Abstract 5271
Background
Clinical trials improve our knowledge of diseases and treatments while providing patients access to investigational agents. However, approximately 3% of newly diagnosed cancer patients are enrolled in clinical trials in the United States. Identifying an appropriate trial for a patient is time-consuming and cumbersome in the busy clinical practice. The Watson for Clinical Trial Matching (CTM) cognitive system uses AI to derive patient and cancer-related attributes from structured and unstructured text found in the electronic health record. These attributes are matched to complex eligibility criteria in clinical trial protocols.
Methods
In April 2019, a pilot study was launched to test the feasibility of implementing CTM in Gastrointestinal (GI) oncology at Mayo Clinic in Rochester, MN. Two clinical research coordinators (CRCs) screened patients for potential clinical trials prior to their clinic visits using both CTM and the traditional manual screening method. To avoid bias, each CRC screened a separate set of patients by both methods alternating which methodology was used first. The clinical trial match results were blinded to both CRCs. For each method, time to complete the screen and number of potential clinical trial matches were recorded.
Results
A total of 35 GI cancer patients with new diagnosis, recent resection or restaging scans were analyzed. Patients were evaluated against 50 GI-specific drug therapy and multi-disease phase I clinical trials. Clinical trial matching using CTM took an average of 10.1 minutes (Range: 4 to 20 min) per patient compared to an average of 30.5 minutes (Range: 5 to 75 min) per patient (p < 0.0001) using the manual method. CTM identified an average of 7.66 clinical trials (Range: 0-16) while the manual screening method identified an average of 1.97 clinical trials (Range: 0 to 6) per patient (p < 0.0001).
Conclusions
Implementation of Watson for CTM system with a CRC team may enable high volume patient screening for a large number of clinical trials in an efficient manner and promote awareness of clinical trial opportunities within the GI oncology practice. Further analysis to evaluate CTM accuracy and impact on enrollment is warranted and currently underway.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Mayo Clinic.
Disclosure
T. Haddad: Advisory / Consultancy: TerSera Therapeautics; Research grant / Funding (self): Takeda. S. Coverdill: Full / Part-time employment: IBM Watson Health; Shareholder / Stockholder / Stock options: IBM. M. Rammage: Full / Part-time employment: IBM Watson Health; Licensing / Royalties: IBM. All other authors have declared no conflicts of interest.
Resources from the same session
5822 - Greek nursing students experience facing death in clinical practice
Presenter: Maria Dimoula
Session: Poster Display session 3
Resources:
Abstract
2866 - HOPEVOL: Hospice care appropriate to the wishes and needs of patients in the palliative terminal phase.
Presenter: Merel van Klinken
Session: Poster Display session 3
Resources:
Abstract
829 - Mindfulness-based stress reduction in early palliative care for advanced cancer patients : an italian single-centre study. MINDEEP
Presenter: Emilia Gianotti
Session: Poster Display session 3
Resources:
Abstract
2702 - Optimising Inpatient Oncology Care
Presenter: Lisa Judge
Session: Poster Display session 3
Resources:
Abstract
1527 - Analysis on the Implementation Results of Family Sickbed for Oncology Patients in Dongshi Township Health Centers from 2015 to 2017
Presenter: Yayu Huang
Session: Poster Display session 3
Resources:
Abstract
2054 - Exploring needs for palliative care and quality of life for oncology patients with advanced disease who undergo radiotherapy
Presenter: Foteini Antonopoulou
Session: Poster Display session 3
Resources:
Abstract
5605 - Cytotoxic contamination in cancer care settings – Risks and safety awareness among cancer nurses
Presenter: Sandra Lundman Vikberg
Session: Poster Display session 3
Resources:
Abstract
5769 - Understanding Chemotherapy - group education sessions prior to commencing chemotherapy
Presenter: Aileen McHale
Session: Poster Display session 3
Resources:
Abstract
2620 - Estimation of HPQ-based absenteeism and presenteeism in cancer patients via ResearchKit
Presenter: Shunsuke Kondo
Session: Poster Display session 3
Resources:
Abstract
4705 - Identifying falls-related variables and risk factors in hospitalised cancer patients
Presenter: Maria Montserrat Martí Dillet
Session: Poster Display session 3
Resources:
Abstract