Caisis: A prostate cancer database management system for translational research.

Abstract

INTRODUCTION & OBJECTIVES: Within Epworth Prostate Cancer Centre we are working towards new techniques for the diagnosis and treatment of prostate cancer. To do this, there was a need for high quality clinically annotated prostate cancer tissue, biological fluids and associated clinical data, as well as quality of lie (QoL) data to be stored in an easily accessible system. METHOD: We adopted "CAISIS" as our Database Management System (DBMS). CAISIS is a customisable, web-based, cancer specific DBMS. The system was developed at the Department of Urology at Memorial Sloan-Kettering Cancer Centre in 2002. Patients were recruited from the Epworth Hospital, where those undergoing robotic assisted radical prostatectomy (RARP) are consented pre-operatively for specimen and questionnaire collection. CAISIS has the ability to import/export data, and we have developed routines to allow easy updating from pathology providers. RESULTS: From 2003-2015 we consented 2,211 patients who underwent RARP in our institution for data and/or tissue collection. From these, 1,333 had their prostate cancer tissue and biological fluids preserved in Liquid Nitrogen. The information we collected from RARP patients included; Demographics, PSA data, Biopsy Details, Operating Details, Pathology Results, and QoL Surveys. We have collected pre-op PSA data on 99% of this cohort and clinical T-Stage data on 98%, compared to Post-Op PSA data on 93% and Pathological T-Stage data on 98%. We had a return rate of 80% for Pre-Op Surveys, and 71% for Post-Op Surveys. These data have been used to support downstream research and published studies. CONCLUSION: The benefits of using Caisis as our DBMS includes; useable on Smart Devices, Remote Access, Modifiable/Customisable, No Cost for initial Software, No limit on number of users, Support and access to development through the Caisis Support Community. These data can then be easily accessed and used by researchers to address specific questions of translational relevance.