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Clinical Utility of Multicancer Detection in Symptomatic Patients: A Decision-Making Perspective.

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Multicancer detection (MCD) blood tests show clinical utility for symptomatic patients, particularly for gynecologic and GI cancers. Optimization for specific pathways is needed, but classifier retraining is not required.

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Area of Science:

  • Oncology
  • Diagnostic Medicine
  • Health Services Research

Background:

  • Growing interest in multicancer detection (MCD) blood tests for symptomatic patients.
  • Concerns exist regarding MCD test sensitivity for ruling out cancer in symptomatic individuals without classifier retraining.

Purpose of the Study:

  • To formally assess the clinical utility of MCD testing in symptomatic patients using a diagnostic decision-making framework.
  • To evaluate MCD test performance against clinical guidelines for suspected cancer referral.

Main Methods:

  • Utilized data from the SYMPLIFY study evaluating the Galleri MCD test.
  • Extracted decision thresholds from National Institute for Health and Care Excellence Guideline 12.
  • Estimated clinical utility via Bayesian decision curve analysis.

Main Results:

  • The Galleri MCD test demonstrated a 99.4% probability of clinical utility, avoiding 18,005 unnecessary referrals per 100,000 patients at a 3% threshold.
  • High utility was found for gynecologic, lower GI, and upper GI pathways, avoiding 25,414–62,501 unnecessary referrals.
  • Negligible utility was observed for rapid diagnostic center and lung pathways, with varying sensitivity requirements across pathways.

Conclusions:

  • Clinical utility of MCD testing in symptomatic UK patients is pathway-dependent, showing favorability for gynecologic and GI cancers.
  • Pathway-specific optimization of MCD tests should prioritize clinical utility.
  • Retraining machine learning classifiers is not necessary for future MCD test optimization.