How Well Does The Partin Nomogram Predict Pathological Stage After Radical Prostatectomy In A Community Based Population? Results Of The Cancer Of The Prostate Strategic Urological Research Endeavor

Current controversies on the role of lymphadenectomy for prostate cancer

Lymph node dissection is part of the standard treatment protocol for various cancers, but its role in prostate cancer has been debatable for some time. Pelvic lymphadenectomy has been shown to better help stage prostate cancer patients, but has yet to be definitively proven to be of any benefit for survival. Various templates for lymph node dissections exist, and though some national guidelines have endorsed an extended pelvic node dissection, the choice of template is still controversial. Pelvic lymphadenectomy may lead to a slightly higher rate complications and operative time, and their use must be judiciously applied to patients with a high enough risk of lymph node involvement. We present a comprehensive review of the literature regarding the benefits and harms of lymph node dissection in prostate cancer.

Stage T3b prostate cancer diagnosed by seminal vesicle biopsy and treated with neoadjuvant hormone therapy, permanent brachytherapy and external beam radiotherapy

OBJECTIVES

To report the long-term results of prostate brachytherapy followed by external beam radiotherapy (EBRT) in men with a positive seminal vesicle biopsy (+SVB).

PATIENTS AND METHODS

In all, 1081 men with localised prostate cancer were treated with permanent brachytherapy, of which 615 had staging SVB and 53 (9.4%) were positive. Higher stage, Gleason score and PSA level were associated with a +SVB (P < 0.001). Patients with +SVB and negative laparoscopic pelvic lymph node dissection, bone and CT scans had 3 months of androgen-deprivation therapy (ADT) followed by ¹⁰³ Pd implant to the prostate (dose 100 Gy) and proximal SVs, and 2 months later 45 Gy EBRT. ADT was continued for a median of 6 months (total ADT 9 months). The mean (range) follow-up was 9 (5-22) years.

RESULTS

Biochemical freedom from failure (computed by the Phoenix definition), freedom from metastasis, and cause-specific survival (CSS) for patients with a negative SVB (-SVB) vs +SVB at 15 years, was 76.3% vs 60.6% (P = 0.001), 95.4% vs 78.2% (P < 0.001), and 95% vs 70.4% (P < 0.001), respectively. Prostate cancer death occurred in 45 of 590 (7.6%) men with a -SVB vs eight of 25 (32%) with a +SVB (odds ratio 5.7, 95% confidence interval 2.35-13.9, P < 0.001). Cox proportion hazard rates (HRs) demonstrated Gleason score (P < 0.001, HR 1.9), stage (P = 0.010, HR 1.42), RT dose (P = 0.013, HR 0.991), and +SVB (P = 0.001, HR 4.48), as significantly associated with CSS.

CONCLUSIONS

Men with a +SVB have inferior CSS compared to those with a -SVB. However, a strategy that included a SVB in high-risk patients and implantation of the SVs in men undergoing combined therapy still yields favourable long-term results.

Population-Based External Validation of the Updated 2012 Partin Tables in Contemporary North American Prostate Cancer Patients

OBJECTIVE

To externally validate the updated 2012 Partin Tables in contemporary North American patients treated with radical prostatectomy (RP) for localized prostate cancer (PCa) at community institutions.

MATERIALS AND METHODS

We examined records of 25,254 patients treated with RP and pelvic lymph node dissection (PLND) between 2010 and 2013, within the surveillance, epidemiology, and end results database. The ROC derived AUC assessed discriminant properties of the updated 2012 Partin Tables of organ confined disease (OC), extracapsular extension (ECE), seminal vesical invasion (SVI), and lymph node invasion (LNI). Calibration plots focused on calibration between predicted and observed rates.

RESULTS

Proportions of OC, ECE, SVI, and LNI at RP were 69.8%, 18.4%, 7.4%, and 4.4%, respectively. Accuracy for prediction of OC, ECE, SVI, and LNI was 70.4%, 59.9%, 72.9%, and 77.1%, respectively. In subgroup analyses in patients with nodal yield >10, accuracy for LNI prediction was 76.0%. Subgroup analyses in elderly patients and in African American patients revealed decreased accuracy for prediction of all four endpoints. Last but not least, SVI and LNI calibration plots showed excellent agreement, versus good agreement for OC (maximum underestimation of 10%) and poor agreement for ECE (maximum overestimation of 12%).

CONCLUSION

Taken together, the updated 2012 Partin Tables can be unequivocally endorsed for prediction of OC, SVI, and LNI in community-based patients with localized PCa. Conversely, ECE predictions failed to reach the minimum accuracy requirements of 70%. Prostate 77:105-113, 2017. © 2016 Wiley Periodicals, Inc.

Multi-parametric MRI of the prostate: Factors predicting extracapsular extension at the time of radical prostatectomy

Objective

Extracapsular extension (ECE) of prostate cancer is a poor prognostic factor associated with progression, recurrence after treatment, and increased prostate cancer-related mortality. Accurate staging prior to radical prostatectomy is crucial in avoidance of positive margins and when planning nerve-sparing procedures. Multi-parametric magnetic resonance imaging (mpMRI) of the prostate has shown promise in this regard, but is hampered by poor sensitivity. We sought to identify additional clinical variables associated with pathologic ECE and determine our institutional accuracy in the detection of ECE amongst patients who went on to radical prostatectomy.

Methods

mpMRI studies performed between the years 2012 and 2014 were cross-referenced with radical prostatectomy specimens. Predictive properties of ECE as well as additional clinical and biochemical variables to identify pathology-proven prostate cancer ECE were analyzed.

Results

The prevalence of ECE was 32.4%, and the overall accuracy of mpMRI for ECE was 84.1%. Overall mpMRI sensitivity, specificity, positive predictive value, and negative predictive value for detection of ECE were 58.3%, 97.8%, 93.3%, and 81.5%, respectively. Specific mpMRI characteristics predictive of pathologic ECE included primary lesion size ((20.73 ± 9.09) mm, mean ± SD, p < 0.001), T2 PIRADS score (p = 0.009), overall primary lesion score (p < 0.001), overall study suspicion score (p = 0.003), and MRI evidence of seminal vesicle invasion (SVI) (p = 0.001).

Conclusion

While mpMRI is an accurate preoperative assessment tool for the detection of ECE, its overall sensitivity is poor, likely related to the low detection rate of standard protocol MRI for microscopic extraprostatic disease. The additional mpMRI findings described may also be considered in surgical margin planning prior to radical prostatectomy.

Prediction of pathological stage based on clinical stage, serum prostate-specific antigen, and biopsy Gleason score: Partin Tables in the contemporary era

OBJECTIVE

To update the Partin Tables for prediction of pathological stage in the contemporary setting and examine trends in patients treated with radical prostatectomy (RP) over the past three decades.

PATIENTS AND METHODS

From January 2010 to October 2015, 4459 men meeting inclusion criteria underwent RP and pelvic lymphadenectomy for histologically confirmed prostate cancer at the Johns Hopkins Hospital. Preoperative clinical stage, serum prostate-specific antigen (PSA) level, and biopsy Gleason score (i.e. prognostic Grade Group) were used in a polychotomous logistic regression model to predict the probability of pathological outcomes categorised as: organ-confined (OC), extraprostatic extension (EPE), seminal vesicle involvement (SV+), or lymph node involvement (LN+). Preoperative characteristics and pathological findings in men treated with RP since 1983 were collected and clinical-pathological trends were described.

RESULTS

The median (range) age at surgery was 60 (34-77) years and the median (range) PSA level was 4.9 (0.1-125.0) ng/mL. The observed probabilities of pathological outcomes were: OC disease in 74%, EPE in 20%, SV+ in 4%, and LN+ in 2%. The probability of EPE increased substantially when biopsy Gleason score increased from 6 (Grade Group 1, GG1) to 3 + 4 (GG2), with smaller increases for higher grades. The probability of LN+ was substantially higher for biopsy Gleason score 9-10 (GG5) as compared to lower Gleason scores. Area under the receiver operating characteristic curves for binary logistic models predicting EPE, SV+, and LN+ vs OC were 0.724, 0.856, and 0.918, respectively. The proportion of men treated with biopsy Gleason score ≤6 cancer (GG1) was 47%, representing a substantial decrease from 63% in the previous cohort and 77% in 2000-2005. The proportion of men with OC cancer has remained similar during that time, equalling 73-74% overall. The proportions of men with SV+ (4.1% from 3.4%) and LN+ (2.3% from 1.4%) increased relative to the preceding era for the first time since the Partin Tables were introduced in 1993.

CONCLUSIONS

The Partin Tables remain a straightforward and accurate approach for projecting pathological outcomes based on readily available clinical data. Acknowledging these data are derived from a tertiary care referral centre, the proportion of men with OC disease has remained stable since 2000, despite a substantial decline in the proportion of men with biopsy Gleason score 6 (GG1). This is consistent with the notion that many men with Gleason score 6 (GG1) disease were over treated in previous eras.

Machine learning for improved pathological staging of prostate cancer: a performance comparison on a range of classifiers

OBJECTIVES

Prediction of prostate cancer pathological stage is an essential step in a patient's pathway. It determines the treatment that will be applied further. In current practice, urologists use the pathological stage predictions provided in Partin tables to support their decisions. However, Partin tables are based on logistic regression (LR) and built from US data. Our objective is to investigate a range of both predictive methods and of predictive variables for pathological stage prediction and assess them with respect to their predictive quality based on U.K. data.

METHODS AND MATERIAL

The latest version of Partin tables was applied to a large scale British dataset in order to measure their performances by mean of concordance index (c-index). The data was collected by the British Association of Urological Surgeons (BAUS) and gathered records from over 1700 patients treated with prostatectomy in 57 centers across UK. The original methodology was replicated using the BAUS dataset and evaluated using concordance index. In addition, a selection of classifiers, including, among others, LR, artificial neural networks and Bayesian networks (BNs) was applied to the same data and compared with each other using the area under the ROC curve (AUC). Subsets of the data were created in order to observe how classifiers perform with the inclusion of extra variables. Finally a local dataset prepared by the Aberdeen Royal Infirmary was used to study the effect on predictive performance of using different variables.

RESULTS

Partin tables have low predictive quality (c-index=0.602) when applied on UK data for comparison on patients with organ confined and extra prostatic extension conditions, patients at the two most frequently observed pathological stages. The use of replicate lookup tables built from British data shows an improvement in the classification, but the overall predictive quality remains low (c-index=0.610). Comparing a range of classifiers shows that BNs generally outperform other methods. Using the four variables from Partin tables, naive Bayes is the best classifier for the prediction of each class label (AUC=0.662 for OC). When two additional variables are added, the results of LR (0.675), artificial neural networks (0.656) and BN methods (0.679) are overall improved. BNs show higher AUCs than the other methods when the number of variables raises

CONCLUSION

The predictive quality of Partin tables can be described as low to moderate on U.K. data. This means that following the predictions generated by Partin tables, many patients would received an inappropriate treatment, generally associated with a deterioration of their quality of life. In addition to demographic differences between U.K. and the original U.S. population, the methodology and in particular LR present limitations. BN represents a promising alternative to LR from which prostate cancer staging can benefit. Heuristic search for structure learning and the inclusion of more variables are elements that further improve BN models quality.

Predictive models before and after radical prostatectomy

CONTEXT

In the last 10 years, several user-friendly predictive tools have been developed to help clinicians in decision-making process before and after radical prostatectomy.

OBJECTIVE

To review the most known and used predictive models in pre-operative and post-operative setting.

EVIDENCE ACQUISITION

A structured, comprehensive literature review was performed using data retrieved from recent review articles, original articles, and abstracts. Used keywords were predictive models, nomograms, look-up tables, classification and regression-tree analysis, artificial neural networks, and radical prostatectomy.

EVIDENCE SYNTHESIS

A great amount of predictive models has been provided in oncology setting: nomograms, look-up tables, classification and regression-tree analysis, propensity scores, risk-group stratification models, and artificial neural networks. Pre-surgery predictive tools offer the opportunity of getting the most evidence-based and individualized selection of available treatment alternatives. Post-operative predictive models usually provide higher accuracy relative to the pre-surgery models.

CONCLUSIONS

Decisions and treatment should be tailored to each individual patient and to the specific characteristics of patients. A number of available predictive models represent a tool to provide accurate prediction of cancer natural history and to improve patients' care.

Critical review of prostate cancer predictive tools

Prostate cancer is a very complex disease, and the decision-making process requires the clinician to balance clinical benefits, life expectancy, comorbidities and potential treatment-related side effects. Accurate prediction of clinical outcomes may help in the difficult process of making decisions related to prostate cancer. In this review, we discuss attributes of predictive tools and systematically review those available for prostate cancer. Types of tools include probability formulas, look-up and propensity scoring tables, risk-class stratification prediction tools, classification and regression tree analysis, nomograms and artificial neural networks. Criteria to evaluate tools include discrimination, calibration, generalizability, level of complexity, decision analysis and ability to account for competing risks and conditional probabilities. The available predictive tools and their features, with a focus on nomograms, are described. While some tools are well-calibrated, few have been externally validated or directly compared with other tools. In addition, the clinical consequences of applying predictive tools need thorough assessment. Nevertheless, predictive tools can facilitate medical decision-making by showing patients tailored predictions of their outcomes with various alternatives. Additionally, accurate tools may improve clinical trial design.

Validation of the partin nomogram for prostate cancer in a national sample

PURPOSE

The Partin tables are a nomogram that is widely used to discriminate prostate cancer pathological stages, given common preoperative clinical characteristics. The nomogram is based on patients undergoing radical prostatectomy at The Johns Hopkins Medical Institutions. We validated the Partin tables in a large, population based sample.

MATERIALS AND METHODS

The National Cancer Institute Surveillance, Epidemiology and End Results database was used to identify patients treated from 2004 to 2005 who underwent radical prostatectomy. The 2007 Partin tables were used to estimate the prevalence of positive lymph nodes, seminal vesicle invasion, extraprostatic extension and organ confined disease in men with prostate cancer in the database using clinical stage, preoperative prostate specific antigen and Gleason score. The discriminative ability of the tables was explored by constructing ROC curves.

RESULTS

We identified 11,185 men who underwent radical prostatectomy for prostate cancer in 2004 to 2005. The Partin tables discriminated well between patient groups at risk for positive lymph nodes and seminal vesicle invasion (AUC 0.77 and 0.74, respectively). The discrimination of extraprostatic extension and organ confined disease was more limited (AUC 0.62 and 0.68, respectively). The AUC for positive lymph nodes was 0.78 in white men, 0.73 in black men and 0.83 in Asian/Pacific Islander men (p = 0.17). The AUC for positive lymph nodes in men 61 years old or younger was 0.80 vs 0.74 in men older than 61 years (p = 0.03).

CONCLUSIONS

The Partin tables showed excellent discrimination for seminal vesicle invasion and positive lymph nodes. Discrimination of extraprostatic extension and organ confined disease was more limited. The Partin tables performed best in young men.

Evaluating localized prostate cancer and identifying candidates for focal therapy

Can focal therapy successfully control prostate cancer? Also, if so, which patients should be considered eligible? With limited data available from relatively few patients, these questions are difficult to answer. At this writing, the most likely candidates for focal therapy are patients with low-risk, small-volume tumors, located in 1 region or sector of the prostate, who would benefit from early intervention. The difficulty lies in reliably identifying these men. The larger number of cores obtained in each needle biopsy session has increased both the detection of prostate cancer and the potential risk of overtreating many patients whose cancers pose very little risk to life or health. Urologists typically perform at least a 12-core template biopsy. Although the debate continues about the optimal template, laterally and peripherally directed biopsies have been shown to improve the diagnostic yield. However, as many as 25% of tumors arise anteriorly and can be missed with peripherally directed techniques. Prostate cancer tends to be multifocal, even in its earliest stages. However, the secondary cancers are usually smaller and less aggressive than the index cancer. They appear similar to the incidental cancers found in cystoprostatectomy specimens and appear to have little effect on prognosis in surgical series. When a single focus of cancer is found in 1 core, physicians rightly suspect that more foci of cancer are present in the prostate. Assessing the risk in these patients is challenging when determined by the biopsy data alone. To predict the presence of a very low-risk or "indolent" cancer, nomograms have been developed to incorporate clinical stage, Gleason grade, prostate-specific antigen levels, and prostate volume, along with the quantitative analysis of the biopsy results. Transperineal "mapping" or "saturation" biopsies have been advocated to detect cancers missed or underestimated by previous transrectal biopsies. This approach could provide the accurate staging, grading, and tumor localization needed for a focal therapy program. Nevertheless, for men with minimal cancer who are amenable to active surveillance or focal therapy, consensus about the most accurate biopsy strategy has not yet been reached. Imaging, particularly magnetic resonance imaging and magnetic resonance spectroscopic imaging, has been used to assess men with early-stage prostate cancer. Large-volume cancers can be seen reasonably well, but small lesions have been difficult to detect reliably or measure accurately. Factors such as voxel resolution, organ movement, biopsy artifact, and benign changes have limited the consistent estimation of the quantitative tumor volume. Nevertheless, magnetic resonance imaging and magnetic resonance spectroscopic imaging can aid in evaluating patients with prostate cancer being considered for focal therapy by providing additional evidence that the patient does not harbor an otherwise undetected high-risk, aggressive cancer. In some cases, imaging can usefully identify the location of even a limited-sized index cancer. When imaging findings are substantiated by mapping biopsy results, confidence in the accurate characterization of the cancer is enhanced. Correlating the imaging results with tissue changes during and after treatment can be of use in monitoring the ablative effects in the prostate and in assessing for tumor recurrence. More work is necessary before staging studies can uniformly characterize a prostate cancer before therapy, much less reliably identify and locate small-volume cancer within the prostate. However, exploring the role of focal ablation as a therapeutic option for selected men with low-risk, clinically localized, prostate cancer need not await the emergence of perfectly accurate staging studies, any more than the application of radical surgery or radiotherapy have. Modern biopsy strategies, combined with optimal imaging and nomograms to estimate the pathologic stage and risk, taken together, provide a sound basis for the selection of appropriate patients for entry into prospective clinical trials of focal therapy.

External validation of the updated partin tables in a cohort of French and Italian men

PURPOSE

To test the discrimination and calibration properties of the newly developed 2007 Partin Tables in two European cohorts with localized prostate cancer.

METHODS

Data on clinical and pathologic characteristics were obtained for 1,064 men treated with radical prostatectomy at the Creteil University Health Center in France (n = 839) and at the Milan University Vita-Salute in Italy (n = 225). Overall discrimination was assessed with receiver operating characteristic curve analysis, which quantified the accuracy of stage predictions for each center. Calibration plots graphically explored the relationship between predicted and observed rates of extracapsular extension (ECE), seminal vesicle invasion (SVI) and lymph node invasion (LNI).

RESULTS

The rates of ECE, SVI, and LNI were 28%, 14%, and 2% in the Creteil cohort vs. 11%, 5%, and 5% in the Milan cohort. In the Creteil cohort, the accuracy of ECE, SVI, and LNI prediction was 61%, 71%, and 82% vs. 66%, 92% and 75% for the Milan cohort. Important departures were recorded between Partin Tables' predicted and observed rates of ECE, SVI, and LNI within both cohorts.

CONCLUSIONS

The 2007 Partin Tables demonstrated worse performance in European men than they originally did in North American men. This indicates that predictive models need to be externally validated before their implementation into clinical practice.

Multi-institutional external validation of seminal vesicle invasion nomograms: head-to-head comparison of Gallina nomogram versus 2007 Partin tables

PURPOSE

The Partin tables represent one of the most widely used prostate cancer staging tools for seminal vesicle invasion (SVI) prediction. Recently, Gallina et al. reported a novel staging tool for the prediction of SVI that further incorporated the use of the percentage of positive biopsy cores. We performed an external validation of the Gallina et al. nomogram and the 2007 Partin tables in a large, multi-institutional North American cohort of men treated with robotic-assisted radical prostatectomy.

METHODS AND MATERIALS

Clinical and pathologic data were prospectively gathered from 2,606 patients treated with robotic-assisted radical prostatectomy at one of four North American robotic referral centers between 2002 and 2007. Discrimination was quantified with the area under the receiver operating characteristics curve. The calibration compared the predicted and observed SVI rates throughout the entire range of predictions.

RESULTS

At robotic-assisted radical prostatectomy, SVI was recorded in 4.2% of patients. The discriminant properties of the Gallina et al. nomogram resulted in 81% accuracy compared with 78% for the 2007 Partin tables. The Gallina et al. nomogram overestimated the true rate of SVI. Conversely, the Partin tables underestimated the true rate of SVI.

CONCLUSION

The Gallina et al. nomogram offers greater accuracy (81%) than the 2007 Partin tables (78%). However, both tools are associated with calibration limitations that need to be acknowledged and considered before their implementation into clinical practice.

Percentage of Positive Biopsy Cores Can Improve the Ability to Predict Lymph Node Invasion in Patients Undergoing Radical Prostatectomy and Extended Pelvic Lymph Node Dissection

OBJECTIVE

We hypothesized that the information stemming from biopsy cores can enhance the ability to predict the rate of lymph node invasion (LNI) at radical retropubic prostatectomy (RRP) in men subjected to extended pelvic lymphadenectomy (ePLND).

MATERIALS AND METHODS

A cohort of 278 consecutive patients (mean age: 66.2 yr) underwent a RRP and an ePLND, in which 10 or more nodes were removed and examined. The median PSA was 7.5 ng/ml. Clinical stage was mostly T1c (59.4%) and T2 (37.8%). Biopsy Gleason sum was 2-5 in 26.6%, 6 in 39.2%, 7 in 27%, and 8-10 in 7.2%. The number of positive cores was 1-19 (median: 4), whilst percentage of positive cores was 7.1-100% (median: 37.5%). Logistic regression models tested the association between the above predictors and LNI. Testing of PSA was coded as either a continuous variable (CV) or a cubic spline (CS). Individual variables and combined accuracy were tested in regression-based nomograms, which were subjected to 10,000 bootstrap resamples to reduce overfit bias.

RESULTS

Mean number of lymph nodes examined was 17.5 (range: 10-38); 29 patients (10.4%) had LNI. Percentage of positive cores (78.5%) and biopsy Gleason sum (78.4%) were the most informative predictors of LNI. A nomogram based on clinical stage, PSA (CV), and biopsy Gleason sum was 79.7% accurate versus 83% (3.3% gain, p<0.001) when percentage of positive cores was added. A 2.7% gain (83.7% vs. 81%; p<0.001) was recorded after the addition of the percentage of positive cores when PSA was coded as a CS.

CONCLUSIONS

Percentage of positive biopsy cores should be considered in prediction of LNI at ePLND, because it significantly improves the combined accuracy of established clinical predictors such as PSA, clinical stage, and biopsy Gleason sum.

Updated nomogram to predict pathologic stage of prostate cancer given prostate-specific antigen level, clinical stage, and biopsy Gleason score (Partin tables) based on cases from 2000 to 2005

OBJECTIVES

To update the 2001 "Partin tables" with a contemporary patient cohort and revised variable categorization, correcting for the effects of stage migration.

METHODS

We analyzed 5730 men treated with prostatectomy (without neoadjuvant therapy) between 2000 and 2005 at the Johns Hopkins Hospital. Average age was 57 years. Multivariable logistic regression was used to estimate the probability of organ-confined disease, extraprostatic extension, seminal vesicle involvement, or lymph node involvement. Predictor variables included preoperative prostate-specific antigen (PSA) level (0 to 2.5, 2.6 to 4.0, 4.1 to 6.0, 6.1 to 10.0, and greater than 10.0 ng/mL), clinical stage (T1c, T2a, and T2b/T2c), and biopsy Gleason score (5 to 6, 3 + 4 = 7, 4 + 3 = 7, or 8 to 10). Bootstrap resampling was used to generate 95% confidence intervals for predicted probabilities.

RESULTS

Seventy-seven percent of patients had T1c, 76% had Gleason score 5 to 6, 80% had a PSA level between 2.5 and 10.0 ng/mL, and 73% had organ-confined disease. Nomograms were developed for the predicted probability of pathologically organ-confined disease, extraprostatic extension, seminal vesicle invasion, or lymph node involvement. The risk of non-organ-confined disease increased with increases in any individual prognostic factor. The dramatic decrease in clinical stage T2c compared with the patient series used in the previous models resulted in T2b and T2c being combined as a single predictor in the nomogram.

CONCLUSIONS

These updated "Partin tables" were generated to reflect trends in presentation and pathologic stage for men diagnosed with clinically localized prostate cancer at our institution. Clinicians and patients can use these nomograms to help make important decisions regarding management of prostate cancer.

[Prognostic factor and prediction tables for clinically localized prostate cancer]

INTRODUCTION AND OBJECTIVES

To identify the independent prognostic factors of prostate cancer and to develop a table for predicting the probabilities of not-localised prostate cancer occurrence, thus permitting to restrict the radical prostatectomy indication to those patients who have greater probabilities of being cured by the procedure.

METHODS

1293 patients with clinically localised prostate cancer, with histories of neither hormone therapy nor prostate radiation therapy, in whom radical prostatectomy was performed during the period 1990-2003, were retrospectively evaluated. In order to analyse the prognostic factors, logistic regression was carried out by studying all the potential confusion and interaction factors, and by introducing the independent variables in a forward fashion with the following criteria: BCON(0.0001) LCON(0.00001) ITER(50) POUT(0.1). The prognostic variables were categorised, and the prediction table of the not-localised prostate cancer probability was developed from them.

RESULTS

Clinical stage, prostatic specific antigen and Gleason's "grade" were identified as prognostic factors, taking into account that the higher they are, the higher the probability of not-localised prostate cancer occurrence. Logistic regression enabled us to develop a table to predict the probability of not-localised prostate cancer in which, taking a 50% probability as the cutoff point, a 26.13% sensitivity and a 94.65% specificity are obtained. The pathological examination of the prostate and the lymphadenectomy showed that, globally, 70% of the tumours were localised.

CONCLUSIONS

Application of tables to predicting the probability of having not-localised prostate cancer offers the possibility of improving the prognostic accuracy of the so-called "risk groups", and enables to issue a therapeutic indication better adjusted to the actual status of the disease.

Validation of a Nomogram Predicting the Probability of Lymph Node Invasion among Patients Undergoing Radical Prostatectomy and an Extended Pelvic Lymphadenectomy

INTRODUCTION

Our goal was to develop and internally validate a nomogram for prediction of lymph node invasion (LNI) in patients with clinically localized prostate cancer undergoing extended pelvic lymphadenectomy (ePLND).

METHODS

602 consecutive patients (mean age 65.8 years) underwent an ePLND, where 10 or more nodes were removed. PSA was 1.1-49.9 (median 7.2). Clinical stages were: T1c in 55.6%, T2 in 41.4% and T3 in 3%. Biopsy Gleason sums were: 6 or less in 66%, 7 in 25.4%, 8-10 in 8.6%. Multivariate logistic regression models tested the association between all of the above predictors and LNI. Regression-based coefficients were used to develop a nomogram predicting LNI and 200 bootstrap resamples were used for internal validation.

RESULTS

Mean number of lymph nodes removed was 17.1 (range 10-40). LNI was detected in 66 patients (11.0%). Univariate predictive accuracy for total PSA, clinical stage and biopsy Gleason sum was 63%, 58% and 73%, respectively. A nomogram based on clinical stage, PSA and Biopsy Gleason sum demonstrated bootstrap-corrected predictive accuracy of 76%.

CONCLUSIONS

A nomogram based on pre-treatment PSA, clinical stage and biopsy Gleason sum can highly accurately predict LNI at ePLND.

Predictive Ability of Partin Tables 2001 in a Welsh Population

OBJECTIVES

Partin tables are widely used to select and counsel patients prior to radical surgery for prostate cancer. However, Partin tables have been developed in the USA which has a different ethnic mixture from that of North Wales. We aimed to assess Partin tables' predictive ability in a Welsh population.

MATERIALS AND METHODS

193 patients underwent radical retropubic prostatectomy for clinically localized carcinoma of the prostate between April 1993 and July 2004 in a single institution in North Wales. Complete preoperative clinical staging information was available in 177 patients. Receiver operating characteristic curve analysis was used.

RESULTS

The mean patient age was 64 (48-73) years. Preoperative clinical staging distribution was: T1c 46.6% and T2 53.4%. 75% had organ-confined disease (TNM 1992). Extracapsular extension without seminal vesicle or lymph node involvement was seen in 13.5%. Nine percent had seminal vesicle invasion without lymph node involvement. Lymph node metastasis was found in 2.2%. The predictive effectiveness of the Partin table was high with an area under ROC curve of 0.733 for organ confinement, 0.738 for seminal vesicle invasion and 0.780 for lymph node involvement (CI 95%).

CONCLUSION

Our study demonstrated that the predictive ability of Partin tables for prostate cancer is also applicable to a Welsh population.

Validation of a Nomogram for Prediction of Side Specific Extracapsular Extension at Radical Prostatectomy

PURPOSE

We have previously have reported a tree structured regression model for predicting SS-ECE. Others recently reported a logistic regression based SS-ECE nomogram. We developed a nomogram and compared the performance and discriminant properties of the tree regression and the nomogram in a contemporary cohort of European patients treated with radical retropubic prostatectomy.

MATERIALS AND METHODS

The cohort consisted of 1,118 patients with pretreatment prostate specific antigen 0.1 to 73.2 ng/ml (median 6.6). Each of the 2,236 prostate lobes was considered separately. Clinical stage, pretreatment PSA, biopsy Gleason sum, percent positive cores and percent cancer in the biopsy specimen were used as predictors in a logistic regression model predicting SS-ECE. Regression coefficients were then used to generate an SS-ECE nomogram. Performance characteristics and discriminant properties of the previously published tree regression were also tested in the same cohort. For internal validation and to decrease overfit bias 200 bootstrap re-samples were applied to accuracy estimates for each method.

RESULTS

ECE was present in 303 of 1,118 radical retropubic prostatectomy specimens (27%) and in 385 lobes (17%). In logistic regression models all variables were statistically significant multivariate predictors of SS-ECE except the percent of positive biopsy cores (p = 0.7). Bootstrap corrected predictive accuracy of the SS-ECE nomogram was 0.840 vs 0.700 for the tree regression model.

CONCLUSIONS

Logistic regression based nomogram predictions of SS-ECE are highly accurate and represent a valuable aid for assessing the risk of ECE prior to surgery.

Development and internal validation of a nomogram predicting the probability of prostate cancer Gleason sum upgrading between biopsy and radical prostatectomy pathology

OBJECTIVE

Previous reports indicate that as many as 43% of men with low grade PCa at biopsy will be diagnosed with high-grade PCa at RP. We explored the rate of upgrading from biopsy to RP specimen in our contemporary cohort, and developed a model capable of predicting the probability of biopsy Gleason sum upgrading.

MATERIALS AND METHODS

The study cohort consisted of 2982 men treated with RP, with available clinical stage, serum prostate specific antigen and biopsy Gleason scores. These clinical data were used as predictors in multivariate logistic regression models (LRM) addressing the rate of Gleason sum upgrading between biopsy and RP pathology. LRM regression coefficients were used to develop a nomogram predicting the probability of Gleason sum upgrading and was subjected to 200 bootstrap resamples for internal validation and to reduce overfit bias.

RESULTS

Overall, 875 patients were upgraded (29.3%). In multivariate LRMs, all predictors were highly significant (all p values <0.0001). Bootstrap-corrected predictive accuracy of the nomogram predicting the probability of Gleason sum upgrading between biopsy and RP was 0.804.

CONCLUSION

We developed a highly accurate clinical aid for treatment decision-making. It may prove useful when the possibility of a more aggressive Gleason variant may change the treatment options.

Multigene Methylation Analysis for Detection and Staging of Prostate Cancer

PURPOSE

Aberrant gene promoter methylation profiles have been well-studied in human prostate cancer. Therefore, we rationalize that multigene methylation analysis could be useful as a diagnostic biomarker. We hypothesize that a new method of multigene methylation analysis could be a good diagnostic and staging biomarker for prostate cancer.

EXPERIMENTAL DESIGN

To test our hypothesis, prostate cancer samples (170) and benign prostatic hyperplasia samples (69) were examined by methylation-specific PCR for three genes: adenomatous polyposis coli (APC), glutathione S-transferase pi (GSTP1), and multidrug resistance 1 (MDR1). The methylation status of representative samples was confirmed by bisulfite DNA sequencing analysis. We further investigated whether methylation score (M score) can be used as a diagnostic and staging biomarker for prostate cancer. The M score of each sample was calculated as the sum of the corresponding log hazard ratio coefficients derived from multivariate logistic regression analysis of methylation status of various genes for benign prostatic hyperplasia and prostate cancer. The optimal sensitivity and specificity of the M score for diagnosis and for staging of prostate cancer was determined by receiver-operator characteristic (ROC) curve analysis. A pairwise comparison was employed to test for significance using the area under the ROC curve analysis. For each clinicopathologic finding, the association with prostate-specific antigen (PSA) failure-free probability was determined using Kaplan-Meier curves and a log-rank test was used to determine significance. The relationship between M score and clinicopathologic findings was analyzed by either the Mann-Whitney U test, Kruskal-Wallis test, or the Spearman rank correlation test.

RESULTS

The frequency of positive methylation-specific PCR bands for APC, GSTP1, and MDR1 genes in prostate cancer samples was 64.1%, 54.0%, and 55.3%, respectively. In benign prostatic hyperplasia samples, it was 8.7%, 5.8%, and 11.6%, respectively. There was a significant correlation of M score with high pT category (P < 0.001), high Gleason sum (P < 0.001), high preoperative PSA (P = 0.027), and advanced pathologic features. For all patients, the M score had a sensitivity of 75.9% and a specificity of 84.1% as a diagnostic biomarker using a cutoff value of 1.0. In patients with low or borderline PSA levels (<10.0 ng/mL), the M score was significantly higher in prostate cancers than in benign prostatic hyperplasias (2.635 +/- 0.200 and 0.357 +/- 0.121, respectively). ROC curve analysis revealed that the M score had a sensitivity of 65.4% and a specificity of 94.2% when 1.0 was used as a cutoff value. For all patients, M score can distinguish organ-confined (< or =pT(2)) from locally advanced cancer (> or =pT(3)) with a sensitivity of 72.1% and a specificity of 67.8%. Moreover, considering patients with PSA levels of <10 ng/mL, the M score has a sensitivity of 67.1% and a specificity of 85.7%. The ROC curve analysis showed a significant difference between M score and PSA (P = 0.010).

CONCLUSIONS

This is the first report demonstrating that M score is a new method for multigene methylation analysis that can serve as a good diagnostic and staging biomarker for prostate cancer.

Validation of 2001 Partin tables in Turkey: a multicenter study

OBJECTIVE

Although Partin tables were developed in United States to predict the stage of prostate cancer preoperatively, they are used by many clinics throughout the world assuming that these figures apply to their population as well. However the predictive value of current Partin tables, which was updated in 2001, has not been validated in most of the countries as well as in Turkey. Therefore, we evaluated the validity of 2001 Partin tables, for the ability to predict the pathological stage in Turkish patients.

PATIENTS AND METHODS

The clinical and pathological findings of 1043 patients who have had radical prostatectomy were assessed. Serum PSA values, clinical stage, biopsy Gleason score and the pathological features of the radical prostatectomy specimens were collected from each clinic and evaluated. The predictive value of Partin nomogram and pathological findings of prostatectomy specimens were compared and analyzed according to Receiver Operating Characteristics (ROC) analysis.

RESULTS

Median age of the patients was 60 (45-74). In the presented study, percentage of patients with clinical stage T1c was 43%. Patients with Gleason score of 2-4 in biopsy constituted 23.4% of the study group. In the present study, the ratio of the patients with serum PSA higher than 10 ng/ml was 39.6%. Organ confined disease, seminal vesicle involvement, lymph node metastases ratios were 64.7%, 10.3%, 1.8% respectively. Area Under Curve (AUC) values for organ confined disease, seminal vesicle involvement and lymph node involvement were calculated as 0.665, 0.733 and 0.759 respectively.

CONCLUSION

It appears that Partin tables have a reasonable predictive value for the final pathological features like organ confined disease, seminal vesicle and lymph node involvement in Turkish patients. This multicenter study showed that current Partin tables could also be used in Turkish patients with comparable accuracy.

Transition zone cancers undermine the predictive accuracy of Partin table stage predictions

PURPOSE

The Partin tables represent the most widely used predictor of pathological stage in men with localized prostate cancer (PCa). The accuracy and performance of the tables have been tested across different populations. However, to our knowledge the potential limitations that may stem from differences between transition zone (TZ) and peripheral zone (PZ) prostate cancers has not been explored. We tested the predictive accuracy and performance of the Partin tables according to TZ vs PZ tumor predominance.

MATERIALS AND METHODS

Preoperative serum prostate specific antigen, clinical stage and biopsy Gleason sum data on 1,990 patients treated with radical retropubic prostatectomy were used to define the 2001 Partin probabilities of organ confinement and seminal vesicle invasion (SVI). Data on 1,320 patients who underwent staging pelvic lymphadenectomy and radical retropubic prostatectomy were used to define the probabilities of lymph node invasion (LNI) and organ confined disease (OC). ROC area under the curve was used to assess the predictive accuracy of the 2001 Partin tables relative to observed extracapsular extension (ECE), SVI, LNI and OC. Performance characteristics for each prediction were explored graphically with local regression, nonparametric smoothing plots. Results were compared between 222 TZ cancers and 1,768 PZ cancers.

RESULTS

The 1,990 radical retropubic prostatectomy specimens demonstrated ECE in 689 cases (34.6%) (TZ in 58 or 27.1% and PZ in 631 or 35.8%) and SVI in 224 (TZ in 13 or 6.1% and PZ in 211 or 11.9%). The 1,320 lymphadenectomy specimens demonstrated LNI in 56 cases (TZ in 2 or 0.9% and PZ in 54 or 4.6%). OC was found in 784 cases (59.4%) (TZ in 95 or 69.9% and PZ in 689 or 58.2%). Predictive accuracy was for ECE 76.4% (TZ 69.0% and PZ 77.2%), 78.0% for SVI (TZ 73.5% and PZ 78.3%), 78.6% for LNI (TZ 44.5% and PZ 79.9%) and 79.4% for OC (TZ 73.8% and PZ 80.0%).

CONCLUSIONS

The biological tumor characteristics of TZ PCa differ from those of PZ PCa. These differences appear to undermine the accuracy of pathological stage predictions.

Surgical margin and Gleason score as predictors of postoperative recurrence in prostate cancer with or without chromosome 8p allelic imbalance

BACKGROUND

Identification of prostate cancer patients at risk for postoperative disease recurrence is an important clinical issue. Existing pathological markers can predict disease recurrence only to a certain extent, and there is a need for more accurate predictors.

METHODS

Using "counting alleles," a novel experimental method, we determined allelic status of chromosome 8p in 107 prostatectomy specimens. Statistical analyses examined the association between pathologic predictors (Gleason score, stage, surgical margin, etc.) and cancer recurrence in patients with and without 8p allelic imbalance (8p AI).

RESULTS

8p AI cancers were more likely to recur in the presence of a positive surgical margin, whereas recurrence of 8p retaining tumors was associated with the Gleason score, but not with the surgical margin.

CONCLUSIONS

Our findings suggest that chromosome 8p allelic status affects the predictive value of "traditional" markers of prostate cancer recurrence. If confirmed by larger studies, these results may have important clinical implications.

Patterns of practice in the United States: insights from CaPSURE on prostate cancer management

The Cancer of the Prostate Strategic Urologic Research Endeavor (CaPSURE) is a national disease registry of more than 10,000 patients with prostate cancer treated at 31 primarily community-based sites across the country. The database tracks oncologic and health-related quality-of-life outcomes. Because the urologists participating in the project treat according to their usual practices, CaPSURE facilitates the study of trends in disease-management strategies, offering a reflection of "real world" practice patterns. This review highlights key studies during the past several years that document downward risk migration, validates widely used prognostic nomograms, establishes prostate-specific antigen doubling time as a surrogate endpoint for disease-specific mortality, assesses the impact of treatment on patient-reported quality of life, and presents national trends in imaging test use and primary treatment strategies for localized disease.

THE CONTEMPORARY MANAGEMENT OF PROSTATE CANCER IN THE UNITED STATES: LESSONS FROM THE CANCER OF THE PROSTATE STRATEGIC UROLOGIC RESEARCH ENDEAVOR (CAPSURE), A NATIONAL DISEASE REGISTRY

PURPOSE

The epidemiology and treatment of prostate cancer have changed dramatically in the prostate specific antigen era. A large disease registry facilitates the longitudinal observation of trends in disease presentation, management and outcomes.

MATERIALS AND METHODS

The Cancer of the Prostate Strategic Urologic Research Endeavor (CaPSURE) is a national disease registry of more than 10000 men with prostate cancer accrued at 31 primarily community based sites across the United States. Demographic, clinical, quality of life and resource use variables are collected on each patient. We reviewed key findings from the data base in the last 8 years in the areas of disease management trends, and oncological and quality of life outcomes.

RESULTS

Prostate cancer is increasingly diagnosed with low risk clinical characteristics. With time patients have become less likely to receive pretreatment imaging tests, less likely to pursue watchful waiting and more likely to receive brachytherapy or hormonal therapy. Relatively few patients treated with radical prostatectomy in the database are under graded or under staged before surgery, whereas the surgical margin rate is comparable to that in academic series. CaPSURE data confirm the usefulness of percent positive biopsies in risk assessment and they have further been used to validate multiple preoperative nomograms. CaPSURE results strongly affirm the necessity of patient reported quality of life assessment. Multiple studies have compared the quality of life impact of various treatment options, particularly in terms of urinary and sexual function, and bother.

CONCLUSIONS

The presentation and management of prostate cancer have changed substantially in the last decade. CaPSURE will continue to track these trends as well as oncological and quality of life outcomes, and will continue to be an invaluable resource for the study of prostate cancer at the national level.

Optimal combinations for detection of prostate cancer: systematic sextant and laterally directed biopsies versus systematic sextant and color doppler-targeted biopsies

OBJECTIVES

To determine the accuracy of different combinations of biopsies in detecting prostate cancer. The standard sextant protocol for obtaining prostate biopsy underestimates the presence of prostate cancer. Conversely, an increased cancer detection rate has been obtained with additional laterally directed biopsies. The results of the studies dedicated to transrectal color Doppler (CD) sonography have shown that it might detect neoplastic lesions with no corresponding gray-scale abnormality.

METHODS

A total of 120 consecutive patients underwent sextant biopsy with additional biopsy cores taken from the lateral peripheral zone (four to six cores, depending on the prostate volume) and CD-guided biopsy. The sensitivity of laterally directed, CD-guided, and different combinations of biopsies was compared. Various patient, clinical, and pathologic factors were compared, and multivariate analysis was performed to assess the strongest predictor of cancer detection.

RESULTS

Cancer was detected in 43 (35.8%) of 120 patients. The combination of sextant biopsy with laterally directed cores gained sensitivity to 56.6% compared with 67.4% obtained in the regimen that combined sextant and CD-guided biopsy. The CD regimen detected cancer in 11 additional patients. However, the differences in the detection rates of these combinations were not statistically significant (P = 0.797). The results of multivariate analysis showed that sextant biopsy and laterally directed cores were the strongest predictors of cancer detection (odds ratio 8.356 versus 49.282; 95% confidence interval 1.698 to 41.114 versus 10.508 to 231.130).

CONCLUSIONS

The regimen that included sextant and CD-guided biopsy was the most sensitive. However, only standard sextant and laterally directed biopsies were statistically significant predictors of cancer detection on biopsy.

Comparison of Accuracy Between the Partin Tables Of 1997 and 2001 to Predict Final Pathological Stage in Clinically Localized Prostate Cancer

PURPOSE

We validated externally the predictive accuracy of the 2001 Partin tables and compared the 1997 and 2001 versions.

MATERIALS AND METHODS

We used ROC derived AUC to test the predictive accuracy of organ confinement (OC), extraprostatic extension (ECE), seminal vesicle invasion (SVI) and lymph node involvement (LNI) of 1997 and 2001 Partin tables derived probabilities. These probabilities were defined by the pretreatment clinical stage, serum prostate specific antigen and biopsy Gleason grade of 2,139 patients treated with radical prostatectomy for clinically localized prostate cancer.

RESULTS

OC, ECE, SVI and LNI were noted in 63.5%, 23.1%, 10.5% and 2.9% of cases, respectively. AUC of the 2001 tables was 0.787, 0.766, 0.775 and 0.790, for OC, ECE, SVI and LNI, respectively. These values were virtually the same as the respective 1997 Partin table AUC values, namely 0.784, 0.728, 0.791 and 0.799.

CONCLUSIONS

This external validation of the 2001 Partin tables confirms good predictive accuracy of the updated tables. However, predictive accuracy in this external validation data set of 2,139 European men is virtually the same as that of the original 1997 tables. Therefore, a transition from the 1997 tables to the updated 2001 version does not appear warranted unless superior accuracy is demonstrated in other external cohorts.

Global registries for measuring pharmacoeconomic and quality-of-life outcomes: focus on design and data collection, analysis and interpretation

Disease registries have traditionally been vehicles for the collection of clinical data, in most instances following a large number of patients for a long time period in an observational manner, and enhancing our understanding of disease aetiology and epidemiology. However, over recent decades, the potential for additional data collection and analyses to be conducted within the framework of a registry has been recognised and utilised. This is evident by the sheer number of registries that are now referenced in the medical literature, covering a vast array of therapeutic areas and topics much more varied than incidence, prevalence and survival. The opportunity to collect QOL and pharmacoeconomic data has been utilised within the registry framework as more and more countries have increased their demands for such information for regulatory procedures, including pricing and reimbursement decisions. This increased need for information has led to a marked increase in the number of registries undertaken that are primarily sponsored by the pharmaceutical industry. Disease registries offer tremendous opportunities to realise improvements in care. The length of data collection and the large number of patients involved offer some unusual advantages for QOL and health economic analyses; however, these advantages are not yet fully exploited.

Introducing a prognostic score for pretherapeutic assessment of seminal vesicle invasion in patients with clinically localized prostate cancer

PURPOSE

To identify prostate cancer patients who will have the most likely benefit from sparing the seminal vesicles during 3D conformal radiation therapy.

METHODS AND MATERIALS

From 1988 to 2001, 532 patients underwent radical prostatectomy for clinically localized prostate cancer. Primary endpoint was the pathological evidence of seminal vesicle invasion. Variables for univariate and multivariate analyses were age, prostate weight, clinical stage, PSA level, Gleason score, number and site of positive prostate sextant biopsies. Multivariate logistic regression with backward stepwise variable selection was used to identify a set of independent predictors of seminal vesicle invasion, and the variable selection procedure was validated by non-parametric bootstrap.

RESULTS

Seminal vesicle invasion was reported in 14% of the cases. In univariate analysis, all variables except age and prostate weight were predictors of seminal vesicle invasion. In multivariate analysis, only the number of positive biopsies (P<0.0001), Gleason score (P<0.007) and PSA (P<0.0001) were predictors for seminal vesicles invasion. Based on the multivariate model, we were able to develop a prognostic score for seminal vesicle invasion, which allowed us to discriminate two patient groups: A group with low risk of seminal vesicles invasion (5.7%), and the second with a higher risk of seminal vesicles invasion (32.7%).

CONCLUSIONS

Using the number of positive biopsies, Gleason score and PSA, it is possible to identify patients with low risk of seminal vesicles invasion. In this population, seminal vesicles might be excluded as a target volume in radiation therapy of prostate cancer.