Evidence map›Paper›PMID 39583247›Full record

ReviewOncoTargets and therapy2024

Advances in the Treatment of Rare Mutations in Non-Small Cell Lung Cancer.

Yanning Sun, Li Ma, Xiaofei Zhang, Zhaoxia Wang

Abstract readReview
In one paragraph

Review in OncoTargets and therapy, 2024. 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
–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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  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.

Yanning Sun *Cancer Medical Center, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, People's Republic of China.
Li Ma *Cancer Medical Center, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, People's Republic of China.ORCID 0000-0001-7748-0418
Xiaofei Zhang *Cancer Medical Center, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, People's Republic of China.
Zhaoxia WangCancer Medical Center, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, People's Republic of China.ORCID 0000-0002-1893-371X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer is a malignant tumor with the highest morbidity and mortality rate worldwide, with nearly 2.5 million new cases and more than 1.8 million deaths reported globally in 2022. Lung cancer is broadly categorized into two main types: non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC), with NSCLC accounting for about 85% of all cases. Early-stage lung cancers often present without obvious symptoms, resulting in most patients being diagnosed at an advanced stage where traditional chemotherapy has limited efficacy. Recent advances in molecular biology have elucidated the pivotal role of gene mutations in tumor development, paving the way for targeted therapies that have markedly benefited patients. Beyond the well-known epidermal growth factor receptor (EGFR) mutation, an increasing number of new molecular targets have been identified, including ROS1 rearrangement, BRAF mutation, NTRK fusion, RET fusion, MET mutation, KRAS G12C mutation, HER2 mutation, ALK rearrangement, and NRG1 fusion. Some of these targeted therapies have already been approved by the Food and Drug Administration (FDA), and many others are currently undergoing clinical trials. This review summarizes recent advances in NSCLC treatment with molecular targets, highlighting progress, challenges, and their impact on patient prognosis.

Indexed as

immunotherapynon-small cell lung cancerrare mutationstargeted therapy

Identifiers

PMID39583247
PMCPMC11585992

What OpenQuestion holds

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LicenceCC BY-NC
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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.