Combined immunoscore and pan-immune inflammation value associated with pathological response and survival outcomes in esophageal squamous cell carcinoma receiving neoadjuvant immunotherapy.
Jiang-Shan Huang, Qi-Hong Zhong, Ye-Qin Zhang, Huai-Yuan Zhang, Fei-Long Guo, Jing-Yu Wu, Sui Chen, Wen-Wei Lin, Zhen-Yang Zhang, Jiang-Bo Lin
Abstract
Open AccessOBJECTIVE: To evaluate the efficacy of combined tumor immunoscore (IS) and pan-immune inflammation value (PIV) in assessing pathological response and survival following neoadjuvant chemoimmunotherapy (NACI) in locally advanced esophageal squamous cell carcinoma (ESCC). METHODS: A retrospective cohort of 226 ESCC patients undergoing NACI followed by surgery was analyzed. Local immune status was assessed via IS calculated from CD3⁺/CD8⁺ T-cell densities on immunohistochemical stained tumor sections. Systemic inflammation was measured by peripheral blood PIV. Patients were stratified by median values. The association of IS, PIV alone, and their combination for major pathological response (TRG 0-1) and overall survival (OS) was evaluated. RESULTS: The pathological response rate was significantly higher in the high IS group versus the low IS group (54.3% vs. 38.6%; P = 0.023) and in the low PIV group p versus the high PIV group (67.3% vs. 21.2%; P < 0.001). In the combined model, the low IS + high PIV group (Group D) exhibited the lowest pathological response rate (32.0%) and a significantly increased risk of death compared with the optimal group [high IS + low PIV; Group A; hazard ratios = 2.85; 95% confidence interval (CI): 1.70-4.77; P < 0.001]. The dual-parameter IS + PIV model demonstrated superior discriminatory performance: area under the curve (AUC) = 0.78 (95% CI: 0.73-0.84) for discriminating pathological response and AUC = 0.82 (95% CI: 0.75-0.88) for predicting 36-month OS, significantly outperforming single parameters and clinical staging. CONCLUSION: The IS + PIV dual-parameter model, by integrating local immune activity and systemic inflammatory status, accurately identifies NACI beneficiaries (high IS + low PIV) and high-risk patients (low IS + high PIV), providing an efficient prognostic tool for personalized treatment strategies.