CR-Possum-Can It Be Used to Predict Morbidity? A Single-Centre Retrospective Study

Abstract

Preoperative prediction of morbidity in colorectal cancer (CRC) surgery helps to optimize the surgical outcome. In this study, we aim to develop a dedicated equation for predicting operative morbidity using colorectal possum scoring system and also to validate the predictive accuracy of CR-POSSUM scoring system in prognosticating actual complications. We did a retrospective analysis of 322 patients undergoing colorectal cancer surgery from a single centre in South India from 2004 to 2016. Mortality and morbidity risk factors as defined by CR POSSUM were collected from 322 patients who underwent CRC surgery and were used to derive equations to predict morbidity, and the results were compared with the observed morbidity. Logistic regression analysis was used to derive the equation. The model fit and model discrimination were analysed using the Hosmer-Lemeshow statistical test for goodness of fit, the Nagelkerke R ² and area under the receiver operating characteristic (ROC) curve respectively. Out of 322 patients, 103 (32%) patients developed complications and 10 (3%) died due to complications. The regression equation we derived has an overall correct classification of about 70% (P < 0.01) with positive and negative predictive value of 60% and 73% respectively. The Hosmer-Lemeshow goodness of fit was 3.147 (P = 0.829), and the Nagelkerke R ² was 17% and area under ROC as model discrimination was 71.6%. Hence, CR-POSSUM scoring which was originally used for predicting mortality risk can also be extrapolated to predict morbidity.

Keywords: Colorectal POSSUM; Colorectal surgery; Morbidity and mortality; POSSUM; Prediction model; SSI.

Fig. 1

Duration of hospital stay in patients with and without complications

Fig. 2

Receiver operator characteristic curve (ROC) for the derived equation (Area under the curve is 71.6%)