Publications

Publications

Age, obesity, medical comorbidities and surgical technique are predictive of symptomatic anastomotic strictures after contemporary radical prostatectomy.

By:
Contributors: Geoffrey Gotto, MD
J Urol. 2011 Jun;185(6):2148-52. doi: 10.1016/j.juro.2011.02.003. Epub 2011 Apr 15.

Abstract

PURPOSE:

Anastomotic strictures are relatively common after radical prostatectomy and are associated with significant morbidity, often requiring multiple surgical interventions. There is controversy in the literature regarding which factors predict the development of anastomotic strictures. In this study we determined predictors of symptomatic anastomotic strictures following contemporary radical prostatectomy.

MATERIALS AND METHODS:

Between 1999 and 2007, 4,592 consecutive patients underwent radical prostatectomy without prior radiotherapy at our institution. Data were collected from prospective surgical and institutional morbidity databases, and retrospectively from inpatient and outpatient medical and billing records. Cases were assigned a Charlson score to account for comorbidities. Complications were graded according to the modified Clavien classification.

RESULTS:

Open radical prostatectomy was performed in 3,458 men (75%) and laparoscopic radical prostatectomy was performed in 1,134 (25%). The laparoscopic radical prostatectomy group included 97 robotic-assisted cases. Median patient age was 59.5 years (IQR 54.7, 64.2). Symptomatic anastomotic strictures developed in 198 patients (4%) after a median postoperative followup of 3.5 months (IQR 2.1, 6.1). On multivariate analysis significant predictors included patient age, body mass index, Charlson score, renal insufficiency, individual surgeon, surgical approach and the presence of postoperative urine leak or hematoma.

CONCLUSIONS:

Patient factors as well as technical factors influence the development of symptomatic anastomotic strictures following contemporary radical prostatectomy. The impact of these factors is influenced by the individual surgeon and the approach used.

 

PubMed

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Russ Greiner’s Team “PC LEARN”, tied for 1st in the Prostate Cancer DREAM Challenge

Competing with 50 teams from around the world in the Prostate Cancer DREAM Challenge, University of Alberta’s PC LEARN team tied for 1st in one of the 3 sub-challenges
to predict the survival and toxicity of Docetaxel treatment in patients with metastatic castrate resistant prostate cancer!

“The DREAM Challenge was an exciting opportunity for us to apply machine learning to real medical data and possibly to contribute to medical research.” said lead PI and APCaRI member Russ Greiner.

The primary benefit of this Challenge will be to establish new quantitative benchmarks for prognostic modeling in mCRPC, with a potential impact for clinical decision making and ultimately understanding the mechanism of disease progression. https://www.synapse.org/#!Synapse:syn2813558/wiki/70844

- Russ Greiner