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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Introduction: Nowadays, invasive prostate biopsy is the standard diagnostic test for patients with suspected prostate cancer (PCa). However, it has some shortcomings such as perioperative complications, economic and psychological burden on patients, and some patients may undergo repeated prostate biopsy. In this study protocol, our aim is to provide a non-invasive diagnostic strategy we call the 'prostate-specific membrane antigen (PSMA) combined model' for the diagnosis of PCa. If patients are diagnosed with PCa using PSMA combined model, we want to prove these patients can receive radical prostatectomy directly without prior prostate biopsies.
Methods: The SNOTOB trial adopts a prospective, single-centre, single-arm, open-label study design. The PSMA combined model consists of a diagnostic model based on what we previously reported and F-PSMA-1007 positron emission tomography/CT (F-PSMA-1007 PET/CT) examinations in series. First, patients use the diagnostic model (online address: https://ustcprostatecancerprediction.shinyapps.io/dynnomapp/) to calculate the risk probability of clinically significant PCa (csPCa). When the risk probability of csPCa is equal or greater than 0.60, F-PSMA-1007 PET/CT will be applied for further diagnosis. If patients are still considered as csPCa after F-PSMA-1007 PET/CT examinations, we define this condition as positive results of PSMA combined model. Subsequently, we will recommend these patients to accept radical prostatectomy without prostate biopsy directly. Finally, the diagnostic performance of PSMA combined model will be verified with the pathological results. Totally, 57 patients need to be enrolled in this clinical trial.
Ethics And Dissemination: This study was approved by the ethics committee of The First Affiliated Hospital of USTC (No. 2022KY-142). The results of this study will be published in peer-reviewed journals and reported at academic conferences.
Trial Registration Number: NCT05587192.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10660686 | PMC |
http://dx.doi.org/10.1136/bmjopen-2023-073983 | DOI Listing |
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