Metastatic Versus Localized Disease as Inclusion Criteria That Can Be Automatically Extracted From Randomized Controlled Trials Using Natural Language Processing.

Journal: JCO clinical cancer informatics
PMID: 39602661

Abstract

PURPOSE: Extracting inclusion and exclusion criteria in a structured, automated fashion remains a challenge to developing better search functionalities or automating systematic reviews of randomized controlled trials in oncology. The question "Did this trial enroll patients with localized disease, metastatic disease, or both?" could be used to narrow down the number of potentially relevant trials when conducting a search.

Authors

  • Paul Windisch
    European CyberKnife Center, Munich, Germany. paul.windisch@ksw.ch.
  • Fabio Dennstädt
    Department of Radiation Oncology, Kantonsspital St. Gallen, St. Gallen, Switzerland.
  • Carole Koechli
    Department of Radiation Oncology, Cantonal Hospital Winterthur, Winterthur, Switzerland.
  • Robert Förster
    Department of Radiation Oncology, Cantonal Hospital Winterthur, Winterthur, Switzerland.
  • Christina Schröder
    Department of Radiation Oncology, Cantonal Hospital Winterthur, Winterthur, Switzerland.
  • Daniel M Aebersold
    Department of Radiation Oncology, Inselspital, Bern University Hospital, and University of Bern, Freiburgstrasse, 3010, Bern, Switzerland.
  • Daniel R Zwahlen
    Department of Radiation Oncology, Cantonal Hospital Winterthur, Winterthur, Switzerland.

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