2009
DOI: 10.1016/j.juro.2008.10.035
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Is it Necessary to Remove the Seminal Vesicles Completely at Radical Prostatectomy? Decision Curve Analysis of European Society of Urologic Oncology Criteria

Abstract: Purpose-A publication on behalf of the European Society of Urologic Oncology (ESUO) questioned the need for removing the seminal vesicles (SV) during radical prostatectomy (RP) in patients with PSA < 10 ng/ml, except when biopsy Gleason score is >6 or with > 50% positive biopsy cores. Our objective was to apply the ESUO algorithm to an independent data set to determine its predictive value. Results-Of 90 patients (6.4%) with SVI, 81 were ESUO positive for a sensitivity of 90%; 656 of 1,316 patients without SVI… Show more

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Cited by 20 publications
(10 citation statements)
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References 18 publications
(14 reference statements)
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“…The 5-year PSA recurrence rate was 18% for stage pT2 cancer, and the 10-year survival rate was 85% for stage pT3. These results are equivalent to those of similar surgery reported in recent studies [16-30]. PSA recurrence occurred in one case in our series although the short follow-up duration.…”
Section: Discussionsupporting
confidence: 92%
“…The 5-year PSA recurrence rate was 18% for stage pT2 cancer, and the 10-year survival rate was 85% for stage pT3. These results are equivalent to those of similar surgery reported in recent studies [16-30]. PSA recurrence occurred in one case in our series although the short follow-up duration.…”
Section: Discussionsupporting
confidence: 92%
“…Thus, if resection of the tip of the SV is not oncologically necessary, it would seem wise to spare it. However, the benefits and the risks of SV tip preservation are subject to considerable uncertainty [30][31][32][33][34][35]. There are no good estimates of the degree to which SV sparing improves function and similarly we have no good estimates of the degree to which SV preservation increases the risk of recurrence.…”
Section: Discussionmentioning
confidence: 99%
“…First proposed in 2006, decision curves have been used in cancer research [2][3][4][5][6] and many other fields. 7-11 For example, decision curves have evaluated models that predict lung cancer in high-risk populations which can then be used as tools for recommending computed tomography (CT) screening.…”
Section: Decision Curvesmentioning
confidence: 99%