Genitourinary tuberculosis (GT) includes 8-15% of extrapulmonary tuberculosis (TB), which is more frequent in men. Epididymides, seminal vesicles, prostate and testis are the most common sites of GT. Although testicular TB is uncommon, we report 2 patients with unilateral testicular TB. The main treatment of urogenital tuberculosis is anti-tuberculosis pharmacotherapy, sometimes combined with surgery.

No abstract

Kallikarein‐related peptidase 3 (KLK3) gene polymorphisms seem to play a role in susceptibility to prostate cancer (PC). The purpose of this study was to investigate the association between rs2735839 polymorphism of KLK3 gene and risk of PC in an Iranian population. In this case‐control study, rs2735839 was genotyped in 532 patients with PC and 602 controls with benign prostate hyperplasia (BPH) using polymerase chain reaction‐restriction fragment length polymorphism assay. The frequency of GG, AG, and AA genotypes of KLK3 polymorphism was 24.6% and 76.2%, 46.6% and 21.7%, and 28.8% and 2.1%, in patients with BPH and PC, respectively (P < 0.001). The frequency of G allele in patients with BPH and PC was 47.9% and 87%, respectively (odds ratio: 7.31; confidence interval: 5.88‐9.10; P < 0.001). Patients with AG and GG genotypes had a higher total serum level of prostate‐specific antigen (PSA) compared to those with AA genotype (P < 0.001). Patients with this polymorphism had higher risk of tumor with higher grade (P = 0.23), advanced stage (P = 0.11), perineural invasion (P = 0.07), and vascular invasion (P = 0.07) compared to those without it but this difference was not statistically significant. Based on our results, KLK3 gene polymorphism was associated with the risk of PC. Higher levels of PSA in the presence of KLK3 polymorphism in patients with PC indicated that rs2735839 polymorphism could be a risk factor for increased levels of PSA.

No abstract

A147patient population. Based on a representative population-based patient-cohort, the objective of this study was to develop a decision model that could reflect realworld practice and predict the costs throughout treatment pathway. Methods: All patients newly diagnosed with FL in the UK's population-based Haematological Malignancy Research Network (www.hmrn.org) between 2004 and 2011 were followed until 2014 (n= 741). The mapped treatment pathways, alongside cost information derived from the National Tariff 2013/14, were incorporated into a discrete event simulation in order to reflect the heterogeneity of clinical characteristics, such as stage, and treatment options. Results: The annual cost of treating FL across the UK (population ~ 64 million) was estimated to be around £17 million. The predicted mean cost per patient from diagnosis to death was £10,202. Based on the initial treatment decision average costs were; £17,054 for those treated with chemotherapy (46%), £4,651 for those treated with radiotherapy (12%), and £2,185 for those managed by "watch-and-wait" (42%). The model's predicted costs per patient captured 95% of the actual costs calculated from empirical data, supporting the validity of the model. ConClusions: This is the first modelling study using 'real world' evidence to predict costs of entire FL treatment pathways. As several expensive new technologies/treatments for FL are on the horizon, future application of the model developed here could be used to assess their economic impacts and support healthcare decision makers, especially in the era of personalised medicine.

No abstract

No abstract

No abstract