What question did this study set out to answer?

This study aims to evaluate the prognostic value of HALP and LMR in predicting disease-free survival in stage III colon cancer patients.

May 4, 2026Frontiers in Oncology2 citationsOpen Access

Preoperative HALP and LMR predict disease-free survival in stage III colon cancer and enable nomogram-based risk stratification

JXJiayan Xu FQFei Qu XWXiaoyu Wang

Key Points

This study aims to evaluate the prognostic value of HALP and LMR in predicting disease-free survival in stage III colon cancer patients.
Retrospective analysis of 210 patients with stage III colon cancer and 220 with benign colonic lesions.
Patients were randomly assigned to training (70%) and validation (30%) cohorts.
Cox regression identified independent predictors, and a nomogram was developed and validated.
HALP and LMR were significant predictors of disease-free survival (HR = 0.384, 95% CI: 0.225–0.655 for HALP; HR = 0.483, 95% CI: 0.286–0.815 for LMR).
The nomogram achieved a C-index of 0.759 in the training set and 0.743 in the validation set for predicting DFS.
Tumor stage and chemotherapy cycles also identified as independent risk factors for DFS.

Abstract

Background Colorectal cancer remains a major cause of cancer-related mortality worldwide. Despite curative resection and standard adjuvant chemotherapy, patients with stage III colon cancer remain at considerable risk of recurrence, with marked survival heterogeneity within the same pathological stage. Systemic inflammatory and immunonutritional biomarkers, including the hemoglobin–albumin–lymphocyte–platelet (HALP) score, systemic immune-inflammation index (SII), and lymphocyte-to-monocyte ratio (LMR), may reflect host–tumor interactions. However, their combined diagnostic and prognostic value in stage III colon cancer patients have not been fully established. Methods This retrospective study included 210 patients with stage III colon cancer who underwent curative resection and 220 comparable patients with benign colonic lesions. Diagnostic performance was assessed using receiver operating characteristic analysis and logistic regression. Patients with stage III disease were randomly assigned to training and validation cohorts (7:3). Independent predictors of disease-free survival (DFS) were identified using Cox regression, and a nomogram was constructed and internally validated using the concordance index (C-index), time-dependent ROC analysis, calibration curves, and decision curve analysis. Results HALP, SII, and LMR showed moderate discrimination for malignancy, with AUC of 0.773, 0.758, and 0.739, respectively. Multivariable analysis identified HALP (HR = 0.384, 95% CI: 0.225–0.655), LMR (HR = 0.483, 95% CI: 0.286–0.815), tumor stage (HR = 2.435, 95% CI: 1.432–4.140), and chemotherapy cycles (HR = 0.380, 95% CI: 0.223–0.647) as independent predictors of DFS. The nomogram demonstrated good discrimination (C-index 0.759 and 0.743 in the training and validation set) with satisfactory calibration and clinical net benefit. Conclusion Preoperative HALP and LMR independently predict DFS in stage III colon cancer. A nomogram integrating inflammatory biomarkers with clinicopathological variables enables individualized recurrence risk estimation and may inform postoperative risk-adapted management.

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