Evidence map›Paper›PMID 34017689›Full record

ReviewFrontiers in oncology2021

Combination of Immune Checkpoint Inhibitors and Anti-Angiogenic Agents in Brain Metastases From Non-Small Cell Lung Cancer.

Likui Fang, Wuchen Zhao, Bo Ye, Da Chen

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.3field-weighted citation impact, top 11% 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

17 citing papers in PubMed, 22 citations in OpenAlex.

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  16. Tumor vessel normalization and immunotherapy in gastric cancer.Therapeutic advances in medical oncology · 2022
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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 at 1 institution in 1 country.

Likui FangDepartment of Thoracic Surgery, Affiliated Hangzhou Chest Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Wuchen ZhaoDepartment of Thoracic Surgery, Affiliated Hangzhou Chest Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Bo YeDepartment of Thoracic Surgery, Affiliated Hangzhou Chest Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Da ChenDepartment of Thoracic Surgery, Affiliated Hangzhou Chest Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Second Affiliated Hospital of Zhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Brain metastases remain a critical issue in the management of non-small cell lung cancer (NSCLC) because of the high frequency and poor prognosis, with survival rates often measured in just months. The local treatment approach remains the current standard of care, but management of multiple asymptomatic brain metastases always involves systemic therapy. Given that anti-angiogenic agents and immune checkpoint inhibitors (ICIs) both target the tumor microenvironment (TME), this combination therapy has become a promising strategy in clinical practice. Increasing number of preclinical and clinical studies have shown remarkable anti-tumor activity of the combination therapy, but the efficacy in brain metastases is unclear due to the strict selection criteria adopted in most clinical trials. This review briefly summarizes the potential synergistic anti-tumor effect and clinical development of the combination of anti-angiogenic agents and ICIs in NSCLC brain metastases, and discusses the existing challenges and problems.

Indexed as

anti-angiogenesisbrain metastasescombination therapyimmune checkpoint inhibitorsnon-small cell lung cancer

Identifiers

PMID34017689
PMCPMC8130929
OpenAlexW3158563216

What OpenQuestion holds

Textmetadata
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.