Data Note

Data and programming code from the studies on the learning curve for radical prostatectomy

Andrew J Vickers^* and Angel M Cronin

• * Corresponding author: Andrew J Vickers vickersa@mskcc.org

Author Affiliations

Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, NY, USA

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BMC Research Notes 2010, 3:234 doi:10.1186/1756-0500-3-234

Published: 2 September 2010

Abstract

Our group analyzed a multi-institutional data set to address the question of how the outcomes of surgery for prostate cancer are affected by surgeon-specific factors. The cohort consists of 9076 patients treated by open radical prostatectomy at one of four US academic institutions 1987 - 2003. The primary analyses focused on 7765 patients without neoadjuvant therapy. The most well-known finding is that of a surgical "learning curve", with rates of prostate cancer cure strongly dependent on surgeon experience. In this "data note", we provide the raw data set, as well as well-annotated programming code for the main analyses. Data include markers of cancer severity (stage, grade and prostate-specific antigen level), cancer outcome, and surgeon variables such as training and experience.