International validation of a risk prediction algorithm for patients with malignant colorectal polyps.

Aim: The optimal management strategy for patients with endoscopically resected malignant colorectal polyps (MCP) has yet to be defined. The aim of this study was to validate a published decision‐making tool, termed the Scottish Polyp Cancer Study (SPOCS) algorithm, on a large international population. Methods: The SPOCS algorithm allocates patients to risk groups based on just two variables: the polyp resection margin and the presence of lymphovascular invasion (LVI). The risk groups are termed low (clear margin, LVI absent), medium (clear margin, LVI present) or high (involved/non‐assessable margin). The International Polyp Cancer Collaborative was formed to validate the algorithm on data from Australia, Denmark, UK and New Zealand. Results: In total, 1423 patients were included in the final dataset. 680/1423 (47.8%) underwent surgical resection and 108/680 (15.9%) had residual disease (luminal disease 8.8%, lymph node metastases 8.8%). The SPOCS algorithm classified 602 patients as low risk (in which 1.5% had residual disease), 198 patients as medium risk (in which 7.1% had residual disease) and 484 as high risk (in which 14.5% had residual disease) (P < 0.001, χ2 test). Receiver operating characteristic curve analysis demonstrated good accuracy of the algorithm in predicting residual disease (area under the curve 0.732, 95% CI 0.687–0.778, P < 0.001). When patients were designated as low risk, the negative predictive value was 98.5%. Conclusion: The SPOCS algorithm can be used to predict the risk of residual disease in patients with endoscopically resected MCPs. Surgery can be safely avoided in patients who have a clear margin of excision and no evidence of LVI. This study, a collaboration between Scotland, Australia, New Zealand and Denmark aimed to define the optimal management strategy for patients with malignant colorectal polyps. The results confirmed the SPOCS algorithm (margin & LVI) can be used to accurately predict the risk of residual disease. [ABSTRACT FROM AUTHOR]