Using a novel PSMA-PET and PSA-based model to enhance the diagnostic accuracy for clinically significant prostate cancer and avoid unnecessary biopsy in men with PI-RADS ≤ 3 MRI.

Introduction The diagnostic evaluation of men with suspected prostate cancer (PCa) yet inconclusive MRI (PI-RADS ≤ 3) presents a common clinical challenge. [68Ga]Ga-labelled prostate-specific membrane antigen ([68Ga]Ga-PSMA) positron emission tomography/computed tomography (PET/CT) has shown promise in identifying clinically significant PCa (csPCa). We aim to establish a diagnostic model incorporating PSMA-PET to enhance the diagnostic process of csPCa in PI-RADS ≤ 3 men.Materials And Methods This study retrospective included 151 men with clinical suspicion of PCa and PI-RADS ≤ 3 MRI. All men underwent [68Ga]Ga-PSMA PET/CT scans and ultrasound/MRI/PET fusion-guided biopsies. csPCa was defined as Grade Group ≥ 2. PRIMARY-scores from PSMA-PET scans were evaluated. A diagnostic model incorporating PSMA-PET and prostate-specific antigen (PSA)-derived parameters was developed. The discriminative performance and clinical utility were compared with conventional methods. Internal validation was conducted using a fivefold cross-validation with 1000 iterations.Results In this PI-RADS ≤ 3 cohort, areas-under-the-curve (AUCs) for detecting csPCa were 0.796 (95%CI, 0.738-0.853), 0.851 (95%CI, 0.783-0.918) and 0.806 (95%CI, 0.742-0.870) for PRIMARY-score, SUVmax and routine clinical PSMA-PET assessment, respectively. The diagnostic model comprising PRIMARY-score, SUVmax and serum free PSA/total PSA (fPSA/tPSA) achieved a significantly higher AUC of 0.906 (95%CI, 0.851-0.961) compared to strategies based on PRIMARY-score or SUVmax (P < 0.05) and markedly superior to conventional strategies typically based on PSA density (P < 0.001). The average fivefold cross-validated AUC with 1000 iterations was 0.878 (95%CI, 0.820-0.954). Theoretically, using a threshold of 21.6%, the model could have prevented 78% of unnecessary biopsies while missing only 7.8% of csPCa cases in this cohort.Conclusions A novel diagnostic model incorporating PSMA-PET derived metrics-PRIMARY-score and SUVmax-along with serum fPSA/tPSA, has been developed and validated. The integrated model may assist clinical decision-making with enhanced diagnostic accuracy over the individual conventional metrics. It has great potential to reduce unnecessary biopsies for men with PI-RADS ≤ 3 MRI results and warrants further prospective and external evaluations.

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Publication Details

Journal
Open Access CRIS of the University of Bern
Published
2024-11-19
DOI
https://doi.org/10.48620/76329
Primary Topic
Prostate Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
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article

Using a novel PSMA-PET and PSA-based model to enhance the diagnostic accuracy for clinically significant prostate cancer and avoid unnecessary biopsy in men with PI-RADS ≤ 3 MRI.

Open Access CRIS of the University of Bern
Prostate Cancer Diagnosis and Treatment
article

Using a novel PSMA-PET and PSA-based model to enhance the diagnostic accuracy for clinically significant prostate cancer and avoid unnecessary biopsy in men with PI-RADS ≤ 3 MRI.

article en

Abstract

Introduction The diagnostic evaluation of men with suspected prostate cancer (PCa) yet inconclusive MRI (PI-RADS ≤ 3) presents a common clinical challenge. [68Ga]Ga-labelled prostate-specific membrane antigen ([68Ga]Ga-PSMA) positron emission tomography/computed tomography (PET/CT) has shown promise in identifying clinically significant PCa (csPCa). We aim to establish a diagnostic model incorporating PSMA-PET to enhance the diagnostic process of csPCa in PI-RADS ≤ 3 men.Materials And Methods This study retrospective included 151 men with clinical suspicion of PCa and PI-RADS ≤ 3 MRI. All men underwent [68Ga]Ga-PSMA PET/CT scans and ultrasound/MRI/PET fusion-guided biopsies. csPCa was defined as Grade Group ≥ 2. PRIMARY-scores from PSMA-PET scans were evaluated. A diagnostic model incorporating PSMA-PET and prostate-specific antigen (PSA)-derived parameters was developed. The discriminative performance and clinical utility were compared with conventional methods. Internal validation was conducted using a fivefold cross-validation with 1000 iterations.Results In this PI-RADS ≤ 3 cohort, areas-under-the-curve (AUCs) for detecting csPCa were 0.796 (95%CI, 0.738-0.853), 0.851 (95%CI, 0.783-0.918) and 0.806 (95%CI, 0.742-0.870) for PRIMARY-score, SUVmax and routine clinical PSMA-PET assessment, respectively. The diagnostic model comprising PRIMARY-score, SUVmax and serum free PSA/total PSA (fPSA/tPSA) achieved a significantly higher AUC of 0.906 (95%CI, 0.851-0.961) compared to strategies based on PRIMARY-score or SUVmax (P < 0.05) and markedly superior to conventional strategies typically based on PSA density (P < 0.001). The average fivefold cross-validated AUC with 1000 iterations was 0.878 (95%CI, 0.820-0.954). Theoretically, using a threshold of 21.6%, the model could have prevented 78% of unnecessary biopsies while missing only 7.8% of csPCa cases in this cohort.Conclusions A novel diagnostic model incorporating PSMA-PET derived metrics-PRIMARY-score and SUVmax-along with serum fPSA/tPSA, has been developed and validated. The integrated model may assist clinical decision-making with enhanced diagnostic accuracy over the individual conventional metrics. It has great potential to reduce unnecessary biopsies for men with PI-RADS ≤ 3 MRI results and warrants further prospective and external evaluations.

Open Access CRIS of the University of Bern
Exponent (United States) (US)
Reduced inequalities
Openalex Percentile: Top 51%
Prostate Cancer Diagnosis and Treatment
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