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.

[De Novo renal mass on kidney grafts.] / Tumores de novo en trasplante renal.

OBJECTIVE: Cancer is the 3rd cause of death in the Spanish kidney transplant population. The risk of developing a tumour is multifactorial. Improvements in follow-up and increased graft survival have led to an increase in the incidence of de novo tumours in these patients. MATERIAL AND METHODS: We have conducted a systematic review of articles published in online medical databases related to de novo tumours in kidney transplant recipients. We have evaluated the incidence of de novo neoplasms in patients who under went a kidney transplant at the Hospital Universitario de Cruces from January 2011 to December 2018. RESULTS AND DISCUSSION: Different characteristics have been described within the transplanted population that could promote the development of tumours. The alteration of the antitumor response, the altered ability to respond to infections, drug´s carcinogenic effect, and agreater susceptibility ultraviolet rays damage are some of the most repeated. As a consequence, overall risk of cancer increases two to three times in the transplanted population. Overall, in our analysis, the neoplasms that showed the highest incidence were urological (21.98%), followed by haematological (16.63%) and digestive tract (14.58%). CONCLUSION: There is a higher incidence and risk of de novo tumour development in the kidney transplant population, which probably requires optimizing patient follow-up and developing more precise screening strategies that can be modified depending on geographic and individual variations, to reduce the impact on survival that it may have on our patients.

OBJETIVO: Las neoplasias son la 3ª causa de muerte en la población trasplantada renal en España. El riesgo de desarrollar una neoplasia es multifactorial. Con las mejoras en el seguimiento y el aumento de la supervivencia del injerto, se está produciendo un incremento en la incidencia de neoplasias de novo en estos pacientes.MATERIAL Y MÉTODOS: Análisis bibliográfico de las neoplasias de novo en pacientes trasplantados renales mediante la revisión sistemática de artículos publicados en bases de datos médicas online. Recogida y evaluación de la incidencia de neoplasias de novo en pacientesa los que se les realizó un trasplante de riñón en el Hospital Universitario de Cruces desde enero de 2011 hasta diciembre 2018.RESULTADOS Y DISCUSIÓN: Dentro de la población trasplantada se han descrito diferentes vías que podrían promover la aparición de neoplasias. Unas de las hipótesis más repetidas son la alteración de la respuesta antitumoral, la capacidad alterada para contrarrestar infecciones, características cancerígenas de los medicamentos en sí y una mayor susceptibilidad a los efectos dañinos de los rayos ultravioleta. La influencia de todos estos factores se traduce en un incremento de dos a tres veces en la incidencia de neoplasias en esta población. De forma global, en todos los estudios analizados, las neoplasias que mostraron mayor incidencia fueron las urológicas (21,98%), seguidas de las hematológicas (16,63%) y del tracto digestivo (14,58%).CONCLUSIÓN: Se evidencia una mayor incidencia de tumores de novo en la población trasplantada renal, que probablemente requiera una optimización en el seguimiento de los pacientes, desarrollando estrategias de screening más precisas que puedan modificarse en función de las variaciones geográficas e individuales, para disminuir el impacto en la supervivencia que puedan tener estas neoplasias de novo.

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.

[Substitution urethroplasty. Long term follow up results in a group of 50 patients]. / Uretroplastia de sustitución. Resultados del seguimiento a largo plazo en un grupo de 50 pacientes.

OBJECTIVES: To assess the results of substitution urethroplasty after a long follow-up in a group of 50 patients. METHODS: We conducted a retrospective study of patients with diagnosis of urethral stricture treated by augmentation techniques in the period 1999-2009. We included patients with penile and bulbar urethral stricture and, penile skin or oral mucosa as substitute tissue type. Urethral strictures of the meatus or fossa navicularis and posterior urethra, and other endoscopic or surgical procedures were excluded from the study. RESULTS: Fifty patients were included. Penile skin was used in 26 cases and buccal mucosa in 24. The average follow-up was 108 months. Recurrence rate was 25% in the cases in which oral mucosa was used as substitute tissue and 30.7% in the penile skin group. Of the 14 cases with recurrence of the stricture, 13 (92%) did so in the first five years of follow-up. Only one case was a recurrent stricture after six years of surgery. CONCLUSIONS: The recurrence of the stricture after augmentation urethroplasty occurs, in the majority of cases, in the first five years. After this period of time recurrence is very rare. Oral mucosa showed better results as substitute tissue in the urethral stricture surgery.