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Determining the Optimal Sequence of Multiple Tests.

Lucas Böttcher1,2, Stefan Felder3,4

  • 1Department of Computational Science and Philosophy, Frankfurt School of Finance and Management, Frankfurt am Main, Germany.

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|October 17, 2025
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Summary
This summary is machine-generated.

Optimizing medical test selection involves balancing benefits and harms. This study introduces a method to calculate the incremental net benefit (INB) of single and multiple diagnostic tests, guiding optimal test choices and sequences.

Keywords:
combination testingdiagnostic testsoptimal testingreceiver operating characteristicstest thresholdtreatment thresholdvalue of information

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Area of Science:

  • Medical Decision Making
  • Health Economics
  • Diagnostic Test Evaluation

Background:

  • Clinical decisions involve balancing treatment benefits against testing harms and costs.
  • Accurate diagnosis is crucial for effective patient management and resource allocation.

Purpose of the Study:

  • To quantify the incremental net benefit (INB) of single and multiple diagnostic tests.
  • To develop a framework for optimizing test selection and sequencing based on disease probability and cost-benefit trade-offs.

Main Methods:

  • Decomposition of INB into value of information and test-related costs/harms.
  • Analysis of aggregation functions (conjunctive, disjunctive, majority) for test combinations.
  • Application to prostate cancer, colorectal cancer, and coronary artery disease diagnostics.

Main Results:

  • Optimal test choice and sequence depend on pre-test disease probability and treatment cost-benefit ratio.
  • Decision boundaries identify optimal strategies for single, conjunctive, disjunctive, and majority test approaches.
  • Empirical data from three disease examples demonstrate the practical application of the INB framework.

Conclusions:

  • The proposed INB framework provides a comprehensive approach to optimizing diagnostic test strategies.
  • The optimal use of diagnostic tests is context-dependent, varying with disease prevalence and treatment value.
  • An online tool is available to visualize the INB for combined tests, aiding clinical decision support.