Evidence map›Paper›PMID 36238240›Full record

ArticleFrontiers in public health2022

Spatial and temporal analysis of liver cancer mortality in Yunnan province, China, 2015-2019.

Chengcheng Feng, Jinghua Liu, Hailiang Ran, Linxiong Wu, Xuemeng Liang, Hao Sun, Yuanyuan Xiao, Wei Chang

Abstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
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.

Chengcheng FengSchool of Public Health, Kunming Medical University, Kunming, China.
Jinghua LiuDepartment of Gastroenterology, Affiliated Hospital of Yunnan University, Kunming, China.
Hailiang RanSchool of Public Health, Kunming Medical University, Kunming, China.
Linxiong WuSchool of Public Health, Kunming Medical University, Kunming, China.
Xuemeng LiangSchool of Public Health, Kunming Medical University, Kunming, China.
Hao SunSchool of Public Health, Kunming Medical University, Kunming, China.
Yuanyuan XiaoSchool of Public Health, Kunming Medical University, Kunming, China.
Wei ChangSchool of Public Health, Kunming Medical University, Kunming, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Liver cancer is a major public health challenge. Few published studies reported temporal trend and geographical distribution of liver cancer mortality in China, especially in less developed southwest regions with higher liver cancer incidence. In the current study, we obtained liver cancer mortality data from population-based death surveillance system in Yunnan province in 2015-2019. The mortality of liver cancer was analyzed by using the joinpoint regression model. The space distribution of liver cancer mortality in 129 counties and districts in Yunnan province was illustrated by using the ArcGIS software. Moran's I method was used to estimate the global and local spatial autocorrelation of liver cancer mortality. Analytical results revealed that from 2015 to 2019, the average mortality rate of liver cancer in Yunnan province was 12.96/100,000, with an average annual growth rate of 6.26% (

Indexed as

Liver NeoplasmsChinaHumansIncidenceMaleSpatial AnalysisSpatio-Temporal Analysisliver cancermortalityspatial autocorrelationtemporal trendtime-series data

Identifiers

PMID36238240
PMCPMC9553124

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.