Prognostic Significance of Perineural Invasion in Patients with Rectal Cancer using R Environment for Statistical Computing and Graphics
Keywords:Rectal cancer, Prognostic factors, Perineural invasion, R environment for statistical computing and graphics
Purpose: In recent studies perineural invasion (PNI) is associated with poor survival rates in rectal cancer, but the impact of PNI it’s still controversial. We assessed PNI as a potential prognostic factor in rectal cancer. Patients and Methods: We analyzed 317 patients with rectal cancer resected at The Oncology Institute”Prof. Dr. Ion Chiricuţă” Cluj-Napoca, between January 2000 and December 2008. Tumors were reviewed for PNI by a pathologist. Patients data were reviewed and entered into a comprehensive database. The statistical analysis in our study was carried out in R environment for statistical computing and graphics, version 1.15.1. Overall and disease-free survivals were determined using the Kaplan-Meier method, and multivariate analysis using the Cox multiple hazards model. Results were compared using the log-rank test. Results: In our study PNI was identified in 19% of tumors. The 5-year disease-free survival rate was higher for patients with PNI-negative tumors versus those with PNI-positive tumors (57.31% vs. 36.99%, p=0.009). The 5-year overall survival rate was 59.15% for PNI-negative tumors versus 39.19% for PNI-positive tumors (p=0.014). On multivariate analysis, PNI was an independent prognostic factor for overall survival (Hazard Ratio = 0.6; 95% CI = 0.41 to 0.87; p = 0.0082). Conclusions: PNI can be considered an independent prognostic factor of outcomes in patients with rectal cancer. PNI should be taken into account when selecting patients for adjuvant treatment. R environment for statistical computing and graphics is complex yet easy to use software that has proven to be efficient in our clinical study.
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