Percentage of high-grade tumour volume does not meaningfully improve prediction of early biochemical recurrence after radical prostatectomy compared with Gleason score

Development of risk-score model in patients with negative surgical margin after robot-assisted radical prostatectomy

A total of 739 patients underwent RARP as initial treatment for PCa from November 2011 to October 2018. Data on BCR status, clinical and pathological parameters were collected from the clinical records. After excluding cases with neoadjuvant and/or adjuvant therapies, presence of lymph node or distant metastasis, and positive SM, a total of 537 cases were eligible for the final analysis. The median follow-up of experimental cohort was 28.0 (interquartile: 18.0-43.0) months. We identified the presence of International Society of Urological Pathology grade group (ISUP-GG) ≥ 4 (Hazard ratio (HR) 3.20, 95% Confidence Interval (95% CI) 1.70-6.03, P < 0.001), lymphovascular invasion (HR 2.03, 95% CI 1.00-4.12, P = 0.049), perineural invasion (HR 10.7, 95% CI 1.45-79.9, P = 0.020), and maximum tumor diameter (MTD) > 20 mm (HR 1.9, 95% CI 1.01-3.70, P = 0.047) as significant factors of BCR in the multivariate analysis. We further developed a risk model according to these factors. Based on this model, 1-year, 3-year, and 5-year BCR-free survival were 100%, 98.9%, 98.9% in the low-risk group; 99.1%, 94.1%, 86.5% in the intermediate-risk group; 93.9%, 84.6%, 58.1% in the high-risk group. Internal validation using the bootstrap method showed a c-index of 0.742 and an optimism-corrected c-index level of 0.731. External validation was also carried out using an integrated database derived from 3 other independent institutions including a total of 387 patients for the final analysis. External validation showed a c-index of 0.655. In conclusion, we identified risk factors of biochemical failure in patients showing negative surgical margin after RARP and further developed a risk model using these risk factors.

A Novel Angiogenesis-Related Gene Signature to Predict Biochemical Recurrence of Patients with Prostate Cancer following Radical Therapy

Background

Prostate cancer (PCa) is one of the most common malignancies in males; we aim to establish a novel angiogenesis-related gene signature for biochemical recurrence (BCR) prediction in PCa patients following radical therapy.

Methods

Gene expression profiles and corresponding clinicopathological data were acquired from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We quantified the levels of various cancer hallmarks and identified angiogenesis as the primary risk factor for BCR. Then machine learning methods combined with Cox regression analysis were used to screen prognostic genes and construct an angiogenesis-related gene signature, which was further verified in external cohorts. Furthermore, estimation of immune cell abundance and prediction of drug responses were also conducted to detect potential mechanisms.

Results

Angiogenesis was regarded as the leading risk factor for BCR in PCa patients (HR = 1.58, 95% CI: 1.38–1.81), and a novel prognostic signature based on three genes (NRP1, JAG2, and VCAN) was developed in the training cohort and successfully validated in another three independent cohorts. In all datasets, this signature was identified as a prognostic factor with promising and robust predictive values. Moreover, it also predicted higher infiltration of regulatory T cells and M2-polarized macrophages and increased drug sensitivity of angiogenesis inhibitors in high-risk patients.

Conclusions

The angiogenesis-related three-gene signature may serve as an independent prognostic factor for BCR, which would contribute to risk stratification and personalized management of PCa patients after radical therapy in clinical practice.

Predicting biochemical-recurrence-free survival using a three-metabolic-gene risk score model in prostate cancer patients

BACKGROUND

Biochemical recurrence (BCR) after initial treatment, such as radical prostatectomy, is the most frequently adopted prognostic factor for patients who suffer from prostate cancer (PCa). In this study, we aimed to construct a prognostic model consisting of gene expression profiles to predict BCR-free survival.

METHODS

We analyzed 70 metabolic pathways in 152 normal prostate samples and 494 PCa samples from the UCSC Xena dataset (training set) via gene set enrichment analysis (GSEA) to select BCR-related genes and constructed a BCR-related gene risk score (RS) model. We tested the power of our model using Kaplan-Meier (K-M) plots and receiver operator characteristic (ROC) curves. We performed univariate and multivariate analyses of RS using other clinicopathological features and established a nomogram model, which has stronger prediction ability. We used GSE70770 and DFKZ 2018 datasets to validate the results. Finally, we performed differential expression and quantitative real-time polymerase chain reaction analyses of the UCSC data for further verification of the findings.

RESULTS

A total of 194 core enriched genes were obtained through GSEA, among which 16 BCR-related genes were selected and a three-gene RS model based on the expression levels of CA14, LRAT, and MGAT5B was constructed. The outcomes of the K-M plots and ROC curves verified the accuracy of the RS model. We identified the Gleason score, pathologic T stage, and RS model as independent predictors through univariate and multivariate Cox analyses and constructed a nomogram model that presented better predictability than the RS model. The outcomes of the validation set were consistent with those of the training set. Finally, the results of differential expression analyses support the effectiveness of our model.

CONCLUSION

We constructed an RS model based on metabolic genes that could predict the prognosis of PCa patients. The model can be easily used in clinical applications and provide important insights into future research on the underlying mechanism of PCa.

Screening to Identify an Immune Landscape-Based Prognostic Predictor and Therapeutic Target for Prostate Cancer

Objectives

Existing prognostic risk assessment strategies for prostate cancer (PCa) remain unsatisfactory. Similar treatments for patients at the same disease stage can lead to different survival outcomes. Thus, we aimed to explore a novel immune landscape-based prognostic predictor and therapeutic target for PCa patients.

Methods

A total of 490 PCa patients from The Cancer Genome Atlas Project (TCGA) cohort were analyzed to obtain immune landscape-based prognostic features. Then, analyses at different levels were performed to explore the relevant survival mechanisms, prognostic predictors, and therapeutic targets. Finally, experimental verification was performed using a tissue microarray (TMA) from 310 PCa patients. Furthermore, a nomogram was constructed to provide a quantitative approach for predicting the prognosis of patients with PCa.

Results

The immune landscape-based risk score (ILBRS) was obtained. Then, VAV1, which presented a significant positive correlation with Treg infiltration and ILBRS, was screened and identified to be significantly related to the prognosis of PCa. Finally, experimental verification confirmed the prognostic value of VAV1 for PCa prognosis at the protein level.

Conclusions

VAV1 has the potential to be developed as an immune landscape-based PCa prognostic predictor and therapeutic target and will help improve prognosis by enabling the selection of individualized, targeted therapy.

The 2019 Genitourinary Pathology Society (GUPS) White Paper on Contemporary Grading of Prostate Cancer

CONTEXT.—

Controversies and uncertainty persist in prostate cancer grading.

OBJECTIVE.—

To update grading recommendations.

DATA SOURCES.—

Critical review of the literature along with pathology and clinician surveys.

CONCLUSIONS.—

Percent Gleason pattern 4 (%GP4) is as follows: (1) report %GP4 in needle biopsy with Grade Groups (GrGp) 2 and 3, and in needle biopsy on other parts (jars) of lower grade in cases with at least 1 part showing Gleason score (GS) 4 + 4 = 8; and (2) report %GP4: less than 5% or less than 10% and 10% increments thereafter. Tertiary grade patterns are as follows: (1) replace "tertiary grade pattern" in radical prostatectomy (RP) with "minor tertiary pattern 5 (TP5)," and only use in RP with GrGp 2 or 3 with less than 5% Gleason pattern 5; and (2) minor TP5 is noted along with the GS, with the GrGp based on the GS. Global score and magnetic resonance imaging (MRI)-targeted biopsies are as follows: (1) when multiple undesignated cores are taken from a single MRI-targeted lesion, an overall grade for that lesion is given as if all the involved cores were one long core; and (2) if providing a global score, when different scores are found in the standard and the MRI-targeted biopsy, give a single global score (factoring both the systematic standard and the MRI-targeted positive cores). Grade Groups are as follows: (1) Grade Groups (GrGp) is the terminology adopted by major world organizations; and (2) retain GS 3 + 5 = 8 in GrGp 4. Cribriform carcinoma is as follows: (1) report the presence or absence of cribriform glands in biopsy and RP with Gleason pattern 4 carcinoma. Intraductal carcinoma (IDC-P) is as follows: (1) report IDC-P in biopsy and RP; (2) use criteria based on dense cribriform glands (>50% of the gland is composed of epithelium relative to luminal spaces) and/or solid nests and/or marked pleomorphism/necrosis; (3) it is not necessary to perform basal cell immunostains on biopsy and RP to identify IDC-P if the results would not change the overall (highest) GS/GrGp part per case; (4) do not include IDC-P in determining the final GS/GrGp on biopsy and/or RP; and (5) "atypical intraductal proliferation (AIP)" is preferred for an intraductal proliferation of prostatic secretory cells which shows a greater degree of architectural complexity and/or cytological atypia than typical high-grade prostatic intraepithelial neoplasia, yet falling short of the strict diagnostic threshold for IDC-P. Molecular testing is as follows: (1) Ki67 is not ready for routine clinical use; (2) additional studies of active surveillance cohorts are needed to establish the utility of PTEN in this setting; and (3) dedicated studies of RNA-based assays in active surveillance populations are needed to substantiate the utility of these expensive tests in this setting. Artificial intelligence and novel grading schema are as follows: (1) incorporating reactive stromal grade, percent GP4, minor tertiary GP5, and cribriform/intraductal carcinoma are not ready for adoption in current practice.

Identification of seven long noncoding RNAs signature for prediction of biochemical recurrence in prostate cancer

Accumulating evidence suggested that long noncoding RNAs (lncRNAs) possess a potential role in prostate cancer (PCa) diagnosis and prognosis. Rapid biochemical recurrence (BCR) is considered as a sign for clinical recurrence metastasis and PCa-specific mortality. Hence, the aim of the present study was to identify a lncRNA signature that can predict BCR of PCa accurately. Bioinformatics analysis, Kaplan–Meier analyses, Cox regression analyses, and Gene Set Enrichment Analysis (GSEA) were performed in a publicly available database with 499 PCa tissues and 52 matched normal tissues. A signature was identified. All these lncRNAs were differentially expressed between tumor and normal tissues and differentially expressed between high Gleason score and low Gleason score tissues. Furthermore, we developed a seven lncRNAs signature that can predict PCa BCR. Patients classified into low-risk group showed better BCR survival significantly than the patients in the high-risk group (hazard ratio = 0.32, 95% CI: 0.20–0.52, concordance index = 0.63). The area under the curve was 0.68 for BCR. The signature also had good discrimination for BCR in men with Gleason 7 PCa. In conclusion, our results suggest that the seven lncRNAs signature is a new biomarker of BCR and high risk in PCa. In addition, the individual lncRNA warrants further study to uncover the associated mechanisms of PCa progression and the signature could be used to design direct clinical trials for adjuvant therapy.

A novel gene signature to predict immune infiltration and outcome in patients with prostate cancer

Prostate cancer (PCa) is one of the most common malignancies in male. We aim to establish a novel gene signature for immune infiltration and outcome (biochemical recurrence (BCR) and overall survival (OS)) of patients with prostate cancer (PCa) to augment Gleason patterns for evaluating prognosis and managing patients undergoing radical prostatectomy (RP). Combined with our microarray data and the Cancer Genome Atlas Project (TCGA) database (discovery set), we identified a six-gene signature. The Gene Expression Omnibus (GEO) database served as the test set. The databases of Fudan University Shanghai Cancer Center (FUSCC) and Third Affiliated Hospital of Nantong University (TAHNU) served as an external validation set. Immunohistochemistry was used to investigate the relationship between risk groups and the immune infiltrate. We identified a six-gene signature to predict immune cell infiltration and outcome of PCa patients. The AUC values used to predict early BCR in the discovery, test, FUSCC, and TAHNU sets were 0.73, 0.76, 0.72, and 0.81, respectively. Low-risk score patients in each dataset experienced significantly longer OS (P = .01, 0.04, 0.02, respectively). The signature also predicted high regulatory T cells (Tregs) and M2-polarized macrophages infiltration in high-risk score patients with PCa. Additionally, high mutation load, related signal pathways, and sensitivity to anticancer drugs that correlated with high-risk score of cancer progression and death were also identified. The six-gene signature may improve prognostic information, serve as a prognostic tool to manage patients after RP, and advance basic studies of PCa.

Percent tumor volume vs American Joint Committee on Cancer staging system subclassification for predicting biochemical recurrence in patients with pathologic T2 prostate cancer

PURPOSE

Here, we re-checked the American Joint Committee on Cancer 7th edition subclassification and confirmed the possibility of percent tumor volume as a prognostic factor for biochemical recurrence in the 8th edition subclassification.

METHODS

A total of 1073 patients with pathologic T2 stage disease who underwent radical prostatectomy were included. Exclusion criteria were neoadjuvant therapy and pathologic T3 and N1 disease. Biochemical recurrence-free survival was estimated using the Kaplan-Meier method. Cox hazard regression was used to predict biochemical recurrence.

RESULTS

According to the 7th edition subclassification, 141 patients (13.1%) had T2a, 43 (4.0%) had T2b, and 889 (82.9%) had T2c disease. The 7th edition subclassification did not differ significantly on Kaplan-Meier analysis (p = 0.502). Mean percent tumor volume was 8.7 ± 8.0% (interquartile range, 5-10%). Percent tumor volume was positively correlated with initial prostate-specific antigen, grade group, surgical margin, and T2 subclassification (all p < 0.001). The 7th edition subclassification was not a significant factor, whereas percent tumor volume was (hazard ratio, 1.023; 95% confidence interval, 1.005-1.041; p = 0.0128) on multivariate analysis. On Kaplan-Meier analysis, percent tumor volume (> 7.5% vs ≤ 7.5%) differed significantly for biochemical recurrence-free survival (p < 0.001).

CONCLUSIONS

The 7th edition pathologic T2 subclassification had poor prognostic value for biochemical recurrence in our cohort. Elimination of the 8th edition subclassification was suitable. Percent tumor volume classified biochemical recurrence prognosis in pathologic T2 stage. Therefore, percent tumor volume can be a candidate factor for the next T2 subclassification.

Development and validation of lncRNAs-based nomogram for prediction of biochemical recurrence in prostate cancer by bioinformatics analysis

Background: Early biochemical recurrence (BCR) was considered as a sign for clinical recurrence and metastasis of prostate cancer (PCa). The purpose of the present study was to identify a lncRNA-based nomogram that can predict BCR of PCa accurately.

Materials and methods: Bioinformatics analysis, such as propensity score matching (PSM) and differentially expressed genes (DEGs) analyses were used to identify candidate lncRNAs for further bioinformatics analysis. LASSO Cox regression model was used to select the most significant prognostic lncRNAs and construct the lncRNAs signature for predicting BCR in discovery set. Additionally, a nomogram based on our lncRNAs signature was also formulated. Both lncRNAs signature and nomogram were validated in test set. GSEA was carried out to identify various gene sets which share a common biological function, chromosomal location, or regulation.

Results: A total of 457 patients with sufficient BCR information were included in our analysis. Finally, a five lncRNAs signature significantly associated with BCR was identified in discovery set (HR=0.44, 95%CI: 0.27-0.72, C-index = 0.63) and validated in test set (HR=0.22, 95%CI: 0.09-0.56, C-index = 0.65). Additionally, the lncRNAs-based nomogram showed significant performance for predicting BCR in both discovery set (C-index = 0.74) and test set (C-index = 0.78).

Conclusion: In conclusion, our lncRNAs-based nomogram is a reliable prognostic tool for BCR in PCa patients. In addition, the present study put forward the direction for the further investigation on the mechanism of PCa progression.

Clinical Usefulness of Prostate and Tumor Volume Related Parameters following Radical Prostatectomy for Localized Prostate Cancer

PURPOSE

We evaluated whether the prediction of biochemical recurrence after radical prostatectomy is enhanced by any of 6 parameters, including prostate volume, total tumor volume, high grade total tumor volume, the ratio of high grade total tumor volume to total tumor volume, the ratio of total tumor volume to prostate volume and/or the ratio of high grade total tumor volume to prostate volume.

MATERIALS AND METHODS

A total of 1,261 patients who underwent radical prostatectomy during a 3-year period had tumor maps constructed with the Gleason pattern denoted as low-3 or high-4 or 5 and volumetric data generated using commercially available software. Univariate Cox regression models were used to assess whether each volume related parameter was associated with biochemical recurrence after radical prostatectomy. A multivariable Cox regression base model (age, prostate specific antigen, Gleason score/grade group, pathological stage and margin status) was compared with 6 additional models (base model plus each volume related parameter) to evaluate enhancement in predictive accuracy. Decision curve analysis was performed to determine the clinical utility of parameters that enhanced predictive accuracy.

RESULTS

On univariate analysis each parameter was significantly associated with biochemical recurrence except prostate volume. Predictive accuracy of the multivariable base model was high (c-index = 0.861). Adding volume related parameters marginally enhanced discrimination. Decision curve analysis failed to show added benefit even for high grade total tumor volume/total tumor volume, which was the parameter with the highest discriminative improvement.

CONCLUSIONS

Tumor volume related parameters are significantly associated with radical prostatectomy but do not add important discrimination to standard clinicopathological variables for radical prostatectomy prediction or provide benefit across a range of clinically relevant decision thresholds. Volume related measurement is not warranted in routine pathological evaluation and reporting.

Surface-enhanced Raman spectroscopy before radical prostatectomy predicts biochemical recurrence better than CAPRA-S

Objective

The objective of this study was to evaluate the performance of surface-enhanced Raman spectroscopy (SERS) in the prediction of early biochemical recurrence after radical prostatectomy (RP).

Patients and methods

We synthesized monodisperse gold nanoparticles as SERS-enhanced substrates and analyzed preoperative plasma samples of patients who underwent RP. The roles of clinical risk model (Cancer of the Prostate Risk Assessment [CAPRA] score) and distinctive SERS spectra on prediction of early biochemical recurrence were evaluated. The principal component analysis and linear discriminant analysis (PCA-LDA) were used to manage the spectral data and develop diagnostic algorithm.

Results

A total of 306 preoperative plasma Raman spectra from 102 patients were collected. SERS spectrum from those who developed early biochemical recurrence were compared to those who remained biochemical recurrence-free. The SERS detected more abundant circulating free nucleic acid bases in biochemical recurrence population, presenting significant stronger intensities at SERS spectral bands 725 and 1,328 cm⁻¹. The addition of Raman spectral peak 1,328 cm⁻¹ to CAPRA postsurgical (CAPRA-S) score significantly improved the predictive power of logistic regression model compared to simple CAPRA score (P<0.001). Meanwhile, the leave-one-out cross-validation method was used to validate the PCA-LDA model and revealed the sensitivity, specificity, and accuracy of 65.8%, 87.5%, and 79.4%, respectively. The receiver operating characteristic (ROC) curve was used to evaluate the performance of different models. Area under the ROC curve of the CAPRA-S score model alone was 0.77, however, when combined with Raman spectral peak 1,328 cm⁻¹, it improved to 0.81.

Conclusion

Our primary results suggested that SERS could be a meaningful technique for prediction of early biochemical recurrence in prostate cancer.

Predictors of early, intermediate and late biochemical recurrence after minimally invasive radical prostatectomy in a single-centre cohort with a mean follow-up of 8 years

OBJECTIVE

To determine the predictors of early, intermediate and late biochemical recurrence (BR) following minimally invasive radical prostatectomy in patients with localised prostate cancer (PC).

MATERIAL AND METHODS

We included 6195 patients with cT1-3N0M0 prostate cancer treated using radical laparoscopic prostatectomy (RLP) and radical robot-assisted prostatectomy at our institution between 2000 and 2016. None of the patients underwent adjuvant therapy. BR is defined as PSA levels ≥0.2 ng/dL. The time to BR is divided into terciles to identify the variables associated with early (<12 months), intermediate (12-36 months) and late (>36 months) recurrence. We employed logistic regression models to determine the risk factors associated with each interval.

RESULTS

We identified 1148 (18.3%) patients with BR. The median time to BR was 24 months (IQR, 0.98-53.18). The multivariate analysis showed that preoperative PSA levels, lymph node invasion, positive margins and RLP are associated with early recurrence (P≤.029 for all). Laparoscopic surgery was the only predictor of intermediate recurrence (P=.001). The predictors of late recurrence included a pathological Gleason score ≥7, stage ≥pT3, positive margins and RLP (P≤.02 for all).

CONCLUSIONS

The patients with high-risk prostate cancer can develop late recurrence and require long-term follow-up. Identifying patients with higher PSA levels and lymph node invasion has an important predictive role in the first year after surgery. The association between RLP and BR warrants further assessment.

The Gleason pattern 4 in radical prostatectomy specimens in current practice - Quantification, morphology and concordance with biopsy

PURPOSE

The upgrading of a prostate acinar adenocarcinoma grade group 1 (GG1) between needle biopsy and prostatectomy is common. The extent of high-grade tumor and cribriform morphology are currently suggested as prognostic factors.

METHODS

We reviewed 159 prostatectomy specimens from a private laboratory and an academic/public institution in Salvador, Bahia.

RESULTS

Tumors signed as GG1 at biopsy were upgraded in 59% of all cases. These tumors showed a low frequency of non-focal extraprostatic extension (one case, 3%), extensive positive surgical margins (two cases, 6%) and seminal vesicle invasion (one case, 3%). Among GG2 and GG3 tumors at prostatectomy, the percentage of Gleason pattern 4 (Gp4) involving the gland at ≤1%, 2-5% and >5% was associated with extensive extraprostatic extension (9%, 8% and 42%, respectively) and seminal vesicle invasion (1%, 10% and 31%, respectively). The volume of Gp4 of ≤1ml, >1 to 2ml and >2ml was associated with extensive extraprostatic extension (8%, 26% and 38%, respectively), seminal vesicle invasion (2%, 21% and 33%, respectively) and non-focal positive surgical margins (12%, 26% and 29%, respectively). Some GG2 tumors (~20%) indeed showed at least one measurement of Gp4 higher than one quarter of GG3 carcinomas. Cribriform morphology showed no significant associations for other adverse pathologic prognostic factors.

CONCLUSION

Upgrading from GG1 to GG2 is associated with a very low frequency of morphologic features associated with poor prognosis. Routine quantification of Gp4 is feasible in radical prostatectomy products and seems to better stratify tumors regarding the association with other morphologic parameters of prognostic importance.

Tumor Volume and Clinical Failure in High-Risk Prostate Cancer Patients Treated With Radical Prostatectomy

INTRODUCTION

To identify the most significant cut-off of tumor volume (TV) for prediction of clinical failure (CF) among high-risk prostate cancer (hPCa) patients.

METHODS

Within a multi-institutional cohort, 262 patients treated with radical prostatectomy (RP) for hPCa were identified. CF was defined as local recurrence or distant metastases. A time dependent ROC curve was used to evaluate the area under the curve (AUC) using TV as single marker to predict clinical failure at 10 years. We searched for the TV cut off value with the highest combined sensitivity and specificity predicting CF. Three multivariable Cox regression analyses (MVA) tested the predictors of CF after RP. Predictors of the model 1 were pre-operative PSA, pathologic stage (PT), pathologic Gleason sum (GS), surgical margin status, and lymph node invasion. Predictors of the models 2 and 3 were the same of model 1 plus TV as a continuous or dichotomous variable using the defined cutoff, respectively. Validation (leave-one-out-cross-validation-LOOCV) of each model was performed.

RESULTS

Overall, 46 (17.6%) patients experienced CF. The TV value was 6.29 ml. In MVA of models 2 and 3, PT and GS remained independent predictors of CF. Moreover, in model 2 TV (HR:1.07,) and in model 3 TV >6.29 ml (HR:2.99,) were independently associated with CF. In LOOCV, the C-index of models 1-3 were 65.53%, 71.75%, and 70.26%, respectively.

CONCLUSIONS

TV is an independent predictor of CF in hPCa patients. Patients with a TV exceeding the cut-off of 6.29 ml are more likely to develop CF. Prostate 77:3-9, 2017. © 2016 Wiley Periodicals, Inc.

Predictors of time to biochemical recurrence in a radical prostatectomy cohort within the PSA-era

INTRODUCTION

We sought to determine predictors for early and late biochemical recurrence following radical prostatectomy among localized prostate cancer patients.

METHODS

The study included localized prostate cancer patients treated with radical prostatectomy (RP) at the University of Southern California from 1988 to 2008. Competing risks regression models were used to determine risk factors associated with earlier or late biochemical recurrence, defined using the median time to biochemical recurrence in this population (2.9 years after radical prostatectomy).

RESULTS

The cohort for this study included 2262 localized prostate cancer (pT2-3N0M0) patients who did not receive neoadjuvant or adjuvant therapies. Of these patients, 188 experienced biochemical recurrence and a subset continued to clinical recurrence, either within (n=19, 10%) or following (n=13, 7%) 2.9 years after RP. Multivariable stepwise competing risks analysis showed Gleason score ≥7, positive surgical margin status, and ≥pT3a stage to be associated with biochemical recurrence within 2.9 years following surgery. Predictors of biochemical recurrence after 2.9 years were Gleason score 7 (4+3), preoperative prostate-specific antigen (PSA) level, and ≥pT3a stage.

CONCLUSIONS

Higher stage was associated with biochemical recurrence at any time following radical prostatectomy. Particular attention may need to be made to patients with stage ≥pT3a, higher preoperative PSA, and Gleason 7 prostate cancer with primary high-grade patterns when considering longer followup after RP.

Size-adjusted Quantitative Gleason Score as a Predictor of Biochemical Recurrence after Radical Prostatectomy

BACKGROUND

The risk of biochemical recurrence (BCR) following radical prostatectomy for pathologic Gleason 7 prostate cancer varies according to the proportion of Gleason 4 component.

OBJECTIVE

We sought to explore the value of several novel quantitative metrics of Gleason 4 disease for the prediction of BCR in men with Gleason 7 disease.

DESIGN, SETTING, AND PARTICIPANTS

We analyzed a cohort of 2630 radical prostatectomy cases from 1990-2007. All pathologic Gleason 7 cases were identified and assessed for quantity of Gleason pattern 4. Three methods were used to quantify the extent of Gleason 4: a quantitative Gleason score (qGS) based on the proportion of tumor composed of Gleason pattern 4, a size-weighted score (swGS) incorporating the overall quantity of Gleason 4, and a size index (siGS) incorporating the quantity of Gleason 4 based on the index lesion.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Associations between the above metrics and BCR were evaluated using Cox proportional hazards regression analysis.

RESULTS AND LIMITATIONS

qGS, swGS, and siGS were significantly associated with BCR on multivariate analysis when adjusted for traditional Gleason score, age, prostate specific antigen, surgical margin, and stage. Using Harrell's c-index to compare the scoring systems, qGS (0.83), swGS (0.84), and siGS (0.84) all performed better than the traditional Gleason score (0.82).

CONCLUSIONS

Quantitative measures of Gleason pattern 4 predict BCR better than the traditional Gleason score.

PATIENT SUMMARY

In men with Gleason 7 prostate cancer, quantitative analysis of the proportion of Gleason pattern 4 (quantitative Gleason score), as well as size-weighted measurement of Gleason 4 (size-weighted Gleason score), and a size-weighted measurement of Gleason 4 based on the largest tumor nodule significantly improve the predicted risk of biochemical recurrence compared with the traditional Gleason score.