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Clin Genitourin Cancer. 2006 Jun;5(1):61-6.

Development of an integrated prostate cancer research information system.

Author information

1
Lank Center for Genitourinary Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA. william_oh@dfci.harvard.edu

Abstract

BACKGROUND:

In this article, we describe the design and implementation of a comprehensive prostate cancer database developed to collect, store, and access clinical, treatment, and outcomes data for research and clinical care.

PATIENTS AND METHODS:

The Prostate Cancer Clinical Research Information System is a relational database. Data are entered from multiple sources, including medical records, institutional laboratory, patient registration, pharmacy systems, and clinician forms. The history, design, and operational characteristics of the database are described. Issues regarding necessary staffing and funding of databases are reviewed.

RESULTS:

Four thousand two hundred forty-six patients have information in the Prostate Cancer Clinical Research Information System. Mean age of patients is 62 years, and 89% are white. Seventy-one percent of patients presented at diagnosis with T1 or T2 disease, and 78% had biopsy Gleason scores of <or=7, 8-10 in 18%. Median prostate-specific antigen level at diagnosis was 7 ng/mL, and 77% of patients presented with increased prostate-specific antigen as a trigger symptom. Sixty-four percent of patients presented to our clinic having had no previous treatment for prostate cancer. The majority of approached patients provided consent for collection of clinical data, blood, and tissue. Quality control assessments demonstrate high levels of concordance among data entry personnel.

CONCLUSION:

Clinical databases are difficult to implement and maintain; however, they represent a valuable resource, particularly when linked to blood and tissue banks. Elements needed for a successful clinical database include engagement of clinicians, utility for research, and the ability to integrate with legacy systems. As cancer centers develop such databases, lessons learned from each experience should be shared in order to optimize the process.

PMID:
16859581
DOI:
10.3816/CGC.2006.n.019
[Indexed for MEDLINE]

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