Evidence map›Paper›PMID 35211471›Full record

ArticleFrontiers in cell and developmental biology2022

Integrated Analysis of MATH-Based Subtypes Reveals a Novel Screening Strategy for Early-Stage Lung Adenocarcinoma.

Chang Li, Chen Tian, Yulan Zeng, Jinyan Liang, Qifan Yang, Feifei Gu, Yue Hu, Li Liu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in cell and developmental biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
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.

Chang LiCancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Chen TianCancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yulan ZengCancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Jinyan LiangDepartment of Ultrasound, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Qifan YangCancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Feifei GuCancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yue HuCancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Li LiuCancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung adenocarcinoma (LUAD) is a frequently diagnosed cancer type, and many patients have already reached an advanced stage when diagnosed. Thus, it is crucial to develop a novel and efficient approach to diagnose and classify lung adenocarcinoma at an early stage. In our study, we combined

Indexed as

classificationdiagnosisdrug sensitivityimmunotherapylung adenocarcinomamachine learningmutant allele tumor heterogeneity

Identifiers

PMID35211471
PMCPMC8861524

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.