Identification of Predictive Factors for Survival of Patients With Recurrent Prostate Cancer From Clinical Features, Tissue Image Features and Molecular Biomarker Data
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.
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..
Exclusion Criteria:
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)
