A systematic review of POSSUM and its related models as predictors of post-operative mortality and morbidity in patients undergoing surgery for colorectal cancer.
BACKGROUND
The Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity (POSSUM) model and its Portsmouth (P-POSSUM) and colorectal (CR-POSSUM) modifications are used extensively to predict and audit post-operative mortality and morbidity. This aim of this systematic review was to assess the predictive value of the POSSUM models in colorectal cancer surgery.


METHODS
Major electronic databases, including Medline, Embase, Cochrane Library and Pubmed were searched for original studies published between 1991 and 2010. Two independent reviewers assessed each study against inclusion and exclusion criteria. All data was specific to colorectal cancer surgery. Predictive value was assessed by calculating observed to expected (O/E) ratios.


RESULTS
Nineteen studies were included in final review. The mortality analysis included ten studies (4,799 patients) on POSSUM, 17 studies (6,576 patients) on P-POSSUM and 14 studies (5,230 patients) on CR-POSSUM. Weighted O/E ratios for mortality were 0.31 (CI 0.31-0.32) for POSSUM, 0.90 (CI 0.88-0.92) for P-POSSUM and 0.64 (CI 0.63-0.65) for CR-POSSUM. The morbidity analysis included four studies (768 patients) on POSSUM with a weighted O/E ratio of 0.96 (CI 0.94-0.98).


CONCLUSIONS
P-POSSUM was the most accurate model for predicting post-operative mortality after colorectal cancer surgery. The original POSSUM model was accurate in predicting post-operative complications.
Richards
Colin Hewitt
CH
University Department of Surgery, Faculty of Medicine-University of Glasgow, Royal Infirmary, Glasgow G4 0SF, UK. colinrichards@nhs.net
Leitch
Fiona E
FE
Horgan
Paul G
PG
McMillan
Donald C
DC
D003082:Colectomy / Q000401:mortality / Q000706:statistics & numerical data*; D015179:Colorectal Neoplasms / Q000601:surgery*; D013505:Digestive System Surgical Procedures / Q000401:mortality / Q000706:statistics & numerical data; D006305:Health Status Indicators; D006801:Humans; D008962:Models, Theoretical; D009017:Morbidity; D011237:Predictive Value of Tests; D012004:Rectal Neoplasms / Q000601:surgery
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