Evidence map›Paper›PMID 31199587›Full record

ArticleCancer medicine2019

Spatial distribution characteristics of tumor marker CA724 reference values in China.

Jing Jing, Miao Ge, Ziqi Yang, Peng Li

Abstract read
In one paragraph

Article in Cancer medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

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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

13 citing papers in PubMed.

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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

4 authors.

Jing JingInstitute of Healthy Geography, College of Geography and Tourism, Shaanxi Normal University, Xi'an, Shaanxi, China.ORCID 0000-0002-5841-4826
Miao GeInstitute of Healthy Geography, College of Geography and Tourism, Shaanxi Normal University, Xi'an, Shaanxi, China.
Ziqi YangBaoji University of Arts and Sciences, Baoji, Shaanxi, China.
Peng LiDepartment of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong Unversity Health Science Center, Xi'an, Shaanxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectsThis study aims to explore the Cancer antigen 724 (CA724) reference values spatial distribution characteristics in healthy Chinese adults. The study can provide regional reference for medical diagnosis. STUDY

designThe relationship between CA724 and 25 geographical environmental factors was analyzed firstly. Artificial neural network simulation training was used to construct the prediction model. The national forecast distribution map of the CA724 reference values was obtained by the geostatistical mapping method. Analyzing and exploring the influence mechanism of geographical environment factors on CA724 reference values.

methodsCollecting 34470 cases from more than 106 cities healthy adults CA724 reference values via several paper databases in 10 recent years. Correlation analysis, RBF artificial neural networks and trend surface analysis were applied to explore if there was any tendency of spatial variation. The Kriging interpolation of geostatistical analysis was developed to reveal the spatial distribution characteristics of the CA724 reference values.

resultsThe distribution of CA724 reference values of Chinese healthy adults shows a downward trend from south to north. CA724 reference values have negative correlations with latitude, annual sunshine duration and topsoil cation exchange capacity in clay. CA724 have positive correlations with annual mean air temperature, annual mean relative humidity, and annual precipitation amount. High temperature and high humidity environment will reduce gastrointestinal function and breeze various mold bacteria. Lack of sunshine can easily lead to vitamin C deficiency in the body. These will increase the incidence of gastrointestinal diseases and gastric cancer, then increase the CA724 value.

conclusionCA724 reference values show spatial autocorrelation and regional variation. There are some geographical environment factors effected Chinese healthy adults CA724 reference values. Geographic factors such as sunshine, temperature, and humidity have effects on CA724 reference values can provide new ideas and directions of prevention and clinical diagnosis in the future.

Indexed as

Antigens, Tumor-Associated, CarbohydrateBiomarkers, TumorChinaEnvironmental BiomarkersFemaleGeographyHealthy VolunteersHumansMaleNeural Networks, ComputerReference ValuesSpatial AnalysisAntigens, Tumor-Associated, CarbohydrateBiomarkers, TumorCA-72-4 antigenEnvironmental BiomarkersCA724gastric cancergeographical environment factorsreference valuestumor markers

Identifiers

PMID31199587
PMCPMC6675733

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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.