Prediction rules for aggressive prostate cancer in AS population

Abbreviated Name
PCA3 Sanda-PHI
Lead Investigator
Sanda, MartinEmory University
Coordinating Investigator
Feng, Ziding Fred Hutchinson Cancer Center
Involved Investigators


No abstract availalbe.


In the development phase, we plan to formulate a number of rules: The first one is to linearly combine PCA3, phi, and clinical variables via logistic regression. The clinical variables include age, BMI, race, DRE result, initial biopsy indicator, number of previous negative biopsies after diagnosis, cores ratio (ratio of biopsy cores containing cancer to total cores), months since diagnosis, and prostate volume. Appropriate variable selection will be implemented in the logistic regression to screen out non-informative clinical variables. The second rule is to linearly combine PCA3, phi, and initial biopsy indicator only, without other clinical variables. Obviously, this rule is expected to have less predictive power than the first one, but can be more practical if the predictive power reduction is limited. The third rule is a “or” logic combination of PCA3, phi, and a composite score of clinical variables. The composite score is obtained via logistic regression. The fourth rule is a “or” logic combination of PCA3 and phi only.

Analytic Method

No analytic method available.


  • No publications available at this time for this protocol.


Data Collections

  • No data collections available at this time for this protocol.
Start Date
May 1 2018
Estimated Finish Date
May 1 2019
Protocol ID
Protocol Type
Reference Set
Fields of Research
  • Proteomics
Collaborative Group
Prostate and Urologic Cancers Research Group
Cancer Types
  • Malignant neoplasm of prostate
Phased Status

Associated Forms