Objective: To compare the short-term and long-term outcomes of robotic rectectomy and laparoscopic rectectomy for rectal cancer based on propensity score matching. Methods: The clinical data of 106 patients who underwent robotic or laparoscopic radical resection of rectal cancer at Department of General Surgery, the First Affiliated Hospital of Nanchang University from January 2015 to December 2015 were retrospectively collected. Propensity score matching method was used to perform 1∶1 matching between robot and laparoscopic rectal cancer radical surgery. Thirty-two patients in robot group and 32 patients in laparoscopic group were successfully matched. There were 15 males and 17 females in the robotic group, aging (56.2±7.5) years, 19 males and 13 females in the laparoscopic group, aged (55.5±7.6) years. The clinical outcome of the two groups were compared using t-test or Mann-Whitney U test for continuous variables, repeated measures analysis of variance, χ² test, Fisher exact test or Wilcoxon rank sum test for dichotomous variables. The overall survival curve was drawn by Kaplan-Meier curve and the difference of survival curve was compared by Log-rank method. Results: The general data of the two groups of patients were comparable after matching. Sixty-four patients successfully completed robotic or laparoscopic operation without conversion to open surgery or perioperative death case. The total operative time, the lymph node namely No. 253 group dissection time, intraoperative blood loss, postoperative urethral catheter retention time, the serum C-reactive protein levels of 24 hours after surgery were (135.7±12.1) minutes, (11.6±2.7) minutes, (66.8±10.2) ml, 3.0(1.0) d,(50.9±7.7) μg/L, respectively, while in laparoscopic group were (124.9±23.2) minutes, (13.2±2.7) minutes, (74.8±13.9) ml, 4.0(2.0) d, (55.9±6.7) μg/L respectively. The differences were statistically significant (t=2.341, t=-2.354, t=-2.621, Z=-2.743, F=7.902, respectively, P<0.05). There were no statistical differences in separation time, numbers of retrieved lymph nodes, time to first flatus, postoperative hospital stay, postoperative complication and Clavien-Dindo classification of postoperative complications (t=0.336, t=0.714, t=-0.568, Z=-1.766, Fisher Z=-0.586, respectively, all P>0.05). Conclusions Robotic surgery not only has similar safety and feasibility but also has advantages of short-term outcomes compared with laparoscopic rectectomy for rectal cancer. The long-term outcomes were similar between two groups.

PURPOSE: Effective biomarkers and models are needed to improve the prognostic prospects of clear cell renal cell carcinoma (ccRCC). The purpose of this work was to identify DNA methylation biomarkers and to evaluate the utility of DNA methylation analysis for ccRCC prognosis. MATERIALS AND METHODS: An overview of genome-wide methylation of ccRCC tissues derived from The Cancer Genome Atlas (TCGA) database was download for analysis. DNA methylation signatures were identified using Cox regression methods. The potential clinical significance of methylation biomarkers acting as a novel prognostic markers was analyzed using the Kaplan-Meier method and receiver operating characteristic (ROC) curves. RESULTS: This study analyzed data for 215 patients with information on 23171 DNA methylation sites and identified a two-DNA methylation signature (cg18034859, cg24199834) with the help of a step-wise multivariable Cox regression model. The area under the curve of ROCs for the two-DNA methylation signature was 0.819. The study samples were stratified into low- and high-risk classifications based on an optimal threshold, and the two groups showed markedly different survival rates. Moreover, the two-DNA methylation marker was suitable for patients of varying ages, sex, stages (I and IV), and histologic grade (G2). CONCLUSION: The two-DNA methylation signature was deemed to be a potential novel prognostic biomarker of use in increasing the accuracy of predicting overall survival of ccRCC patients.
Biomarkers ; Carcinoma, Renal Cell ; Classification ; DNA Methylation ; Genome ; Humans ; Methods ; Methylation ; Prognosis ; ROC Curve ; Survival Rate