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Area of Science:

  • Oncology
  • Genomics
  • Medical Diagnostics

Background:

  • Multi-cancer early detection (MCED) blood tests identify signals from various cancer types, including rare ones lacking screening.
  • Post-signal detection, a diagnostic process is crucial to confirm cancer status.
  • Current MCED tests predict a cancer signal origin (CSO) to guide this diagnostic workup.

Purpose of the Study:

  • To extend a model for MCED cancer screening by incorporating predicted CSO categories.
  • To develop a model of the diagnostic chain to predict outcomes based on CSO.
  • To evaluate the diagnostic utility of CSO predictions in diverse clinical risk populations.

Main Methods:

  • An existing MCED cancer screening model was enhanced with predicted CSO categories.
  • A simplified model of the diagnostic chain was integrated.
  • Outcomes of the diagnostic chain were predicted for each CSO and across populations with varying risk factors.

Main Results:

  • Typical positive predictive values exceeded 40%.
  • Diagnostic workup was generally warranted for any CSO prediction (positive predictive value >7%).
  • Continued workup for cancers outside the predicted CSO was justifiable, demonstrating clinical utility.

Conclusions:

  • CSO predictions from MCED tests support diagnostic workup, potentially improving efficiency.
  • The model indicates a conditional benefit warranting diagnostic workup for any MCED-derived CSO prediction.
  • Further research is needed to confirm MCED's impact on mortality reduction.