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BACKGROUND: Colorectal cancer (CRC) remains a significant global health burden, ranked among the most common causes of cancer-related fatalities. While insulin resistance (IR) biomarkers have been associated with CRC prognosis, their role in predicting metastasis remains unclear. Metastasis remains a critical determinant of prognosis and treatment planning in CRC. Identifying precise biomarkers can improve CRC management. This study evaluates the prognostic efficacy of lipid-based IR biomarkers in predicting metastasis in treatment-naïve CRC patients and selects the most appropriate one. We also explore their association with clinicopathological characteristics. METHOD: Eighty-seven CRC patients (metastatic, n = 24; non-metastatic, n = 63) from four tertiary hospitals in India were analysed. Clinical data included TNM staging, ECOG-PS, KPS, CEA, and lipid profiles. Statistical tests included Fisher’s exact test, Mann-Whitney U-test, ROC curve analysis, Spearman’s correlation, multiple linear regression, and binary logistic regression. RESULTS: Statistically significant differences were observed in job status, diet, smoking, alcohol use, diabetes, BMI, and IR markers between metastatic and non-metastatic CRC patients. Among the IR biomarkers, the ratio of LDL to HDL (LHR) demonstrated the highest diagnostic accuracy with an AUC of 0.867 (p < 0.05, CI: 0.79–0.94), a sensitivity of 83.3%, and a specificity of 74.6%. Spearman correlation analysis unveiled a moderate-positive relationship between IR biomarkers and carcinoembryonic antigen (CEA) levels, except for the triglyceride glucose index (TyG). Binary logistic regression identified LHR as the sole significant predictor of metastasis, with a one-unit increase in LHR corresponding to a 19.35% higher likelihood of metastasis. Multiple linear regression confirmed a moderate, significant combined effect of TNM staging, ECOG-PS, KPS, and LHR. CONCLUSION: LHR strongly predicts metastasis in CRC patients, with high sensitivity and specificity among IR biomarkers. Its significant association with TNM staging, ECOG-PS, and CEA levels highlights its potential for early detection of metastasis and improved risk stratification. Larger studies are needed to validate its clinical utility for personalised treatment planning.
Narayanan et al. (Wed,) studied this question.
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