Full Text:   <629>

Summary:  <297>

Suppl. Mater.: 

CLC number: 

On-line Access: 2023-06-26

Received: 2022-12-07

Revision Accepted: 2023-04-20

Crosschecked: 2023-09-26

Cited: 0

Clicked: 866

Citations:  Bibtex RefMan EndNote GB/T7714

-   Go to

Article info.
Open peer comments

Journal of Zhejiang University SCIENCE B 2023 Vol.24 No.10 P.935-942

http://doi.org/10.1631/jzus.B2200631


Development and validation of a risk-prediction model for immune-related adverse events in patients with non-small-cell lung cancer receiving PD-1/PD-L1 inhibitors


Author(s):  Qing QIU, Chenghao WU, Wenxiao TANG, Longfei JI, Guangwei DAI, Yuzhen GAO, Enguo CHEN, Hanliang JIANG, Xinyou XIE, Jun ZHANG

Affiliation(s):  Department of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China; more

Corresponding email(s):   jameszhang2000@zju.edu.cn, scottxie@zju.edu.cn

Key Words:  Non-small cell lung cancer, PD-1/PD-L1 inhibitor, Immune-related adverse events, Systemic immune-inflammation index, Body mass index, Age


Share this article to: More <<< Previous Article|

Qing QIU, Chenghao WU, Wenxiao TANG, Longfei JI, Guangwei DAI, Yuzhen GAO, Enguo CHEN, Hanliang JIANG, Xinyou XIE, Jun ZHANG. Development and validation of a risk-prediction model for immune-related adverse events in patients with non-small-cell lung cancer receiving PD-1/PD-L1 inhibitors[J]. Journal of Zhejiang University Science B, 2023, 24(10): 935-942.

@article{title="Development and validation of a risk-prediction model for immune-related adverse events in patients with non-small-cell lung cancer receiving PD-1/PD-L1 inhibitors",
author="Qing QIU, Chenghao WU, Wenxiao TANG, Longfei JI, Guangwei DAI, Yuzhen GAO, Enguo CHEN, Hanliang JIANG, Xinyou XIE, Jun ZHANG",
journal="Journal of Zhejiang University Science B",
volume="24",
number="10",
pages="935-942",
year="2023",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.B2200631"
}

%0 Journal Article
%T Development and validation of a risk-prediction model for immune-related adverse events in patients with non-small-cell lung cancer receiving PD-1/PD-L1 inhibitors
%A Qing QIU
%A Chenghao WU
%A Wenxiao TANG
%A Longfei JI
%A Guangwei DAI
%A Yuzhen GAO
%A Enguo CHEN
%A Hanliang JIANG
%A Xinyou XIE
%A Jun ZHANG
%J Journal of Zhejiang University SCIENCE B
%V 24
%N 10
%P 935-942
%@ 1673-1581
%D 2023
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.B2200631

TY - JOUR
T1 - Development and validation of a risk-prediction model for immune-related adverse events in patients with non-small-cell lung cancer receiving PD-1/PD-L1 inhibitors
A1 - Qing QIU
A1 - Chenghao WU
A1 - Wenxiao TANG
A1 - Longfei JI
A1 - Guangwei DAI
A1 - Yuzhen GAO
A1 - Enguo CHEN
A1 - Hanliang JIANG
A1 - Xinyou XIE
A1 - Jun ZHANG
J0 - Journal of Zhejiang University Science B
VL - 24
IS - 10
SP - 935
EP - 942
%@ 1673-1581
Y1 - 2023
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.B2200631


Abstract: 
Lung cancer remains the leading cause of cancer deaths worldwide and is the most common cancer in males. Immune-checkpoint inhibitors (ICIs) that target programmed cell death protein-1 (PD-1) or programmed cell death-ligand 1 (PD-L1) have achieved impressive efficacy in the treatment of non-small-cell lung cancer (NSCLC) (Pardoll, 2012; Champiat et al., 2016; Gao et al., 2022). Although ICIs are usually well tolerated, they are often accompanied by immune-related adverse events (irAEs) (Doroshow et al., 2019). Non-specific activation of the immune system produces off-target immune and inflammatory responses that can affect virtually any organ or system (O'Kane et al., 2017; Puzanov et al., 2017). Compared with adverse events caused by chemotherapy, irAEs are often characterized by delayed onset and prolonged duration and can occur in any organ at any stage of treatment, including after cessation of treatment (Puzanov et al., 2017; von Itzstein et al., 2020). They range from rash, pneumonitis, hypothyroidism, enterocolitis, and autoimmune hepatitis to cardiovascular, hematological, renal, neurological, and ophthalmic irAEs (Nishino et al., 2016; Kumar et al., 2017; Song et al., 2020). Hence, we conducted a retrospective study to identify validated factors that could predict the magnitude of the risk of irAEs in patients receiving PD-1/PD-L1 inhibitors; our approach was to analyze the correlation between the clinical characteristics of patients at the start of treatment and relevant indicators such as hematological indices and the risk of developing irAEs. Then, we developed an economical, practical, rapid, and simple model to assess the risk of irAEs in patients receiving ICI treatment, as early as possible.

建立和验证非小细胞肺癌PD-1/PD-L1抑制剂相关不良反应的风险预测模型

邱晴1,4, 吴呈昊1,4, 唐文潇1,2, 嵇龙飞1,3, 代广卫1,4, 高瑜振1,4, 陈恩国5, 蒋汉梁5, 谢鑫友1,4, 张钧1,4
1浙江大学医学院附属邵逸夫医院检验科, 中国杭州市, 310016
2浙江省荣军医院检验科, 中国嘉兴市, 314000
3浙江省湖州市第一人民医院检验科, 中国湖州市, 313000
4浙江省医学精准检验与监测研究重点实验室, 中国杭州市, 310016
5浙江大学医学院附属邵逸夫医院呼吸与危重症医学科, 中国杭州市, 310016
摘要:在非小细胞肺癌(NSCLC)患者中,程序性细胞死亡蛋白-1/程序性细胞死亡蛋白-配体1(PD-1/PD-L1)抑制剂治疗后的免疫相关不良事件(irAEs)已被广泛报道。然而,在NSCLC患者中缺少PD-1/PD-L1抑制剂使用后发生irAEs的预测模型。本回顾性研究纳入了357例接受PD-1/PD-L1抑制剂治疗的NSCLC患者,从电子病历系统中收集了治疗前一周内患者的基线人口统计学特征和实验室参数。通过随访采集患者PD-1/PD-L1抑制剂治疗后发生irAEs的情况及长期预后,包括无进展生存期(PFS)和总生存期(OS)。首先,应用Cox比例风险回归模型探究irAEs(≥2级)与长期预后的相关性。然后,构建并验证irAEs(≥2级)的预测模型,按照入组时间顺序以6∶4的比例将患者分为训练集和验证集。在训练集中,通过Cox回归模型筛选出与PD-1/PD-L1抑制剂治疗后发生irAEs(≥2级)相关的变量。根据回归系数确定每个变量的得分并构建irAEs风险预测模型。最后,在训练集和验证集中分别使用受试者工作特征曲线和校准曲线评估预测模型的判别能力和校准度。使用Kaplan-Meier曲线和Cox模型评估irAEs(≥2级)风险预测模型与长期预后(PFS和OS)的相关性。我们建立并验证了基于全身免疫炎症指数、身体质量指数和年龄的irAEs风险预测模型,以帮助医生早期评估接受PD-1/PD-L1抑制剂的NSCLC患者发生irAEs(≥2级)的风险,且发生irAEs(≥2级)与患者的较好的PFS和OS明显相关。

关键词:非小细胞肺癌;PD-1/PD-L1抑制剂;免疫相关性不良事件;全身免疫炎症指数;身体质量指数;年龄

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]BiswasT, KangKH, GawdiR, et al., 2020. Using the systemic immune-inflammation index (SII) as a mid-treatment marker for survival among patients with stage-III locally advanced non-small cell lung cancer (NSCLC). Int J Environ Res Public Health, 17(21):7995.

[2]Castelo-BrancoC, SoveralI, 2014. The immune system and aging: a review. Gynecol Endocrinol, 30(1):16-22.

[3]ChampiatS, LambotteO, BarreauE, et al., 2016. Management of immune checkpoint blockade dysimmune toxicities: a collaborative position paper. Ann Oncol, 27(4):559-574.

[4]CortelliniA, ChiariR, RicciutiB, et al., 2019. Correlations between the immune-related adverse events spectrum and efficacy of anti-PD1 immunotherapy in NSCLC patients. Clin Lung Cancer, 20(4):237-247.e1.

[5]CortelliniA, BersanelliM, SantiniD, et al., 2020. Another side of the association between body mass index (BMI) and clinical outcomes of cancer patients receiving programmed cell death protein-1 (PD-1)/programmed cell death-ligand 1 (PD-L1) checkpoint inhibitors: a multicentre analysis of immune-related adverse events. Eur J Cancer, 128:17-26.

[6]DalyLE, PowerDG, O'ReillyÁ, et al., 2017. The impact of body composition parameters on ipilimumab toxicity and survival in patients with metastatic melanoma. Br J Cancer, 116(3):310-317.

[7]DeurenbergP, YapM, van StaverenWA, 1998. Body mass index and percent body fat: a meta analysis among different ethnic groups. Int J Obes, 22(12):1164-1171.

[8]DoroshowDB, SanmamedMF, HastingsK, et al., 2019. Immunotherapy in non-small cell lung cancer: facts and hopes. Clin Cancer Res, 25(15):4592-4602.

[9]DvorakHF, 2015. Tumor stroma, tumor blood vessels, and antiangiogenesis therapy. Cancer J, 21(4):237-243.

[10]EunY, KimIY, SunJM, et al., 2019. Risk factors for immune-related adverse events associated with anti-PD-1 pembrolizumab. Sci Rep, 9:14039.

[11]GaoZR, LingX,Shi CYY, et al., 2022. Tumor immune checkpoints and their associated inhibitors. J Zhejiang Univ-Sci B (Biomed & Biotechnol), 23(10):823-843.

[12]GeorgiadisMS, SteinbergSM, HankinsLA, et al., 1995. Obesity and therapy-related toxicity in patients treated for small-cell lung cancer. J Natl Cancer Inst, 87(5):361-366.

[13]HuB, YangXR, XuY, et al., 2014. Systemic immune-inflammation index predicts prognosis of patients after curative resection for hepatocellular carcinoma. Clin Cancer Res, 20(23):6212-6222.

[14]HuangYQ, SoonYY, AminkengF, et al., 2022. Risk factors for immune-related adverse events from anti-PD-1 or anti-PD-L1 treatment in an Asian cohort of nonsmall cell lung cancer patients. Int J Cancer, 150(4):636-644.

[15]KugelCH III, DouglassSM, WebsterMR, et al., 2018. Age correlates with response to anti-PD1, reflecting age-related differences in intratumoral effector and regulatory T-cell populations. Clin Cancer Res, 24(21):5347-5356.

[16]KumarV, ChaudharyN, GargM, et al., 2017. Current diagnosis and management of immune related adverse events (irAEs) induced by immune checkpoint inhibitor therapy. Front Pharmacol, 8:49.

[17]LiNL, 2016. Platelets in cancer metastasis: to help the “villain” to do evil. Int J Cancer, 138(9):2078-2087.

[18]MailletD, CorbauxP, StelmesJJ, et al., 2020. Association between immune-related adverse events and long-term survival outcomes in patients treated with immune checkpoint inhibitors. Eur J Cancer, 132:61-70.

[19]MantovaniA, AllavenaP, SicaA, et al., 2008. Cancer-related inflammation. Nature, 454(7203):436-444.

[20]MirsoianA, MurphyWJ, 2015. Obesity and cancer immunotherapy toxicity. Immunotherapy, 7(4):319-322.

[21]NishinoM, Giobbie-HurderA, HatabuH, et al., 2016. Incidence of programmed cell death 1 inhibitor-related pneumonitis in patients with advanced cancer: a systematic review and meta-analysis. JAMA Oncol, 2(12):1607-1616.

[22]O'KaneGM, LabbéC, DohertyMK, et al., 2017. Monitoring and management of immune-related adverse events associated with programmed cell death protein-1 axis inhibitors in lung cancer. Oncologist, 22(1):70-80.

[23]PardollDM, 2012. The blockade of immune checkpoints in cancer immunotherapy. Nat Rev Cancer, 12(4):252-264.

[24]PawelecG, 2018. Unexpected benefits of aging for favorable responses to PD-1 blockade in melanoma? Clin Cancer Res, 24(21):5193-5194.

[25]PengLH, WangY, LiuF, et al., 2020. Peripheral blood markers predictive of outcome and immune-related adverse events in advanced non-small cell lung cancer treated with PD-1 inhibitors. Cancer Immunol Immunother, 69(9):1813-1822.

[26]PuzanovI, DiabA, AbdallahK, et al., 2017. Managing toxicities associated with immune checkpoint inhibitors: consensus recommendations from the Society for Immunotherapy of Cancer (SITC) Toxicity Management Working Group. J Immunother Cancer, 5(1):95.

[27]SongP, ZhangDD, CuiXX, et al., 2020. Meta-analysis of immune-related adverse events of immune checkpoint inhibitor therapy in cancer patients. Thorac Cancer, 11(9):2406-2430.

[28]von ItzsteinMS, KhanS, GerberDE, 2020. Investigational biomarkers for checkpoint inhibitor immune-related adverse event prediction and diagnosis. Clin Chem, 66(6):779-793.

[29]WangQ, LiSB, QiaoSM, et al., 2021. Changes in T lymphocyte subsets in different tumors before and after radiotherapy: a meta-analysis. Front Immunol, 12:648652.

[30]ZamoraC, RiudavetsM, AngueraG, et al., 2021. Circulating leukocyte-platelet complexes as a predictive biomarker for the development of immune-related adverse events in advanced non-small cell lung cancer patients receiving anti-PD-(L)1 blocking agents. Cancer Immunol Immunother, 70(6):1691-1704.

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2024 Journal of Zhejiang University-SCIENCE