Published in:
Open Access
01-12-2016 | Research article
The impact of gender difference on operative time in laparoscopic partial nephrectomy for T1 renal tumor and the utility of retroperitoneal fat thickness as a predictor of operative time
Authors:
Hiroki Ito, Kazuhide Makiyama, Takashi Kawahara, Kimito Osaka, Koji Izumi, Yumiko Yokomizo, Noboru Nakaigawa, Masahiro Yao
Published in:
BMC Cancer
|
Issue 1/2016
Login to get access
Abstract
Background
To investigate the impact of biological gender on operative parameters, especially operative time, in laparoscopic partial nephrectomy (LPN) for T1 renal tumor.
Methods
One hundred and eleven (28 female and 83 male) patients and 64 (20 female and 44 male) patients with renal tumors suspected to be RCC cT1aN0M0 who underwent retroperitoneal and transperitoneal LPN, respectively, were analyzed. The influence of sex on operative factors including retroperitoneal fat tissue thickness, determined on CT, was analyzed. The correlation between operative time and gender was evaluated by unpaired t-test and linear logistic regression model.
Results
In both retroperitoneal and transperitoneal LPN, the retroperitoneal fat tissue thickness was greater in men than in women. In retroperitoneal LPN, the operative time was significantly longer in men than in women. In contrast, in transperitoneal LPN, no gender difference was observed in regard to the operative time. In retroperitoneal LPN, linear logistic regression assessment showed that gender, retroperitoneal fat tissue thickness, and tumor size were significantly associated with operative time. Coefficient of determination of the prediction model was 0.317.
Conclusions
The operative time of retroperitoneal LPN is significantly correlated with gender, maximum tumor diameter, and retroperitoneal fat tissue thickness. We have developed a prediction model for the operative time of retroperitoneal LPN based on preoperative parameters. Interestingly, in transperitoneal LPN, a gender difference in operative time was not apparent, and also predicting operative time might be difficult.