A Method for Matching Patients to Advanced Prostate Cancer Clinical Trials
Objective: To illustrate a new method for simplifying patient recruitment for advanced prostate cancer clinical trials using natural language processing techniques.
Background: The identification of eligible patients for clinical trials is a critical factor to increase patient recruitment rates and an important issue for discovery of new treatment interventions. The current practice of identifying eligible patients is highly constrained due to manual processing of disparate sources of unstructured patient data.Informatics-based approaches can simplify the complex task of evaluating patient’s eligibility for clinical trials. We show that an ontology-based approach can address the challenge of matching patients to suitable clinical trials.
Methods: The free-text descriptions of clinical trial criteria as well as patient data were analysed. A set of common inclusion and exclusion criteria was identified through consultations with expert clinical trial coordinators. A research prototype was developed using Unstructured Information Management Architecture (UIMA) that identified SNOMED concepts in the patient data and clinical trial description.
Results: Our experimental research prototype describes a semi-automated method for filtering patient records using common clinical trial criteria. Our method simplified the patient recruitment process. The discussion with clinical trial coordinators showed that the efficiency in patient recruitment process could be improved by 25%.
Conclusion: An UIMA-based approach can resolve complexities in patient recruitment for advanced prostate cancer clinical trials.
This work is licensed under a Creative Commons Attribution 3.0 License.
--- eJHI - electronic Journal of Health Informatics - ISSN 1446-4381 ---