Evidence map›Paper›PMID 37304273›Full record

ArticleFrontiers in immunology2023

On-treatment lung immune prognostic index is predictive for first-line PD-1 inhibitor combined with chemotherapy in patients with non-small cell lung cancer.

Anning Xiong, Jianlin Xu, Shuyuan Wang, Runbo Zhong, Jun Lu, Tianqing Chu, Wei Zhang, Ying Li, Xiaoxuan Zheng, Baohui Han and 3 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
1.8field-weighted citation impact, top 13% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.

  1. Pooled it
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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

13 authors at 1 institution in 1 country.

Anning XiongDepartment of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jianlin XuDepartment of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Shuyuan WangDepartment of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Runbo ZhongDepartment of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jun LuDepartment of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Tianqing ChuDepartment of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Wei ZhangDepartment of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Ying LiDepartment of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xiaoxuan ZhengDepartment of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Baohui HanDepartment of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Wei NieDepartment of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Hua ZhongDepartment of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xueyan ZhangDepartment of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Shanghai Jiao Tong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Inflammation is a factor that promotes tumor progression and immunosuppression. Lung immune prognostic index (LIPI) is a non-invasive and easily calculated indicator of inflammation. This study aimed to investigate whether continuous assessment of LIPI has predictive value for chemoimmunotherapy in non-small cell lung cancer (NSCLC) patients receiving first-line programmed cell death 1 (PD-1) inhibitor plus chemotherapy. In addition, the predictive value of LIPI in patients with the negative or low programmed death-ligand (PD-L1) expression level was also explored. Methods: Totally, 146 stage IIIB to IV or recurrent NSCLC patients who received first-line PD-1 inhibitor combined with chemotherapy were enrolled in this study. The LIPI scores were calculated at baseline (PRE-LIPI) and after two cycles of the combined administration (POST-LIPI). This study analyzed the relationship between good/intermediate/poor PRE (POST)-LIPI and objective response rate (ORR), as well as progression-free survival (PFS) using logistic and Cox regression models. In addition, the predictive value of LIPI in patients with the negative or low PD-L1 expression level was explored. To further assess the potential predictive value of continuous assessment of LIPI, the association of sum (LIPI) [sum(LIPI) = PRE-LIPI + POST-LIPI] and PFS was analyzed in the 146 patients. Results: Compared with good POST-LIPI group, significantly lower ORRs were found in intermediate POST-LIPI (P = 0.005) and poor POST-LIPI (P = 0.018) groups. Moreover, intermediate POST-LIPI (P =0.003) and poor POST-LIPI (P < 0.001) were significantly associated with a shorter PFS than good POST-LIPI. Additionally, a higher POST-LIPI score was still significantly associated with poorer treatment efficacy in patients with the negative or low PD-L1 expression level. Moreover, a higher sum (LIPI) score was significantly correlated with a shorter PFS (P = 0.001). Conclusion: Continuous assessment of LIPI might be an effective method for predicting the efficacy of PD-1 inhibitor plus chemotherapy in NSCLC patients. In addition, in patients with the negative or low PD-L1 expression level, it might also have a potential predictive value for therapeutic efficacy to continuously assess LIPI during the treatment.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsB7-H1 AntigenHumansImmune Checkpoint InhibitorsInflammationLungNeoplasm Recurrence, LocalPrognosisB7-H1 AntigenImmune Checkpoint Inhibitorscombination chemotherapyimmune-checkpoint inhibitorslung immune prognostic indexnon-small cell lung cancerperipheral blood cells

Identifiers

PMID37304273
PMCPMC10247997
OpenAlexW4378176708

What OpenQuestion holds

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LicenceCC BY
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 OpenQuestion graph.