The Role of Pre-Treatment Inflammatory Biomarkers in Predicting Tumor Response to Neoadjuvant Chemoradiotherapy in Rectal Cancer

<i>Background and Objectives</i>: This study aimed to investigate the predictive and prognostic value of pre-treatment systemic inflammatory markers in patients with locally advanced rectal cancer (RC) undergoing neoadjuvant chemoradiotherapy (CRT) or radiotherapy (RT) alone. <i>Materials and Methods</i>: A total of 79 patients with biopsy-confirmed locally advanced RC treated at a single tertiary center between 2011 and 2017 were retrospectively analyzed. Pre-treatment blood-based inflammatory indices, including neutrophil-to-lymphocyte ratio (NLR), derived NLR, platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and hemoglobin levels, were recorded. Tumor response was assessed using the Ryan tumor regression grade (TRG), and associations between laboratory parameters, treatment response, and recurrence-free survival (RFS) were evaluated. <i>Results</i>: Among 79 patients (mean age: 55.9 ± 11.98 years; 67.1% male), 57 received neoadjuvant CRT and 22 underwent short-course RT. Complete pathological response (pCR) was observed in 10 patients (12.7%). No statistically significant associations were found between baseline inflammatory markers and TRG, tumor differentiation, or pCR. ROC analysis revealed that none of the markers demonstrated significant discriminatory power for predicting tumor response or recurrence. However, a weak but statistically significant inverse correlation was identified between poor TRG response and higher baseline values of NLR, derived NLR, and PLR (<i>p</i> < 0.05). <i>Conclusions</i>: Inflammatory biomarkers such as NLR, PLR, and LMR, while easily accessible and cost-effective, did not demonstrate strong predictive or prognostic value in this cohort of RC patients receiving neoadjuvant therapy. These findings suggest that reliance solely on systemic inflammatory indices may be insufficient for predicting treatment outcomes, emphasizing the need for integrative models incorporating molecular and pathological markers.