The Revised ACPGBI Model is a Simple and Accurate Predictor of Operative Mortality After Potentially Curative Resection of Colorectal Cancer
The Association of Coloproctology of Great Britain and Ireland (ACPGBI) risk-adjustment model for colorectal cancer surgery has been recently revised. The aim of the present study was to compare the performance of the revised ACPGBI model, the original ACPGBI model, P-POSSUM, and CR-POSSUM, in the prediction of operative mortality after resection of colorectal cancer.
A total of 423 patients who underwent potentially curative resection of colorectal cancer at a single institution (1997–2007) were included. Data used in the construction of the ACPGBI model was collected prospectively. The models were compared by examining observed to expected (O:E) ratios, the Hosmer-Lemeshow (H-L) goodness-of-fit test, and area under the receiver operator characteristic curve (AUC) analysis.
The 30-day mortality rate was 4%. The performance of the models was as follows: revised ACPGBI model (O:E ratio = 1.05, AUC = 0.73, H-L = 11.02), original ACPGBI model (O:E ratio = 0.58, AUC = 0.76, H-L = 14.23), P-POSSUM (O:E ratio = 0.87, AUC = 0.79, H-L = 10.63), and CR-POSSUM (O:E ratio = 0.63, AUC = 0.84, H-L = 15.84). In subgroup analysis, the revised ACPGBI model performed well in both elective cases (O:E ratio = 1.06) and emergency cases (O:E ratio = 0.91).
The revised ACPGBI model is simple to construct and accurately predicts operative mortality after potentially curative resection of colorectal cancer.
KeywordsColorectal Cancer Curative Resection Operative Mortality Laparoscopic Resection Colorectal Cancer Resection
Conflict of interest
- 1.Cancer Research UK. http://www.cancerresearchuk.org. Accessed September 2010.
- 11.Ren L, Upadhyay AM, Wang L, Li L, Lu J, Fu W. Mortality rate prediction by physiological and operative severity score for the enumeration of mortality and morbidity (POSSUM), Portsmouth POSSUM and colorectal POSSUM and the development of new scoring systems in Chinese colorectal cancer patients. Am J Surg. 2009;198:31–8.PubMedCrossRefGoogle Scholar
- 14.Risk prediction in surgery. http://www.riskprediction.org.uk. Accessed September 2010.