Evidence map›Paper›PMID 31700868›Full record

ArticleAnnals of translational medicine2019

Clinical relevance of mutant-allele tumor heterogeneity and lung adenocarcinoma.

Hengyu Mao

Open access · diamondAbstract read
In one paragraph

Article in Annals of translational medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 29% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

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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

1 author at 1 institution in 1 country.

Hengyu MaoDepartment of Thoracic Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China.
Fudan University Shanghai Cancer Center · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIntra-tumor heterogeneity (ITH) plays an important role in the progressing of lung adenocarcinoma (LUAD). We used a mutant-allele tumor heterogeneity (MATH) algorithm to measure ITH and the correlation between ITH and clinical parameters and its prognosis.

methodsWe assessed 230 LUAD patients from The Cancer Genome Atlas (TCGA). We calculated the MATH values from whole-exome sequencing data and further investigated their correlation with clinical characteristics.

resultsThe patients were divided into low and high MATH groups. People with high MATH were more likely to be female, smoking and EGFR mutation. And a high MATH may predict a poor prognosis.

conclusionsMATH is a new method for describing the internal heterogeneity of tumors in lung cancer. We used TCGA data to demonstrate that groups with higher MATH values are more likely to be female, smoker and EGFR mutations, and may have a poor prognosis.

Indexed as

mutant-allele tumor heterogeneity (MATH)non-small cell lung cancer (NSCLC)Prognosis

Identifiers

PMID31700868
PMCPMC6803207
OpenAlexW2971844094

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.