Why the study?
The Surgical Outcome Risk Tool (SORT) had not been validated for predicting mortality in patients undergoing surgery for colorectal cancer.
Does the Surgical Outcome Risk Tool (SORT) accurately predict 30-day mortality compared to traditional risk models in patients undergoing surgery for colorectal cancer?
Does the Surgical Outcome Risk Tool (SORT) accurately predict 30-day mortality compared to traditional risk models in patients undergoing surgery for colorectal cancer?
The Surgical Outcome Risk Tool (SORT) is an accurate and easily adopted risk-assessment tool for predicting 30-day mortality in patients undergoing surgery for colorectal cancer.
SORT supports perioperative mortality prediction in colorectal cancer surgery; leaves open broader adoption pending prospective validation.
BACKGROUND: The accurate evaluation of perioperative risk is crucial to facilitate the shared decision-making process. Surgical outcome risk tool (SORT) has been developed to provide enhanced and more feasible identification of high-risk surgical patients. Nonetheless, SORT has not been validated for patients with colorectal cancer undergoing surgery. Our aim was to determine whether SORT can accurately predict mortality after surgery for colorectal cancer and to compare it with traditional risk models. METHOD: 526 patients undergoing surgery performed by a colorectal surgical team in a single Greek tertiary hospital (2011-2019) were included. Five risk models were evaluated: (1) SORT, (2) Physiology and Operative Severity Score for the enumeration of Mortality and Morbidity (POSSUM), (3) Portsmouth POSSUM (P-POSSUM), (4) Colorectal POSSUM (CR-POSSUM), and (5) the Association of Great Britain and Ireland (ACPGBI) score. Model accuracy was assessed by observed to expected (O:E) ratios, and area under Receiver Operating Characteristic curve (AUC). RESULTS: Ten patients (1.9%) died within 30 days of surgery. SORT was associated with an excellent level of discrimination [AUC:0.81 (95% CI:0.68-0.94); p = 0.001] and provided the best performing calibration of all models in the entire dataset analysis (H-L:2.82; p = 0.83). Nonetheless, SORT underestimated mortality. SORT model demonstrated excellent discrimination and calibration predicting perioperative mortality in patients undergoing (1) open surgery, (2) emergency/acute surgery, and (3) in cases with colon-located cancer. CONCLUSION: SORT is an easily adopted risk-assessment tool, associated with enhanced accuracy, that could be implemented in the perioperative pathway of patients undergoing surgery for colorectal cancer.
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Magouliotis et al. (2021) studied this question.
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