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A modeling approach to derive baseline risk estimates for GRADE recommendations: Concepts, development, and results of its application to the American Society of Hematology 2019 guidelines on prevention of venous thromboembolism in surgical hospitalized patients

  • Gian Paolo Morgano
  • , Wojtek Wiercioch
  • , David R. Anderson
  • , Jan L. Brożek
  • , Nancy Santesso
  • , Feng Xie
  • , Adam Cuker
  • , Robby Nieuwlaat
  • , Elie A. Akl
  • , Andrea J. Darzi
  • , Juan José Yepes-Nuñez
  • , Itziar Exteandia-Ikobaltzeta
  • , Maryam Rahman
  • , Anita Rajasekhar
  • , Frederick Rogers
  • , Kari A.O. Tikkinen
  • , Adolph J. Yates
  • , Philipp Dahm
  • , Holger J. Schünemann
  • McMaster University
  • Dalhousie University
  • University of Pennsylvania
  • American University of Beirut
  • Universidad de los Andes Colombia
  • University of Florida
  • University of Helsinki
  • South Karelian Central Hospital
  • University of Pittsburgh
  • Minneapolis VA Healthcare System
  • University of Minnesota Twin Cities

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: The goal of this study was to develop an approach that can be used where baseline risk estimates that are directly applicable to prioritized patient-important outcomes are not available from published studies. Study design: The McMaster University GRADE Centre and the ASH guideline panel for the prevention of VTE in surgical patients developed a modeling approach based on explicit assumptions about the distribution of symptoms, anatomical location, and severity of VTE events. Results: We applied the approach to derive modeled estimates of baseline risk. These estimates were used to calculated absolute measures of anticipated effects that informed the discussion of the evidence and the formulation of 30 guideline recommendations. Conclusion: Our approach can assist guideline developers facing a lack of information about baseline risk estimates that directly apply to outcomes of interest. The use of modeled estimates increases transparency in the process and makes the baseline risk used by guideline experts explicit during their decision-making.

Original languageEnglish
Pages (from-to)69-78
Number of pages10
JournalJournal of Clinical Epidemiology
Volume140
DOIs
StatePublished - Dec 2021

Keywords

  • Absolute effects
  • Baseline risk
  • Clinical practice guidelines
  • GRADE
  • Modeling approach
  • Surrogate estimates

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