Evidence map›Paper›PMID 40389764›Full record

ArticleEndocrine2025

Spatial and temporal distribution and evolutionary trend of thyroid cancer incidence in Guangzhou, 2010-2020.

Boheng Liang, Jingjing Zhou, Suixiang Wang, Huan Xu, Ke Li, Huiting Liang, Zeyu Sun, Yanhong Liu, Yawen Wang, Jiaqi Zhang and 2 more

Abstract read
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In one paragraph

Article in Endocrine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  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

12 authors.

Boheng LiangDepartment of Chronic Noncommunicable Disease Prevention and Control, Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China.
Jingjing ZhouDepartment of Epidemiology, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China.
Suixiang WangDepartment of Chronic Noncommunicable Disease Prevention and Control, Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China.
Huan XuDepartment of Chronic Noncommunicable Disease Prevention and Control, Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China.
Ke LiDepartment of Chronic Noncommunicable Disease Prevention and Control, Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China.
Huiting LiangDepartment of Epidemiology, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China.
Zeyu SunDepartment of Epidemiology, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China.
Yanhong LiuDepartment of Epidemiology, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China.
Yawen WangDepartment of Epidemiology, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China.
Jiaqi ZhangDepartment of Epidemiology, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China.
Pengzhe QinDepartment of Chronic Noncommunicable Disease Prevention and Control, Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China. petgyy@gmail.com.
Xiaoqin HuDepartment of Epidemiology, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China. huxiaoqin.love@163.com.

Funding

Applied Basic Research Program of Shanxi 202403021221162Basic Research Project of Guangzhou 2023A03J0936Guangzhou Key Research and Development Project 202206080008Shanxi Province Higher Education "Billion Project'' Science and Technology Guidance Project BYBLD002the National Natural Science Foundation of China 81803326
6 · The paper itself

Abstract

purposeThe spatial and temporal distribution of thyroid cancer in Guangzhou was studied using spatial information system technology, offering a scientific foundation for successful thyroid cancer prevention and treatment.

methodsThe Joinpoint model was used to assess the incidence rate of thyroid cancer over time in various regions. Hierarchical maps were created with the ArcGIS software to investigate the spatial distribution features of the incidence rate. Spatial autocorrelation and spatiotemporal scanning analysis methods were used to assess geographical clustering. Standard deviation ellipse analysis was used to analyze the spatial and temporal trends of incidence.

resultsThe age-standardized incidence rate (ASIR) increased from 6.46/10

conclusionsSignificant heterogeneity and clustering were seen in the spatial distribution of the thyroid cancer incidence rate in Guangzhou, and the regional disparity decreased. The direction of evolution consistent with Guangzhou's "Southern Expansion, Northern Enhancement, Eastern Advancement, Western Integration and Central Revitalization" spatial development policy.

Indexed as

Thyroid NeoplasmsAdultChinaFemaleHumansIncidenceMaleMiddle AgedRural PopulationSpatio-Temporal AnalysisUrban PopulationIncidenceJoinpoint modelSpatial distributionTemporal trendThyroid cancer

Identifiers

PMID40389764

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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.