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Updated: Jun 4, 2025

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Applicability of the Scottish screen-detected polyp cancer study (SSPoCS) algorithm in a multicentric cohort in the
André Ruge Gonçalves1, Maria Azevedo Silva1, Cristiana Sequeira2
1Gastroenterology Department, Centro Hospitalar de Leiria, Leiria, Portugal.
Background/Objectives:
Robust evidence regarding the management after endoscopic resection of malignant colorectal polyps (MCP) is lacking. Inconsistencies in reporting on potential prognostic factors hinder the decision process. To address these issues, the Scottish Screen-detected Polyp Cancer Study (SSPoCS) introduced an algorithm based in two easily obtainable variables: resection margin and lymphovascular invasion. This study aims to assess the applicability of the SSPoCS algorithm in a Portuguese multicentric cohort.
Methods:
Endoscopically resected MCP in five centers were included. The main outcome was residual/recurrent malignancy (RRM), defined as any of the following: (1) residual intramural or lymph node malignancy in the surgical specimen after completion surgery; (2) local or systemic recurrent disease in conservatively managed patients.
Results:
Two-hundred and eleven patients were included (mean age: 68.6 ± 10.4 years; male participants: 65.4%); 121 underwent completion surgery while 90 remained in surveillance. Thirty-two patients (15.2%) experienced RRM: 27 displayed residual malignancy in the surgical specimen and five developed recurrent disease. According to the SSPoCS algorithm: 120 patients were classified as having low-risk of residual disease, six of whom displayed RRM (5.0%); 10 as medium-risk, with one having RRM (10.0%); and 81 as high-risk, 25 of whom experienced RRM (30.9%). Lesions classified as low risk showed a negative predictive value (NPV) of 95.0% to exclude RRM. The algorithm demonstrated good accuracy in predicting RRM in a Receiver Operating Characteristic curve analysis (AUC: 0.74; 95% CI: 0.65-0.83; p < 0.001).
Conclusions:
The SSPoCS algorithm revealed good accuracy in predicting residual/recurrent malignancy with a NPV of 95.0% to exclude RRM in low-risk lesions.

