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

This study has been completed.
Sponsor:
Collaborators:
Aureon Biosciences, Inc.
NYU MEDICAL CENTER
Information provided by:
Memorial Sloan-Kettering Cancer Center
ClinicalTrials.gov Identifier:
NCT00578409
First received: December 19, 2007
Last updated: April 27, 2010
Last verified: April 2010

December 19, 2007
April 27, 2010
May 2004
April 2010   (final data collection date for primary outcome measure)
The analysis for the progressive castrate mets disease population consists of two analytical steps. The first step involved the development of a predictive model of pt survival using supervised multivariate analytical (SMA)techniques [ Time Frame: 2 years ] [ Designated as safety issue: No ]
Same as current
Complete list of historical versions of study NCT00578409 on ClinicalTrials.gov Archive Site
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Identification of Predictive Factors for Survival of Patients With Recurrent Prostate Cancer From Clinical Features, Tissue Image Features and Molecular Biomarker Data
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.

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Observational
Observational Model: Cohort
Time Perspective: Retrospective
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Retention:   Samples With DNA
Description:

In a first analytical step, using only the clinical and pathological variables used in the original clinical mets castrate disease nomogram as inputs, supervised multivariate analytical techniques (SMA) were used to generate a new predictive model for patient survival. A similar approach will then be used to analyze a second group of approximately 223 pts in the state of a rising PSA14 after surgery or radiation therapy treated on a sequential series of IRB approved trials testing conjugate vaccines also consented on IRB protocol 90-40.

Non-Probability Sample

Stage 1 - Population: Progressive Metastatic Disease Stage 2 - Population: Rising PSA

Prostate Cancer
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*   Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline.
 
Completed
0
April 2010
April 2010   (final data collection date for primary outcome measure)

Inclusion Criteria:

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)

Male
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No
Contact information is only displayed when the study is recruiting subjects
United States
 
NCT00578409
04-062
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Howard I. Scher, MD, Memorial Sloan-Kettering Cancer Center
Memorial Sloan-Kettering Cancer Center
  • Aureon Biosciences, Inc.
  • NYU MEDICAL CENTER
Principal Investigator: Howard I Scher, MD Memorial Sloan-Kettering Cancer Center
Memorial Sloan-Kettering Cancer Center
April 2010

ICMJE     Data element required by the International Committee of Medical Journal Editors and the World Health Organization ICTRP