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An R-Based Landscape Validation of a Competing Risk Model
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Prognosis Research Strategy (PROGRESS) 3: prognostic model research.

Ewout W Steyerberg1, Karel G M Moons, Danielle A van der Windt

  • 1Department of Public Health, Erasmus MC, Rotterdam, Netherlands.

Plos Medicine
|February 9, 2013
PubMed
Summary
This summary is machine-generated.

This review covers the development, validation, and practical impact of prognostic models in medicine. It aims to improve the clinical use of these important tools for better patient outcomes.

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Area of Science:

  • Medical Informatics
  • Clinical Epidemiology
  • Health Services Research

Background:

  • Prognostic models are frequently developed but infrequently used in clinical practice.
  • Limited uptake hinders the potential benefits of these models for patient care.

Purpose of the Study:

  • To review the development and validation processes for prognostic models.
  • To discuss methods for assessing the impact of prognostic models on clinical practice and patient outcomes.

Main Methods:

  • Literature review of prognostic model development and validation.
  • Discussion of impact assessment strategies for clinical tools.
  • Illustration with practical examples from medical literature.

Main Results:

  • Prognostic models require rigorous development and validation.
  • Assessing the real-world impact on practice and outcomes is crucial for adoption.
  • Examples demonstrate the application and evaluation of these models.

Conclusions:

  • Effective development and validation are prerequisites for prognostic model utility.
  • Demonstrating impact on practice and patient outcomes is key to successful implementation.
  • Further research should focus on bridging the gap between model development and clinical application.