An analysis of risk factors for biochemical progression in patients with seminal vesicle invasion: validation of Kattan's nomogram in a pathological subgroup

Does perineural invasion in a radical prostatectomy specimen predict biochemical recurrence in men with prostate cancer?

INTRODUCTION

The ability of perineural invasion (PNI) in radical prostatectomy (RP) specimens to predict biochemical recurrence (BCR) is unclear. This study investigates this controversial question in a large cohort.

METHODS

A retrospective analysis was undertaken of prospectively collected data from 1497 men who underwent RP (no neoadjuvant therapy) for clinically localized prostate cancer. The association of PNI at RP with other clinicopathological parameters was evaluated. The correlation of clinicopathological factors and BCR (defined as prostate-specific antigen [PSA] >0.2 ng/mL) was investigated with univariable and multivariable Cox regression analysis in 1159 men.

RESULTS

PNI-positive patients were significantly more likely to have a higher RP Gleason score, pT3 disease, positive surgical margins, and greater cancer volume (p < 0.0005). The presence of PNI significantly correlated with BCR on univariable (hazard ratio 2.30, 95% confidence interval 1.50-3.55, p < 0.0005), but not multivariable analysis (p = 0.602). On multivariable Cox regression analysis the only independent prognostic factors were preoperative PSA, RP Gleason score, pT-stage, and positive surgical margin status. These findings are limited by a relatively short follow-up time and retrospective study design.

CONCLUSIONS

PNI at RP is not an independent predictor of BCR. Therefore, routine reporting of PNI is not indicated. Future research should be targeted at the biology of PNI to increase the understanding of its role in prostate cancer progression.

Multiparametric magnetic resonance imaging and image-guided biopsy to detect seminal vesicle invasion by prostate cancer

OBJECTIVES

To evaluate the correlation between multiparametric prostate MRI (MP-MRI) suspicion for seminal vesicle invasion (SVI) by prostate cancer (PCa) and pathology on MRI/ultrasound (US) fusion-guided biopsy.

PATIENTS AND METHODS

From March 2007 to June 2013, 822 patients underwent MP-MRI at 3 Tesla and MRI/US fusion-guided biopsy. Of these, 25 patients underwent targeted biopsy of the seminal vesicles (SVs). In six patients, bilateral SVI was suspected, resulting in 31 samples. MP-MRI findings that triggered these SV biopsies were scored as low, moderate, or high suspicion for SVI based on the degree of involvement on MRI. Correlative prostate biopsy and radical prostatectomy (RP) pathology were reviewed by a single genitourinary pathologist.

RESULTS

At the time of MP-MRI, the median age was 64 years with a median prostate-specific antigen of 10.74 ng/mL. Of the 31 SV lesions identified, MP-MRI suspicion scores of low, moderate, and high were assigned to 3, 19, and 9 lesions, respectively. MRI/US fusion-guided biopsy detected SVI in 20/31 (65%) of cases. For the four patients who underwent RP after a preoperative assessment of SVI, biopsy pathology and RP pathology were concordant in all cases.

CONCLUSIONS

As this technology becomes more available, MP-MRI and MRI/US fusion-guided biopsy may play a role in the preoperative staging for PCa. Future work will determine if improved preoperative staging leads to better surgical outcomes.

Seminal vesicle invasion in prostate cancer: evaluation by using multiparametric endorectal MR imaging

PURPOSE

To retrospectively evaluate the diagnostic performance of multiparametric endorectal magnetic resonance (MR) imaging, including T2-weighted, diffusion-weighted (DW), and dynamic contrast material-enhanced (DCE) MR techniques, for the diagnosis of seminal vesicle invasion (SVI) and to determine the incremental value of DW MR and DCE MR images.

MATERIALS AND METHODS

This retrospective HIPAA-compliant study was approved by the institutional review board, with a waiver of informed consent. The study included 131 patients (mean age, 68 years; range, 43-75 years) who underwent endorectal MR imaging before radical prostatectomy between January 2007 and April 2010. Two radiologists (A: experienced, B: less experienced) estimated the likelihood of SVI by using a five-point ordinal scale in three image-viewing settings: T2-weighted images alone; T2-weighted and DW MR images; and T2-weighted, DW MR, and DCE MR images. Sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC) were calculated. Confidence intervals estimated with bootstrapping and the McNemar test or Fisher exact test were used to compare sensitivity, specificity, positive predictive value, and negative predictive value.

RESULTS

Of the 131 patients, 23 (17.6%) had SVI identified after surgery. Review of T2-weighted MR images alone resulted in high specificity (93.1% and 93.6%, for radiologists A and B, respectively) and high negative predictive value (94.8% and 94.0%) but moderate sensitivity (59% and 52%) and positive predictive value (52% and 50%). Review of T2-weighted and DW MR images significantly improved specificity (96.6% [P = .02] and 98.3% [P = .003]) and positive predictive value (70% [P < .05] and 79% [P < .05]) without significantly improving AUC. Additional review of DCE MR images did not yield further incremental improvement.

CONCLUSION

Additional review of DW MR images improves specificity and positive predictive value in SVI detection compared with reviewing T2-weighted images alone. Addition of DCE MR images to this combination, however, does not provide incremental value for diagnosis of SVI.

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.

Incremental value of magnetic resonance imaging in the advanced management of prostate cancer

Prostate cancer is a major public health burden throughout the world. The high incidence of prostate cancer, combined with earlier detection and downstaging at the time of diagnosis, and the slow natural progression and biological heterogeneity of the disease, has made its management a complex and controversial issue. There is growing demand for patient-specific therapies that can minimize treatment morbidity while maximizing treatment benefits. There are a number of clinical parameters and clinical nomograms to help with the choice of treatment. Magnetic resonance imaging (MRI) is a technique which makes safer, more individualized therapies possible due to high spatial resolution, superior contrast resolution, multiplanar capability, and a large field of view. Other MRI techniques such as MR spectroscopic imaging, dynamic contrast-enhanced MRI or perfusion MRI, and diffusion-weighted imaging complement MRI by reflecting tissue biochemistry, Brownian motion of water molecules, and capillary wall permeability, respectively. This editorial review highlights the incremental value of MRI in the advanced management of prostate cancer to non-invasively improve cancer staging, biologic potential, treatment planning, therapy response, local recurrence, and to guide target biopsy for clinical suspected cancer with previous negative biopsy. Finally, some future prospects for MRI in prostate cancer management are given.

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.

Parameters of perineural invasion in radical prostatectomy specimens lack prognostic significance

The prognostic significance of perineural invasion by prostate cancer is debated. We have evaluated the association between biochemical failure and measurements of perineural invasion in radical prostatectomy specimens. Perineural invasion was identified in sections using S-100 protein immunostaining. For nerves showing invasion, the involved nerve closest to the edge of the prostate and to the surgical excision margin, as well as the diameter of these nerves, the largest nerve showing perineural invasion and its proximity to the excision margin, and the percentage of nerves showing perineural invasion up to 1.75 mm from the excision margin was determined and tested against time to prostate-specific antigen failure, along with preoperative prostate-specific antigen levels, highest Gleason primary grade, Gleason score and TNM T category. Perineural invasion was present in 90% of cases, with extraprostatic perineural invasion in 25% of tumors. Diameter of nerves showing perineural invasion ranged from 11 to 680 microm and the shortest distance to the surgical excision margin ranged from 33 to 2.57 mm. Perineural invasion density ranged from 6 to 96%. Gleason scores were six in 58 cases, seven in 43 cases, eight in three cases and nine in one case. Clinical T categories were T1c in 75 cases, T2a in 22 cases, T2b in five cases, T2c in two cases, T3 in one case. During a follow-up period of 11 to 55 months (median 26 months), 27 patients showed prostate-specific antigen failure. On univariate analysis only presence of extraprostatic perineural invasion, among parameters of perineural invasion, showed a weak correlation with outcome, while on multivariate analysis this lost significance and preoperative prostate-specific antigen levels, Gleason score and excision margin status were independently associated with biochemical failure. We conclude that the investigated parameters of perineural invasion do not predict prostate-specific antigen recurrence in radical prostatectomy specimens.

The role of endorectal coil MRI in preoperative staging and decision-making for the treatment of clinically localized prostate cancer

INTRODUCTION

The optimal management of newly diagnosed prostate cancer requires individualization of the treatment plan based upon the most accurate clinical characterization of tumor location and extent of disease. The role of imaging in prostate cancer staging continues to evolve. In this review, we address the utility of endorectal coil magnetic resonance imaging (eMRI) in both local staging and its ability to facilitate the decision in choosing one treatment strategy over another after the initial diagnosis of localized prostate cancer.

MATERIALS AND METHODS

Using the PubMed database and reference lists of key articles, we identified studies addressing the use of eMRI in tumor characterization and risk stratification in patients undergoing treatment for clinically localized prostate cancer.

RESULTS

The findings identified within 54 selected studies were incorporated into a summary discussing the current limitations in cancer staging and the role eMRI plays in both the preoperative assessment and clinical decision-making in an attempt to improve our ability to individualize management approaches and tailor treatment.

CONCLUSION

eMRI allows for more accurate local staging by complementing the existing clinical variables through improvements in spatial characterization of the prostatic zonal anatomy and molecular changes. These improvements in tumor staging enhance our ability to individualize treatment selection and tailor the approach to maximize cancer control while minimizing treatment related morbidity.

Prognostic factors in prostate cancer

In the nineteenth century the main goal of medicine was predictive: diagnose the disease and achieve a satisfying prognosis of the patient's chances. Today the effort has shifted to cure the disease. Since the twentieth century, the word prognosis has also been used in nonmedical contexts, for example in corporate finance or elections. The most accurate form of prognosis is achieved statistically. Based on different prognostic factors it should be possible to tell patients how they are expected to do after prostate cancer has been diagnosed and how different treatments may change this outcome. A prognosis is a prediction. The word prognosis comes from the Greek word (see text) and means foreknowing. In the nineteenth century this was the main goal of medicine: diagnose the disease and achieve a satisfying prognosis of the patient's chances. Today the effort has shifted towards seeking a cure. Prognostic factors in (prostate) cancer are defined as "variables that can account for some of the heterogeneity associated with the expected course and outcome of a disease". Bailey defined prognosis as "a reasoned forecast concerning the course, pattern, progression, duration, and end of the disease. Prognostic factors are not only essential to understand the natural history and the course of the disease, but also to predict possible different outcomes of different treatments or perhaps no treatment at all. This is extremely important in a disease like prostate cancer where there is clear evidence that a substantial number of cases discovered by prostate-specific antigen (PSA) testing are unlikely ever to become clinically significant, not to mention mortal. Furthermore, prognostic factors are of paramount importance for correct interpretation of clinical trials and for the construction of future trials. Finally, according to WHO national screening committee criteria for implementing a national screening programme, widely accepted prognostic factors must be defined before assessing screening.

Prediction of Seminal Vesicle Invasion in Prostate Cancer: Incremental Value of Adding Endorectal MR Imaging to the Kattan Nomogram

PURPOSE

To retrospectively determine whether endorectal magnetic resonance (MR) imaging findings contribute incremental value to the Kattan nomogram for predicting seminal vesicle invasion (SVI) in patients with prostate cancer.

MATERIALS AND METHODS

The institutional review board issued a waiver of authorization, which included a waiver of informed consent, for this HIPAA-compliant study. From October 2000 through January 2005, 573 patients (mean age, 58.3 years; age range, 36-86 years) underwent endorectal MR imaging before prostate cancer surgery. The endorectal MR imaging results had been prospectively interpreted by seven radiologists, and the likelihood of SVI was retrospectively scored on the basis of radiologists' written reports. MR imaging findings, individual clinical variables (serum prostate-specific antigen [PSA] level, Gleason grade, clinical stage, greatest percentage of cancer in all biopsy cores, percentage of positive cores in all biopsy cores, and perineural invasion), and the Kattan nomogram were evaluated with respect to SVI prediction; surgical pathologic analysis was used as the reference standard. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed.

RESULTS

At pathologic analysis, 28 (4.9%) of 573 patients had SVI. At univariate analysis, endorectal MR imaging results and all clinical variables except the percentage of positive biopsy cores were significantly associated with SVI (P<.02); endorectal MR imaging (0.76) had a larger area under the ROC curve (AUC) than any clinical variable (0.62-0.73). At multivariate analysis, endorectal MR imaging results, Gleason grade, PSA level, and the percentage of cancer in all biopsy cores were significantly associated with SVI (P<or=.02). The Kattan nomogram plus endorectal MR imaging (0.87) had a significantly larger (P<.05) AUC than either endorectal MR imaging alone (0.76) or the Kattan nomogram alone (0.80).

CONCLUSION

The addition of endorectal MR imaging contributes significant incremental value to the Kattan nomogram for predicting SVI.

Endorectal MR Imaging in the Evaluation of Seminal Vesicle Invasion: Diagnostic Accuracy and Multivariate Feature Analysis

PURPOSE

To retrospectively determine the accuracy of endorectal magnetic resonance (MR) imaging in demonstrating seminal vesicle invasion (SVI) and to investigate the MR imaging features that can predict SVI.

MATERIALS AND METHODS

The Institutional Review Board granted exempt status for this retrospective study, with waiver of informed consent; patient data were collected and handled in accordance with HIPAA regulations. Fifty-one men (age range, 44-73 years) with SVI and 303 men (age range, 40-76 years) without SVI who underwent endorectal MR imaging before radical prostatectomy between January 2000 and October 2004 were included in the study. Endorectal MR images were retrospectively and independently analyzed by two radiologists for SVI, tumor at prostate base, extracapsular extension, and other features considered indicative of SVI. Areas under the receiver operating characteristic curves (AUCs) were used to assess the accuracy of detecting SVI at endorectal MR imaging. A multiple logistic regression was used to explore the combinations of MR imaging features that might facilitate the detection of SVI.

RESULTS

Readers 1 and 2 had an AUC of 0.93 and 0.81, respectively, for the detection of SVI. For both readers, the features that had the highest sensitivity and specificity were low signal intensity within the seminal vesicle and lack of preservation of seminal vesicle architecture. At multiple regression analysis, tumor at the prostate base that extended beyond the capsule and low signal intensity within a seminal vesicle that has lost its normal architecture were highly predictive of SVI.

CONCLUSION

Endorectal MR imaging is accurate in demonstrating SVI prior to radical prostatectomy, and recognition of the most predictive features may facilitate the use of this modality.

p300 Modulates Nuclear Morphology in Prostate Cancer

Alterations in nuclear structure distinguish cancer cells from noncancer cells. These nuclear alterations can be translated into quantifiable features by digital image analysis in a process known as quantitative nuclear morphometry. Recently, quantitative nuclear morphometry has been shown to predict metastasis and biochemical recurrence of prostate cancer. However, little is known about the cellular mechanisms underlying these nuclear morphometric changes. Alterations of nuclear matrix proteins are frequently involved in changes of nuclear structure. A number of co-activators interact with these nuclear structure–related proteins, suggesting that they might be involved in quantitative nuclear morphometry changes. We have shown previously that the transcriptional co-activator p300 is involved in prostate cancer progression. However, the ability of a transcriptional regulator like p300 to modulate nuclear morphology has not been described previously. In the present study, we show that p300 expression in prostate cancer biopsy tissue from 95 patients correlates with quantifiable nuclear alterations. Moreover, we show that transfection of p300 into prostate cancer cells in culture induces quantifiable nuclear alterations, such as diameter, perimeter, and absorbance among others, as assessed by digital image analysis. These alterations correlate individually with aggressive features in prostate cancer, such as expression of the proliferation marker Ki-67 and extraprostatic extension of the tumor. Finally, we found that transfection of p300 into prostate cancer cells specifically increases mRNA and protein levels of nuclear matrix peptides lamins A and C, suggesting that these proteins mediate the p300-induced effects. These findings reveal a new insight into the transcriptional and structural regulation of prostate cancer.