Evidence map›Paper›PMID 34795315›Full record

ArticleScientific reports2021

Spatial distribution and determinants of thyroid cancer incidence from 1999 to 2013 in Korea.

Jieun Jang, Dae-Sung Yoo, Byung Chul Chun

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. 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
0.5field-weighted citation impact, top 31% 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

3 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
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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

3 authors at 1 institution in 1 country.

Jieun JangDepartment of Preventive Medicine, Korea University College of Medicine, Seoul, Korea.
Dae-Sung YooDepartment of Preventive Medicine, Korea University College of Medicine, Seoul, Korea.
Byung Chul ChunDepartment of Preventive Medicine, Korea University College of Medicine, Seoul, Korea. chun@korea.ac.kr.
Korea University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We evaluated the spatial variation in thyroid cancer incidence and its determinants in Korea considering its importance in cancer prevention and control. This study was based on the ecological design with cancer incidence data by administrative district from the National Cancer Center and regional characteristics generated from the Korea Community Health Survey Data. We identified spatial clusters of thyroid cancer incidences based on spatial scan statistics. Determinants of regional variation in thyroid cancer incidence were assessed using the Besag-York-Mollie model with integrated nested Laplace approximations. Spatial clusters for low and high thyroid cancer incidences were detected in the northeastern and southwestern regions, respectively. Regional variations in thyroid cancer incidence can be attributed to the prevalence of recipients of basic livelihood security (coefficient, - 1.59; 95% credible interval [CI], - 2.51 to - 0.67), high household income (coefficient, 0.53; 95% CI, 0.31 to 0.76), heavy smoking (coefficient, - 0.91; 95% CI, - 1.59 to - 0.23), thyroid dysfunction (coefficient, 3.24; 95% CI, 1.47 to 5.00), and thyroid cancer screening (coefficient, 0.38; 95% CI, 0.09 to 0.67). This study presented the spatial variations in thyroid cancer incidence, which can be explained by the prevalence of socioeconomic factors, thyroid cancer screening, thyroid dysfunction, and smoking.

Indexed as

Bayes TheoremEarly Detection of CancerFemaleGeographyHumansIncidenceMaleMonte Carlo MethodPrevalenceRepublic of KoreaRisk FactorsSmokingSocial ClassSocioeconomic FactorsSpatial AnalysisThyroid Neoplasms

Identifiers

PMID34795315
PMCPMC8602462
OpenAlexW3211853365

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.