Evidence map›Paper›PMID 36439478›Full record

ArticleFrontiers in oncology2022

Case report: Almonertinib in combination with bevacizumab for leptomeningeal metastases from epidermal growth factor receptor-mutation non-small cell lung cancer: Case series.

Yuhai Zhang, Meilin Zhang, Wanwan Cheng, Shencun Fang

Open access · goldAbstract readCase Reports
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 24% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
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 2 institutions in 1 country.

Yuhai ZhangDepartment of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
Meilin ZhangDepartment of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Wanwan ChengDepartment of Respiratory Medicine, Nanjing Chest Hospital, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
Shencun FangDepartment of Respiratory Medicine, Nanjing Chest Hospital, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
Nanjing Medical University · CNNanjing Brain Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Leptomeningeal metastasis (LM) is a lethal complication of advanced non-small cell lung cancer (NSCLC) with rapid deterioration and poor prognosis. It has no standard treatment for epidermal growth factor receptor mutation (EGFRm) NSCLC, and improving the clinical outcomes for patients with LM has become an urgent problem in clinical treatment. Both almonertinib and bevacizumab are capable of crossing the blood-brain barrier with comparable central nervous system effectiveness. To date, the almonertinib treatment in combination with bevacizumab in EGFRm NSCLC with LM has not been studied. We herein present five cases to further evaluate the effectiveness and tolerability of almonertinib in combination with bevacizumab for patients with EGFRm NSCLC and LM. For the first time, we report that almonertinib plus bevacizumab can not only effectively improve the neurological symptoms caused by LM but also prolong the survival time of patients with limited and controllable side effects, which provided a novel therapeutic approach for LM from EGFRm NSCLC.

Indexed as

almonertinibbevacizumabEGFRmleptomeningeal metastasisnon-small cell lung cancer

Identifiers

PMID36439478
PMCPMC9685536
OpenAlexW4308867694

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.