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The efficient stored specimen design for evaluating multiple screening technologies: Application to multicancer

Stuart G Baker1, Hormuzd A Katki2

  • 1Independent Researcher, Columbia, MD, USA.

Journal of Medical Screening
|December 8, 2025
PubMed
Summary
This summary is machine-generated.

The efficient stored specimen (ESS) design significantly reduces sample size for evaluating multiple multicancer detection (MCD) tests compared to standard methods. This novel approach enhances efficiency in cancer screening research.

Keywords:
Intended effectliquid biopsymulticancer detection (MCD) testrandomized trail

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Area of Science:

  • Oncology
  • Biostatistics
  • Medical Diagnostics

Background:

  • Multicancer detection (MCD) tests aim to reduce cancer mortality by screening for multiple cancers using blood specimens.
  • Developing efficient study designs is crucial for evaluating the numerous MCD tests currently under development.
  • Traditional designs for evaluating multiple MCD tests can be sample-size intensive.

Purpose of the Study:

  • To introduce and evaluate a novel study design, the efficient stored specimen (ESS) design, for assessing multiple multicancer detection (MCD) tests.
  • To compare the sample size efficiency of the ESS design against the standard stored specimen (SSS) design.
  • To develop a simple analysis method for evaluating individual MCD tests within the ESS framework.

Main Methods:

  • The efficient stored specimen (ESS) design randomizes participants to either delayed MCD testing or a single group receiving multiple immediate MCD tests.
  • The standard stored specimen (SSS) design involves randomizing participants to a control group with delayed testing or multiple groups with immediate testing.
  • Both designs utilize stored specimens, but the ESS design consolidates immediate testing into one arm.

Main Results:

  • The ESS design and SSS design have the same sample size per randomization group.
  • For evaluating *k* MCD tests, the ESS design requires only 2 randomization groups, whereas the SSS design requires *k*+1 groups of the same size.
  • This consolidation substantially reduces the overall sample size needed for the ESS design.

Conclusions:

  • The ESS design offers a significant improvement in sample size efficiency over the SSS design for evaluating multiple MCD tests.
  • This enhanced efficiency is achieved without requiring additional statistical assumptions.
  • The ESS design represents a more resource-effective approach for advancing multicancer detection test research.