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Introduction: The ability of prostate-specific antigen density (PSAD) to predict metastatic disease on prostate-specific membrane antigen-positron emission tomography (PSMA-PET) at initial staging in high-risk prostate cancer (PCa) for men with negative conventional imaging is unclear. We hypothesized that there might be a PSAD cutoff below which PSMA-PET would be unnecessary, as it would so rarely identify metastatic disease.
Methods: A retrospective cohort study of all men receiving F-DCFPyl PSMA PET for primary staging between January 2018 and December 2022 at the University Health Network was performed. Student's t-tests or Mann-Whitney U tests were used to compare continuous variables by PSMA-PET positivity status. Receiver operating characteristic curve analysis to compare PSA and PSAD performance and Chi-squared automatic interaction detector methodologies were used to identify predictors of metastatic disease.
Results: A total of 140 men with high-risk PCa and negative conventional imaging were included. The median age was 68 years (interquartile range [IQR] 63-74). Median PSA and PSAD were 13.9 (IQR 6.9-29.5) and 0.36 ng/ml (IQR 0.19-0.83), respectively. PSMA-PET was positive in 40% of cases for metastatic disease. The area under the curve (AUC) to predict metastatic disease on PSMA-PET was 0.55 for PSAD (p=0.57). Patients with metastatic disease on PSMA-PET had higher Gleason grade group (GG) scores on biopsy (53 vs. 20% GG5, p<0.001) and more extraprostatic extension (19 vs. 6%, p=0.03) and perineural invasion (65 vs. 45%, p=0.03).
Conclusions: In this retrospective cohort, PSAD does not reliably predict which patients with high-risk PCa and negative conventional imaging will have metastatic disease unveiled by PSMA-PET.
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http://dx.doi.org/10.5489/cuaj.9113 | DOI Listing |
Cancer Metastasis Rev
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Institute for Integrative Biology of the Cell (I2BC), Université Paris-Saclay, CEA, CNRS, Gif-Sur-Yvette, 91198, France.
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School of Cancer Sciences, University of Glasgow, Glasgow, UK; Cancer Research UK Scotland Institute, Glasgow, UK. Electronic address:
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