Evidence map›Paper›PMID 38323283›Full record

ArticleAmerican journal of cancer research2024

Genetic alterations predict poor efficacy, outcomes and resistance to second-line osimertinib treatment in non-small cell lung cancer.

Hao Bai, Lei Cheng, Wanting Liu, Wang-Yang Xu, Yingying Huo, Le Diao, Hao Ji, Liwen Xiong

Abstract read
In one paragraph

Article in American journal of cancer research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

8 authors.

Hao BaiDepartment of Pulmonary and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine Shanghai 200030, P. R. China.
Lei ChengDepartment of Pulmonary and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine Shanghai 200030, P. R. China.
Wanting LiuDepartment of Pulmonary and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine Shanghai 200030, P. R. China.
Wang-Yang XuSinglera Genomics Ltd. Shanghai 201203, P. R. China.
Yingying HuoSinglera Genomics Ltd. Shanghai 201203, P. R. China.
Le DiaoSinglera Genomics Ltd. Shanghai 201203, P. R. China.
Hao JiDepartment of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine Shanghai 200030, P. R. China.
Liwen XiongDepartment of Pulmonary and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine Shanghai 200030, P. R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The genetic heterogeneity of non-small cell lung cancer (NSCLC) may impact clinical response and outcomes to targeted therapies. In second-line osimertinib treatment for NSCLC, real-world data on genetic biomarkers for treatment efficacy and prognosis remain incomplete. This real-world study involved 68 NSCLC patients receiving first-generation epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). All of these patients developed resistance, and 49 of them subsequently underwent second-line osimertinib treatment. A 639-gene DNA panel was employed to assess the impact of molecular alterations on treatment efficacy, clinical outcomes and resistance. The findings showed that the median progression-free survival (PFS) for second-line osimertinib therapy was 13.3 months. Genes alterations such as P21 (RAC1) activated kinase 5 (

Indexed as

Clinical outcomeefficacygenetic alterationnon-small cell lung cancerresistance

Identifiers

PMID38323283
PMCPMC10839301

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.