Evidence map›Paper›PMID 29850136›Full record

ArticleJournal of thoracic disease2018

The alteration of T790M between 19 del and L858R in NSCLC in the course of EGFR-TKIs therapy: a literature-based pooled analysis.

Hengrui Liang, Zhenkui Pan, Wei Wang, Chengye Guo, Difei Chen, Jianrong Zhang, Yiyin Zhang, Shiyan Tang, Jianxing He, Wenhua Liang and 1 more

Abstract read
In one paragraph

Article in Journal of thoracic disease, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
–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

34 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Are 19del and L858R really different disease entities?Future oncology (London, England) · 2024
    Review
  7. Article
  8. Article
  9. Article
  10. The efficacy of neoadjuvantFrontiers in oncology · 2023
    Article
  11. Review
  12. Article
  13. Multiple mutations in theTranslational lung cancer research · 2022
    Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

11 authors.

Hengrui LiangDepartment of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou 510120, China.
Zhenkui PanDepartment of Oncology, Qingdao Municipal Hospital, Qingdao 266011, China.
Wei WangDepartment of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou 510120, China.
Chengye GuoDepartment of Oncology, Qingdao Municipal Hospital, Qingdao 266011, China.
Difei ChenDepartment of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou 510120, China.
Jianrong ZhangDepartment of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou 510120, China.
Yiyin ZhangDepartment of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou 510120, China.
Shiyan TangDepartment of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou 510120, China.
Jianxing HeDepartment of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou 510120, China.
Wenhua LiangDepartment of Thoracic Surgery and Oncology, the First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou 510120, China.
written on behalf of AME Lung Cancer Cooperative Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTreatment-naive epidermal growth factor receptor (EGFR) T790M mutation is more inclined to coexist with L858R than with 19 del in non-small cell lung cancer (NSCLC) patients. However, EGFR-tyrosine kinase inhibitors (EGFR-TKIs) might alter this status. We sought to compare the prevalence of T790M upon acquired resistance to EGFR-TKIs between 19 del and L858R by assembling all existing data.

methodsElectronic databases were comprehensively searched for eligible studies. The primary endpoint was the odds ratio (OR) of T790M mutation in NSCLC co-existing with L858R mutation and 19 del upon resistance to first-generation EGFR-TKIs. A random effects model was used. Stratified analysis was performed based on study type (retrospective and prospective), race (Asians and Caucasians) and sample type (tissue and plasma).

resultsA total of 25 studies involving 1,770 patients were included. The overall T790M existent rate was 45.25%. Post-resistance T790M was more frequent in 19 del than in L858R mutated patients (53%

conclusionsOpposite to the situation of

Indexed as

epidermal growth factor receptor (EGFR)exon 19 deletionsL858RNon-small cell lung cancer (NSCLC)T790M

Identifiers

PMID29850136
PMCPMC5949462

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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.