SITE SPECIFIC PREDICTORS OF POSITIVE MARGINS AT RADICAL PROSTATECTOMY: AN ARGUMENT FOR RISK BASED MODIFICATION OF TECHNIQUE

Clinicopathological Significances of Positive Surgical Resection Margin after Radical Prostatectomy for Prostatic Cancers: A Meta-Analysis

Background and Objectives: This study aims to elucidate the positive rate and the clinicopathological significance of surgical margin after radical prostatectomy (RP) through a meta-analysis. Materials and Methods: This meta-analysis finally used 59 studies, including the information about the positive surgical margin (PSM) and those clinicopathological significances after RP. The subgroup analysis for the estimated rates of PSM was evaluated based on types of surgery, grade groups, and pathological tumor (pT) stages. We compared the clinicopathological correlations between positive and negative surgical margins (NSM). Results: The estimated PSM rate was 25.3% after RP (95% confidence interval [CI] 21.9-29.0%). The PSM rates were 26.0% (95% CI 21.5-31.1%) 28.0% (95% CI 20.2-37.5%) in robot-assisted RP and nerve-sparing RP, respectively. The PSM rate was significantly higher in high-grade groups than in low-grade groups. In addition, the higher pT stage subgroup had a high PSM rate compared to the lower pT stage subgroups. Patients with PSM showed significantly high PSA levels, frequent lymphovascular invasion, lymph node metastasis, and extraprostatic extension. Biochemical recurrences (BCRs) were 28.5% (95% CI 21.4-36.9%) and 11.8% (95% CI 8.1-16.9%) in PSM and NSM subgroups, respectively. Patients with PSM showed worse BCR-free survival than those with NSM (hazard ratio 2.368, 95% CI 2.043-2.744%). Conclusions: Our results showed that PSM was significantly correlated with worse clinicopathological characteristics and biochemical recurrence-free survival. Among the results in preoperative evaluations, grade group and tumor stage are useful for the prediction of PSM.

[Treatment of locally advanced prostatic cancer]

INTRODUCTION

A locally advanced prostate cancer is defined as a malignant process spreading beyond the prostate capsule or in seminal vesicles but without distant metastasis or regional lymph nodes invasion.

CLINICAL CLASSIFICATION, PREDICTION AND TREATMENT OF PROSTATE CANCER

An exact staging of clinical T3 stadium is usually difficult because of the frequent over and under staging. The risk prognostic stratification is performed through nomograms and ANN (artificial neural networks). The options for treatment are: radical prostatectomy, external radiotherapy and interstitial implantation of radioisotopes, hormonal therapy by androgen blockade. Radical prostatectomy is considered in patients with T3 stage but extensive dissection of lymph nodes, dissection of neurovascular bundle (on tumor side), total removal of seminal vesicle and sometimes resection of bladder neck are obligatory. Postoperative radiotherapy is performed in patients with invasion of seminal vesicles and capsular penetration or with prostate specific antigen value over 0.1 ng/ml, one month after the surgical treatment. Definitive radiotherapy could be used as the best treatment option considering clinical stage, Gleason score, age, starting prostate specific antigen (PSA) value, concomitant diseases, life expectancy, quality of life, through multidisciplinary approach (combined with androgen deprivation). Hormonal therapy in intended for patients who are not eligible for surgical treatment or radiotherapy. Conclusion Management of locally advanced prostate cancer is still controversial and studies fbr better diagnosis and new treatment modalities are ongoing.

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.

Inventory of prostate cancer predictive tools

PURPOSE OF REVIEW

We created an inventory of current predictive tools available for prostate cancer. This review may serve as an initial step toward a comprehensive reference guide for physicians to locate published nomograms that apply to the clinical decision in question. Using MEDLINE a literature search was performed on prostate cancer predictive tools from January 1966 to November 2007. We describe the patient populations to which they apply and the outcomes predicted, and record their individual characteristics.

RECENT FINDINGS

The literature search generated 111 published prediction tools that may be applied to patients in various clinical stages of disease. Of the 111 prediction tools, only 69 had undergone validation. We present an inventory of models with input variables, prediction form, number of patients used to develop the prediction tools, the outcome being predicted, prediction tool-specific features, predictive accuracy, and whether validation was performed.

SUMMARY

Decision rules, such as nomograms, provide evidence-based and at the same time individualized predictions of the outcome of interest. Such predictions have been repeatedly shown to be more accurate than those of clinicians, regardless of their level of expertise. Accurate risk estimates are also required for clinical trial design, to ensure homogeneous high-risk patient groups for whom new cancer therapeutics will be investigated.

A comparison of the incidence and location of positive surgical margins in robotic assisted laparoscopic radical prostatectomy and open retropubic radical prostatectomy

PURPOSE

Surgical technique, patient characteristics and method of pathological review may influence surgical margin status. We evaluated the incidence and location of positive surgical margins in 200 sequential robotic assisted laparoscopic radical prostatectomy and 200 sequential open radical retropubic prostatectomy cases.

MATERIALS AND METHODS

From July 2002 until December 2006 a total of 1,747 patients underwent radical prostatectomy at our institution (robotic assisted laparoscopic radical prostatectomy in 1,238, radical retropubic prostatectomy in 509). From these we selected the last 200 consecutive radical retropubic prostatectomies and 200 robotic assisted laparoscopic radical prostatectomies performed before August 2006. Preoperative clinical characteristics including age, clinical stage, prostate specific antigen and Gleason score were evaluated. Postoperatively pathological specimens were assessed for specimen weight, Gleason score, tumor volume, pathological stage and margin status. The incidence and location of positive surgical margins were compared between robotic assisted laparoscopic radical prostatectomy and radical retropubic prostatectomy.

RESULTS

Patients undergoing robotic assisted laparoscopic radical prostatectomy compared to radical retropubic prostatectomy had more favorable tumor characteristics including lower prostate specific antigen, clinical stage and Gleason score. No statistically significant differences were found between groups for prostate volume or tumor volume. However, tumor volume as a percentage of prostate volume was higher among radical retropubic prostatectomy compared to robotic assisted laparoscopic radical prostatectomy cases (17.7% vs 13%, p = 0.001). The overall incidence of positive surgical margins was significantly lower among the robotic assisted laparoscopic radical prostatectomy compared to radical retropubic prostatectomy cases (15% vs 35%, p <0.001). The incidence of positive surgical margins according to pathological stage for robotic assisted laparoscopic radical prostatectomy vs radical retropubic prostatectomy cases was 16 of 171 (9.4%) vs 33 of 137 (24.1%) for pT2 (p <0.001) and 14 of 28 (50%) vs 36 of 60 (60%) for pT3. In both groups the apex was the most common site of positive surgical margins with 52% in the robotic assisted laparoscopic radical prostatectomy group vs 37% in the radical retropubic prostatectomy group (p >0.05).

CONCLUSIONS

In the hands of surgeons experienced in robotic assisted laparoscopic radical prostatectomy and radical retropubic prostatectomy, there was a statistically significant lower positive margin rate for patients undergoing robotic assisted laparoscopic radical prostatectomy. The most common location of a positive surgical margin in robotic assisted laparoscopic radical prostatectomy and radical retropubic prostatectomy cases was at the apex. Patients treated with radical retropubic prostatectomy had higher risk features which may have independently influenced these results. The method of pathological specimen analysis and reporting may account for the higher positive margin rates in both groups compared to some reports.

Apical soft tissue biopsies predict biochemical failure in radical perineal prostatectomy patients with apical cancer involvement

The aim of the study was to prospectively assess the role of apical soft tissue biopsies in radical perineal prostatectomy (RPP) patients with documented apical prostate cancer (PCA) involvement. Between June 1998 and May 1999, 77 consecutive men with localized PCA and documented invasion of the prostatic apex underwent RPP by a single surgeon. Soft tissue biopsies were systematically obtained from the prostatic fossa overlying the apex at the time of surgery. Time to biochemical failure was calculated using the Kaplan-Meier method. The rates of positive apical margins and positive apical soft tissue biopsies were 23.4% (18/77) and 15.6% (12/77). The sensitivity, specificity and positive predictive value of positive apical margins for residual apical disease as determined by apical soft tissue biopsy were 41.7, 80, and 28%, respectively. The overall biochemical failure rate was 28.6% (22/77) with a median follow-up of 51 months (range 3-73 months). The 36-month biochemical recurrence-free survival rate was 55.9+/-14.9% for patients with positive apical biopsies and 78.7+/-5.3% for those with negative biopsies (P=0.023). In conclusion, positive apical soft tissue biopsy is an independent predictor of biochemical failure in patients with apical PCA who undergo RPP. Positive apical surgical margins poorly predict residual apical disease that is frequently identifiable by apical soft tissue biopsy. Apical soft tissue biopsies should therefore be obtained in patients with known extensive apical cancer involvement at the time of RPP.

Conventional assessment of needle biopsy specimens is more useful than digital image analysis of proliferation and DNA ploidy in prediction of positive surgical margins at radical prostatectomy

OBJECTIVES

The preoperative prediction of the likelihood of positive surgical margins (+SMs) at radical retropubic prostatectomy (RRP) may be useful for counseling and determining the surgical approach. The aim of this study was to assess the additional value of digital image analysis (DIA) of ploidy and proliferation on needle biopsies, in addition to the known preoperative predictors of +SMs at RRP.

METHODS

We identified 454 patients treated by RRP at our institution from 1995 to 1998 for prostate cancer verified by transrectal ultrasound-guided biopsy, with a specimen adequate for DIA. Patients receiving preoperative hormonal therapy were excluded. The clinical features, transrectal ultrasound-guided biopsy findings, and DIA evaluation of MIB-I immunostaining and DNA ploidy were assessed in a multivariate logistic regression model to predict for +SMs at RRP.

RESULTS

The mean +/- SD age at treatment was 64.5 +/- 6.5 years, the percentage of positive cores was 40.4% +/- 24.3%, the median prostate-specific antigen level was 6.3 ng/mL (range 0.6 to 112.0), median biopsy Gleason score was 6 (range 4 to 9), and median percentage of diploid nuclei was 67% (range 0% to 100%). Of the 454 patients, 185 (40.7%) had +SMs; this finding was time dependent (1995 to 1996, 45% and 1997 to 1998, 31%; P = 0.004). Univariately, preoperative prostate-specific antigen, biopsy Gleason score, extent of cancer on biopsy, MIB-1 expression, percentage of diploid or nondiploid nuclei, and year of surgery were predictive for +SMs. On multivariate analysis, the preoperative prostate-specific antigen level, biopsy Gleason score, percentage of positive cores, and year of surgery remained significant.

CONCLUSIONS

The results of our study have shown that the likelihood of +SMs at RRP is best predicted on the basis of conventional prognostic factors. The DIA features of needle biopsies did not provide additional predictive power.

Prostate cancer diagnosed after repeat biopsies have a favorable pathological outcome but similar recurrence rate

PURPOSE

We investigated whether repeat prostate biopsies are associated with more favorable prognoses, less extensive disease or higher rates of IC in patients who are ultimately diagnosed with prostate cancer and treated with RRP.

MATERIALS AND METHODS

We examined standard clinical and pathological data on 1,357 patients treated with RRP from 1983 to 2001. In addition, we noted the rate of IC in a subgroup of 847 patients in whom tumor volume was measured.

RESULTS

Cancer was found in 1,042 patients (77%) at the first biopsy, in 227 (17%) at the second biopsy, in 59 (4%) at the third biopsy and in 29 (2%) at the fourth or later biopsy. Patients with 2 or greater biopsies had a higher rate of clinical T1c stage cancer and larger prostates than patients with only 1 biopsy (each p < 0.0001). After RRP patients with 1 biopsy had a lower rate of organ confined tumors (61% vs 75%, p < 0.0001), and a higher rate of extracapsular extension, seminal vesicle invasion, lymph node metastases and Gleason sum 7 or greater than other patients. IC was found in 10% of patients with 1 biopsy and 18% of those with 2 or greater biopsies (p = 0.018). Despite these more favorable pathological outcomes there was no difference in biochemical recurrence rate.

CONCLUSIONS

Although we found that a greater number of biopsies was related to a better pathological outcome after RRP, the number of biopsies did not predict disease recurrence. The increasing number of biopsies currently being performed, especially in patients with larger prostates, likely results in higher rates of IC.

Is intraoperative frozen section analysis an efficient way to reduce positive surgical margins?

OBJECTIVES

To assess the accuracy and efficiency of frozen section analysis to detect positive surgical margins (+SMs) during radical prostatectomy.

METHODS

In a consecutive series of 760 patients treated with radical prostatectomy from 1998 to 2002, areas suspicious for +SMs on the surface of the removed prostate were examined by frozen section analysis. In a subset of 520 patients, the surgeon's level of suspicion for +SMs was scored and recorded during radical prostatectomy.

RESULTS

Overall, 259 patients underwent frozen section examination. Of these, 55 patients (21%) had +SMs on permanent section examination compared with 50 (10%) of 501 patients with no frozen section analysis (P <0.005). Cancer was present in 23 (8.9%) frozen section specimens, all of which were confirmed on permanent section analysis. Frozen section examination missed 32 +SMs in 236 patients with negative frozen section results. The sensitivity, specificity, and positive and negative predictive value of frozen section analysis to identify +SMs was 42%, 100%, 100%, and 86%, respectively. However, the sensitivity of frozen section analysis was much lower (23 of 105, 22%) when analyzed for the entire population, including those who did not have frozen section analysis. Among the subset of 520 patients with the level of suspicion recorded, 79 had a +SM on permanent section examination. However, 51 (64%) of these were in patients with no suspicious area in the prostatectomy specimen.

CONCLUSIONS

Although the positive predictive value of frozen section analysis for +SMs is high, the sensitivity is too low to expect that a policy of routine frozen section analysis of suspicious areas will reduce the rate of +SMs substantially.

Prognostic factors in prostate cancer. College of American Pathologists Consensus Statement 1999

BACKGROUND

Under the auspices of the College of American Pathologists, a multidisciplinary group of clinicians, pathologists, and statisticians considered prognostic and predictive factors in prostate cancer and stratified them into categories reflecting the strength of published evidence and taking into account the expert opinions of the Prostate Working Group members.

MATERIALS AND METHODS

Factors were ranked according to the previous College of American Pathologists categorical rankings: category I, factors proven to be of prognostic importance and useful in clinical patient management; category II, factors that have been extensively studied biologically and clinically but whose importance remains to be validated in statistically robust studies; and category III, all other factors not sufficiently studied to demonstrate their prognostic value. Factors in categories I and II were considered with respect to variations in methods of analysis, interpretation of findings, reporting of data, and statistical evaluation. For each factor, detailed recommendations for improvement were made. Recommendations were based on the following aims: (1) increasing uniformity and completeness of pathologic evaluation of tumor specimens, (2) enhancing the quality of data collected pertaining to existing prognostic factors, and (3) improving patient care.

RESULTS AND CONCLUSIONS

Factors ranked in category I included preoperative serum prostate-specific antigen level, TNM stage grouping, histologic grade as Gleason score, and surgical margin status. Category II factors included tumor volume, histologic type, and DNA ploidy. Factors in category III included perineural invasion, neuroendocrine differentiation, microvessel density, nuclear roundness, chromatin texture, other karyometric factors, proliferation markers, prostate-specific antigen derivatives, and other factors (oncogenes, tumor suppressor genes, apoptosis genes, etc).