Predictive and prognostic models in radical prostatectomy candidates: a critical analysis of the literature

Predictive factors for disease progression after salvage radiation therapy in biochemical recurrent patients treated by radical prostatectomy

Objective

Salvage radiation therapy (SRT) is standard treatment for patients after radical prostatectomy (RP). However, the optimal timing of SRT remains to be elucidated.

Material and methods

We retrospectively reviewed 133 prostate cancer (PCa) patients who underwent SRT for biochemical recurrence after RP. Disease progression was defined as repeated prostate-specific antigen (PSA) level more than 0.2 ng/mL, greater than the post-SRT nadir or radiographic progression. A receiver operating characteristic curve analysis was used to identify the optimal pre-SRT PSA level for predicting progression after SRT. Cox regression analyses were performed to elucidate the association between clinicopathologic characteristics and disease progression.

Results

Fifty-one PCa patients (38.4%) experienced disease progression after SRT. The optimal cutoff value of the pre-SRT PSA for predicting disease progression was 0.44 ng/mL. In multivariable analysis, pre-SRT PSA >0.44 ng/mL was a significant independent predictor of post-SRT disease progression [hazard ratio (HR): 2.02, P = 0.02]. Although the pre-SRT PSA >0.44 ng/mL did not maintain its independent association with disease progression in the multivariable analysis of patients with adverse pathology (HR: 1.63, P = 0.22), PSA within 4 weeks after RP as a continuous variable was significantly associated with disease progression (HR: 1.19, P = 0.04).

Conclusions

Our results highlight that in PCa patients who undergo RP, SRT should be performed before their PSA reaches 0.44 ng/mL. In patients with adverse pathology disease, a high PSA level within the 4 weeks after RP might identify those who are likely to have disease progression, and these patients might require systemic therapy.

Salvage lymphadenectomy after primary therapy with curative intent for prostate cancer

PURPOSE OF REVIEW

To provide a summary of the current literature on salvage lymph node dissection (sLND) in patients with nodal recurrent prostate cancer (PCa) with focus on imaging, the extent of sLND and oncologic outcomes.

RECENT FINDINGS

The clinical practice guidelines recommend performing PET/CT in patients with biochemical recurrence (BCR) after primary therapy. PSMA PET/CT has demonstrated superiority over choline PET/CT and MRI, especially at low prostate-specific antigen (PSA) levels. Although the heterogeneity in available literature does not allow standardization of surgical templates for sLND and PET/CT scan can guide the extent of surgical dissection, an anatomically defined extended template is typically considered. Radio-guided surgery (RGS) suggests an improved positive lymph node yield compared with standard sLND. However, long-term data are needed to evaluate the oncologic impact of sLND. The main aims of sLND are to delay recurrence and to postpone the need for systemic therapy. Available evidence suggests that around 40-80% of men can achieve complete biochemical response after sLND and 10-30% remain BCR free after 5 years. Robotic sLND might represent an option to reduce the risk of complications without compromising oncological outcomes; validation in controlled prospective studies is, however, needed.

SUMMARY

sLND is a valid treatment option for patients with nodal recurrence only after primary therapy for PCa. Further optimization of patient selection based on highly sensitive and specific imaging and clinical factors remains an unmet need. To maximize the benefit of this approach, sLND should be discussed with patients who harbor lymph node-only recurrence after primary therapy in a shared decision-making.

Positive family history as a predictor for disease outcomes after radical prostatectomy for nonmetastatic prostate cancer

Background

While family history (FHx) of prostate cancer (PCa) increases the risk of PCa, comparably less is known regarding the impact of FHx on pathologic and oncologic outcomes after radical prostatectomy (RP).

Methods

We retrospectively reviewed our multicenter database comprising 6,041 nonmetastatic PCa patients treated with RP. Patients with a FHx of PCa in one or more first-degree relatives were considered as FHx positive. We examined the association of FHx with pathologic outcomes and biochemical recurrence (BCR) using logistic and Cox regression models, respectively.

Results

In total, 1,677 (28%) patients reported a FHx of PCa. Compared to patients without FHx, those with, were younger at RP (median age of 59 vs. 62 years, p < 0.01), and had significantlymore favorable biopsy and RP histopathologic findings. On multivariable logistic regression analysis, positive FHx was associated with extracapsular extension (odds ratio [OR] 0.77, 95% confidence interval [CI] 0.66-0.90, p < 0.01; model AUC 0.73) and upgrading (OR 0.70, 95% CI 0.62-0.80, p < 0.01; model AUC 0.68). Incorporating FHx significantly improved the AUC of the base model for upgrading (p < 0.01). Positive FHx was not associated with BCR in pre- and postoperative multivariable models (p = 0.1 and p = 0.7); c-indexes of Cox multivariable models were: 0.73 and 0.82, respectively.

Conclusions

We found that patients with clinically nonmetastatic PCa who have positive FHx of PCa undergo RP at a younger age and have more favorable pathologic outcomes. Nevertheless, FHx of PCa did not confer better BCR rates, suggesting that FHx leads to potentially early detection and treatment without impact on BCR.

From past to future: Bibliometric analysis of global research productivity on nomogram (2000-2021)

Background

Nomogram, a visual clinical predictive model, provides a scientific basis for clinical decision making. Herein, we investigated 20 years of nomogram research responses, focusing on current and future trends and analytical challenges.

Methods

We mined data of scientific literature from the Core Collection of Web of Science, searching for the original articles with title "Nomogram^*/Parton Table^*/Parton Nomogram^*", published within January 1st, 2000 to December 30th, 2021. Data records were validated using HistCite Version and analyzed with a transformable statistical method, the Bibliometrix 3.0 package of R Studio.

Results

In total, 4,176 original articles written by 19,158 authors were included from 915 sources. Annually, Nomogram publications are continually produced, which have rapidly grown since 2018. China published the most articles; however, its total citations ranked second after the United States. Both total citations and average article citations in the United States rank first globally, and a high degree of cooperation exists between countries. Frontiers in Oncology published the most papers (238); this number has grown rapidly since 2019. Journal of Urology had the highest H-index, with an average increase in publications over the past 20 years. Most research topics were tumor-related, among which tumor risk prediction and prognostic evaluation were the main contents. Research on prognostic assessment is more published and advanced, while risk prediction and diagnosis have good developmental prospects. Furthermore, nomogram of the urinary system has been highly developed. Following advancements in nomogram modeling, it has recently been applied to non-oncological subjects.

Conclusion

This bibliometric analysis provides a comprehensive overview of the current nomogram status, which could enable better understanding of its development over the years, and provide global researchers a comprehensive analysis and structured information to help identify hot spots and gaps in future research.

A Systematic Review and Meta-Analysis of Prognostic Nomograms After UTUC Surgery

Background

Current guidelines recommend assessing the prognosis in high-risk upper tract urothelial carcinoma patients (UTUC) after surgery. However, no specific method is endorsed. Among the various prognostic models, nomograms represent an easy and accurate tool to predict the individual probability for a specific event. Therefore, identifying the best-suited nomogram for each setting seems of great interest to the patient and provider.

Objectives

To identify, summarize and compare postoperative UTUC nomograms predicting oncologic outcomes. To estimate the overall performance of the nomograms and identify the most reliable predictors. To create a reference tool for postoperative UTUC nomograms, physicians can use in clinical practice.

Design

A systematic review was conducted following the recommendations of Cochrane’s Prognosis Methods Group. Medline and EMBASE databases were searched for studies published before December 2021. Nomograms were grouped according to outcome measurements, the purpose of use, and inclusion and exclusion criteria. Random-effects meta-analyses were performed to estimate nomogram group performance and predictor reliability. Reference tables summarizing the nomograms’ important characteristics were created.

Results

The systematic review identified 26 nomograms. Only four were externally validated. Study heterogeneity was significant, and the overall Risk of Bias (RoB) was high. Nomogram groups predicting overall survival (OS), recurrence-free survival (RFS), and intravesical recurrence (IVR) had moderate discrimination accuracy (c-Index summary estimate with 95% confidence interval [95% CI] and prediction interval [PI] > 0.6). Nomogram groups predicting cancer-specific survival (CSS) had good discrimination accuracy (c-Index summary estimate with 95% CI and PI > 0.7). Advanced pathological tumor stage (≥ pT3) was the most reliable predictor of OS. Pathological tumor stage (≥ pT2), age, and lymphovascular invasion (LVI) were the most reliable predictors of CSS. LVI was the most reliable predictor of RFS.

Conclusions

Despite a moderate to good discrimination accuracy, severe heterogeneity discourages the uninformed use of postoperative prognostic UTUC nomograms. For nomograms to become of value in a generalizable population, future research must invest in external validation and assessment of clinical utility. Meanwhile, this systematic review serves as a reference tool for physicians choosing nomograms based on individual needs.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=282596, identifier PROSPERO [CRD42021282596].

Radiation therapy compared to radical prostatectomy as first-line definitive therapy for patients with high-risk localised prostate cancer: An updated systematic review and meta-analysis

Objective

To present an update of the available literature on external beam radiation therapy (EBRT) with or without brachytherapy (BT) compared to radical prostatectomy (RP) for patients with high-risk localised prostate cancer (PCa).

Methods

We conducted a systematic review and meta-analysis of the literature assessing the survival outcomes in patients with high-risk PCa who received EBRT with or without BT compared to RP as the first-line therapy with curative intent. We queried PubMed and Web of Science database in January 2021. Moreover, we used random or fixed-effects meta-analytical models in the presence or absence of heterogeneity per the I² statistic, respectively. We performed six meta-analyses for overall survival (OS) and cancer-specific survival (CSS).

Results

A total of 27 studies were selected with 23 studies being eligible for both OS and CSS. EBRT alone had a significantly worse OS and CSS compared to RP (hazard ratio [HR] 1.38, 95% confidence interval [CI] 1.16–1.65; and HR 1.55, 95% CI 1.25–1.93). However, there was no difference in OS (HR 1.1, 95% CI 0.76–1.34) and CSS (HR 0.69, 95% CI 0.45–1.06) between EBRT plus BT compared to RP.

Conclusion

While cancer control affected by EBRT alone seems inferior to RP in patients with high-risk PCa, BT additive to EBRT was not different from RP. These data support the need for BT in addition to EBRT as part of multimodal RT for high-risk PCa.

Abbreviations: ADT: androgen-deprivation therapy; BT: brachytherapy; CSS: cancer-specific survival; HR: hazard ratio; MFS, metastatic-free survival; MOOSE: Meta-analyses of Observational Studies in Epidemiology; OR: odds ratio; OS: overall survival; PCa: prostate cancer; RR: relative risk; RP: radical prostatectomy; RCT: randomised controlled trials; (EB)RT: (external beam) radiation therapy

Comparison of short-term and long-term neoadjuvant hormone therapy prior to radical prostatectomy: a systematic review and meta-analysis

PURPOSE

This study aimed to evaluate the efficacy of long-term neoadjuvant androgen-deprivation therapy (ADT) before radical prostatectomy (RP).

METHODS

We conducted meta-analyses and network meta-analyses, which included randomized controlled trials that assessed patients with prostate cancer (PC) who received either short-term (<6 months) or long-term (≥6 months) neoadjuvant ADT before RP.

RESULTS

Thirteen articles with 2778 patients were eligible for analysis. Short-term neoadjuvant ADT was neither associated with biochemical recurrence (OR 1.19, 95% CI, 0.93-1.51, p = 0.17), metastasis (OR 0.73, 95% CI, 0.45-1.19, p = 0.21), nor overall mortality (OR 0.72, 95% CI 0.43-1.21, p = 0.22); no study investigated survival outcomes in patients on long-term neoadjuvant ADT. In terms of pathologic outcomes, long-term neoadjuvant ADT was significantly associated with a reduced risk of positive surgical margin (SM) and an increased rate of organ-confined disease (OCD) compared to short-term neoadjuvant ADT (OR 0.56, 95% CI 0.39-0.80, p = 0.001, and OR 1.48, 95% CI 1.10-1.99, p = 0.009, respectively). These findings were confirmed in the network meta-analyses. Meanwhile, only a non-significant trend favoring long-term neoadjuvant ADT was observed for pathologic complete response (OR 1.98, 95% Crl 1.00-3.93).

CONCLUSION

Long-term neoadjuvant ADT was associated with more favorable pathologic outcomes, but whether these findings translate into favorable survival outcomes still remains unproven due to very limited evidence. Since there are no reliable survival data, long-term neoadjuvant ADT before RP should not be used in clinical practice until more robust evidence arises from ongoing trials.

Association of statins use and mortality outcomes in prostate cancer patients who received androgen deprivation therapy: a systematic review and meta-analysis

Introduction

While several recent studies investigated the influence of statins on survival outcomes in prostate cancer (PCa) patients on androgen deprivation therapy (ADT), definitive conclusions are still missing. The present systematic review and meta-analysis aimed to develop an overarching framework for the association of statins use and survival outcomes in PCa patients who receive ADT.

Material and methods

We conducted a systematic review and meta-analysis of the literature assessing the survival outcomes for statin compared to non-statin users in PCa patients who received ADT. We searched PubMed and Web of Science for studies published before March 1, 2021. We used the random effect model in the presence of heterogeneity and the fixed-effects model in the absence of heterogeneity per the I² statistic. We did two meta-analyses; the primary meta-analysis was accomplished for articles reporting cancer-specific survival (CSS) as an outcome. A secondary meta-analysis was completed for articles reporting overall survival (OS) as an outcome.

Results

Ten studies were eligible for inclusion. Nine studies included in the first meta-analysis comprising 136,285 patients showed no statistically significant difference in CSS (HR 0.77; 95% CI 0.49–1.21) between statin users and non-users in PCa patients who received ADT. In four studies included in the second meta-analysis comprising 95,032 patients, statin users had a significantly better OS compared to non-users (HR 0.67; 95% CI 0.62–0.73).

Conclusions

Although the combination of statins and ADT in PCa patients significantly improves OS, it seems not to be through an effect on cancer-specific factors.

Impact of preoperative systemic immune-inflammation Index on oncologic outcomes in bladder cancer patients treated with radical cystectomy

PURPOSE

To investigate the predictive and prognostic value of the preoperative systemic immune-inflammation index (SII) in patients undergoing radical cystectomy (RC) for clinically non-metastatic urothelial cancer of the bladder (UCB).

METHODS

Overall, 4,335 patients were included, and the cohort was stratified in two groups according to SII using an optimal cut-off determined by the Youden index. Uni- and multivariable logistic and Cox regression analyses were performed, and the discriminatory ability by adding SII to a reference model based on available clinicopathologic variables was assessed by area under receiver operating characteristics curves (AUC) and concordance-indices. The additional clinical net-benefit was assessed using decision curve analysis (DCA).

RESULTS

High SII was observed in 1879 (43%) patients. On multivariable preoperative logistic regression, high SII was associated with lymph node involvement (LNI; P = 0.004), pT3/4 disease (P <0.001), and non-organ confined disease (NOCD; P <0.001) with improvement of AUCs for predicting LNI (P = 0.01) and pT3/4 disease (P = 0.01). On multivariable Cox regression including preoperative available clinicopathologic values, high SII was associated with recurrence-free survival (P = 0.028), cancer-specific survival (P = 0.005), and overall survival (P = 0.006), without improvement of concordance-indices. On DCAs, the inclusion of SII did not meaningfully improve the net-benefit for clinical decision-making in all models.

CONCLUSION

High preoperative SII is independently associated with pathologic features of aggressive disease and worse survival outcomes. However, it did not improve the discriminatory margin of a prediction model beyond established clinicopathologic features and failed to add clinical benefit for decision making. The implementation of SII as a part of a panel of biomarkers in future studies might improve decision-making.

The role of lymph node dissection in salvage radical prostatectomy for patients with radiation recurrent prostate cancer

PURPOSE

To examine the effect of lymph node dissection on the outcomes of patients who underwent salvage radical prostatectomy (SRP).

MATERIAL AND METHODS

We retrospectively reviewed data from radiation-recurrent patients with prostate cancer (PCa) who underwent SRP from 2000-2016. None of the patients had clinical lymph node involvement before SRP. The effect of the number of removed lymph nodes (RLNs) and the number of positive lymph nodes (PLNs) on biochemical recurrence (BCR)-free survival, metastases free survival, and overall survival (OS) was tested in multivariable Cox regression analyses.

RESULTS

About 334 patients underwent SRP and pelvic lymph node dissection (PLND). Lymph node involvement was associated with increased risk of BCR (p < .001), metastasis (p < .001), and overall mortality (p = .006). In a multivariable Cox regression analysis, an increased number of RLNs significantly lowered the risk of BCR (hazard ratio [HR] 0.96, p = .01). In patients with positive lymph nodes, a higher number of RLNs and a lower number of PLNs were associated with improved freedom from BCR (HR 0.89, p = .001 and HR 1.34, p = .008, respectively). At a median follow-up of 23.9 months (interquartile range, 4.7-37.7), neither the number of RLNs nor the number of PLNs were associated with OS (p = .69 and p = .34, respectively).

CONCLUSION

Pathologic lymph node involvement increased the risk of BCR, metastasis and overall mortality in radiation-recurrent PCa patients undergoing SRP. The risk of BCR decreased steadily with a higher number of RLNs during SRP. Further research is needed to support this conclusion and develop a precise therapeutic adjuvant strategy based on the number of RLNs and PLNs.

Prognostic value of the pre-operative serum albumin to globulin ratio in patients with non-metastatic prostate cancer undergoing radical prostatectomy

PURPOSE

To evaluate the potential predictive value of the preoperative serum albumin to globulin ratio (AGR) for oncological outcomes in patients treated with radical prostatectomy (RP) for clinically non-metastatic prostate cancer (PCa).

METHODS

Pre-operative AGR was assessed in a multi-institutional cohort of 6041 patients treated with RP. Logistic regression analyses were performed to assess the association of the AGR with advanced disease. We performed Cox regression analyses to determine the relationship between AGR and biochemical recurrence (BCR).

RESULTS

The optimal cut-off value was determined to be 1.31 according to receiver operating curve analysis. Compared to patients with a higher AGR, those with a lower preoperative AGR had worse BCR-free survival (P < 0.01) in the Kaplan-Meier analysis. Pre- and post-operative multivariable models that adjusted for the effects of established clinicopathologic features, confirmed its independent association with BCR [hazard ratio (HR) 1.52, 95% confidence interval (CI) 1.31-1.75, P < 0.01, HR 1.55, 95% CI 1.34-1.79, P < 0.01, respectively]. However, the addition of AGR to established prognostic models did not improve their discrimination.

CONCLUSION

While AGR is significantly associated with BCR, in the present study, the clinical impact of AGR was not large enough to affect patient management. Longer follow-up is necessary to observe the true effect of AGR.

Impact of systemic Immune-inflammation Index on oncologic outcomes in patients treated with radical prostatectomy for clinically nonmetastatic prostate cancer

PURPOSE

To evaluate the predictive and prognostic value of the Systemic Immune-inflammation Index (SII) in a large cohort of patients treated with radical prostatectomy (RP) for clinically non-metastatic prostate cancer (PCa).

METHODS

We retrospectively analyzed our multicenter database comprising 6,039 consecutive patients. The optimal preoperative SII cut-off value was assessed with the Youden index calculated on a time-dependent receiver operating characteristic (ROC) curve. Logistic regression and Cox regression analyses were used to investigate the association of SII with pathologic features and biochemical recurrence (BCR), respectively. The discriminatory ability of the models was evaluated by calculating the concordance-indices (C-Index). The clinical benefit of the implementation of SII in clinical decision making was assessed using decision curve analysis (DCA).

RESULTS

Patients with high preoperative SII (≥ 620) were more likely to have adverse clinicopathologic features. On multivariable logistic regression analysis, high preoperative SII was independently associated with extracapsular extension (odds ratio [OR] 1.16, P = 0.041), non-organ confined disease (OR 1.18, P = 0.022), and upgrading at RP (OR 1.23, P < 0.001). We built two Cox regression models including preoperative and postoperative variables. In the preoperative multivariable model, high preoperative SII was associated with BCR (hazard ratio [HR] 1.34, 95% CI 1.15-1.55, P < 0.001). In the postoperative multivariable model, SII was not associated with BCR (P = 0.078). The addition of SII to established models did not improve their discriminatory ability nor did it increase the clinical net benefit on DCA.

CONCLUSION

In men treated with RP for clinically nonmetastatic PCa, high preoperative SII was statistically associated with an increased risk of adverse pathologic features at RP as well as BCR. However, it did not improve the predictive accuracy and clinical value beyond that obtained by current predictive and prognostic models. SII together with a panel of complementary biomarkers is praised to help guide decision-making in clinically nonmetastatic PCa.

Application of Machine Learning Algorithms in Breast Cancer Diagnosis and Classification

Breast cancer continues to be the most frequent cancer in females, affecting about one in 8 women and causing the highest number of cancer-related deaths in females worldwide despite remarkable progress in early diagnosis, screening, and patient management. All breast lesions are not malignant, and all the benign lesions do not progress to cancer. However, the accuracy of diagnosis can be increased by a combination or preoperative tests such as physical examination, mammography, fine-needle aspiration cytology, and core needle biopsy. Despite some limitations, these procedures are more accurate, reliable, and acceptable, when compared with a single adopted diagnostic procedure. Recent studies have shown that breast cancer can be accurately predicted and diagnosed using machine learning (ML) technology. The objective of this study was to explore the application of ML approaches to classify breast cancer based on feature values generated from a digitized image of a fine-needle aspiration (FNA) of a breast mass. To achieve this objective, we used ML algorithms, collected a scientific dataset of 569 breast cancer patients from Kaggle (https://www.kaggle.com/uciml/breast-cancer-wisconsin-data), analyze and interpreted the data based on ten real-valued features of a breast mass FNA including the radius, texture, perimeter, area, smoothness, compactness, concavity, concave points, symmetry, and fractal dimension. Among the 569 patients tested, 63% were diagnosed with benign breast cancer and 37% were diagnosed with malignant breast cancer. Benign tumors grow slowly and do not spread while malignant tumors grow rapidly and spread to other parts of the body.

Independent validation of a predictive nomogram for risk of reinfection in women with recurrent non-complicated urinary tract infections

Aims:

Independent external validation of a predictive nomogram for risk of reinfection in women with a history of non-complicated recurrent urinary tract infection (UTI).

Methods:

A retrospective longitudinal study was conducted to validate the LUTIRE nomogram in a Brazilian female cohort. The nomogram was applied to 81 women presenting non-complicated recurring UTI screened at a urological clinic. External validation was performed using the nomogram variables in patients followed up from January 2014 to December 2016 at a urological clinic. Accuracy of the nomogram was obtained by analyzing the predictive capacity observed in the area under the receiver operating characteristic (ROC) curve. A multivariate logistic regression model was used to assess the ability of the nomogram variables to predict the recurrence of UTI over 12 months. The time to recurrence of infection was calculated using a Kaplan–Meier curve and the log-rank test with calculation of the hazard ratio.

Results:

The mean age of the study population was 42.8 years; 57 women (70.37%) had recurrence. The independent variables with statistical significance in the multivariate analysis were gram-negative bacteria [odds ratio (OR) 18.38; p = 0.03897] and number of UTIs in the past 12 months (OR 25.11; p = 0.00006). The accuracy of the nomogram for discriminating patients who had UTI recurrence was 82.6% (95% CI = 72.5–90.1).

Conclusion:

The LUTIRE nomogram showed good accuracy among Brazilian women with recurrent UTI.

Library of deep-learning image segmentation and outcomes model-implementations

An open-source library of implementations for deep-learning-based image segmentation and outcomes models based on radiotherapy and radiomics is presented. As oncology treatment planning becomes increasingly driven by automation, such a library of model implementations is crucial to (i) validate existing models on datasets collected at different institutions, (ii) automate segmentation, (iii) create ensembles for improving performance and (iv) incorporate validated models in the clinical workflow. Inclusion of deep-learning-based image segmentation and outcomes models in the same library provides a fully automated and reproduceable pipeline to estimate prognosis. The library was developed with the Computational Environment for Radiological Research (CERR) software platform. Centralizing model implementations in CERR builds upon its rich set of radiotherapy and radiomics tools and caters to the world-wide user base. CERR provides well-validated feature extraction pipelines for radiotherapy dosimetry and radiomics with fine control over the calculation settings, allowing users to select appropriate parameters used in model derivation. Models for automatic image segmentation are distributed via containers, allowing them to be deployed with a variety of scientific computing architectures. The library includes implementations of popular DVH-based models outlined in the Quantitative Analysis of Normal Tissue Effects in the Clinic effort and recently published literature. Radiomics models include features from the Image Biomarker Standardization Initiative and application-specific features found to be relevant across multiple sites and image modalities. The library is distributed as a module within CERR at https://www.github.com/cerr/CERR under the GNU-GPL copyleft with additional restrictions on clinical and commercial use and provision to dual license in future.

Independent external validation of nomogram to predict extracapsular extension in patients with prostate cancer

INTRODUCTION

The objective of this study was to perform an independent external validation of the Giganti-Coppola nomogram (GCN), which uses clinical and radiological parameters to predict prostate extracapsular extension (ECE) on the final pathology of patients undergoing radical prostatectomy (RP).

MATERIAL AND METHODS

Seventy-two patients diagnosed with prostate cancer (PCa), who were RP candidates from two institutions, were prospectively included. All patients underwent preoperative multi-parametric magnetic resonance imaging (mpMRI) at 1.5 T, without the use of an endorectal coil, with multiplanar images in T1WI, T2WI, DWI, and DCE. The AUC and a calibration graph were used to validate the nomogram, using the regression coefficients of the Giganti-Coppola study.

RESULTS

The original nomogram had an AUC of 0.90 (p = 0.001), with a sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 100%, 5.1%, 47.1%, 100%, and 48%, respectively. The calibration graph showed an overestimation of the nomogram for ECE.

CONCLUSION

The GCN has an adequate ability in predicting ECE; however, in our sample, it showed limited accuracy and overestimated likelihood of ECE in the final pathology of patients with PCa submitted to RP.

KEY POINTS

• Knowledge of preoperative local staging of prostate cancer is essential for surgical treatment. Extracapsular extension increases the chance of positive surgical margins. • Imaging modalities such as mpMRI alone does not have suitable accuracy in local staging. • Giganti-Coppola's nomogram achieved an adequate ability in predicting ECE.

Preoperative %p2PSA and Prostate Health Index Predict Pathological Outcomes in Patients with Prostate Cancer Undergoing Radical Prostatectomy

To evaluate the predictive accuracy of the %p2PSA and prostate health index (PHI) in predicting aggressive pathological outcomes in patients with prostate cancer (PCa) undergoing radical prostatectomy (RP), we enrolled 91 patients with organ-confined PCa who were treated with robot-assisted RP. p2PSA levels and the PHI were investigated for their ability to predict pathological results. The %p2PSA and PHI were both significantly higher in patients with ≥pT3 disease, high-risk disease, positive surgical margin, or seminal vesical invasion (SVI). In univariable analysis, p2PSA derivatives were significant predictors of the presence of ≥pT3 disease, high-risk disease, positive surgical margin, and SVI. To predict adverse pathological outcomes at a sensitivity of 90%, p2PSA derivatives had higher specificity than standard PSA derivatives. In multivariable analysis, additional increases in the area under the receiver operating characteristic curve (AUC) were observed with the %p2PSA and PHI for ≥pT3 disease, high-risk disease, and positive surgical margin (8.2% and 2.7%, 6.2% and 4.1%, and 8.6% and 5.4%, respectively). A PHI ≥61.26 enhanced the predictive accuracy of the model for SVI by increasing the AUC from 0.624 to 0.819 (p = 0.009). The preoperative %p2PSA and PHI accurately predict adverse pathological results and are useful for decision-making.

Expression of urokinase-type plasminogen activator system in non-metastatic prostate cancer

PURPOSE

To investigate the prognostic role of expression of urokinase-type plasminogen activator system members, such as urokinase-type activator (uPA), uPA-receptor (uPAR), and plasminogen activator inhibitor-1 (PAI-1), in patients treated with radical prostatectomy (RP) for prostate cancer (PCa).

METHODS

Immunohistochemical staining for uPA system was performed on a tissue microarray of specimens from 3121 patients who underwent RP. Cox regression analyses were performed to investigate the association of overexpression of these markers alone or in combination with biochemical recurrence (BCR). Decision curve analysis was used to assess the clinical impact of these markers.

RESULTS

uPA, uPAR, and PAI-1 were overexpressed in 1012 (32.4%), 1271 (40.7%), and 1311 (42%) patients, respectively. uPA overexpression was associated with all clinicopathologic characteristics of biologically aggressive PCa. On multivariable analysis, uPA, uPAR, and PAI-1 overexpression were all three associated with BCR (HR: 1.75, p < 0.01, HR: 1.22, p = 0.01 and HR: 1.20, p = 0.03, respectively). Moreover, the probability of BCR increased incrementally with increasing cumulative number of overexpressed markers. Decision curve analysis showed that addition of uPA, uPAR, and PAI-1 resulted in a net benefit compared to a base model comparing standard clinicopathologic features across the entire threshold probability range. In subgroup analyses, overexpression of all three markers remained associated with BCR in patients with favorable pathologic characteristics.

CONCLUSION

Overexpression of uPA, uPAR, and PAI-1 in PCa tissue were each associated with worse BCR. Additionally, overexpression of all three markers is informative even in patients with favorable pathologic characteristics potentially helping clinical decision-making regarding adjuvant therapy and/or intensified follow-up.

Prostate biopsy: guidelines and evidence

PURPOSE OF REVIEW

To summarize the highest level evidence that was acquired within the last years, with regard to diagnosis of prostate cancer. With many secondary diagnostic tools becoming available, and not being mentioned in the guidelines, this review is meant to assist clinical decision-making in initial biopsy and rebiopsy settings.

RECENT FINDINGS

The PROMIS Trial delivered level 1b evidence about the diagnostic accuracy of prostate multiparametric MRI (mpMRI) as a triage tool for prostate biopsy. MRI-ultrasound-fusions-targeted biopsy has been evaluated and compared with the standard of care, and has been found to have a higher cancer detection rate. The different approaches to MRI-guided biopsies do not show significant differences. Urine biomarkers analysing RNA as well as genetic assays of biopsy specimen have also shown to be helpful in the decision to (re-)biopsy a patient, especially in combination with MRI.

SUMMARY

Patients and doctors alike have been trying to avoid prostate biopsies, the risks, and the side effects of potential overtreatment. Imaging and other biomarkers are used to increase diagnostic accuracy, yielding more precise information to act on. None of these secondary diagnostic tools are perfect, yet they can, and should be used if one stays aware of their limitations.

Positive STAT5 Protein and Locus Amplification Status Predicts Recurrence after Radical Prostatectomy to Assist Clinical Precision Management of Prostate Cancer

BACKGROUND

A significant fraction of prostate cancer patients experience post-radical prostatectomy (RP) biochemical recurrence (BCR). New predictive markers are needed for optimizing postoperative prostate cancer management. STAT5 is an oncogene in prostate cancer that undergoes amplification in 30% of prostate cancers during progression.

METHODS

We evaluated the significance of a positive status for nuclear STAT5 protein expression versus STAT5 locus amplification versus combined positive status for both in predicting BCR after RP in 300 patients.

RESULTS

Combined positive STAT5 status was associated with a 45% disadvantage in BCR in Kaplan-Meier survival analysis in all Gleason grade patients. Patients with Gleason grade group (GG) 2 and 3 prostate cancers and combined positive status for STAT5 had a more pronounced disadvantage of 55% to 60% at 7 years after RP in univariate analysis. In multivariate analysis, including the Cancer of the Prostate Risk Assessment Postsurgical nomogram (CAPRA-S) variables, combined positive STAT5 status was independently associated with a shorter BCR-free survival in all Gleason GG patients (HR, 2.34; P = 0.014) and in intermediate Gleason GG 2 or 3 patients (HR, 3.62; P = 0.021). The combined positive STAT5 status improved the predictive value of the CAPRA-S nomogram in both ROC-AUC analysis and in decision curve analysis for BCR.

CONCLUSIONS

Combined positive status for STAT5 was independently associated with shorter disease-free survival in univariate analysis and was an independent predictor for BCR in multivariate analysis using the CAPRA-S variables in prostate cancer.

IMPACT

Our results highlight potential for a novel precision medicine concept based on a pivotal role of STAT5 status in improving selection of prostate cancer patients who are candidates for early adjuvant interventions to reduce the risk of recurrence.

Combination possibility and deep learning model as clinical decision-aided approach for prostate cancer

This study aims to introduce as proof of concept a combination model for classification of prostate cancer using deep learning approaches. We utilized patients with prostate cancer who underwent surgical treatment representing the various conditions of disease progression. All possible combinations of significant variables from logistic regression and correlation analyses were determined from study data sets. The combination possibility and deep learning model was developed to predict these combinations that represented clinically meaningful patient's subgroups. The observed relative frequencies of different tumor stages and Gleason score Gls changes from biopsy to prostatectomy were available for each group. Deep learning models and seven machine learning approaches were compared for the classification performance of Gleason score changes and pT2 stage. Deep models achieved the highest F1 scores by pT2 tumors (0.849) and Gls change (0.574). Combination possibility and deep learning model is a useful decision-aided tool for prostate cancer and to group patients with prostate cancer into clinically meaningful groups.

Models predicting survival to guide treatment decision-making in newly diagnosed primary non-metastatic prostate cancer: a systematic review

OBJECTIVES

Men diagnosed with non-metastatic prostate cancer require standardised and robust long-term prognostic information to help them decide on management. Most currently-used tools use short-term and surrogate outcomes. We explored the evidence base in the literature on available pre-treatment, prognostic models built around long-term survival and assess the accuracy, generalisability and clinical availability of these models.

DESIGN

Systematic literature review, pre-specified and registered on PROSPERO (CRD42018086394).

DATA SOURCES

MEDLINE, Embase and The Cochrane Library were searched from January 2000 through February 2018, using previously-tested search terms.

ELIGIBILITY CRITERIA

Inclusion required a multivariable model prognostic model for non-metastatic prostate cancer, using long-term survival data (defined as ≥5 years), which was not treatment-specific and usable at the point of diagnosis.

DATA EXTRACTION AND SYNTHESIS

Title, abstract and full-text screening were sequentially performed by three reviewers. Data extraction was performed for items in the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies checklist. Individual studies were assessed using the new Prediction model Risk Of Bias ASsessment Tool.

RESULTS

Database searches yielded 6581 studies after deduplication. Twelve studies were included in the final review. Nine were model development studies using data from over 231 888 men. However, only six of the nine studies included any conservatively managed cases and only three of the nine included treatment as a predictor variable. Every included study had at least one parameter for which there was high risk of bias, with failure to report accuracy, and inadequate reporting of missing data common failings. Three external validation studies were included, reporting two available models: The University of California San Francisco (UCSF) Cancer of the Prostate Risk Assessment score and the Cambridge Prognostic Groups. Neither included treatment effect, and both had potential flaws in design, but represent the most robust and usable prognostic models currently available.

CONCLUSION

Few long-term prognostic models exist to inform decision-making at diagnosis of non-metastatic prostate cancer. Improved models are required to inform management and avoid undertreatment and overtreatment of non-metastatic prostate cancer.

Focal Neuroendocrine Differentiation of Conventional Prostate Adenocarcinoma as a Prognostic Factor after Radical Prostatectomy: A Systematic Review and Meta-Analysis

The biologic and prognostic value of focal neuroendocrine differentiation (NED) in conventional prostate adenocarcinoma (PC) patients who undergo radical prostatectomy (RP) remains controversial. In this systematic review and meta-analysis, we assessed the association of focal NED in conventional PC with oncological outcomes after RP. A literature search using PubMed, Scopus, Web of Science, and Cochrane Library was conducted on December 2018 to find relevant studies according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. We used a fixed-effect model to analyze the impact of focal NED in RP specimen on progression-free survival defined by biochemical recurrence (BCR). A total of 16 studies with the outcomes of disease progression and survival were eligible. No patient in these studies received androgen deprivation therapy prior to RP. Eleven studies found no significant correlation between focal NED and outcomes of interest, while five studies reported a significant association of focal NED assessed by immunohistochemical chromogranin A or serotonin staining with BCR or survival. Focal NED was associated with higher BCR rates after RP with a pooled HR of 1.39 (95% CI 1.07‒1.81) in five studies. No heterogeneity was reported in this analysis (I² = 21.7%, p = 0.276). In conclusion, focal NED in conventional PC is associated with worse prognosis after RP. Its presence should be reported in pathologic reports and its true clinical impact should be assessed in well-designed prospective controlled studies.

Outcomes of very high-risk prostate cancer after radical prostatectomy: Validation study from 3 centers

BACKGROUND

Among men with localized high-risk prostate cancer (PCa), patients who meet very high-risk (VHR) criteria have been shown to experience worse outcomes after radical prostatectomy (RP) in a previous study. Variations of VHR criteria have been suggested to be prognostic in other single-center cohorts, but multicenter outcomes validating VHR criteria have not been described. This study was designed to validate VHR criteria for identifying which PCa patients are at greatest risk for cancer progression.

METHODS

Patients with high-risk PCa undergoing RP (2005-2015) at 3 tertiary centers were pooled. The outcomes of men with VHR PCa were compared with the outcomes of those who did not meet VHR criteria. The high-risk criteria were a clinical stage of T3 to T4, a prostate-specific antigen level > 20 ng/mL, or a biopsy Gleason grade sum of 8 to 10. The VHR criteria were multiple high-risk features, >4 biopsy cores with a Gleason grade sum of 8 to 10, or primary Gleason grade pattern 5. Biochemical recurrence, metastasis (METS), and cancer-specific mortality (CSM) were assessed with competing risks regressions. Overall mortality was assessed with Cox survival models.

RESULTS

Among 1981 patients with high-risk PCa, men with VHR PCa (n = 602) had adverse pathologic outcomes: 37% versus 25% for positive margins and 37% versus 15% for positive lymph nodes (P <  .001 for both comparisons). Patients with VHR PCa also had higher adjusted hazard ratios for METS (2.78; 95% confidence interval [CI], 2.08-3.72), CSM (6.77; 95% CI, 2.91-15.7), and overall mortality (2.44; 95% CI, 1.56-3.80; P <  .001 for all comparisons).

CONCLUSIONS

In a validation study of patients who underwent treatment for high-risk PCa, VHR criteria were strongly associated with adverse pathologic and oncologic outcomes.

Ultrasensitive prostate-specific antigen level as a predictor of biochemical progression after robot-assisted radical prostatectomy: Towards risk adapted follow-up

BACKGROUND

Ultrasensitive prostate-specific antigen (USPSA) is useful for stratifying patients according to their USPSA-based risk. Aim of our study was to determine the usefulness of USPSA as predictor of biochemical recurrence (BCR) after robot-assisted radical prostatectomy (RARP).

METHODS

This retrospective study included 213 prostate cancer patients who had a postoperative USPSA between 0.01 and 0.2 ng/mL and at least 2 years of follow-up. We developed predictive models for BCR with PSA ≥0.2 and ≥0.5 ng/mL.

RESULTS

A total of 103 patients (48.3%) had BCR at a median follow-up of 13.3 months. Higher postoperative USPSA (odds ratio [OR] = 4.73, P < 0.01), bilateral positive surgical margin in both sides (OR = 1.32, P = 0.044), higher average PSA rise (OR = 1.67, P = 0.031), ISUP grade group ≥3 (OR = 1.48, P = 0.003), and shorter interval since RARP (OR = 0.58, P < 0.001) were independent predictors of BCR with PSA ≥0.2 ng/mL. Higher postoperative USPSA (OR = 3.85, P < 0.01), bilateral positive surgical margin (OR = 1.34, P = 0.011), ISUP grade group ≥3 (OR = 1.5, P = 0.002), and shorter interval since RARP (OR = 0.61, P = 0.001) were independent predictors of BCR with PSA ≥0.5 ng/mL. The areas under the curve for the first and second model were 0.865 and 0.834, respectively.

CONCLUSION

Ultrasensitive PSA after RARP is a useful prognostic indicator of BCR which could guide postoperative risk stratification and layout follow-up scheduling.

The Prognostic PDE4D7 Score in a Diagnostic Biopsy Prostate Cancer Patient Cohort with Longitudinal Biological Outcomes

Purpose. To further validate the prognostic power of the biomarker PDE4D7, we investigated the correlation of PDE4D7 scores adjusted for presurgical clinical variables with longitudinal postsurgical biological outcomes. Methods. RNA was extracted from biopsy punches of resected tumors (550 patients; RP cohort) and diagnostic needle biopsies (168 patients; DB cohort). Cox regression and survival were applied to correlate PDE4D7 scores with patient outcomes. Logistic regression was used to combine the clinical CAPRA score with PDE4D7. Results. In univariate analysis, the PDE4D7 score was significantly associated with PSA recurrence after prostatectomy in both studied patient cohorts' analysis (HR 0.53; 95% CI 0.41-0.67; p<1.0E-04 and HR 0.47; 95% CI 0.33-0.65; p<1.0E-04, respectively). After adjustment for the presurgical clinical variables preoperative PSA, PSA density, biopsy Gleason, clinical stage, percentage tumor in the biopsy (data only available for RP cohort), and percentage of positive biopsies, the HR was 0.49 (95% CI 0.38-0.64; p<1.0E-04) and 0.43 (95% CI 0.29-0.63; p<1.0E-04), respectively. The addition of the PDE4D7 to the clinical CAPRA score increased the AUC by 5% over the CAPRA score alone (0.82 versus 0.77; p=0.004). This combination model stratified 14.6% patients of the DB cohort to no risk of biochemical relapse (NPV 100%) over a follow-up period of up to 15 years. Conclusions. The PDE4D7 score provides independent risk information for pretreatment risk stratification. Combining CAPRA with PDE4D7 scores significantly improved the clinical risk stratification before surgery.

Significant association between urethral length measured by magnetic resonance imaging and urinary continence recovery after robot-assisted radical prostatectomy

Introduction

To determine the clinical predictive factors affecting the recovery from postoperative urinary incontinence after robot-assisted radical prostatectomy (RARP).

Materials and methods

We consecutively analyzed 320 patients who underwent RARP between January 2012 and March 2015. The restoration of urinary continence was defined as follows: the use of no pads/no leakage of urine or the use of a safety pad. Preoperative covariates were statistically assessed by multivariate logistic regression analysis to investigate their predict factor to recovery of urinary incontinence. Therefore, in this study, we sought to identify predictors of early urinary continence status in a single-center retrospective study of consecutive patients who underwent RARP.

Results

Continence rates at 1, 3, 6, and 12 months after the catheter was removed were 44%, 71%, 83%, and 93%, respectively. Age, body mass index, and prostate volume had no significant association with urinary continence recovery. In contrast to this, longer preoperative membranous urethral length (MUL) was significantly associated with earlier postoperative continence recovery. Multivariate analysis demonstrated that longer preoperative MUL is significantly associated with continence recovery at 1 month (P = 0.0235).

Conclusion

Approximately 70% of patients achieved urinary continence within 3 months after RARP. Multivariate analysis showed that age, body mass index, and prostate volume had no significant association with urinary continence recovery. Preoperative MUL assessed by magnetic resonance imaging was an independent predictor of early recovery from urinary incontinence after RARP.

A Multi-Institutional Validation of Gleason Score Derived from Tissue Microarray Cores

To test the agreement between high-grade PCa at RP and TMA, and the ability of TMA to predict BCR. Validation of concordance between tissue microarray (TMA) and radical prostatectomy (RP) high-grade prostate cancer (PCa) is crucial because latter determines the treated natural history of PCa. We hypothesized that TMA Gleason score is in agreement with RP pathology and capable of accurately predicting biochemical recurrence (BCR). Data were provided from a multi-institutional Canadian sample of 1333 TMA and RP specimens with complete clinicopathological data. First, rate of agreement between TMA and high-grade Gleason at RP or biopsy and RP was tested. Second, ability of RP, TMA and biopsy to predict BCR was compared. Multivariable (MVA) Cox regression models were fitted and BCR rates were illustrated with Kaplan-Meier plots. Agreement between RP and TMA and between RP and biopsy was 72.6% (95% CI:69.7-75.5) and 60.4% (95% CI:57.2-63.6), respectively. In MVA predicting BCR, the accuracy for RP, TMA and biopsy was 0.73, 0.72 and 0.68, respectively. TMA added discriminatory ability among exclusively low-grade Gleason RP patients (p = 0.02), but did not improve BCR discrimination in exclusive high-grade PCa RP patients (p = 0.8). TMA Gleason grade accurately reflects presence of high-grade Gleason in RP specimen, accurately predicts BCR rates after RP and improves prediction of BCR in low-grade Gleason patients at RP.

Prognostic significance of six clinicopathological features for biochemical recurrence after radical prostatectomy: a systematic review and meta-analysis

Identifying patients with high risk of biochemical recurrence after radical prostatectomy is of immense value in clinical practice. Assessment of prognostic significance of specific clinicopathological features plays an important role in surgical management after prostatectomy. The purpose of our meta-analysis was to investigate the association between the six pathological characteristics and the prognosis of prostate cancer. We carried out a systematic document retrieval in electronic databases to sort out appropriate studies. Outcomes of interest were gathered from studies comparing biochemical recurrence-free survival (BCFS) in patients with the six pathological traits. Studies results were pooled, and hazard ratios (HRs) combined with corresponding 95% confidence intervals (CIs) for survival were used to estimate the effect size. 29 studies (21,683 patients) were enrolled in our meta-analysis. All the six predictors were statistically significant for BCFS with regard to seminal vesicle invasion (HR = 1.97, 95% CI = 1.79–2.18, p < 0.00001), positive surgical margin (HR = 1.79, 95% CI = 1.56–2.06, p < 0.00001), extracapsular extension (HR = 2.03, 95% CI = 1.65–2.50, p < 0.0001), lymphovascular invasion (HR = 1.85, 95% CI = 1.54–2.22, p < 0.00001), lymph node involvement (HR = 1.88, 95% CI = 1.37–2.60, p = 0.0001) and perineural invasion (HR = 1.59, 95% CI = 1.33–1.91, p < 0.00001). Subgroup analysis showed that all the six predictors had significantly relationship with poor BCFS. The pooled results demonstrated that the six clinical findings indicated a worse prognosis in patients with prostate cancer. In conclusion, our results show several clinicopathological characteristics can predict the risk of biochemical recurrence after radical prostatectomy. Prospective studies are needed to further confirm the predictive value of these features for the prognosis of prostate cancer patients after radical prostatectomy.

When to Perform Preoperative Bone Scintigraphy for Kidney Cancer Staging: Indications for Preoperative Bone Scintigraphy

OBJECTIVE

To identify an objective and reproducible strategy for preoperative staging bone scintigraphy (BS) in patients diagnosed with renal cell carcinoma (RCC), because in the absence of objective criteria, the decision to perform preoperative BS remains a subjective practice.

PATIENTS AND METHODS

The study included a total of 2008 patients with RCC treated with surgery and prospectively included into an institutional database. The study outcome was the presence of 1 or more bone lesions suspicious for metastases at staging BS. A multivariable logistic regression model predicting a positive BS was fitted. The predictors consisted of the preoperative clinical tumor (cT) and clinical nodal (cN) stages, the presence of systemic symptoms, and the platelet-to-hemoglobin (PLT/Hb) ratio.

RESULTS

The rate of positive BS was 4% (n = 81). At the multivariable logistic regression analysis, cT2, cN1, the presence of systemic symptoms, and the PLT/Hb ratio were all associated with am increased risk of positive BS (P <.05). Following the 2000-sample bootstrap validation, the concordance index was 0.77 (proposed model) vs 0.63 (decision making based on symptoms only). At the decision curve analysis, the proposed strategy was associated with a higher net benefit. If BS is performed when the risk of positive result is >5%, a negative BS is spared in 80% and a positive BS is missed in 2% of the population only.

CONCLUSION

Using preoperative variables, it is possible to accurately estimate the risk of positive BS at RCC staging using preoperative characteristics. Compared with the strategy supported by available guidelines, the proposed model was more objective, statistically more accurate, and clinically associated with higher net benefit.

Validation of Cyclic Adenosine Monophosphate Phosphodiesterase-4D7 for its Independent Contribution to Risk Stratification in a Prostate Cancer Patient Cohort with Longitudinal Biological Outcomes

BACKGROUND

The clinical metrics used to date to assess the progression risk of newly diagnosed prostate cancer patients only partly represent the true biological aggressiveness of the underlying disease.

OBJECTIVE

Validation of the prognostic biomarker phosphodiesterase-4D7 (PDE4D7) in predicting longitudinal biological outcomes in a historical surgery cohort to improve postsurgical risk stratification.

DESIGN, PATIENTS, AND METHODS

RNA was extracted from biopsy punches of resected tumors from 550 patients. PDE4D7 was quantified using one-step quantitative reverse transcription-polymerase chain reaction. PDE4D7 scores were calculated by normalization of PDE4D7 to reference genes. Multivariate analyses were adjusted for clinical prognostic variables. Outcomes tested were: prostate-specific antigen relapse, start of salvage treatment, progression to metastases, overall mortality, and prostate cancer-specific mortality. The PDE4D7 score was combined with the clinical risk model Cancer of the Prostate Risk Assessment Postsurgical Score (CAPRA-S) using multivariate regression modeling; the combined score was tested in post-treatment progression free survival prediction.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Correlations with outcomes were analyzed using multivariate Cox regression and logistic regression statistics.

RESULTS AND LIMITATIONS

The PDE4D7 score was significantly associated with time-to-prostate specific antigen failure after prostatectomy (hazard ratio [HR]: 0.53, 95% confidence interval [CI]: 0.41-0.67 for each unit increase, p<0.0001). After adjustment for postsurgical prognostic variables the HR was 0.56 (95% CI: 0.43-0.73, p<0.0001). The PDE4D7 score remained significant after adjusting the multi-variate analysis for the CAPRA-S model categories (HR=0.54, 95% CI=0.42-0.69, p<0.0001). Combination of the PDE4D7 score with the CAPRA-S demonstrated a significant incremental value of 4-6% in 2-yr (p=0.004) or 5-yr (p=0.003) prediction of progression free survival after surgery. The combined model of PDE4D7 and CAPRA-S improves patient selection with very high risk of fast disease relapse after primary intervention.

CONCLUSIONS

The PDE4D7 score has the potential to provide independent risk information and to restratify patients with clinical intermediate- to high-risk characteristics to a very low-risk profile.

PATIENT SUMMARY

In this report, we studied the potential of a novel biomarker to predict outcomes of a cohort of prostate cancer patients who underwent surgery more than 10 yr ago. We found that a gene called phosphodiesterase-4D7 added extra information to the available clinical data. We conclude that the measurement of this gene in tumor tissue may contribute to more effective treatment decisions.

The prostate health index PHI predicts oncological outcome and biochemical recurrence after radical prostatectomy - analysis in 437 patients

The purpose of this study was to investigate the Prostate-Health-Index (PHI) for pathological outcome prediction following radical prostatectomy and also for biochemical recurrence prediction in comparison to established parameters such as Gleason-score, pathological tumor stage, resection status (R0/1) and prostate-specific antigen (PSA).

Out of a cohort of 460 cases with preoperative PHI-measurements (World Health Organization calibration: Beckman Coulter Access-2-Immunoassay) between 2001 and 2014, 437 patients with complete follow up data were included. From these 437 patients, 87 (19.9%) developed a biochemical recurrence. Patient characteristics were compared by using chi-square test. Predictors were analyzed by multivariate adjusted logistic and Cox regression.

The median follow up for a biochemical recurrence was 65 (range 3-161) months. PHI, PSA, [-2]proPSA, PHI- and PSA-density performed as significant variables (p < 0.05) for cancer aggressiveness: Gleason-score <7 or ≥7 (ISUP grade 1 or ≥2) . Concerning pathological tumor stage discrimination and prediction, variables as PHI, PSA, %fPSA, [-2]proPSA, PHI- and PSA-density significantly discriminated between stages <pT3 and ≥pT3 with the highest AUC (0.7) for PHI. In biochemical recurrence prediction PHI, PSA, [-2]proPSA, PHI- and PSA-density were the strongest predictors.

In conclusion, due to heterogeneity of time spans to biochemical recurrence, longer follow up periods are crucial. This study with a median follow up of more than 5 years, confirmed a clinical value for PHI as an independent biomarker essential for biochemical recurrence prediction.

On Risk Estimation versus Risk Stratification in Early Prostate Cancer

In a Perspective article, Sigrid Carlsson and Michael Kattan discuss Gnanapragasam and colleagues' accompanying research study on refining risk stratification in early prostate cancer.

Subclassification of high-risk clinically organ-confined prostate cancer for early cancer-specific mortality after radical prostatectomy

OBJECTIVE

High-risk clinically localized prostate cancer is seen in a highly heterogeneous population with a wide variation of clinical aggressiveness and a novel subclassification for the better prediction of clinical outcomes is needed. The aim of this study is to validate a modified D'Amico risk criteria for substratification of high-risk prostate cancer with regard to the prediction of biochemical recurrence, clinical progression-free survival or prostate cancer-specific mortality after radical prostatectomy.

METHODS

We conducted a retrospective multicenter cohort study including 461 clinically organ-confined (cT1-2), D'Amico high-risk prostate cancer patients who underwent radical prostatectomy with pelvic lymph node dissection. The modified criteria subclassified D'Amico high-risk patients into high-risk (n = 189, single high-risk parameter and two low-risk parameters) and very high-risk (n = 272, at least one more intermediate or high-risk parameter in addition to the qualifying high-risk parameter) groups. Biochemical recurrence-free survival, clinical progression-free survival, prostate cancer-specific mortality and overall survival were analyzed.

RESULTS

The very high-risk group, compared with high-risk group, had significantly poorer biochemical recurrence (5- and 10-year biochemical recurrence-free rates: 52.8 vs 73.9% and 42.1 vs 61.7%, respectively, P < 0.0001), clinical progression-free survival (5- and 10-year survivals: 91.8 vs 98.2% and 80.5 vs 98.2%, respectively, P = 0.0013) and prostate cancer-specific mortality (5- and 10-year mortalities: 2.5 vs 0.0% and 6.7 vs 0.0%, respectively, P = 0.0124).

CONCLUSION

D'Amico high-risk patients can achieve very favorable outcomes unless they are classified as very high risk. Our novel subclassification method is very simple and useful for better patient counseling and decision-making in the pretreatment setting.

Role of survivin expression in predicting biochemical recurrence after radical prostatectomy: a multi-institutional study

OBJECTIVE

To assess the association of survivin expression with clinicopathological features and biochemical recurrence (BCR) after radical prostatectomy (RP) in a large multi-institutional cohort.

METHODS

Survivin expression was evaluated by immunohistochemistry on a tissue microarray of RP cores from 3 117 patients. Survivin expression was considered altered when at least 10% of the tumour cells stained positive. The association of altered survivin expression with BCR was evaluated using Cox proportional hazards regression models.

RESULTS

Survivin expression was altered in 1 330 patients (42.6%). Altered expression was associated with higher Gleason score on RP (P = 0.001), extracapsular extension (P = 0.019), seminal vesicle invasion (P < 0.001) and lymph node metastases (P = 0.009). The median (interquartile range) follow-up was 38 (21-66) months. Patients with altered survivin expression had a shorter BCR-free survival time than those with normal expression (5-year BCR-free survival estimates: 74.7 vs 79.0%; P = 0.008). Altered survivin expression did not retain its prognostic value, however, after adjustment for the effect of established clinicopathological factors (P = 0.73). Subgroup analyses also showed no independent prognostic value of survivin.

CONCLUSIONS

Survivin expression is commonly altered in patients undergoing RP. Altered survivin expression is associated with the clinicopathological features of biologically and clinically aggressive PCa. Survivin expression was associated with BCR only in univariable analysis, limiting its value in daily clinical decision-making.

Antibody response to BK polyomavirus as a prognostic biomarker and potential therapeutic target in prostate cancer

Infectious agents, including the BK polyomavirus (BKPyV), have been proposed as important inflammatory pathogens in prostate cancer. Here, we evaluated whether the preoperative antibody response to BKPyV large T antigen (LTag) and viral capsid protein 1 (VP1) was associated with the risk of biochemical recurrence in 226 patients undergoing radical prostatectomy for primary prostate cancer. Essentially, the multivariate Cox regression analysis revealed that preoperative seropositivity to BKPyV LTag significantly reduced the risk of biochemical recurrence, independently of established predictors of biochemical recurrence such as tumor stage, Gleason score and surgical margin status. The predictive accuracy of the regression model was denotatively increased by the inclusion of the BKPyV LTag serostatus. In contrast, the VP1 serostatus was of no prognostic value. Finally, the BKPyV LTag serostatus was associated with a peculiar cytokine gene expression profile upon assessment of the cellular immune response elicited by LTag. Taken together, our findings suggest that the BKPyV LTag serology may serve as a prognostic factor in prostate cancer. If validated in additional studies, this biomarker may allow for better treatment decisions after radical prostatectomy. Finally, the favorable outcome of LTag seropositive patients may provide a potential opportunity for novel therapeutic approaches targeting a viral antigen.

A Nomogram for Predicting the Likelihood of Obstructive Sleep Apnea to Reduce the Unnecessary Polysomnography Examinations

Background:

The currently available polysomnography (PSG) equipments and operating personnel are facing increasing pressure, such situation may result in the problem that a large number of obstructive sleep apnea (OSA) patients cannot receive timely diagnosis and treatment, we sought to develop a nomogram quantifying the risk of OSA for a better decision of using PSG, based on the clinical syndromes and the demographic and anthropometric characteristics.

Methods:

The nomogram was constructed through an ordinal logistic regression procedure. Predictive accuracy and performance characteristics were assessed with the area under the curve (AUC) of the receiver operating characteristics and calibration plots, respectively. Decision curve analyses were applied to assess the net benefit of the nomogram.

Results:

Among the 401 patients, 73 (18.2%) were diagnosed and grouped as the none OSA (apnea-hypopnea index [AHI] <5), 67 (16.7%) the mild OSA (5 ≤ AHI < 15), 82 (20.4%) the moderate OSA (15 ≤ AHI < 30), and 179 (44.6%) the severe OSA (AHI ≥ 30). The multivariable analysis suggested the significant factors were duration of disease, smoking status, difficulty of falling asleep, lack of energy, and waist circumference. A nomogram was created for the prediction of OSA using these clinical parameters and was internally validated using bootstrapping method. The discrimination accuracies of the nomogram for any OSA, moderate-severe OSA, and severe OSA were 83.8%, 79.9%, and 80.5%, respectively, which indicated good calibration. Decision curve analysis showed that using nomogram could reduce the unnecessary polysomnography (PSG) by 10% without increasing the false negatives.

Conclusions:

The established clinical nomogram provides high accuracy in predicting the individual risk of OSA. This tool may help physicians better make decisions on PSG arrangement for the patients referred to sleep centers.

Identification of Most Aggressive Carcinoma Among Patients Diagnosed With Prostate Cancer Using Mathematical Modeling of Prostate-Specific Antigen Increases

BACKGROUND

Tools for differentiating aggressive and indolent prostate carcinoma (PCa) are needed. Mathematical modeling is a promising approach for longitudinal analysis of tumor marker kinetics.

PATIENTS AND METHODS

The prostate-specific antigen (PSA) increases from patients with PCa and those with benign prostatic hyperplasia (BPH) were retrospectively analyzed using a mathematical model. Using the NONMEM program, individual PSA kinetics were fit to the following equation: [d(PSA)/dt = (PROD.K × exp [RHO1 × t]) × (1 - BPH) + PROD.NK × exp (RHO2 × t) - KELIM × (PSA)], where RHO1 is the PSA production increase rate by PCa cells (PROD.K), RHO2 is the PSA production increase rate by non-PCa cells (PROD.NK), and KELIM is the PSA elimination rate. The comparative value of the modeled kinetic parameters, estimated for each patient, for predicting the D'Amico score and relapse-free survival (RFS) were tested using logistic regression analysis and multivariate survival tests.

RESULTS

The PSA kinetics from 62 patients with BPH and 149 patients with PCa before radical prostatectomy were successfully modeled. We identified statistically significant relationships between the PSA growth rate related to cancer cells (RHO1) and the probability of D'Amico high-risk group (less than the median RHO1 vs. at the median or greater: odds ratio, 2.15; 95% confidence interval [CI], 1.00-4.77; P = .05). RHO1 was also a significant prognostic factor for RFS on univariate analysis and against other reported prognostic factors using multivariate Cox tests. Three independent prognostic factors of RFS were found: RHO1 (hazard ratio [HR], 2.71; 95% CI, 1.25-5.84; P = .01), Gleason score (HR, 8.54; 95% CI, 4.19-17.40; P < .01), and positive surgical margins (HR, 2.04; 95% CI, 1.05-3.97; P = .03).

CONCLUSION

Using a few PSA time points analyzed with a mathematical model (easily manageable in routine practice), it could be possible to determine before surgery whether a patient has presented with aggressive PCa.

The prognostic role of preoperative serum C-reactive protein in predicting the biochemical recurrence in patients treated with radical prostatectomy

BACKGROUND

To assess the prognostic value of preoperative C-reactive protein (CRP) serum levels for prognostication of biochemical recurrence (BCR) after radical prostatectomy (RP) in a large multi-institutional cohort.

METHODS

Data from 7205 patients treated with RP at five institutions for clinically localized prostate cancer (PCa) were retrospectively analyzed. Preoperative serum levels of CRP within 24 h before surgery were evaluated. A CRP level ⩾0.5 mg dl(-1) was considered elevated. Associations of elevated CRP with BCR were evaluated using univariable and multivariable Cox proportional hazards regression models. Harrel's C-index was used to assess prognostic accuracy (PA).

RESULTS

Patients with higher Gleason score on biopsy and RP, extracapsular extension, seminal vesicle invasion, lymph node metastasis, and positive surgical margins status had a significantly elevated preoperative CRP compared to those without these features. Patients with elevated CRP had a lower 5-year BCR survival proportion as compared to those with normal CRP (55% vs 76%, respectively, P<0.0001). In pre- and postoperative multivariable models that adjusted for standard clinical and pathologic features, elevated CRP was independently associated with BCR (P<0.001). However, the addition of preoperative CRP did not improve the accuracy of the standard pre- and postoperative models for prediction of BCR (70.9% vs 71% and 78.9% vs 78.7%, respectively).

CONCLUSIONS

Preoperative CRP is elevated in patients with pathological features of aggressive PCa and BCR after RP. While CRP has independent prognostic value, it does not add prognostically or clinically significant information to standard predictors of outcomes.

Optimizing the clinical utility of PCA3 to diagnose prostate cancer in initial prostate biopsy

Background

PCA3 has been included in a nomogram outperforming previous clinical models for the prediction of any prostate cancer (PCa) and high grade PCa (HGPCa) at the initial prostate biopsy (IBx). Our objective is to validate such IBx-specific PCA3-based nomogram. We also aim to optimize the use of this nomogram in clinical practice through the definition of risk groups.

Methods

Independent external validation. Clinical and biopsy data from a contemporary cohort of 401 men with the same inclusion criteria to those used to build up the reference’s nomogram in IBx. The predictive value of the nomogram was assessed by means of calibration curves and discrimination ability through the area under the curve (AUC). Clinical utility of the nomogram was analyzed by choosing thresholds points that minimize the overlapping between probability density functions (PDF) in PCa and no PCa and HGPCa and no HGPCa groups, and net benefit was assessed by decision curves.

Results

We detect 28 % of PCa and 11 % of HGPCa in IBx, contrasting to the 46 and 20 % at the reference series. Due to this, there is an overestimation of the nomogram probabilities shown in the calibration curve for PCa. The AUC values are 0.736 for PCa (C.I.95 %:0.68–0.79) and 0.786 for HGPCa (C.I.95 %:0.71–0.87) showing an adequate discrimination ability. PDF show differences in the distributions of nomogram probabilities in PCa and not PCa patient groups. A minimization of the overlapping between these curves confirms the threshold probability of harboring PCa >30 % proposed by Hansen is useful to indicate a IBx, but a cut-off > 40 % could be better in series of opportunistic screening like ours. Similar results appear in HGPCa analysis. The decision curve also shows a net benefit of 6.31 % for the threshold probability of 40 %.

Conclusions

PCA3 is an useful tool to select patients for IBx. Patients with a calculated probability of having PCa over 40 % should be counseled to undergo an IBx if opportunistic screening is required.