Background: Pathological response after neoadjuvant chemoradiotherapy for esophageal squamous cell carcinoma may differ between the primary tumor and regional lymph nodes. We evaluated pretreatment factors associated with pathological complete response (pCR) and the anatomical distribution of residual disease after esophagectomy. Methods: This retrospective single-center cohort included 100 patients treated with neoadjuvant chemoradiotherapy followed by esophagectomy. pCR was defined as ypT0N0. Associations with pCR were evaluated using logistic regression. Results: Among 99 response-evaluable patients, 59 achieved pCR (59.6%; 95% CI, 49.7–68.7%). Of 40 patients with non-pCR, residual disease involved only the primary tumor in 26 (65%), both primary and nodal compartments in 10 (25%), and only regional lymph nodes despite complete primary tumor regression in 4 (10%). Overall, 14 patients with non-pCR (35%) had residual nodal disease. In an exploratory adjusted analysis that could not account for baseline cT and cN categories, lower pretreatment lactate dehydrogenase (OR per 10 U/L increase, 0.93; 95% CI, 0.86–0.99; p = 0.026) and female sex (OR, 2.72; 95% CI, 1.02–7.24; p = 0.045) were associated with pCR. Conclusions: Response was heterogeneous across primary tumor and nodal compartments. Primary tumor regression did not invariably indicate nodal clearance, supporting compartment-specific response assessment. The lactate dehydrogenase and sex associations may reflect residual confounding by baseline disease extent and require external validation.

Background: Inflammatory and nutritional biomarkers are associated with survival in gastric cancer; however, their incremental prognostic value beyond routinely available clinical factors and the stability of their associations over time remain uncertain. We compared six routinely available biomarkers within a common clinically adjusted framework and evaluated their associations with overall survival (OS), model performance, temporal variation, and internal robustness. Methods: This retrospective single-center cohort study included 255 patients with gastric adenocarcinoma. A prespecified parsimonious Cox model comprising age, sex, Eastern Cooperative Oncology Group performance status, and metastatic disease at diagnosis served as the clinical reference model. The neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), systemic immune-inflammation index (SII), prognostic nutritional index (PNI), and hemoglobin–albumin–lymphocyte–platelet (HALP) score were added separately. Model fit and discrimination, multiple-testing-adjusted associations, time-varying effects, bootstrap internal validation, and influence-diagnostic sensitivity analyses were assessed. Results: During follow-up, 227 patients (89.0%) died. Median OS was 11.66 months (95% confidence interval [CI], 9.63–13.47), and reverse Kaplan–Meier median follow-up was 88.51 months (95% CI, 69.72–110.59). After adjustment for the prespecified clinical factors, higher NLR, PLR, and SII were associated with increased mortality, whereas higher LMR, PNI, and HALP were associated with lower mortality; all associations remained significant after Benjamini–Hochberg correction (q ≤ 0.007). The clinical model had a C-index of 0.678. Biomarker addition yielded C-indices ranging from 0.682 to 0.695, with the largest numerical increase observed for PNI (ΔC-index, +0.017). The HALP-extended model yielded the numerically lowest Akaike information criterion. Exploratory time-specific estimates suggested stronger biomarker–mortality associations during early follow-up, although the interaction tests did not remain significant after multiplicity correction. Bootstrap-corrected C-indices were 0.689 for PNI, 0.686 for HALP, and 0.682 for SII, with low optimism and successful convergence of all 1000 resamples. Influence-diagnostic sensitivity analyses preserved the direction and statistical significance of these associations. Conclusions: Inflammatory and nutritional biomarkers provided additional prognostic information beyond the prespecified clinical factors. Although all six biomarkers remained associated with OS when evaluated separately, their incremental contribution to overall discrimination was modest. PNI and HALP yielded the most favorable numerical model-performance estimates; however, the absolute differences were modest, and formal paired bootstrap comparisons identified no significant differences between the biomarker-extended models. External and longitudinal validation is required before routine prognostic implementation.