Prediction of clinically significant prostate cancer after negative prostate biopsy: The current value of microscopic findings.

OBJECTIVE: To assess the current ability of atypical small acinar proliferation (ASAP), multifocal high-grade prostatic intraepithelial neoplasia (mHGPIN), HGPIN with atypia (PINATYP) and other non-malignant lesions to predict clinically significant prostate cancer (csPCa) in repeat prostate biopsies. METHODS: This retrospective study analyzed 377 repeat prostate biopsies, carried out between 2.014 and 2.017, and excluding those with previous PCa or 5-alpha reductase inhibitors treatment. ASAP, mHGPIN, PINATYP, prostatic atrophy, prostatic hyperplastic atrophy, proliferative inflammatory atrophy (PIA), chronic prostatitis, acute prostatitis, or granulomatous prostatitis, were prospectively reported after 12-core transrectal ultrasound (TRUS) systematic negative previous biopsies. 3T-multiparametric magnetic resonance imaging (mpMRI) was performed previous repeat biopsies. At least 2-core TRUS targeted biopsies of Prostate Imaging-Reporting and Data Systemv2 lesions ≥3, and/or 12-core TRUS systematic biopsy were performed in repeat prostate biopsies. The main outcome measurements were csPCa detection, which was defined when the International Society of Uro-Pathology group grade >1 and avoided biopsies. After logistic regression analysis the most efficient model was selected, nomogram was designed with internal validation, and clinical utility was analyzed. RESULTS: Normal benign tissue alone was present in less than 2% of previous negative biopsies. mHGPIN (39.7%), ASAP (4.3%) and PINATYP (3.7%) failed to predict csPCa risk in repeat biopsies. The finding of PIA (38.2%) associated with a decreased the risk of csPCa with an Odd ratio of 0.54 (95% confidence interval: 0.31-0.95), P= 0.031. The area under the curve, to predict csPCa, of mpMRI was 0.736, increasing up to 0.860 (95% confidence internal:0.82-0.90) when PSA density, age, digital rectal examination, and differential PSA between biopsies and PIA finding were integrated in a predictive model. At 6% threshold, more than 20% of repeat prostate biopsies were saved without missing csPCa. CONCLUSION: Currently, mHGPIN in negative prostate biopsy seems not able to predict the risk of future csPCa. The low incidence of ASAP and PINATYP, in our series, did not allow us to draw conclusions. PIA finding associated with a reduced risk of csPCa, and it could be integrated in a useful based-mpMRI predictive nomogram.

[Consensus on castration-resistant prostate cancer management in Spain.] / Consenso sobre el manejo del cáncer de próstata resistente a la castración avanzado en España.

OBJECTIVES: To move towards a more standardized approach in clinical practice to manage patients with castration-resistant prostate cancer (CRPC) in Spain. METHODS: A panel of 18 Spanish experts in Urology with expertise managing CRPC followed a modified Delphi process with two rounds and a final face-to-face consensus meeting. The panel considered a total of 106 clinical questions divided into the following 6 sections: definition of CRPC, diagnosis of metastases by imaging techniques, symptoms of CRPC, progression of CRPC, M0 and M1 management and therapeutic sequencing. RESULTS: A bone scan (BS) is recommended at diagnosis, at the onset of bone pain, and depending on PSA levels, but it is not sensitive enough to confirm or exclude bone metastases if there is bone pain. Whole-body MRI and axial MRI are more sensitive than BS and plain X-rays, but more expensive, so they have to be used in certain situations. There is CRPC progression when there is radiologic, clinical or confirmed PSA progression. Flare phenomenon appears in treatment with taxanes and abiraterone. It was agreed that in M0 CRPC patients no drug treatment is currently recommended, although in M1 CRPC patients the first-line therapy would be mainly enzalutamide/abiraterone and/or docetaxel, depending on the symptom burden. CONCLUSION: After the consensus, we provide a series of recommendations for Spanish physicians treating CRPC to address the disease characteristics,how to tailor patient management decisions, the use of imaging techniques, and how to handle disease progression appropriately to improve patients' quality of life.

Consenso sobre el manejo del cáncer de próstata resistente a la castración avanzado en España / Consensus on castration-resistant prostate cancer management in Spain

OBJETIVOS: Establecer recomendaciones sobre la práctica clínica habitual del manejo del cáncer de próstata resistente a la castración (CPRC) en España. MÉTODOS: Un panel de 18 expertos en Urología con experiencia en el manejo del CPRC participaron en un proceso Delphi modificado a dos rondas con una reunión final presencial. El panel consideró un total de 106 cuestiones clínicas divididas en las siguientes secciones: definición del CPRC, diagnóstico de metástasis por técnicas de imagen, síntomatología, progresión, manejo de M0 y M1 y secuenciación terapéutica. RESULTADOS: Se recomienda realizar una gammagrafía ósea (GO) en el diagnóstico, al comienzo del dolor óseo y dependiendo de los niveles de PSA. La resonancia magnética de cuerpo entero y la axial son más sensibles que la GO y la radiografía, pero más caras, por lo que se reservan para ciertas situaciones. Existe progresión del CPRC cuando se confirma la progresión radiológica, clínica o por PSA. El fenómeno "flare" aparece en el tratamiento con taxanos y abiraterona. En pacientes M0 no se recomienda tratamiento farmacológico actualmente, y el tratamiento en primera línea para los pacientes M1 incluiría principalmente enzalutamida/ abiraterona y/o docetaxel, según los síntomas. CONCLUSIÓN: Se proponen recomendaciones para personalizar la toma de decisiones ante cada paciente, el uso de técnicas de imagen y cómo abordar la progresión de la enfermedad para mejorar la calidad de vida de los pacientes

OBJECTIVES: To move towards a more standardized approach in clinical practice to manage patients with castration-resistant prostate cancer (CRPC) in Spain. METHODS: A panel of 18 Spanish experts in Urology with expertise managing CRPC followed a modified Delphi process with two rounds and a final face-to-face consensus meeting. The panel considered a total of 106 clinical questions divided into the following 6 sections: definition of CRPC, diagnosis of metastases by imaging techniques, symptoms of CRPC, progression of CRPC, M0 and M1 management and therapeutic sequencing. RESULTS: A bone scan (BS) is recommended at diagnosis, at the onset of bone pain, and depending on PSA levels, but it is not sensitive enough to confirm or exclude bone metastases if there is bone pain. Whole-body MRI and axial MRI are more sensitive than BS and plain X-rays, but more expensive, so they have to be used in certain situations. There is CRPC progression when there is radiologic, clinical or confirmed PSA progression. Flare phenomenon appears in treatment with taxanes and abiraterone. It was agreed that in M0 CRPC patients no drug treatment is currently recommended, although in M1 CRPC patients the first-line therapy would be mainly enzalutamide/abiraterone and/or docetaxel, depending on the symptom burden. CONCLUSION: After the consensus, we provide a series of recommendations for Spanish physicians treating CRPC to address the disease characteristics how to tailor patient management decisions, the use of imaging techniques, and how to handle disease progression appropriately to improve patients' quality of life

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.

[Usefulness of clinical nomograms and predictive models for pca. Predictive clinical factors of tumor agressiveness]. / Utilidad de los nomogramas clínicos y modelos predictivos del cáncer de próstata. Factores clínicos de predicción de agresividad tumoral.

In this narrative review we present the natural evolution of predictive models to their presentation in the nomogram format. We show their clinical usefulness and the objective parameters that contribute to their clinical use: calibration, discrimination, decision curves and probability density functions. We continue detailing the various existing predictive models/nomograms in relation to prostate cancer aggressiveness before and after biopsy, before and after primary treatment, recurrence and castration resistance. Finally we include future markers in advanced stage of implementation in the context of nomograms and related to the aggressiveness of prostate cancer: PCA3, PHI coefficient, 4Kscore, cell cycle progression (Prolaris®) and single nucleotid polymorphisms.

Utilidad de los nomogramas clínicos y modelos predictivos del CaP. Factores clínicos de predicción de agresividad tumoral / Usefulness of clinical nomograms and predictive models for pca. predictive clinical factors of tumor agressiveness

En la presente revisión narrativa hemos presentado la evolución natural de los modelos predictivos hacia su presentación en formato de nomogramas. A continuación hemos puesto de manifiesto su utilidad clínica y los parámetros objetivos que han de contribuir a su uso clínico: calibración, discriminación, curvas de decisión y funciones de densidad de probabilidad. Seguidamente se han detallado los diferentes modelos predictivos/nomogramas existentes en relación a la agresividad pre y post-biopsia, pre y post-tratamiento primario, a la recidiva y resistencia a la castración en cáncer de próstata. Finalmente se han incluido futuros marcadores en avanzado estado de implementación clínica en el contexto de nomogramas y relacionados con la agresividd del cáncer de próstata: PCA3, coeficiente PHI, 4Kscore, cell cicle progression (Prolaris®), y polimorfismos de un solo nucleótido (SNPs)

In this narrative review we present the natural evolution of predictive models to their presentation in the nomogram format. We show their clinical usefulness and the objective parameters that contribute to their clinical use: calibration, discrimination, decision curves and probability density functions. We continue detailing the various existing predictive models/nomograms in relation to prostate cancer aggressiveness before and after biopsy, before and after primary treatment, recurrence and castration resistance. Finally we include future markers in advanced stage of implementation in the context of nomograms and related to the aggressiveness of prostate cancer: PCA3, PHI coefficient, 4Kscore, cell cycle progression (Prolaris®) and single nucleotid polymorphisms

[Selection criteria and nomograms for active surveillance in prostate cáncer]. / Criterios de selección y nomogramas relacionados con la vigilancia activa en cancer de prostata.

In the present review we detail the more universally accepted selection criteria in the various protocols of active surveillance in prostate cancer; we also identify and classify twenty nomograms/predictive models useful for decision making in active surveillance for prostate cancer. These models are classified in accordance to their prediction (High grade prostate cancer in radical prostatectomy specimen [Gleason grade > 7], understaging on biopsy compared to prostatectomy specimen, pathological stage, indolent cancer or progression after expectant therapy). We also detail the predictive variables used in each model for estimations, their internal validation parameters, the samples used to generate them, and the external validations if they were done. Many of them are presented with their URL address, where they may be consulted on line, this making easier their implementation. Finally we expose our thoughts about the use of probability density functions as a useful tool for validation of these predictive models that help in the definition of cut points facilitating their clinical use and credibility.

Criterios de selección y nomogramas relacionados con la vigilacia activa en cáncer de próstata / Selection criteria and nomograms for active surveillance in prostate cancer

En la presente revisión narrativa se detallan los criterios de selección más universalmente aceptados en los diferentes protocolos de vigilancia activa en cáncer de próstata, así como se identifican y clasifican una veintena de nomogramas/modelos predictivos de utilidad para la toma de decisiones en vigilancia activa en cáncer de próstata. Estos modelos se clasifican de acuerdo a su predicción (cáncer de próstata de alto grado en la pieza de prostatectomía (Suma de Gleason > 7), infragradación en la biopsia respecto a la pieza de prostatectomía, estadio patológico, cáncer indolente, o evolución tras tratamiento expectante).A su vez se detallan las variables predictivas usadas por cada modelo en su estimación, sus parámetros de validación interna, las muestras sobre las que han sido generados, y sus validaciones externas si las ha habido. Muchos de ellos son presentados además con su dirección Url: donde pueden ser consultados on-line lo que facilita su implemetación. Finalmente se hace una reflexión acerca del uso de funciones de densidad de probabilidad como una herramienta útil en la validación de estos modelos predictivos que ayuda a la definición de puntos de corte y facilita su uso y credibilidad en la clínica

In the present review we detail the more universally accepted selection criteria in the various protocols of active surveillance in prostate cancer; we also identify and classify twenty nomograms/predictive models useful for decision making in active surveillance for prostate cancer. These models are classified in accordance to their prediction (High grade prostate cancer in radical prostatectomy specimen [Gleason grade > 7], understaging on biopsy compared to prostatectomy specimen, pathological stage, indolent cancer or progression after expectant therapy).We also detail the predictive variables used in each model for estimations, their internal validation parameters, the samples used to generate them, and the external validations if they were done. Many of them are presented with their URL address, where they may be consulted on line, this making easier their implementation. Finally we expose our thoughts about the use of probability density functions as a useful tool for validation of these predictive models that help in the definition of cut points facilitating their clinical use and credibility

Implementing the use of nomograms by choosing threshold points in predictive models: 2012 updated Partin Tables vs a European predictive nomogram for organ-confined disease in prostate cancer.

OBJECTIVES: To implement the use of nomograms in clinical practice showing how to choose thresholds in nomograms' predictions to select risk groups. To validate and compare the predictive ability and clinical utility of the Hospital Universitario 'Miguel Servet' (HUMS) and the updated Partin Tables 2012 (PT-2012) nomograms to predict organ-confined disease (OCD) after radical prostatectomy (RP). PATIENTS AND METHODS: Cohort of 1285 patients with prostate cancer treated with RP at Instituto Valenciano de Oncología (IVO) between 1986 and 2011. The predictive value of the nomograms was assessed by means of calibration curves, discrimination ability (area under the receiver operating characteristic (ROC) curve (AUC) and probability density functions). The clinical utility was evaluated through Vickers' decision curves and thresholds were chosen through probability density functions. RESULTS: The calibration curves showed a minimal underestimation in low probabilities (<20%), a minimal overestimation in high probabilities (>50%) in the HUMS nomogram and a regular minimal overestimation in the PT-2012. Their AUC of 0.7285 (95% confidence interval [CI] 0.7010-0.7559) and 0.7288 (95%CI 0.7013-0.7562) respectively, show an adequate discrimination ability for both predictive models in the IVO cohort. The decision curves show similar net benefits for both models. In this study we advocate for a threshold of 53% for the identification of OCD. CONCLUSIONS: The HUMS-nomogram and the PT-2012 predictions of OCD confirm their utility in a contemporary cohort of patients. Patients with a probability of OCD >53% should be classified as OCD, helping physicians to better counsel their patients. A selection of adequate thresholds, as presented in this paper, makes nomograms more accessible tools.

Genetic predisposition to early recurrence in clinically localized prostate cancer.

UNLABELLED: WHAT'S KNOWN ON THE SUBJECT? AND WHAT DOES THE STUDY ADD?: Currently available nomograms to predict preoperative risk of early biochemical recurrence (EBCR) after radical prostatectomy are solely based on classic clinicopathological variables. Despite providing useful predictions, these models are not perfect. Indeed, most researchers agree that nomograms can be improved by incorporating novel biomarkers. In the last few years, several single nucleotide polymorphisms (SNPs) have been associated with prostate cancer, but little is known about their impact on disease recurrence. We have identified four SNPs associated with EBCR. The addition of SNPs to classic nomograms resulted in a significant improvement in terms of discrimination and calibration. The new nomogram, which combines clinicopathological and genetic variables, will help to improve prediction of prostate cancer recurrence. OBJECTIVES: To evaluate genetic susceptibility to early biochemical recurrence (EBCR) after radical prostatectomy (RP), as a prognostic factor for early systemic dissemination. To build a preoperative nomogram to predict EBCR combining genetic and clinicopathological factors. PATIENTS AND METHODS: We evaluated 670 patients from six University Hospitals who underwent RP for clinically localized prostate cancer (PCa), and were followed-up for at least 5 years or until biochemical recurrence. EBCR was defined as a level prostate-specific antigen >0.4 ng/mL within 1 year of RP; preoperative variables studied were: age, prostate-specific antigen, clinical stage, biopsy Gleason score, and the genotype of 83 PCa-related single nucleotide polymorphisms (SNPs). Univariate allele association tests and multivariate logistic regression were used to generate predictive models for EBCR, with clinicopathological factors and adding SNPs. We internally validated the models by bootstrapping and compared their accuracy using the area under the curve (AUC), net reclassification improvement, integrated discrimination improvement, calibration plots and Vickers' decision curves. RESULTS: Four common SNPs at KLK3, KLK2, SULT1A1 and BGLAP genes were independently associated with EBCR. A significant increase in AUC was observed when SNPs were added to the model: AUC (95% confidence interval) 0.728 (0.674-0.784) vs 0.763 (0.708-0.817). Net reclassification improvement showed a significant increase in probability for events of 60.7% and a decrease for non-events of 63.5%. Integrated discrimination improvement and decision curves confirmed the superiority of the new model. CONCLUSIONS: Four SNPs associated with EBCR significantly improved the accuracy of clinicopathological factors. We present a nomogram for preoperative prediction of EBCR after RP.

Improved prediction of biochemical recurrence after radical prostatectomy by genetic polymorphisms.

PURPOSE: Single nucleotide polymorphisms are inherited genetic variations that can predispose or protect individuals against clinical events. We hypothesized that single nucleotide polymorphism profiling may improve the prediction of biochemical recurrence after radical prostatectomy. MATERIALS AND METHODS: We performed a retrospective, multi-institutional study of 703 patients treated with radical prostatectomy for clinically localized prostate cancer who had at least 5 years of followup after surgery. All patients were genotyped for 83 prostate cancer related single nucleotide polymorphisms using a low density oligonucleotide microarray. Baseline clinicopathological variables and single nucleotide polymorphisms were analyzed to predict biochemical recurrence within 5 years using stepwise logistic regression. Discrimination was measured by ROC curve AUC, specificity, sensitivity, predictive values, net reclassification improvement and integrated discrimination index. RESULTS: The overall biochemical recurrence rate was 35%. The model with the best fit combined 8 covariates, including the 5 clinicopathological variables prostate specific antigen, Gleason score, pathological stage, lymph node involvement and margin status, and 3 single nucleotide polymorphisms at the KLK2, SULT1A1 and TLR4 genes. Model predictive power was defined by 80% positive predictive value, 74% negative predictive value and an AUC of 0.78. The model based on clinicopathological variables plus single nucleotide polymorphisms showed significant improvement over the model without single nucleotide polymorphisms, as indicated by 23.3% net reclassification improvement (p = 0.003), integrated discrimination index (p <0.001) and likelihood ratio test (p <0.001). Internal validation proved model robustness (bootstrap corrected AUC 0.78, range 0.74 to 0.82). The calibration plot showed close agreement between biochemical recurrence observed and predicted probabilities. CONCLUSIONS: Predicting biochemical recurrence after radical prostatectomy based on clinicopathological data can be significantly improved by including patient genetic information.

Atypical small acinar proliferation: review of a series of 64 patients.

OBJECTIVE: To study the evolution of 64 patients initially diagnosed with ASAP (atypical small acinar proliferation). MATERIAL AND METHODS: Between 1998 and the end of 2003, 64 patients were diagnosed at our centre with ASAP. RESULTS: The mean age of the patients assessed was 69 years (SD 6.4 years), the median prostate-specific antigen (PSA) level was 7.1 ng/ml (range 2-39 ng/ml) and 25% of the patients had a suspicious rectal examination. These 64 patients were subjected to re-biopsy. At re-biopsy, we diagnosed 27 patients (42%) with prostate adenocarcinoma. We classified patients into two groups depending on whether they did (n=27) or did not (n=37) have tumours. There were no significant differences in median PSA level between the two groups. The rectal examination was suspicious in 14% of patients without tumours and in 39% with tumours. Radical prostatectomy was applied to 20/28 patients (71%) diagnosed with prostate cancer. In these 20 patients, the median tumour volume was 0.4 cm3 (range 0.1-3.2 cm3) and 44% of the tumours were significant. The 37 patients with an unsuspicious histology were subjected to follow-up for a median of 12 months (range 1-30 months). The median PSA level in these patients was 5.7 ng/ml (range 0.8-28 ng/ml). A third biopsy was performed in three of these patients in view of an elevated PSA level, and one result was positive. CONCLUSIONS: In our experience, a pathological result of ASAP is associated with a definitive diagnosis of prostate cancer in 42% of cases. Moreover, a significant cancer was found in 44% of patients subjected to radical prostatectomy. We therefore systematically perform repeat biopsies on all patients with a histological result of ASAP.

Malignant mesothelioma of the tunica vaginalis. Report of a case without risk factors and review of the literature.

Malignant mesothelioma of the tunica vaginalis testis is an aggressive tumour with local recurrence being distant metastases the main feature of the clinical course. Usually appears over the fourth decade, having a strong relationship with occupational exposure to asbestos and long lasting hydrocele. We introduce a case of a 78-year-old caucasian male who developed a malignant mesothelioma without personal history of hydrocele or exposure to asbestos. A revision of the current literature is performed to summarize the recent therapeutic options as well as new diagnostic tools.