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全免疫炎症值:手术治疗乳腺癌的一种新的预后指标。

Pan-Immune-Inflammation Value: A New Prognostic Index in Operative Breast Cancer.

作者信息

Lin Fei, Zhang Li-Ping, Xie Shuang-Yan, Huang Han-Ying, Chen Xiao-Yu, Jiang Tong-Chao, Guo Ling, Lin Huan-Xin

机构信息

State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.

Department of Radiotherapy, Sun Yat-sen University Cancer Center, Guangzhou, China.

出版信息

Front Oncol. 2022 Apr 13;12:830138. doi: 10.3389/fonc.2022.830138. eCollection 2022.

Abstract

BACKGROUND

To build a predictive scoring model based on simple immune and inflammatory parameters to predict postoperative survival in patients with breast cancer.

METHODS

We used a brand-new immuno-inflammatory index-pan-immune-inflammation value (PIV)-to retrospectively evaluate the relationship between PIV and overall survival (OS), and based on the results of Cox regression analysis, we established a simple scoring prediction model based on several independent prognostic parameters. The predictive accuracy of the model was evaluated and independently validated.

RESULTS

A total of 1,312 patients were included for analysis. PIV was calculated as follows: neutrophil count (10/L) × platelet count (10/L) × monocyte count (10/L)/lymphocyte count (10/L). According to the best cutoff value of PIV, we divided the patients into two different subgroups, high PIV (PIV > 310.2) and low PIV (PIV ≤ 310.2), associated with significantly different survival outcomes (3-year OS, 80.26% vs. 86.29%, respectively; 5-year OS, 62.5% vs. 71.55%, respectively). Six independent prognostic factors were identified and used to build the scoring system, which performed well with a concordance index (C-index) of 0.759 (95% CI: 0.715-0.802); the calibration plot showed good calibration.

CONCLUSIONS

We have established and verified a simple scoring system for predicting prognosis, which can predict the survival of patients with operable breast cancer. This system can help clinicians implement targeted and individualized treatment strategies.

摘要

背景

基于简单的免疫和炎症参数构建预测评分模型,以预测乳腺癌患者的术后生存率。

方法

我们使用一种全新的免疫炎症指数——全免疫炎症值(PIV)——回顾性评估PIV与总生存期(OS)之间的关系,并根据Cox回归分析结果,基于几个独立的预后参数建立了一个简单的评分预测模型。对该模型的预测准确性进行评估并独立验证。

结果

共纳入1312例患者进行分析。PIV的计算方法如下:中性粒细胞计数(10⁹/L)×血小板计数(10⁹/L)×单核细胞计数(10⁹/L)/淋巴细胞计数(10⁹/L)。根据PIV的最佳截断值,我们将患者分为两个不同的亚组,高PIV(PIV>310.2)和低PIV(PIV≤310.2),其生存结果有显著差异(3年总生存率分别为80.26%和86.29%;5年总生存率分别为62.5%和71.55%)。确定了六个独立的预后因素并用于构建评分系统,该系统表现良好,一致性指数(C指数)为0.759(95%CI:0.715 - 0.802);校准图显示校准良好。

结论

我们建立并验证了一个用于预测预后的简单评分系统,该系统可以预测可手术乳腺癌患者的生存情况。该系统可帮助临床医生实施有针对性的个体化治疗策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9153/9043599/9c57f6eb8fca/fonc-12-830138-g001.jpg

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