Part Of Table Research Articles

Are Predictions from Partin Tables and Kattan Nomograms Useful for the Assessment of the Oncological Outcomes after LDR Brachytherapy +-EBRT +- ADT in Localized (N0M0) Prostate Cancer?

Are Predictions from Partin Tables and Kattan Nomograms Useful for the Assessment of the Oncological Outcomes after LDR Brachytherapy +-EBRT +- ADT in Localized (N0M0) Prostate Cancer?

Accuracy of Multiparametric Magnetic Resonance Imaging for Extracapsular Extension of Prostate Cancer in Community Practice

IntroductionThe presence of extracapsular extension (ECE) in prostate cancer (PCa) can influence a surgeon's decision to perform a nerve-sparing approach during radical prostatectomy (RP). Preoperatively, multiparametric MRI (mp-MRI) is often used to stage PCa. More recently, the use of mp-MRI has gained wide acceptance in fusion biopsy of the prostate. In this framework, the reported accuracy of mp-MRI has been highly variable, with data often originating from large referral centers with experienced radiologists. We sought to determine the sensitivity and specificity of mp-MRI for detecting ECE in the community. Materials and MethodsWe reviewed a prospectively maintained database of men with PCa who had undergone RP. We recorded the prevalence of ECE at RP and determined the sensitivity, specificity, positive predictive value, and negative predictive value of MRI for detecting ECE. We assessed these values according to the D'Amico risk groups and compared the predictive value of MRI to that of the Partin tables. ResultsThe prevalence of ECE was 11.5%, 28.1%, and 47.1% in the low-, intermediate, and high-risk groups, respectively, with an overall prevalence of 24.1%. The overall sensitivity, specificity, positive predictive value, and negative predictive value of MRI was 12.5%, 93.1%, 36.4%, and 77.0%, respectively. ConclusionThe reduction in the sensitivity of preoperative mp-MRI to determine ECE in the community setting is significant. Even with stratification using the D'Amico criteria and Partin tables, the performance of mp-MRI was not significantly improved. Because most cases of PCa are diagnosed and treated in the community, it is questionable whether mp-MRI is a suitable staging modality in the community.

Can Radiologic Staging With Multiparametric MRI Enhance the Accuracy of the Partin Tables in Predicting Organ-Confined Prostate Cancer?

The purpose of this study is to investigate the accuracy of multiparametric MRI with endorectal coil and Partin tables in predicting organ-confined (OC) prostate cancer in a contemporary cohort undergoing radical prostatectomy (RP) and to assess the possible added value of radiologic staging based on multiparametric MRI to the predictive accuracy of Partin tables. One hundred fifty-eight consecutive subjects underwent 3-T multiparametric MRI with endorectal coil before RP between November 2010 and November 2013. Data were randomly split 60% and 40% into derivation (n = 95) and validation (n = 62) datasets. Multiparametric MRI was used to assess the radiologic stage, and logistic regression models were created using the derivation dataset and were fit on the independent validation dataset using multiparametric MRI staging alone and with prostate-specific antigen (PSA) level as the covariate. The probability of each patient to harbor OC disease was calculated using an updated version of Partin tables, using either clinical staging from digital rectal examination (DRE) or radiologic staging (multiparametric MRI). The AUC was calculated to evaluate accuracy of these predictive methods. The accuracy of multiparametric MRI to predict OC disease on pathologic analysis was greater (AUC, 0.88) than that of Partin tables (AUC, 0.70) and improved when multiparametric MRI was combined with PSA level (AUC, 0.91). The accuracy of Partin nomograms to predict OC disease decreased (AUC, 0.63) when staging was based on multiparametric MRI versus DRE. The superior predictive accuracy of multiparametric MRI compared with Partin tables to predict OC disease validates the results of smaller previously published studies. Although there is no added benefit of substituting multiparametric MRI stage for clinical stage when using Partin tables, multiparametric MRI staging information is valuable as a stand-alone test.

Accurate prediction tools in prostate cancer require consistent assessment of included variables

Objective: The aim of this study was to create a preoperative prediction model predicting extraprostatic tumour growth in men with clinically organ-confined disease from a prospectively collected Swedish cohort. Materials and methods: The study used data from 3386 men in the prospective multi-centre Laparoscopic Prostatectomy Robot Open (LAPPRO) trial, with 14 participating urological departments. External validation was performed using a cohort of 634 men from the largest study centre with patients who underwent surgery before and after the inclusion period of the LAPPRO study. External validation of the updated Partin table was used for comparison. The prediction models were created by multivariable logistic regression. Nomogram prediction performance, internal, internal–external and external validation are presented as the area under the receiver operating characteristic curve (AUC). Results: The nomogram reached a prediction performance with an AUC of 0.741, with internal and external validation of 0.738 and 0.698, respectively. Internal–external validation showed great divergence between centres, with AUCs ranging from 0.476 to 0.892, indicating inconsistencies in pathological staging or one or more of the included variables in the regression model. When including centre as a variable in the multivariable model it was significantly associated with the outcome of pT3 (p < 0.001). AUC for external validation of the Partin table was 0.694. Conclusions: Accurate prediction tools in prostate cancer require consistent assessment of included variables, and local validation is needed before the use of such tools in clinical practice.

MP80-06 INTRAOPERATIVE BIMANUAL EXAMINATION AND FROZEN-SECTION ANALYSIS DURING ROBOT-ASSISTED RADICAL PROSTATECTOMY: A NOVEL TECHNIQUE FOR REDUCING POSITIVE SURGICAL MARGINS

INTRODUCTION AND OBJECTIVES: To describe the feasibility and early outcomes of a Modification to robot-assisted radical prostatectomy (RARP) that allows for mitigation of the lack of tactile feedback during RARP by allowing immediate Organ Retrieval for Examination and targeted frozen-section biopsies (MORE technique). METHODS: MORE consists of a GelPOINT device inserted periumbilically. Prostate is excised and retrieved through the GelPOINT without undocking the robot, and examined bimanually on-table by the surgeon. Lesions suspicious for positive surgical margin (PSM) are sent for frozen section analysis (Figure). Biopsies positive/suspicious for cancer resulted in more tissue excision from the corresponding pelvic bed site. 352 patients with a probability of extracapsular extension (EPE) >25% (Partin table) were selected to undergo MORE RARP. MORE RARP patients with pT3a at final pathology (n1⁄4103) were compared to a control group of 74 consecutive patients with pT3a after conventional RARP. RESULTS: Except a greater proportion of clinically palpable disease in the MORE RARP vs. control group (43.7 vs. 17.6%; p1⁄40.005), the two groups had comparable rates of nodal dissection, nerve sparing, pathological stage, grade and nodal status. The PSM rate in the MORE group was 17.5% (18/103) compared to 36.5% (27/74) in the control group (p1⁄40.004); the odds ratio was 0.37 (CI: 0.18-0.74; p1⁄40.005). 8 patients in each group had biochemical recurrence; short follow-up (median 16.6 and 15.4 months respectively) precluded detection of any significant difference. Frozen section biopsy site matched the EPE site at final pathology in 59/79 (73.4%) cases selected for frozen section analyses. CONCLUSIONS: Adoption of the MORE technique led to a significant reduction in the PSM rate following RARP in patients harboring locally advanced disease without increasing operative time. Its easy reproducibility may also allow potential utility in other robotassisted urologic oncologic procedures. Source of Funding: none

Linfadenectomía pélvica extendida en pacientes con cáncer de próstata clínicamente localizado: estudio observacional prospectivo

ObjectiveTo determine the frequency of lymph node involvement in patients with clinically localised prostate adenocarcinoma who had radical prostatectomy and extended pelvic lymphadenectomy. Material and methodsA prospective observational study was conducted on 137 patients with clinically localised prostate cancer of low, intermediate or high risk according to the D’Amico classification. All participants underwent radical prostatectomy plus extended pelvic lymphadenectomy in 3 reference centres in Bogota, Colombia, between 2013 and 2014. The following variables were assessed: age, prostate specific antigen levels, Gleason score of the biopsy, probability of lymph node involvement calculated with Partin tables and the histopathology result of the surgical specimen, with the definitive Gleason pattern and the total number of resected and involved lymph nodes per tumour, according to the territory of the dissection. ResultsA total of 2,876 lymph nodes were extracted (an average of 20.99 lymph nodes per patient). There was lymph node involvement in 14 (10.22%) patients. The high-risk and intermediate-risk group presented lymph node metastases in 28.57% and 5.25%, respectively. There was no lymph node involvement in the low-risk group. Of the patients at risk of lymph node involvement (≥2% according to the Partin tables), 19.40% had lymph node metastases. ConclusionLymph node involvement in our population is similar to that reported in the worldwide literature. Extended pelvic lymphadenectomy increased the probability of detecting lymph node metastases in our community.

Inclusion of corrected calcium and creatinine levels in a novel nomogram for prediction of pathologically localized prostate cancer.

140 Background: The role of routine parameters in the prediction of organ-confined Prostate Cancer (oPCa) remains unclear. Methods: We conducted a retrospective study of 246 patients with PCa diagnosed on biopsy, who underwent radical prostatectomy with extended lymph node dissection. None of these patients received a neoadjuvant therapy. Gleason score (xGLS), percent of positive cores involved by PCa (pCores), results of transrectal evaluation (TRUS, DRE), prostate volume (PVol), albumin-corrected Calcium (Ca), Hemoglobin (Hb), Creatinine (Crea), PSA, and age at RPE were considered. Postoperative variables including Gleason score (pGLS), TNM stages were evaluated. These patients were divided according to disease advancement into pathologically localized (pT2) and advanced PCa (pT3/4 or pN1). A L2 penalized regression model including all preoperative parameters was evaluated to design a nomogram for oPCa prediction. Furthermore, the internal validation of the nomogram was performed using bootstrapping and cross-validations. The precision and accuracy of the novel nomogram were evaluated by using AUC, F-Score, Brier-Score and the classification accuracy (CA). Results: The lowest probability for pathologically localized PCa was found in patients having the following features: PSA &gt; 20 ng/ml, detection of PCa in all cores, high Ca [1.21 fold over upper normal limit (ULN)] and Crea levels (2.27 fold over ULN), xGls &gt; 7 and normal PVol. A nomogram for oPCa was developed including the following parameter: Crea, Ca, PSA, xGls, PVol, TRUS, pCores. The sensitivity and the specificity of the nomogram for prediction of pathologically localized PCa were 92.2% and 35.9%, respectively. AUC of 0.811, CA of 80.1%, F-Score 0.879, a precision of 84.0%. and Brier-Score of 0.2599 were calculated. The predicted probability of the novel nomogram was associated with higher accuracy for prediction of oPCa compared to those of Partin table and Kattan nomogram. Conclusions: Serum creatinine and corrected calcium are indpendent predictors of oPCa. The novel nomogram can predict oPCa with high precision and accuracy. However, an external validation of the novel nomogram is needed.

Editorial Comment

It is hard to imagine what a hot topic active surveillance (AS) has become in the last year or two. We are seduced by molecular markers and multiparametric magnetic resonance imaging as sexy new tools to magically help us and our patients decide between treatment and surveillance. 1 Tay K.J. Mendez M. Moul J.W. Polascik T.J. Active surveillance for prostate cancer: can we modernize contemporary protocols to improve patient selection and outcomes in the focal therapy era?. Curr Opin Urol. 2015; 25: 185-190 Crossref PubMed Scopus (20) Google Scholar , 2 Canfield S.E. Kibel A.S. Kemeter M.J. Febbo P.G. Lawrence H.J. Moul J.W. A guide for clinicians in the evaluation of emerging molecular diagnostics for newly diagnosed prostate cancer. Rev Urol. 2014; 16: 172-180 PubMed Google Scholar However, it is refreshing, relevant, and timely to see the work of Dinh et al on examining the percentage of positive biopsy cores (PBC) as an inexpensive and straightforward tool that we all have at our fingertips. Although this is not a new concept, Dinh et al's work represents the largest study of this type in the literature taking advantage of the Surveillance, Epidemiology, and End Results database. Back in the early 2000s, our group (Gancarczyk et al, Reference 19) used %PBC in place of T clinical stage and developed alternative “Partin Tables.” 3 Eifler J.B. Feng Z. Lin B.M. et al. An updated prostate cancer staging nomogram (Partin tables) based on cases from 2006 to 2011. BJU Int. 2013; 111: 22-29 Crossref PubMed Scopus (278) Google Scholar Interestingly, we did not even consider its use for AS at that time, and this was a mere 12 years ago.

Assessment of the performance of Partin's nomogram (2007) in contemporary Indian cohort.

Introduction:Partin's nomogram is an important prognostic tool to predict adverse pathological features for clinically localized prostate carcinoma. This tool is widely used by both radiation and surgical oncologists for pre-intervention counseling, treatment planning, and predicting the possible need for adjuvant treatment. However, the model is derived from a Western population with typical characteristics of prostate cancer in a prostate-specific antigen (PSA) screened population. Therefore, this study was conducted to assess the performance of the Partin's nomogram as applied to an Indian cohort by assessing the discrimination and calibration properties.Methods:A retrospective review of 282 patients treated with robotic radical prostatectomy from 2010 to 2015 was conducted. Partin tables (year 2007) were used to calculate the predicted probabilities for lymph node invasion (LNI), seminal vesicle invasion (SVI), and extraprostatic extension (EPE). The discrimination properties were assessed using the receiver operating characteristic (ROC) curves. Calibration of the model was done to show the relationship between predicted and observed values.Results:The mean age of the patients was 64.3 years. Most (59.4%) were clinical T2 disease. Patients with PSA >10 ng/ml comprised 60% of the population. ECE, SVI, and LNI were present in 39.2%, 22%, and 11% of cases, respectively. ROC analysis revealed area under curve values for EPE, SVI, and LNI of 68%, 67.5%, and 71.2%, respectively. Calibration plot suggested that the Partin tables under-predicted the risk whenever the values of predicted risk were more than 26%, 3%, and 1% for EPE, SVI, and LNI, respectively, and over predicted when the risk was lower.Conclusion:Our data show that Partin's tables, despite having fair discrimination properties, do not accurately predict LNI, SVI, and ECE across the entire range of predicted values in a contemporary Indian cohort.

Is there still a role for computed tomography and bone scintigraphy in prostate cancer staging? An analysis from the EUREKA-1 database.

According to the current guidelines, computed tomography (CT) and bone scintigraphy (BS) are optional in intermediate-risk and recommended in high-risk prostate cancer (PCa). We wonder whether it is time for these examinations to be dismissed, evaluating their staging accuracy in a large cohort of radical prostatectomy (RP) patients. To evaluate the ability of CT to predict lymph node involvement (LNI), we included 1091 patients treated with RP and pelvic lymph node dissection, previously staged with abdomino-pelvic CT. As for bone metastases, we included 1145 PCa patients deemed fit for surgery, previously staged with Tc-99m methylene diphosphonate planar BS. CT scan showed a sensitivity and specificity in predicting LNI of 8.8 and 98 %; subgroup analysis disclosed a significant association only for the high-risk subgroup of 334 patients (P 0.009) with a sensitivity of 11.8 % and positive predictive value (PPV) of 44.4 %. However, logistic multivariate regression analysis including preoperative risk factors excluded any additional predictive ability of CT even in the high-risk group (P 0.40). These data are confirmed by ROC curve analysis, showing a low AUC of 54 % for CT, compared with 69 % for Partin tables and 80 % for Briganti nomogram. BS showed some positivity in 74 cases, only four of whom progressed, while 49 patients with negative BS progressed during their follow-up, six of them immediately after surgery. According to our opinion, the role of CT and BS should be restricted to selected high-risk patients, while clinical predictive nomograms should be adopted for the surgical planning.

Multiparametric MRI Improves Accuracy of Clinical Nomograms for Predicting Extracapsular Extension of Prostate Cancer

To compare the accuracy of multiparametric magnetic resonance imaging (MP-MRI) with the Partin tables and Memorial Sloan-Kettering (MSK) nomogram for predicting extracapsular extension (ECE) in prostate cancer and to create a tool for clinicians to estimate pathologic ECErisk. A retrospective review of 112 patients who underwent 3T MP-MRI of the prostate and radical prostatectomy was performed. Regression analyses were carried out to identify predictors of ECE. Predictive accuracy of models based on nomogram and MP-MRI were compared. A total of 33 of patients (29%) had ECE on MP-MRI whereas 26 patients (23%) had ECE on final pathology. Mean age was 62.8years and mean prostate-specific antigen was 8.2ng/dL. MRI was a significant predictor of ECE that was independent of age, prostate-specific antigen, Gleason score, clinical stage, and percent positive cores on biopsy. Sensitivity, specificity, positive predictive value, and negative predictive value of MP-MRI for ECE were 84.6%, 87.2%, 66.7%, and 94.9%, respectively. Areas under the curve for Partin and MSK nomograms for predicting ECE were 0.85 and 0.86, respectively. Area under the curve increased to 0.92 and 0.94, respectively, when MP-MRI was added to each nomogram. We provide an online tool that integrates Partin or MSK nomogram results with ECE status determined from MRI to predict pathologic ECE. Within the typical range of risks for ECE provided by the clinical nomograms (ie, 15%-40%), MRI was useful for predicting pathologic ECE. MP-MRI may be a useful adjunct for clinically staging prostate cancer. MP-MRI improved accuracy of existing clinical nomograms for prediction of pathologic ECE.

Could Machine Learning Improve the Prediction of Pelvic Nodal Status of Prostate Cancer Patients? Preliminary Results of a Pilot Study

ABSTRACTWe tested and compared performances of Roach formula, Partin tables and of three Machine Learning (ML) based algorithms based on decision trees in identifying N+ prostate cancer (PC). 1,555 cN0 and 50 cN+ PC were analyzed. Results were also verified on an independent population of 204 operated cN0 patients, with a known pN status (187 pN0, 17 pN1 patients).ML performed better, also when tested on the surgical population, with accuracy, specificity, and sensitivity ranging between 48–86%, 35–91%, and 17–79%, respectively. ML potentially allows better prediction of the nodal status of PC, potentially allowing a better tailoring of pelvic irradiation.

Validación de las tablas de Partin para cáncer de próstata en población mexicana

BackgroundThe Partin tables aid in predicting radical prostatectomy specimen results and in deciding whether a patient will benefit from the procedure. The results justifying the tables were from a United States population and have been validated in other countries. There are no studies in Mexico validating the use of these tables in the Mexican population. AimsTo validate the prediction of results through the use of Partin tables in Mexican patients with localized prostate cancer that underwent radical prostatectomy at a single hospital in Mexico City. MethodsOne hundred and six case records were reviewed of patients that underwent radical prostatectomy as treatment for localized prostate cancer within the time frame of January 2004 to June 2014. For validation purposes, ROC curve results were compared with those of the 2007 Partin cohort. ResultsThe pathologic result distribution was extraprostatic extension 22.6%, seminal vesicle invasion 12.3%, and lymph node invasion 2.8%, whereas the distribution for the 2007 Partin cohort was extraprostatic extension 22%, seminal vesicle invasion 3%, and lymph node invasion 1%. The analysis of the ROC curves showed that the accuracy for predicting the results was 64.6, 81.5, and 89% for extraprostatic extension, seminal vesicle invasion, and lymph node invasion, respectively. DiscussionThe results obtained corroborate the usefulness of the 2007 Partin tables for predicting the pathologic results in patients at our institution; our figures were similar and even higher than those of the validation studies in North America and Europe. ConclusionsThe overall accuracy of the Partin tables in patients that underwent radical prostatectomy in our institution was similar to that of the original 2007 cohort.

Final analysis of a prospective trial on functional imaging for nodal staging in patients with prostate cancer at high risk for lymph node involvement

PurposeAccurate staging modalities to diagnose lymph node involvement in patients with prostate cancer (PCa) are lacking. We wanted to prospectively assess sensitivity, specificity, and positive predictive value (PPV) and negative predictive value of 11C-choline positron emission tomography (PET)-computed tomography (CT) and diffusion-weighted (DW) magnetic resonance imaging (MRI) for nodal staging in patients with PCa at high risk for lymph node involvement. Material and methodsIn total, 75 patients with a risk≥10% but<35% for lymph node (LN) metastases (Partin tables) who had N0 lesions based on the findings of contrast-enhanced CT scans were included. Patients underwent 11C-choline PET-CT and DW MRI before surgery, which consisted of a superextended lymph node dissection followed by radical prostatectomy. LNs were serially sectioned and histopathologically examined after pankeratin staining. These results were used as the gold standard to compare with the imaging results. ResultsOf 1,665 resected LNs (median = 21, range: 7–49), 106 affected LNs (median = 2, range: 1–10) were found in 37 of 75 patients (49%). On a region-based analysis, we found a low sensitivity of 8.2% and 9.5% and a PPV of 50.0% and 40.0% for 11C-choline PET-CT and DW MRI, respectively. The patient-based analysis showed a sensitivity of 18.9% and 36.1% for and a PPV of 63.6% and 86.7% 11C-choline PET-CT and DW MRI, respectively. Even when both imaging modalities were combined, sensitivity values remained too low to be clinically useful. ConclusionsBecause of the low sensitivity, there is no indication for routine clinical use of either 11C-choline PET-CT or DW MRI for LN staging in patients with PCa, in whom CT scan findings were normal.

Reliability of sentinel node procedure for lymph node staging in prostate cancer patients at high risk for lymph node involvement

Aim. To investigate the reliability of a sentinel node (SN) procedure for nodal staging in prostate cancer (PCa) patients at high risk for lymph node (LN) involvement.Material and methods. Seventy-four patients with localized prostate adenocarcinoma, who were clinically node-negative and had a risk of LN involvement of ≥ 10% (Partin tables), were prospectively enrolled. Upon intraprostatic 99mTc-nanocolloid injection, they underwent planar scintigraphy and SPECT imaging. Surgical removal of the SN, located by means of a gamma probe, was completed with a superextended LN dissection (seLND) as a reference and followed by radical prostatectomy.Results. In total, 470 SN (median 6, IQR 3–9) were scintigraphically detected of which 371 (median 4, IQR 2–6) were located by gamma probe and selectively removed during surgery (79%). Histopathology confirmed LN metastases in 37 patients (50%) having 106 affected LN in total (median number per patient 2, IQR 1–4). Twenty-eight patients were node positive (N+) based on the analysis of the resected SN. However, the seLND that was performed as a reference revealed nine additional N+ patients resulting in a sensitivity of 76% (28/37). In total, 15 of 37 patients (41%) had metastases in SN only and could have been spared seLND to remove all affected nodes.Conclusion. We found a relatively low sensitivity when addressing the SN procedure for nodal staging in PCa patients at high risk for LN involvement. Importantly, only less than half of the N+ patients could have been spared a seLND to remove all affected lymphoid tissue.

Prostate-specific antigen density as a parameter for the prediction of positive lymph nodes at radical prostatectomy.

Objective:The aim was to determine the prognostic ability of Partin's tables for a patient collective undergoing radical prostatectomy (RP) and to evaluate the association of prostate-specific antigen (PSA) density (PSAD) and postoperative lymph node status.Methods:From 1999 to 2006, 393 consecutive patients underwent RP at our Urology department. Patients with Gleason scores < 6, clinical stages >T2c or neoadjuvant hormonal therapy were excluded. Preoperative PSA, biopsy results, digital rectal examination, and prostate size at transrectal ultrasound were recorded. Risk stratification according to the Partin scoring system was performed. Postoperative results were compared with preoperative risk estimation. Univariate and multivariate statistical analysis about prediction of postoperative lymph node status was performed.Results:Lymph node invasion (LNI) was found in 36 patients (9.16%). Kendall's rank correlation analysis revealed a significant association between the number of removed LN and LNI (P = 0.016). Patients with LNI had a significantly higher preoperative PSA and PSAD. Preoperative Gleason score was a significant predictor of LNI. The Partin tables' prediction of organ confined stages, extraprostatic extension, and seminal vesicle invasion was in line with the pathological findings in our collective. PSAD was a significant predictor of LNI in univariate and multivariate analysis.Conclusion:The most widely used nomogram is of high value in therapy decision-making, although it remains an auxiliary means. Considering the performance of lymph node dissection, surgeons should be aware of the specifics of the applied nomogram. PSAD appears as a useful adjunctive parameter for preoperative prostate risk estimation and warrants further evaluation.

Artificial neural network for predicting pathological stage of clinically localized prostate cancer in a Taiwanese population

BackgroundWe developed an artificial neural network (ANN) model to predict prostate cancer pathological staging in patients prior to when they received radical prostatectomy as this is more effective than logistic regression (LR), or combined use of age, prostate-specific antigen (PSA), body mass index (BMI), digital rectal examination (DRE), trans-rectal ultrasound (TRUS), biopsy Gleason sum, and primary biopsy Gleason grade. MethodsOur study evaluated 299 patients undergoing retro-pubic radical prostatectomy or robotic-assisted laparoscopic radical prostatectomy surgical procedures with pelvic lymph node dissection. The results were intended to predict the pathological stage of prostate cancer (T2 or T3) after radical surgery. The predictive ability of ANN was compared with LR and validation of the 2007 Partin Tables was estimated by the areas under the receiving operating characteristic curve (AUCs). ResultsOf the 299 patients we evaluated, 109 (36.45%) displayed prostate cancer with extra-capsular extension (ECE), and 190 (63.55%) displayed organ-confined disease (OCD). LR analysis showed that only PSA and BMI were statistically significant predictors of prostate cancer with capsule invasion. Overall, ANN outperformed LR significantly (0.795 ± 0.023 versus 0.746 ± 0.025, p = 0.016). Validation using the current Partin Tables for the participants of our study was assessed, and the predictive capacity of AUC for OCD was 0.695. ConclusionANN was superior to LR at predicting OCD in prostate cancer. Compared with the validation of current Partin Tables for the Taiwanese population, the ANN model resulted in larger AUCs and more accurate prediction of the pathologic stage of prostate cancer.

Predictive Value of Magnetic Resonance Imaging Determined Tumor Contact Length for Extracapsular Extension of Prostate Cancer

Tumor contact length is defined as the amount of prostate cancer in contact with the prostatic capsule. We evaluated the ability of magnetic resonance imaging determined tumor contact length to predict microscopic extracapsular extension compared to existing predictors of extracapsular extension. We retrospectively analyzed the records of 111 consecutive patients with magnetic resonance imaging/ultrasound fusion targeted, biopsy proven prostate cancer who underwent radical prostatectomy from January 2010 to July 2013. Median patient age was 64 years and median prostate specific antigen was 8.9 ng/ml. Clinical stage was cT1 in 93 cases (84%) and cT2 in 18 (16%). Postoperative pathological analysis confirmed pT2 in 71 patients (64%) and pT3 in 40 (36%). We evaluated 1) in the radical prostatectomy specimen the correlation of microscopic extracapsular extension with pathological cancer volume, pathological tumor contact length and Gleason score, 2) the correlation between microscopic extracapsular extension and magnetic resonance imaging tumor contact length, and 3) the ability of preoperative variables to predict microscopic extracapsular extension. Logistic regression analysis revealed that pathological tumor contact length correlated better with microscopic extracapsular extension than the predictive power of pathological cancer volume (0.821 vs 0.685). The Spearman correlation between pathological and magnetic resonance imaging tumor contact length was r = 0.839 (p <0.0001). ROC AUC analysis revealed that magnetic resonance imaging tumor contact length outperformed cancer core involvement on targeted biopsy and the Partin tables to predict microscopic extracapsular extension (0.88 vs 0.70 and 0.63, respectively). At a magnetic resonance imaging tumor contact length threshold of 20 mm the accuracy for diagnosing microscopic extracapsular extension was superior to that of conventional magnetic resonance imaging criteria (82% vs 67%, p = 0.015). We developed a predicted probability plot curve of extracapsular extension according to magnetic resonance imaging tumor contact length. Magnetic resonance imaging determined tumor contact length could be a promising quantitative predictor of microscopic extracapsular extension.

Comparing 3-T multiparametric MRI and the Partin tables to predict organ-confined prostate cancer after radical prostatectomy

ObjectivesThe purpose of our study was to test our hypothesis that multiparametric magnetic resonance imaging (mpMRI) may have a higher prognostic accuracy than the Partin tables in predicting organ-confined (OC) prostate cancer and extracapsular extension (ECE) after radical prostatectomy (RP). Methods and materialsAfter institutional review board approval, we retrospectively reviewed 60 patients who underwent 3-T mpMRI before RP. mpMRI was used to assess clinical stage and the updated version of the Partin tables was used to calculate the probability of each patient to harbor OC disease. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of mpMRI in detecting OC and ECE were calculated. Logistic regression models predicting OC pathology were created using either clinical stage at mpMRI or Partin tables probability. The area under the curve was used to calculate the predictive accuracy of each model. ResultsMedian prostate-specific antigen level at diagnosis was 5ng/ml (range: 4.1–6.7ng/ml). Overall, 52 (86.7%) men had cT1 disease, 7 (11.7%) had cT2a/b, and 1 (1.6%) had cT3b at digital rectal examination. Biopsy Gleason score was 6, 3+4 = 7, 4+3 = 7, 8, and 9 to 10 in 28 (46.7%), 15 (25%), 3 (5%), 10 (16.7%), and 4 (6.6%) patients, respectively. At mpMRI, clinical stage was defined as cT2a/b, cT2c, cT3a, and cT3b in 11 (18.3%), 23 (38.3%), 21 (35%), and 5 (8.4%) patients, respectively. At final pathology, 38 men (63.3%) had OC disease, whereas 18 (30%) had ECE and 4 (6.7%) had seminal vesicle invasion.The sensitivity, specificity, PPV, and NPV of mpMRI in detecting OC disease were 81.6%, 86.4%, 91.2%, and 73.1%, respectively, whereas in detecting ECE were 77.8%, 83.4%, 66.7%, and 89.7%, respectively. At logistic regression, both the Partin tables–derived probability and the mpMRI clinical staging were significantly associated with OC disease (all P<0.01). The area under the curves of the model built using the Partin tables and that of the mpMRI model were 0.62 and 0.82, respectively (P = 0.04). ConclusionsThe predictive accuracy of mpMRI in predicting OC disease on pathological analysis is significantly greater than that of the Partin tables. mpMRI had a high PPV (91.2%) when predicting OC disease and a high NPV (89.7%) with regard to ECE. mpMRI should be considered when planning prostate cancer treatment in addition to readily available clinical parameters.

MP42-16 COMPARISON OF THE PREDICTIVE ACCURACY OF THE PARTIN TABLES VS MULTI-PARAMETRIC MRI IN FORECASTING ORGAN-CONFINED PROSTATE CANCER

You have accessJournal of UrologyProstate Cancer: Staging II1 Apr 2014MP42-16 COMPARISON OF THE PREDICTIVE ACCURACY OF THE PARTIN TABLES VS MULTI-PARAMETRIC MRI IN FORECASTING ORGAN-CONFINED PROSTATE CANCER Niccolo Maria Passoni, Rajan T. Gupta, Christopher R. Kauffman, Kirema Garcia-Reyes, and Thomas J. Polascik Niccolo Maria PassoniNiccolo Maria Passoni More articles by this author , Rajan T. GuptaRajan T. Gupta More articles by this author , Christopher R. KauffmanChristopher R. Kauffman More articles by this author , Kirema Garcia-ReyesKirema Garcia-Reyes More articles by this author , and Thomas J. PolascikThomas J. Polascik More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2014.02.1193AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail Introduction and Objectives Current treatment planning for prostate cancer relies on clinical variables, such as PSA, clinical stage and biopsy findings. These variables have been combined into predictive tools, such as the Partin tables, with the aim of predicting final pathological stage for treatment decision-making. The aim of this study was to assess the predictive accuracy of the Partin tables and mp-MRI in forecasting organ-confined (OC) prostate cancer after radical prostatectomy (RP). Methods We reviewed data on 60 men who underwent 3.0 T prostate mp-MRI (T2, DWI and DCE) with an endorectal coil and subsequent RP. All MRIs were reviewed by a single board-certified fellowship-trained and experienced radiologist blinded to all clinical parameters. Mp-MRI was used to assess clinical stage (T2a/b vs T2c vs T3a vs T3b). The updated version of the Partin tables were used to calculate the probability of each patient to harbor OC disease. Sensitivity, specificity, positive (PPV) and negative predictive values (NPV) of mp-MRI in detecting OC and extra-capsular extension (ECE) were calculated. Linear logistic regression models prediciting OC pathology were created using either clinical stage at mp-MRI or Partin tables probability and AUC was used to calculate the predictive accuracy. Results Median PSA at diagnosis was 5 ng/mL (IQR 4.1-6.7 ng/mL). Overall, 52 (86.7%) men had cT1 disease, 7 (11.7%) had cT2a/b and 1 (1.6%) had cT3b at DRE. Biopsy Gleason score was 6, 3+4=7, 4+3=7, 8 and 9-10 in 28 (46.7%), 15 (25%), 3 (5%), 10 (16.7%) and 4 (6.6%) patients, respectively. At mp-MRI, clinical stage was defined as cT2a/b, cT2c, cT3a and cT3b in 11 (18.3%), 23 (38.3%), 21 (35%) and 5 (8.4%) patients. At final pathology 38 men (63.3%) had OC disease,,18 (30%) ECE and 4 (6.7%) seminal vesicle invasion. Sensitivity, specificity, PPV and NPV of mp-MRI in detecting OC were 81.6%, 86.4%, 91.2% and 73.1%, respectively, while in detecting ECE were 77.8%, 83.4%, 66.7% and 89.7%, respectively. At linear logistic regression, both Partin tables and mp-MRI clinical staging were significantly associated with OC disease (all p<0.01). The AUCs of the Partin tables and that of mp-MRI were 0.69 and 0.82, respectively (p=0.04). Conclusions The predictive accuracy of mp-MRI in predicting OC disease at pathological analysis significantly improves upon that of the Partin tables. Mp-MRI had a high PPV (91.2%) when predicting OC disease and a high NPV (89.7%) with regards to ECE. Mp-MRI should be considered when planning prostate cancer treatment in addition to readily available clinical parameters. © 2014FiguresReferencesRelatedDetails Volume 191Issue 4SApril 2014Page: e474 Advertisement Copyright & Permissions© 2014MetricsAuthor Information Niccolo Maria Passoni More articles by this author Rajan T. Gupta More articles by this author Christopher R. Kauffman More articles by this author Kirema Garcia-Reyes More articles by this author Thomas J. Polascik More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...