Background: Liver metastasis significantly complicates cancer prognosis, yet easily accessible markers for its early detection and monitoring remain crucial. This study aimed to comprehensively evaluate key hematological parameters as potential indicators for liver metastasis in Iraqi patients. Methods: We conducted a cross-sectional study comparing hematological profiles between 90 patients (presumably with liver metastasis) and 30 healthy controls. White Blood Cell (WBC) count, Lymphocyte percentage, Neutrophil percentage, and Neutrophil-to-Lymphocyte Ratio (NLR) were analyzed. Given non-normal data distributions (confirmed by the Shapiro-Wilk test), group comparisons were performed using the non-parametric Mann-Whitney U test. Results: Statistically significant differences were observed across all investigated hematological parameters between the patient and control groups. Patients exhibited elevated WBC counts (p<0.0001) and neutrophil percentages (p=0.0310), indicative of systemic inflammation. Conversely, a highly reduction in lymphocyte percentage (p<0.0001) was noted in the patient group, suggesting relative lymphopenia and a potential shift towards innate over adaptive immune responses. Most notably, the Neutrophil-to-Lymphocyte Ratio (NLR) was significantly higher in patients (p<0.0001), reflecting a pronounced systemic inflammatory state and immune imbalance associated with advanced disease. Conclusion: This study demonstrates a robust association between altered hematological profiles and disease status in patients, consistent with the immune dysregulation characteristic of liver metastasis. These parameters may serve as valuable indicators for early diagnosis and risk stratification in patients with liver metastasis. Their clinical utility could enhance treatment decision-making and patient monitoring in routine practice, and cost-effective and non-invasive markers for early detection, risk stratification, and therapeutic monitoring in Iraqi patients with liver metastasis. Further research is warranted to validate their role in specific clinical algorithms.
