Evidence map›Paper›PMID 37752094›Full record

ArticleJournal of Zhejiang University. Science. B2023

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.

Qing Qiu, Chenghao Wu, Wenxiao Tang, Longfei Ji, Guangwei Dai, Yuzhen Gao, Enguo Chen, Hanliang Jiang, Xinyou Xie, Jun Zhang

Open access · greenAbstract read
In one paragraph

Article in Journal of Zhejiang University. Science. B, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 20% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 1 institution in 1 country.

Qing QiuDepartment of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China.
Chenghao WuDepartment of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China.
Wenxiao TangDepartment of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China.
Longfei JiDepartment of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China.
Guangwei DaiDepartment of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China.
Yuzhen GaoDepartment of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China.
Enguo ChenDepartment of Pulmonary and Critical Care Medicine, Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China.
Hanliang JiangDepartment of Pulmonary and Critical Care Medicine, Regional Medical Center for National Institute of Respiratory Diseases, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China.
Xinyou XieDepartment of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China. scottxie@zju.edu.cn.
Jun ZhangDepartment of Clinical Laboratory, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China. jameszhang2000@zju.edu.cn.
Sir Run Run Shaw Hospital · CN

Funding

the National Natural Science Foundation of China 81972012
6 · The paper itself

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.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsApoptosisHumansImmune Checkpoint InhibitorsMaleProgrammed Cell Death 1 ReceptorRetrospective StudiesImmune Checkpoint InhibitorsProgrammed Cell Death 1 ReceptorAgeBody mass indexImmune-related adverse eventsNon-small cell lung cancerPD-1/PD-L1 inhibitorSystemic immune-inflammation index

Identifiers

PMID37752094
PMCPMC10522565
OpenAlexW4387077067

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.