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Preoperative HALP, SII, and LMR scores predict disease-free survival in stage III colon cancer patients.

Preoperative HALP, SII, and LMR scores predict disease-free survival in stage III colon cancer patie…
Photo by Melinda Gimpel / Unsplash
Key Takeaway
Consider preoperative HALP and LMR scores for risk stratification in stage III colon cancer, noting the retrospective design.

This retrospective cohort study analyzed preoperative HALP, SII, and LMR scores in a population comprising 210 patients with stage III colon cancer who underwent curative resection and 220 patients with benign colonic lesions. The primary outcome was disease-free survival (DFS), with secondary outcomes assessing diagnostic performance for malignancy. The study design was retrospective, and follow-up duration was not reported.

For diagnostic performance, HALP showed an AUC of 0.773, SII showed an AUC of 0.758, and LMR showed an AUC of 0.739. All three markers demonstrated moderate discrimination for malignancy. Absolute numbers for these performance metrics were not reported, and p-values or confidence intervals were not reported for the diagnostic outcomes.

Regarding DFS, HALP was an independent predictor with a hazard ratio of 0.384 (95% CI: 0.225–0.655). LMR was also an independent predictor with a hazard ratio of 0.483 (95% CI: 0.286–0.815). Tumor stage was a risk factor with a hazard ratio of 2.435 (95% CI: 1.432–4.140). Chemotherapy cycles were protective with a hazard ratio of 0.380 (95% CI: 0.223–0.647). A nomogram built on these variables showed good discrimination with a C-index of 0.759 in the training set and 0.743 in the validation set.

Safety data, including adverse events and tolerability, were not reported. The study limitations include its retrospective design, which prevents distinguishing association from causation. Additionally, surrogate versus clinical outcomes were not distinguished. These scores may enable individualized recurrence risk estimation and inform postoperative risk-adapted management.

Study Details

Study typeCohort
EvidenceLevel 3
PublishedApr 2026
View Original Abstract ↓
BackgroundColorectal 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.MethodsThis 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.ResultsHALP, 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.ConclusionPreoperative 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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