Evidence map›Paper›PMID 39101140›Full record

ReviewFrontiers in pharmacology2024

The impact of sarcopenia on the efficacy of PD-1 inhibitors in non-small cell lung cancer and potential strategies to overcome resistance.

Zhenchao Liu, Tianxiang Lei, Yunliang Guo, Chongwen Zheng

Abstract readReview
In one paragraph

Review in Frontiers in pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. 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

4 authors.

Zhenchao LiuSchool of Pharmacy, Qingdao University, Qingdao, Shandong, China.
Tianxiang LeiInstitute of Integrative Medicine, Qingdao University, Qingdao, Shandong, China.
Yunliang GuoInstitute of Integrative Medicine, Qingdao University, Qingdao, Shandong, China.
Chongwen ZhengDepartment of Neurology, The 2nd Affiliated Hospital of Fujian University of Traditional Chinese Medicine, Fuzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent studies have revealed that sarcopenia can adversely affect the efficacy of PD-1 inhibitors in the treatment of non-small cell lung cancer (NSCLC). PD-1 inhibitors are immune checkpoint inhibitors widely used in the treatment of various cancers. However, NSCLC patients may have poorer outcomes when receiving PD-1 inhibitor treatment, and sarcopenia may affect the efficacy of PD-1 inhibitors through immune and metabolic mechanisms. In this article, we summarize the reported negative impact of sarcopenia on the effectiveness of PD-1 inhibitors in the treatment of NSCLC in recent years. Based on existing research results, we analyze the possible mechanisms by which sarcopenia affects the efficacy of PD-1 inhibitors and discuss possible strategies to address this issue. This could help to understand the impact of sarcopenia on the treatment of PD-1 inhibitors and provide more accurate expectations of treatment outcomes for clinicians and patients. Additionally, we present tailored intervention strategies for sarcopenic patients undergoing PD-1 inhibitor therapy, aiming to optimize treatment efficacy and enhance patient quality of life. Nevertheless, further research is warranted to elucidate the mechanisms through which sarcopenia impacts PD-1 inhibitors and to identify more efficacious intervention approaches for improving the effectiveness of PD-1 inhibitor treatment in sarcopenic patients.

Indexed as

immune checkpoint (ICIs)musclenon-small cell lung cancerprogrammed cell death protein-1sarcopenia

Identifiers

PMID39101140
PMCPMC11294093

What OpenQuestion holds

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Registered trials

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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.