Background: Postoperative early recurrence (PER) remains a major challenge to long-term survival after successful conversion therapy and curative resection for initially unresectable colorectal liver metastases (CRLM). Existing prediction models rely heavily on clinicopathological parameters and lack molecular biomarkers, limiting their predictive accuracy. Objectives: To define the optimal recurrence-free survival (RFS) cutoff for PER and develop a comprehensive predictive nomogram incorporating molecular and clinical variables to predict PER in patients with initially unresectable CRLM who undergo curative resection following conversion therapy. Design: Retrospective cohort study. Methods: Clinicopathological and molecular data from 411 patients with initially unresectable CRLM undergoing curative resection after conversion therapy were analyzed. The minimum p value approach determined the optimal RFS cutoff for PER. Least absolute shrinkage and selection operator regression identified significant predictors, followed by multivariate logistic regression to build a nomogram. Model performance was assessed using the area under the curve (AUC), calibration curves, and decision curve analysis (DCA). Results: PER was defined as recurrence within 4 months postoperatively. Independent predictors included dual preoperative positivity for CEA and CA19-9 (odds ratio (OR) = 2.437, p 0.05), and DCA indicated clinical benefit at recurrence risk thresholds above 30%. Conclusion: We identified 4 months as the optimal RFS threshold for PER and proposed a novel nomogram integrating molecular and clinical factors for perioperative decision-making in patients with initially unresectable CRLM.
Lu et al. (Thu,) studied this question.
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