Predictive value of sST2 level in immune-related adverse events

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Predictive value of sST2 level in immune-related adverse events

Article | 更新时间：2025-12-31

- Predictive value of sST2 level in immune-related adverse events
- China Oncology Vol. 32, Issue 8, Pages: 712-718(2022)
- 作者机构：
  
  1. 复旦大学附属中山医院心血管内科,上海 200032
  2. 上海市心血管病研究所,上海 200032
  3. 复旦大学附属中山医院心脏超声诊断科,上海 200032
  4. 上海市影像医学研究所,上海 200032
  5. 复旦大学附属中山医院肿瘤内科,上海 200032
- 作者简介：
- 基金信息：
- DOI：10.19401/j.cnki.1007-3639.2022.08.006
  CLC： R738.6
- Received：17 March 2022，
  
  Revised：2022-08-04，
  
  Published：30 August 2022
- 稿件说明：
移动端阅览
Yuchen XU, Leilei CHENG, Yan WANG, et al. Predictive value of sST2 level in immune-related adverse events[J]. China Oncology, 2022, 32(8): 712-718.
DOI：

Yuchen XU, Leilei CHENG, Yan WANG, et al. Predictive value of sST2 level in immune-related adverse events[J]. China Oncology, 2022, 32(8): 712-718. DOI： 10.19401/j.cnki.1007-3639.2022.08.006.

摘要

背景与目的：

免疫检查点抑制剂（immune checkpoint inhibitor

ICI）在过去10年深刻改变了抗肿瘤治疗的格局

显著延长了恶性肿瘤患者的生存期。但随着其在临床上的广泛使用

免疫治疗相关不良反应（immune-related adverse event

irAE）也逐渐被报道和关注

但目前尚缺乏可靠的生物学指标用于预测irAE的发生风险。本文通过联合多个生物学指标

构建了用于预测肿瘤患者接受ICI治疗后发生irAE风险的模型。

方法：

共纳入2018年10月

&

#x02014;2020年12月于复旦大学附属中山医院肿瘤内科住院治疗的恶性肿瘤患者共91例

将纳入研究的患者按照是否在接受ICI治疗后出现G2级别以上的irAE分为irAE组（

n

=13）和对照组（

n

=78）。回顾性分析了两组患者在接受ICI治疗前后包括血清可溶性肿瘤抑制因子（soluble form of suppression of tumorigenicity-2

sST2）、预后营养指数（prognostic nutritional index

PNI）及血小板与淋巴细胞比例（neutrophil to lymphocyte ratio

PLR）在内的生物学指标

构建logistic回归模型用于预测irAE发生风险。

结果：

irAE组共13例。irAE组与对照组患者的基线PNI水平、基线PLR水平与治疗后sST2峰值水平差异有统计学意义（

P

<

0.05

P

<

0.05

P

<

0.01）。Logistic回归分析显示较低的基线PNI水平、基线PLR水平及较高的治疗后sST2峰值为患者接受ICI治疗后发生irAE的独立危险因素（OR=0.790

OR=0.997

OR=1.013）

该logistic回归模型用于预测irAE发生风险的受试者工作特征（receiver operating characteristic

ROC）曲线下面积为0.857。

结论：

较高的sST2水平是发生irAE的独立危险因素

联合sST2、PNI及PLR构建的logistic预测模型对患者接受ICI治疗后发生irAE具有较好的预测能力。

Abstract

Background and purpose:

Immune checkpoint inhibitors (ICIs) have changed the landscape of cancer treatment during the last 10 years. They have significantly extended survival for patients with malignancy. However

immune-related adverse events (irAE) have been reported and attracted attention with widespread use of ICIs. Currently

there is no reliable biomarker to clinically predict the risk of irAE. This study established a risk prediction model of irAE in tumor patients receiving ICIs based on multiple biological indicators.

Methods:

A total of 91 patients treated i

n Zhongshan Hospital of Fudan University from October 2018 to December 2020 were included in the study. Patients included in the study were divided into irAE group and control group according to whether they had grade 2 or higher irAE after receiving ICIs. Biological indicators including serum soluble form of suppression of tumorigenicity-2 (sST2)

prognostic nutritional index (PNI) and platelet to lymphocyte ratio (PLR) were collected before and after ICIs treatment. Logistic regression model containing these biomarkers was constructed to predict the risk of irAE.

Results:

A total of 13 patients in the irAE group. Baseline PNI level

baseline PLR level and post-treatment sST2 peak level showed a significant difference between the irAE group and control group (

P

<

0.05

P

<

0.05 and

P

<

0.01 respectively). Logistic regression analysis showed that lower baseline PNI level

baseline PLR level and higher post-treatment sST2 peak level were independent risk factors for irAE after ICIs treatment (odds ratio were 0.790

0.997

and 1.013 respectively). The area under the receiver operating characteristic (ROC) curve was 0.857.

Conclusion:

Higher sST2 level is an independent risk factor for irAE. The logistic model consisted of sST2

PNI and PLR has a good predictive ability for the risk of irAE after ICIs treatment.

关键词

Keywords

references

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