Prostate Size and Risk of High-Grade, Advanced Prostate Cancer and Biochemical Progression After Radical Prostatectomy: A Search Database Study

2005 ◽  
Vol 23 (30) ◽  
pp. 7546-7554 ◽  
Author(s):  
Stephen J. Freedland ◽  
William B. Isaacs ◽  
Elizabeth A. Platz ◽  
Martha K. Terris ◽  
William J. Aronson ◽  
...  
Keyword(s):  
Advanced Disease ◽  
Tumor Grade ◽  
Surgical Margins ◽  
Equal Access ◽  
High Grade ◽  
Extracapsular Extension ◽  
Positive Surgical Margins ◽  
Prostate Weight ◽  
Prostate Size ◽  
Biochemical Progression

Purpose Prostate growth and differentiation are under androgenic control, and prior studies suggested that tumors that develop in hypogonadal men are more aggressive. We examined whether prostate weight was associated with tumor grade, advanced disease, or risk of biochemical progression after radical prostatectomy (RP). Patients and Methods We evaluated the association of prostate weight with pathologic tumor grade, positive surgical margins, extracapsular disease, and seminal vesicle invasion using logistic regression and with biochemical progression using Cox proportional hazards regression among 1,602 men treated with RP between 1988 and 2003 at five equal-access medical centers, which composed the Shared Equal Access Regional Cancer Hospital (SEARCH) Database. Results In outcome prediction models including multiple predictor variables, it was found that the predictor variable of prostate weight was significantly inversely associated with the outcomes of high-grade disease, positive surgical margins, extracapsular extension (all P ≤ .004), and biochemical progression (comparing prostate weight < 20 v ≥ 100 g: relative risk = 8.43; 95% CI, 2.9 to 24.0; P < .001). Similar associations were seen between preoperative transrectal ultrasound–measured prostate volume and high-grade disease, positive surgical margins, extracapsular extension (all P ≤ .005), seminal vesicle invasion (P = .07), and biochemical progression (P = .06). Conclusion Men with smaller prostates had more high-grade cancers and more advanced disease and were at greater risk of progression after RP. These results suggest that prostate size may be an important prognostic variable that should be evaluated for use pre- and postoperatively to predict biochemical progression.

scholarly journals Benchmarking PASADENA Consensus along the Learning Curve of Robotic Radical Cystectomy with Intracorporeal Neobladder: CUSUM Based Assessment

2021 ◽  
Vol 10 (24) ◽  
pp. 5969
Author(s):  
Riccardo Lombardo ◽  
Riccardo Mastroianni ◽  
Gabriele Tuderti ◽  
Mariaconsiglia Ferriero ◽  
Aldo Brassetti ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Learning Curve ◽  
Radical Cystectomy ◽  
Operative Time ◽  
Surgical Margins ◽  
Invasive Bladder Cancer ◽  
High Grade ◽  
Muscle Invasive Bladder Cancer ◽  
Positive Surgical Margins ◽  
Muscle Invasive

(1) Aim: Robot assisted radical cystectomy (RARC) with intacorporeal neobladder (iN) is a challenging procedure. There is a paucity of reports on RARC-iN, the extracorporeal approach being the most used. The aim of our study was to assess the learning curve of RARC-iN and to test its performance in benchmarking Pasadena consensus outcomes. (2) Material and methods: The single-institution learning curve of RARC-iN was retrospectively evaluated. Demographic, clinical and pathologic data of all patients were recorded. Indications to radical cystectomy included muscle invasive bladder cancer (pT ≥ 2) or recurrent high grade non muscle invasive bladder cancer. The cumulative sum (CUSUM) technique, one of the methods developed to monitor the performance and quality of the industrial sector, was adopted by the medical field in the 1970s to analyze learning curves for surgical procedures. The learning curve was evaluated using the following criteria: 1. operative time (OT) <5 h; 2. 24-h Hemoglobin (Hb) drop <2 g/dl; 3. severe complications (according to the Clavien classification system) <30%; 4. positive surgical margins <5%; and 5. complete lymph-node dissection defined as more than 16 nodes. Benchmarking of all five items on quintile analysis was tested, and a failure rate <20% for any outcome was set as threshold. (3) Results: the first 100 consecutive RARC-iN patients were included in the analysis. At CUSUM analysis, RARC required 20 cases to achieve a plateau in terms of operative time (defined as more than 3 consecutive procedures below 300 min). Hemoglobin drop, PSM and number of removed lymph-nodes did not change significantly along the learning curve. Overall, 41% of the patients presented at least one complication. Low-grade and high-grade complication rates were 30% and 17%, respectively. When assessing the benchmarks of all five Pasadena consensus outcomes on quintile analysis, a plateau was achieved after the first 60 cases. (4) Conclusions: RARC-iN is a challenging procedure. The potential impact of the learning curve on significant outcomes, such as high grade complications and positive surgical margins, has played a detrimental effect on its widespread adoption. According to this study, in tertiary referral centers, 60 procedures are sufficient to benchmark all outcomes defined in Pasadena RARC consensus.

697: Prostate Size is Inversely Associated with Risk of High-Grade, Advanced Prostate Cancer, and Biochemical Progression Following Radical Prostatectomy

2005 ◽  
Vol 173 (4S) ◽  
pp. 190-190
Author(s):  
Stephen J. Freedland ◽  
William B. Isaacs ◽  
Elizabeth A. Platz ◽  
Martha K. Terris ◽  
William J. Aronson ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Radical Prostatectomy ◽  
Advanced Prostate Cancer ◽  
High Grade ◽  
Prostate Size ◽  
Biochemical Progression

Men With Organ-confined Prostate Cancer and Positive Surgical Margins Develop Biochemical Failure at a Similar Rate to Men With Extracapsular Extension

Urology ◽  
2011 ◽  
Vol 78 (1) ◽  
pp. 121-125 ◽  
Author(s):  
Sarah P. Psutka ◽  
Adam S. Feldman ◽  
David Rodin ◽  
Aria F. Olumi ◽  
Chin-Lee Wu ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Similar Rate ◽  
Biochemical Failure ◽  
Surgical Margins ◽  
Extracapsular Extension ◽  
Positive Surgical Margins

scholarly journals MRI-based radiomics models to assess prostate cancer, extracapsular extension and positive surgical margins

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Dong He ◽  
Ximing Wang ◽  
Chenchao Fu ◽  
Xuedong Wei ◽  
Jie Bao ◽  
...  
Keyword(s):  
Malignant Lesion ◽  
Classification Performance ◽  
Surgical Margins ◽  
Integrated Models ◽  
Extracapsular Extension ◽  
Positive Surgical Margins ◽  
Receiver Operating Characteristic Curves ◽  
Apparent Diffusion ◽  
Magnetic Resonance Imaging Mri ◽  
Malignant Prostate

Abstract Purpose To investigate the performance of magnetic resonance imaging (MRI)-based radiomics models for benign and malignant prostate lesion discrimination and extracapsular extension (ECE) and positive surgical margins (PSM) prediction. Methods and materials In total, 459 patients who underwent multiparametric MRI (mpMRI) before prostate biopsy were included. Radiomic features were extracted from both T2-weighted imaging (T2WI) and the apparent diffusion coefficient (ADC). Patients were divided into different training sets and testing sets for different targets according to a ratio of 7:3. Radiomics signatures were built using radiomic features on the training set, and integrated models were built by adding clinical characteristics. The areas under the receiver operating characteristic curves (AUCs) were calculated to assess the classification performance on the testing sets. Results The radiomics signatures for benign and malignant lesion discrimination achieved AUCs of 0.775 (T2WI), 0.863 (ADC) and 0.855 (ADC + T2WI). The corresponding integrated models improved the AUC to 0.851/0.912/0.905, respectively. The radiomics signatures for ECE achieved the highest AUC of 0.625 (ADC), and the corresponding integrated model achieved the highest AUC (0.728). The radiomics signatures for PSM prediction achieved AUCs of 0.614 (T2WI) and 0.733 (ADC). The corresponding integrated models reached AUCs of 0.680 and 0.766, respectively. Conclusions The MRI-based radiomics models, which took advantage of radiomic features on ADC and T2WI scans, showed good performance in discriminating benign and malignant prostate lesions and predicting ECE and PSM. Combining radiomics signatures and clinical factors enhanced the performance of the models, which may contribute to clinical diagnosis and treatment.

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