Clinical Research Directory
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3 clinical studies listed.
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Tundra lists 3 Prostate Cancer Aggressiveness clinical trials. Each listing includes eligibility criteria, study locations, and direct links to research sites in the Tundra directory.
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NCT04052048
Active Surveillance SNEP Assay Registry Trial for Prostate Cancer
A multi-center, prospective active surveillance registry trial assessing the performance of a non-invasive blood test for indolent prostate cancer disease management.
Gender: MALE
Ages: 40 Years - 80 Years
Updated: 2026-04-02
1 state
NCT03263650
Study of Olaparib Maintenance Following Cabazitaxel-Carbo in Men With AVPC
The goal of this clinical research study is to learn if olaparib, when given after treatment with cabazitaxel, carboplatin, and prednisone, can help to control aggressive variant prostate cancer (AVPC). The safety of these drugs will also be studied. This is an investigational study. Cabazitaxel and carboplatin are FDA approved and commercially available for the treatment of certain types of prostate cancer. Prednisone is FDA-approved and commercially available as a corticosteroid. Olaparib is FDA approved and commercially available for the treatment of certain types of ovarian cancer. The combination of cabazitaxel and carboplatin followed by olaparib in this study is investigational. The study doctor can describe how the study drugs are designed to work. Up to 96 participants will be enrolled on this study. All will take part at MD Anderson.
Gender: MALE
Ages: 18 Years - Any
Updated: 2026-02-17
1 state
NCT06662708
Artificial Intelligence Models for Precision Prediction and Treatment of Prostate Cancer
The aim of this clinical trial is whether artificial intelligence models can be used for accurate clinical preoperative diagnosis and postoperative diagnosis of pathological findings, and will also measure the accuracy of the predictions made by the artificial intelligence models.The main target questions addressed by the model building are: 1. whether the AI model can learn from preoperative MRI and postoperative Whole Slide Images so as to accurately predict information such as benignness or malignancy, aggressiveness, grading, subtypes, genes, etc. for participants suspected of having prostate cancer preoperatively/puncturally. 2. whether the AI model is capable of learning postoperative macropathology slides to enable outcome diagnosis of surgical pathology slides in new participants. Participants will: 1. complete an MRI examination and have their MRI images analysed by the established AI model to make an accurate diagnosis of them. 2. Based on the diagnosis, if prostate cancer is predicted, they will undergo radical prostate cancer surgery and refine their surgical pathology.
Gender: MALE
Ages: 30 Years - Any
Updated: 2024-10-29
1 state