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  11. The Efficacy Of Different Biomarkers And Endpoints To Refine Referrals For Suspected Prostate Cancer: The Target Study (tiered Integrated Tests For Early Diagnosis Of Clinically Significant Prostate Tumours)

The efficacy of different biomarkers and endpoints to refine referrals for suspected prostate cancer: the TARGET study (Tiered integrAted tests for eaRly diaGnosis of clinically significant ProstatE Tumours)

Artitaya Lophatananon1, Kenneth R Muir1, Vincent J Gnanapragasam2,3

  • 1Division of Population Health, Health Services Research & Primary Care, University of Manchester, Manchester, UK.

BMC Medicine
|October 8, 2024

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Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy
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View abstract on PubMed

Summary
This summary is machine-generated.

Biomarkers like Prostate Health Index (phi) and PSA density (PSAd) can help reduce unnecessary prostate cancer investigations after a raised PSA test. These markers are particularly useful when defining clinically significant cancer using prognostic endpoints.

Area of Science:

  • Urology
  • Oncology
  • Biomarker Discovery

Background:

  • Elevated Prostate-Specific Antigen (PSA) levels often lead to tertiary investigations for prostate cancer.
  • Many men undergo unnecessary MRI scans and biopsies following a raised PSA.
  • There is a need to refine referral criteria for tertiary investigations.

Purpose of the Study:

  • To compare different biomarkers for refining tertiary referrals in suspected prostate cancer.
  • To evaluate biomarker performance using various definitions of clinically significant prostate cancer.

Main Methods:

  • Analysis of data and samples from 798 men with raised PSA (≥3 ng/mL) undergoing MRI-guided biopsy.
  • Exploration of biomarkers including PSA + Age, free/total PSA (FTPSA), Prostate Health Index (phi), PSA density (PSAd), and polygenic risk score (PRS).
Keywords:
BiopsyCambridge Prognostic GroupsEarly detectionFree Total PSA

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  • Evaluation of diagnostic endpoints: Grade Group 2 (GG2), GG3, Cambridge Prognostic Group 2 (CPG2), and CPG3, using logistic regression, AUC, and decision curve analysis (DCA).

    • Main Results:

    • Models incorporating phi and PSAd significantly improved prediction performance across all diagnostic endpoints compared to the base model (PSA + Age).
    • Performance gains were most notable when using composite Cambridge Prognostic Group (CPG) endpoints.
    • FTPSA and PRS did not improve predictive performance, especially for higher-grade cancers (GG3, CPG3).
    • Decision curve analysis indicated that models with PSAd and phi effectively reduced unnecessary MRI and biopsies, particularly for CPG3 disease.

    Conclusions:

    • Prostate Health Index (phi) and PSA density (PSAd) can refine patient selection for tertiary investigations after a raised PSA.
    • The incremental value of these biomarkers depends on the definition of clinical significance, showing particular utility with composite prognostic endpoints.
    MRI
    PSA
    PSA density
    Polygenic risk scores
    Prostate Health Index (phi)
    Prostate cancer