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A ROC (Receiver Operating Characteristic) plot is a graphical tool used to assess the performance of a binary classification model by illustrating the trade-off between sensitivity (true positive rate) and specificity (false positive rate). By plotting sensitivity against 1 - specificity across various threshold settings, the ROC curve shows how well the model distinguishes between classes, with a curve closer to the top-left corner indicating a more accurate model. The area under the ROC curve...
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Assessing Diagnostic Tests II: Grading on a Curve.

Daniel C Jupiter1

  • 1Assistant Professor, Department of Preventive Medicine and Community Health, University of Texas Medical Branch, Galveston, TX.

The Journal of Foot and Ankle Surgery : Official Publication of the American College of Foot and Ankle Surgeons
|May 16, 2015
PubMed
Summary

This article discusses introducing new diagnostic tests to replace gold standards. It explains how to assess a group of diagnostics and select the best option.

Keywords:
area under the curvediagnostic testgold standardreceiver operating characteristic (ROC) curve

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Area of Science:

  • Medical Diagnostics
  • Biomedical Engineering
  • Clinical Laboratory Science

Background:

  • Established diagnostic tests are often considered gold standards.
  • Introducing novel diagnostic technologies requires rigorous assessment.
  • Evaluating a new test's performance against a gold standard is crucial.

Purpose of the Study:

  • To provide guidance on assessing new diagnostic tests.
  • To outline methods for evaluating a family of related diagnostic tests.
  • To describe strategies for selecting the optimal diagnostic test within a group.

Main Methods:

  • Discusses frameworks for comparative diagnostic test evaluation.
  • Explains methodologies for assessing diagnostic test families.
  • Highlights criteria for choosing the best performing diagnostic within a class.

Main Results:

  • Provides a structured approach to introducing new diagnostics.
  • Offers methods for evaluating multiple related diagnostic tests simultaneously.
  • Identifies key factors in selecting an optimal diagnostic test.

Conclusions:

  • A systematic approach is necessary for adopting new diagnostic tests.
  • Evaluating a family of diagnostics allows for comprehensive assessment.
  • Choosing the best family member ensures optimal clinical utility.