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A framework for developing PICO research questions with subgroups in clinical practice guidelines.

Emily T Vella1, Fulvia Baldassarre2, Ivan D Florez1

  • 1Department of Oncology, McMaster University, Hamilton, Ontario, Canada; Program in Evidence-Based Care, Ontario Health (Cancer Care Ontario), Hamilton, Ontario, Canada.

Journal of Clinical Epidemiology
|April 17, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a framework to improve research questions for clinical practice guidelines, ensuring better consideration of tests like diagnostic, prognostic, and predictive ones. It helps guideline developers create more trustworthy recommendations by structuring question development.

Keywords:
Clinical practice guidelineDiagnosisPICOPrognosisResearch questionSubgroupSystematic review

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Area of Science:

  • Clinical practice guideline development
  • Evidence-based medicine
  • Health research methodology

Background:

  • Developing research questions for clinical practice guidelines (CPGs) is complex, particularly for test-related inquiries.
  • Current methods often overlook subgroup interactions for prognostic and predictive tests, potentially compromising evidence quality.
  • Existing approaches inadequately address the nuances of research questions involving prognostic and predictive tests.

Purpose of the Study:

  • To present a comprehensive framework for developing research questions on the benefits and harms of interventions and tests.
  • To support the creation of questions for diagnostic, prognostic, and predictive tests.
  • To emphasize the PICO format, subgroup definition, and ideal study designs in question development.

Main Methods:

  • A framework was developed through online brainstorming sessions with guideline methodologists and a clinician.
  • The framework was refined through review and input from experienced methodologists.
  • It was applied in developing a Methods Guide for the Program in Evidence-based Care at McMaster University.

Main Results:

  • Research questions are categorized into interventions and tests (diagnostic, prognostic, predictive).
  • The framework details defining characteristics, ideal study designs, and examples for each category.
  • It provides a structured approach for generating appropriate research questions and identifying key parameters.

Conclusions:

  • The framework streamlines research question development for guideline creators.
  • It enhances the quality and trustworthiness of clinical practice guideline recommendations.
  • It facilitates the anticipation of relevant studies for inclusion in guidelines.