术前全免疫炎症值（PIV）对食管鳞癌患者预后的临床应用价值。

Clinical utility of preoperative pan-immune-inflammation value (PIV) for prognostication in patients with esophageal squamous cell carcinoma.

机构信息

Department of Thoracic Surgery, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang Province, China; Zhejiang Provincial Research Center for Upper Gastrointestinal Tract Cancer, Zhejiang Cancer Hospital, Hangzhou, Zhejiang Province, China; Key Laboratory Diagnosis and Treatment Technology on Thoracic Oncology, Zhejiang Cancer Hospital, Hangzhou, Zhejiang Province, China; The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, Zhejiang Province, China.

Department of Thoracic Surgery, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang Province, China.

出版信息

Int Immunopharmacol. 2023 Oct;123:110805. doi: 10.1016/j.intimp.2023.110805. Epub 2023 Aug 15.

DOI:10.1016/j.intimp.2023.110805

PMID:37591121

Abstract

BACKGROUND

Several researches have shown that pan-immune-inflammation value (PIV) is related to cancer prognosis in recent years. In esophageal squamous cell carcinoma (ESCC), nevertheless, the prognostic impact of PIV remains unclear. The present study sought to investigate the prognostic impact of preoperative PIV in ESCC with radical resection.

METHODS

The data of 294 ESCC patients who received radical resection were retrospectively analyzed. Based on analyzing the non-linear relationship between PIV and cancer-specific survival (CSS), the optimal cutoff value for PIV was calculated by the restricted cubic spline (RCS) model. Cox proportional hazards regression was carried out to identify the prognostic factors. A risk stratification model was established by recursive partitioning analysis (RPA). The performance of the RPA-based model was assessed by the decision curve analysis (DCA) and receiver operating characteristic (ROC).

RESULTS

The RCS visualized the non-linear relationship between PIV and CSS (P < 0.0001). Then patients were then divided into high and low groups based on the optimal threshold of 308.2. The 5-year CSS (17.7 % vs. 48.3 %, P < 0.001) was significantly worse in patients with high PIV than those in the low group. Subgroup analyses confirmed that patients with low PIV also achieved better 5-year survival at different pathological tumor node metastasis (pTNM) stages (pTNM I: P = 0.022; pTNM II: P = 0.001; pTNM III: P = 0.011). PIV served as an independent prognostic factor of CSS (hazard ratio = 1.983, P < 0.001). A new staging involving three risk groups with significantly different CSS was developed using RPA algorithms based on pTNM and PIV. Compared with the pTNM classification, the RPA-based model exhibited significantly superior performance for prognostication.

CONCLUSION

The present study confirmed the prognostic impact of PIV in ESCC who treated with radical resection. PIV was associated with the tumor stage and prognosis, which might be useful in the preoperative assessment of ESCC.

摘要

背景

近年来，多项研究表明，pan-immune-inflammation value（PIV）与癌症预后有关。然而，在食管鳞状细胞癌（ESCC）中，PIV 的预后影响尚不清楚。本研究旨在探讨根治性切除术后术前 PIV 对 ESCC 的预后影响。

方法

回顾性分析 294 例接受根治性切除术的 ESCC 患者的数据。通过分析 PIV 与癌症特异性生存（CSS）之间的非线性关系，采用受限立方样条（RCS）模型计算 PIV 的最佳截断值。采用 Cox 比例风险回归分析确定预后因素。采用递归分区分析（RPA）建立风险分层模型。通过决策曲线分析（DCA）和受试者工作特征（ROC）评估 RPA 模型的性能。

结果

RCS 直观地显示了 PIV 与 CSS 之间的非线性关系（P<0.0001）。然后根据 308.2 的最佳阈值将患者分为高和低两组。高 PIV 组的 5 年 CSS（17.7% vs. 48.3%，P<0.001）明显差于低 PIV 组。亚组分析证实，不同病理肿瘤淋巴结转移（pTNM）分期的低 PIV 患者也获得了更好的 5 年生存率（pTNM I：P=0.022；pTNM II：P=0.001；pTNM III：P=0.011）。PIV 是 CSS 的独立预后因素（危险比=1.983，P<0.001）。基于 pTNM 和 PIV，使用 RPA 算法开发了一种新的涉及三个 CSS 差异显著的风险组的分期。与 pTNM 分类相比，基于 RPA 的模型在预后预测方面表现出明显的优势。