Identification of Predictive Factors for Survival of Patients With Recurrent Prostate Cancer From Clinical Features, Tissue Image Features and Molecular Biomarker Data
Completed
Conditions studied: Prostate Cancer
In brief
We seek to improve the predictive accuracy of the nomogram to predict survival for patients with castrate mets disease through the addition of pathological data, the results of automated machine vision based image analysis of H\&E stained tumor tissue developed at Aureon Biosciences,and molecular biomarker studies (25 markers) determined by immunohistochemistry on tissue microarrays prepared from paraffin-embedded tumor.
Key facts
- Study ID
- NCT00578409
- Run by
- Memorial Sloan Kettering Cancer Center
- People needed
- 758
- Starts
- 2004-05-01
- Expected to finish
- 2010-04-01
- Last updated by the study team
- 2015-12-18
Who can join
Age: any. Sex: male. Healthy volunteers: not accepted.
You may qualify if…
- Patients in the first retrospective study (Stage 1) must be part of the 409 patient strong MSKCC cohort with progressive metastatic prostate cancer which was used for the generation of the original nomogram.
- For details please see original publication by Smaletz et al. Patients involved in the second retrospective study (Stage 2) must be part of the 223 patients with a rising PSA after surgery or radiation therapy who were treated on conjugate vaccine trials at MSKCC..
You may not qualify if…
- For details of excluded patients on the clinical metastases castrate disease study, please see original publication by Smaletz et al.4
- (MSKCC - add reference if publication available for rising PSA patients)
Where it is running
- Memorial Sloan-Kettering Cancer Center — New York, New York, United States
Full record on ClinicalTrials.gov
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