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.

External validation of the Codman score in colorectal surgery: a pragmatic tool to drive quality improvement

“…As shown in our study, the NSQIP model has an AUC of 0.72 and a Codman score of 0.68. Both of these are similar to previous morbidity prediction tools studied in colorectal cancer populations, including the CR-POSSUM (AUC = 0.716), the SURPAS (AUC = 0.66) and the Surgical Apgar Score and American Society of Anesthesiologists physical status classification (AUC = 0.6-0.77) [16,17]. The advantage of the Codman score compared to these alternative models is the relative ease of data collection.…”

Morbimortality assessment in abdominal surgery: are we predicting or overreacting?

“…The P-POSSUM scale was created in order to correct the elevated mortality risk obtained by POSSUM [3]; some studies showed an increased accuracy of P-POS-SUM over POSSUM in mortality prediction, with near results with the observed mortality [9][10][11][12]16]. Given that P-POSSUM has to be correlated to the general condition of the local population for it to be effective [9][10][11][12][13], variability of results obtained is explained by lack of adjustments to population baseline characteristics that generate changes in predicted values. Among these characteristics are malnutrition and economic status; nevertheless literature, as our study, reports P-POSSUM scale has an increased accuracy to predict mortality compared with POSSUM in emergency surgery [12].…”

“…In terms of mortality, both Raut et al and Mohammed et al proved the accuracy of POSSUM and P-POSSUM scores in predicting mortality risk, with more than 80% of accuracy in selected patients [ 9 , 10 ]. Additionally, Prabakaran et al found that selected colorectal surgery patients have an increased prediction force, for that reason a subclass of POSSUM (CR-POSSUM) has been described in these populations [ 11 ]. Nevertheless, it has been described that score results shouldn’t be generalized to all patients that underwent surgical procedures and have to be personalized and analyzed according to each population [ 12 ].…”