A Study Protocol for a Comprehensive Evaluation of Two Artificial Intelligence-Based Tools in Title and Abstract Screening for the Development of Evidence-Based Cancer Guidelines.

Journal: Cancer innovation
Published Date: Jun 29, 2025

Abstract

BACKGROUND: Conducting a systematic review (SR) is a time-intensive process and represents the first phase in developing a clinical practice guideline (CPG). Completing a CPG through the Program in Evidence-Based Care (PEBC), a globally acknowledged guideline program supported by Ontario Health (Cancer Care Ontario), typically takes about 2 years. Thus, expediting an SR can significantly reduce the overall time required to complete a CPG. Our recently published review identified two artificial intelligence (AI) tools, DistillerSR and EPPI-Reviewer that reduced time in the title and abstract screening in an SR process when developing a CPG. However, the consistency and generalizability of these tools remain unclear within or across different SRs related to cancer. This study protocol aims to evaluate and compare the performance of DistillerSR and EPPI-Reviewer against human reviewers for title and abstract screening (Stage I screening) in cancer CPG development.

Authors

  • Xiaomei Yao
    Department of Oncology, Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada; Center for Clinical Practice Guideline Conduction and Evaluation, Children's Hospital of Fudan University, Shanghai, China. Electronic address: yaoxia@mcmaster.ca.
  • Ashirbani Saha
    Department of Radiology, Duke University School of Medicine, 2424 Erwin Road, Suite 302, Durham, NC, 27705, USA. ashirbani.saha@duke.edu.
  • Sharan Saravanan
    Faculty of Health Sciences McMaster University Hamilton Ontario Canada.
  • Ashley Low
    Faculty of Health Sciences McMaster University Hamilton Ontario Canada.
  • Jonathan Sussman
    Department of Oncology, McMaster University, Hamilton, Ontario, Canada.

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