Value of pre-treatment pan-immune inflammation score in predicting prognosis of esophageal cancer patients with postoperative adjuvant radiotherapy

JIANG Meinan; LI Tianyi; REN Yue; SONG Zhenya; LI Mengyang; CHEN Yong; YIN Xudong

doi:10.7619/jcmp.20241370

Journal of Clinical Medicine in Practice > 2024 > 28(17): 1-8. > DOI: 10.7619/jcmp.20241370

JIANG Meinan, LI Tianyi, REN Yue, SONG Zhenya, LI Mengyang, CHEN Yong, YIN Xudong. Value of pre-treatment pan-immune inflammation score in predicting prognosis of esophageal cancer patients with postoperative adjuvant radiotherapy[J]. Journal of Clinical Medicine in Practice, 2024, 28(17): 1-8. DOI: 10.7619/jcmp.20241370

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Value of pre-treatment pan-immune inflammation score in predicting prognosis of esophageal cancer patients with postoperative adjuvant radiotherapy

Department of Oncology, the Affiliated Hospital of Yangzhou University, Yangzhou, Jiangsu, 225000

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Received Date: April 03, 2024
Revised Date: July 13, 2024

Graphical Abstract

Abstract

Abstract

Objective
To investigate the correlation between pre-treatment pan-immune inflammation value (PIV) and clinicopathological features in esophageal squamous cell carcinoma (ESCC) patients with postoperative adjuvant radiotherapy and evaluate its value in prognosis assessment combined with T stage.
Methods
A retrospective analysis was conducted on data of 85 ESCC patients with postoperative adjuvant radiotherapy in the Department of Radiation Oncology of the Affiliated Hospital of Yangzhou University from January 2019 to January 2023. The receiver operating characteristic (ROC) curve was drew to obtain the optimal cut-off value of PIV and other immune-inflammatory biomarkers. The area under the curve (AUC) and clinical applicability of PIV and other immune-inflammatory biomarkers were compared based on the ROC curve and decision curve analysis (DCA). According to the optimal cut-off value, patients were divided into high PIV group and low PIV group, and the correlation between PIV level and clinicopathological features of ESCC was evaluated. Kaplan-Meier method was used for survival analysis, the Cox proportional hazards model was used for multivariate analysis, and a risk stratification model combining PIV and T stage was established by recursive partitioning analysis (RPA).
Results
The optimal cut-off value of pre-treatment PIV was determined as 187.22 based on the ROC curve. The AUC of PIV was 0.679, which was greater than 0.640, 0.583, 0.656 and 0.644 of the other four immune-inflammatory biomarkers such as the systemic immune-inflammation index (SII), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and neutrophil-to-lymphocyte ratio (NLR). The 85 patients were divided into low PIV group (< 187.22, n=48) and high PIV group (≥187.22, n=37). The level of PIV was significantly correlated with tumor diameter (P < 0.05). The 3-year overall survival (OS) (75.6% versus 30.6%, P < 0.001) and 3-year disease-free survival (DFS) (56.1% versus 21.0%, P < 0.001) were significantly higher in the low PIV group than the high PIV group. Tumor diameter, T stage and PIV were independent factors affecting OS in ESCC patients (P < 0.05), and T stage and PIV were independent factors affecting DFS in ESCC patients (P < 0.05). A new staging system with three risk groups was established by the RPA stratification model based on T stage and PIV, which further improved the predictive value of prognosis compared with T stage or PIV alone.
Conclusion
Pre-treatment PIV is helpful in predicting the prognosis of ESCC patients with postoperative adjuvant radiotherapy, and the combination of PIV and T stage can improve the predictive value.

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References (30)

References

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Value of pre-treatment pan-immune inflammation score in predicting prognosis of esophageal cancer patients with postoperative adjuvant radiotherapy