Serum 17β-estradiol fails as a marker in identification of aggressive tumour disease in patients with localized prostate cancer
World journal of urology(2015)
摘要
Background There is evidence that obesity is associated with an aggressive prostate cancer (PC). Furthermore, preclinical studies suggest that oestrogens may play a pivotal role in this context. The biological processes underlying these observations are not fully understood. We prospectively evaluated whether obesity and/or preoperative estradiol levels are associated with high-grade cancer in patients with clinically localized PC at the time they underwent radical retropubic prostatectomy (RRP). Methods Preoperative sex hormone serum 17β-estradiol (E 2 ) as well as body mass index (BMI) and waist circumference (WC) were assessed in a cohort of 746 consecutive men treated with RP from February 2011 to October 2014. The data were correlated with patient-specific and clinicopathologic variables. Results A total of 746 patients underwent RRP. Median age was 68.0 years. Median E2 serum level was 18.3 ng/l (IQR 12.9–24.2 ng/l). Median BMI was 26.6 kg/m 2 (IQR 24.6–29.1 kg/m 2 ), and the median WC was 103 cm (IQR 96–110 cm). Serum E2 below or above the normal range was not found more frequently in obese patients (high BMI: p = 0.62; large WC: p = 0.83). E2 was not associated with BMI in our cohort of patients ( r = 0.07, p = 0.10) or WC ( r = 0.07, p = 0.10). There was no association between preoperative serum E2 levels and tumour stage ( p = 0.86, Fisher’s exact), tumour grade ( p = 0.37), lymph node involvement ( p = 0.59) or Gleason score ( p = 0.44). However, obesity correlated with tumour stage and grade ( p = 0.036, Fisher’s exact) and nodal metastasis ( p = 0.039, Fishers’ exact). Conclusion Pretreatment serum 17β-estradiol (E 2 ) cannot be considered as a suitable marker for aggressive tumour disease in patients with localized prostate cancer.
更多查看译文
关键词
Estradiol,Sex hormone,Testosterone,Prostatectomy,Prostate cancer,Stage,Grade,High-grade prostate cancer
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要