 8.5 patients per month. Time to match patients to trials with Clinical Trial Matching was faster than manual methods but variable depending on the role of the screener and the depth of the matching required by the trial. What should readers take away from your report?

Response: Implementation of the Watson for Clinical Trial Matching system with a screening coordinator team was associated with an increase in breast cancer clinical trial enrollment. The system enabled high volume screening in an efficient manner and promoted awareness of clinical trial opportunities within the breast oncology practice. Furthermore, the goal is for CTM to provide assistance in screening every patient that comes to the Mayo Clinic in Rochester for breast cancer consultation. What recommendations do you have for future research as a result of this work? 

Response: We would like to replicate this study with other cancer types and expand to other disease states. We have also already completed some accuracy pilot studies and would like to further those. 

Citation: ASCO 2018

Abstract: 6550: Impact of a cognitive computing clinical trial matching system in an ambulatory oncology practice.
Author(s): Tufia C. Haddad, Jane Helgeson, Katharine Pomerleau, Marissa Makey, Phillip Lombardo, Sadie Coverdill, Alexandra Urman, Melissa Rammage, Matthew P. Goetz, Nicholas LaRusso; Mayo Clinic, Rochester, MN; IBM, Houston, TX; IBM Watson Health, Somers, NY; IBM, Jacksonville, FL 

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Last Updated on June 22, 2018 by Marie Benz MD FAAD