학술논문

A new dimensional-reducing variable obtained from original inflammatory scores is highly associated to morbidity after curative surgery for colorectal cancer
Original Article
Document Type
Clinical report
Source
International Journal of Colorectal Disease. September 2018, Vol. 33 Issue 9, p1225, 10 p.
Subject
Medical research
Morbidity
Colorectal cancer
Medicine, Experimental
Language
English
ISSN
0179-1958
Abstract
Author(s): Martin Bailon-Cuadrado [sup.1], Baltasar Perez-Saborido [sup.1], Javier Sanchez-Gonzalez [sup.1], Mario Rodriguez-Lopez [sup.1], Agustin Mayo-Iscar [sup.2], David Pacheco-Sanchez [sup.1] Author Affiliations: (1) 0000 0001 1842 3755, grid.411280.e, General and Digestive [...]
Purpose Several scores have been developed to define the inflammatory status of oncological patients. We suspect they share iterative information. Our hypothesis is that we may summarise their information into one or two new variables which will be independent. This will help us to predict, more accurately, which patients are at an increased risk of suffering postoperative complications after curative surgery for CRC. Methods Observational prospective study with those patients undergoing curative surgery for CRC between September 2015 and February 2017. We analysed the influence of inflammatory scores (PNI, GPS, NLR, PLR) on postoperative morbidity (overall and severe complications, anastomotic leakage and reoperation). Results Finally, 168 patients were analysed. We checked these four original scores are interrelated among them. Using a complex and innovative statistical method, we created two new independent variables (resultant A and resultant B) which resume the information coming from them. One of these two new variables (resultant A) was statistically associated to overall complications (OR, 2.239; 95% CI, 1.541-3.253; p = 0.0001), severe complications (OR, 1.773; 95% CI, 1.129-2.785; p = 0.013), anastomotic leakage (OR, 3.208; 95% CI, 1.416-7.268; p = 0.005) and reoperation (OR, 2.349; 95% CI, 1.281-4.305; p = 0.006). Conclusions We evinced the four original scores we used share redundant information. We created two new independent new variables which resume their information. In our sample of patients, one of these variables turned out to be a great predictive factor for the four complications we analysed.