Comparison of Three Different Tools for Prediction of Seminal Vesicle Invasion at Radical Prostatectomy

Lughezzani, Giovanni; Zorn, Kevin C.; Budäus, Lars; Sun, Maxine; Lee, David I.; Shalhav, Arieh L.; Zagaya, Gregory P.; Shikanov, Sergey; Gofrit, Ofer N.; Thong, Alan; Albala, David; Sun, Leon; Cronin, Angel M.; Vickers, Andrew J.; Karakiewicz, Pierre I.

doi:10.1016/j.eururo.2012.04.022

Cited by 12 publications

(11 citation statements)

References 25 publications

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“…Similar to the Partin Tables, 9 which have been widely adopted because of their validated accuracy and ease of use with readily available preoperative data, 14–17 we believe that our derived risk tables may prove useful in the prognostication and pretreatment counseling of patients found to have PNI. For example, in the case of a man with PNI and a high biopsy tumor volume, the urologist may advocate for sacrificing the neurovascular bundle(s) and/or performing an extended lymphadenectomy in an attempt to perform the most oncologically advantageous operation.…”

Section: Commentmentioning

confidence: 90%

Predicting the Risk of Non–organ-confined Prostate Cancer When Perineural Invasion Is Found on Biopsy

Gorin

Chalfin

Epstein³

et al. 2014

Urology

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OBJECTIVE To more precisely define the risk of non–organ-confined (non-OC) prostate cancer among men with perineural invasion (PNI) identified on prostate biopsy. MATERIALS AND METHODS The Johns Hopkins radical prostatectomy database was queried for men with PNI reported on prostate biopsy. Patients with and without non-OC disease were compared for differences in preoperative clinical and pathologic characteristics, including three biopsy-based measures of tumor volume (number of cores with cancer, percentage of cores with cancer, and maximum percent core involvement with cancer). After evaluating the different preoperative variables in univariate analyses, a multivariable logistic regression model was generated, and bootstrap estimates of the risk of non-OC disease were calculated. RESULTS In total, 556 patients with PNI were analyzed, 279 (50.2%) of whom were found to have non-OC prostate cancer. In univariate analyses, preoperative prostate-specific antigen, clinical T stage, biopsy Gleason sum, and the three biopsy-based measures of tumor volume were significantly associated with non-OC disease. Of the three measures of tumor volume, the best fit to the data and highest degree of model discrimination were obtained using maximum percent core involvement with cancer. Incorporating this variable, preoperative prostate-specific antigen, clinical T stage, and biopsy Gleason sum into a multivariable model, the estimated risk of non-OC disease was found to range from 13.8% to 94.4% (bootstrap corrected c-index = 0.735). CONCLUSION Men with PNI on prostate biopsy are at a wide range of risk for non-OC disease. Preoperative estimation of this risk is improved by considering readily available biopsy estimates of tumor volume.

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Section: Commentmentioning

confidence: 90%

Predicting the Risk of Non–organ-confined Prostate Cancer When Perineural Invasion Is Found on Biopsy

Gorin

Chalfin

Epstein³

et al. 2014

Urology

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“…proposed a nomogram that used information from biopsies with at least 10 cores, achieving better AUC and calibration with respect to the Koh nomogram and the Partin tables . However, when compared with the updated Partin tables and the ESUO criteria, the updated Partin tables represent the most useful tool in terms of net benefit evaluated with the DCA method with respect to the Gallina nomogram and ESUO criteria …”

Section: Discussionmentioning

confidence: 99%

“…13 However, when compared with the updated Partin tables and the ESUO criteria, 21 the updated Partin tables represent the most useful tool in terms of net benefit evaluated with the DCA method with respect to the Gallina nomogram and ESUO criteria. 22 The advent of mpMRI led some authors to evaluate the impact of MRI findings when added to predictive models. Wang et al showed that the addition of mpMRI data to the nomogram by Koh et al improves predictive accuracy in terms of AUC; resulting in an AUC improvement from 80% to 87%.…”

Section: Discussionmentioning

confidence: 99%

Novel nomogram for the prediction of seminal vesicle invasion including multiparametric magnetic resonance imaging

et al. 2019

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Objectives To create a model that predicts side‐specific seminal vesicle invasion using clinical, biopsy and multiparametric magnetic resonance imaging data. Methods We analyzed data from 544 patients who underwent robot‐assisted radical prostatectomy at a single institution. To develop a side‐specific predictive model, we ultimately considered four variables: prostate‐specific antigen, highest ipsilateral biopsy Gleason grade, highest ipsilateral percentage core involvement and seminal vesicle invasion on multiparametric magnetic resonance imaging. A binary multivariable logistic regression model was fitted to predict seminal vesicle invasion. A nomogram was then built based on the coefficients of the resulting logit function. The leave‐one‐out cross validation method was used for internal validation, and the decision curve analysis for the evaluation of the net clinical benefit. Results We relied on 804 side‐specific cases after excluding negative biopsy observations (n = 284). Seminal vesicle invasion was reported on multiparametric magnetic resonance imaging in 41 (5%) cases, and on final pathology in 64 (8%) cases. All variables in the model emerged as predictors of seminal vesicle invasion (all P ≤ 0.001) and were subsequently considered to build a nomogram. The area under the curve of multiparametric magnetic resonance imaging alone in predicting seminal vesicle invasion was 59.1%; whereas one of the clinical variables only was 85.1%. The area under the curve of the nomogram resulting from their combination was 86.5%. After internal validation, this resulted in 84.7%. The model achieved good calibration and the decision curve analysis showed its clinical benefit, especially when compared with relying only on multiparametric magnetic resonance imaging prediction of seminal vesicle invasion. Conclusions A nomogram based on clinical and multiparametric magnetic resonance imaging data can predict seminal vesicle invasion and serve as a tool to urologists for surgical planning.

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“…[ 13 ] Moreover, this method has been widely used for comparing different statistical models in predicting clinical results. [ 33 34 35 36 ]…”

Section: Discussionmentioning

confidence: 99%

Prediction of low birth weight delivery by maternal status and its validation: Decision curve analysis

et al. 2017

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Background:In this study, we evaluated assessed elements connected with low birth weight (LBW) and used decision curve analysis (DCA) to define a scale to anticipate the probability of having a LBW newborn child.Methods:This hospital-based case–control study was led in Arak Hospital in Iran. The study included 470 mothers with LBW neonate and 470 mothers with natural neonates. Information were gathered by meeting moms utilizing preplanned organized questionnaire and from hospital records. The estimated probabilities of detecting LBW were calculated using the logistic regression and DCA to quantify the clinical consequences and its validation.Results:Factors significantly associated with LBW were premature membrane rupture (odds ratio [OR] = 3.18 [1.882–5.384]), former LBW infants (OR = 2.99 [1.510–5.932]), premature pain (OR = 2.70 [1.659–4.415]), hypertension in pregnancy (OR = 2.39 [1.429–4.019]), last trimester of pregnancy bleeding (OR = 2.58 [1.018–6.583]), mother age >30 (OR = 2.17 [1.350–3.498]). However, with DCA, the prediction model made on these 15 variables has a net benefit (NB) of 0.3110 is best predictive with the highest NB. NB has simple clinical interpretation and utilizing the model is what might as well be called a procedure that distinguished what might as well be called 31.1 LBW per 100 cases with no superfluous recognize.Conclusions:It is conceivable to foresee LBW utilizing a prediction model show in light of noteworthy hazard components connected with LBW. The majority of the hazard elements for LBW are preventable, and moms can be alluded amid early pregnancy to a middle which is furnished with facilities for administration of high hazard pregnancy and LBW infant.

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Comparison of Three Different Tools for Prediction of Seminal Vesicle Invasion at Radical Prostatectomy

Cited by 12 publications

References 25 publications

Predicting the Risk of Non–organ-confined Prostate Cancer When Perineural Invasion Is Found on Biopsy

Predicting the Risk of Non–organ-confined Prostate Cancer When Perineural Invasion Is Found on Biopsy

Novel nomogram for the prediction of seminal vesicle invasion including multiparametric magnetic resonance imaging

Prediction of low birth weight delivery by maternal status and its validation: Decision curve analysis

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