Evidence map›Paper›PMID 35386540›Full record

ArticleAdvanced biomedical research2022

Relative Risk of Gastrointestinal Cancers in Isfahan County, Iran, 2005-2010.

Vahid Ahmadipanah, Behzad Mahaki, Maryam Nasirian, Maryam Zamani, Akbar Hassanzadeh

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In one paragraph

Article in Advanced biomedical research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
–field-weighted citation impact, top 97% 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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Vahid AhmadipanahDepartment of Public Health, Asadabad School of Medical Sciences, Asadabad, Iran.
Behzad MahakiDepartment of Biostatistics, School of Public Health, Kermanshah University of Medical Sciences, Kermanshah, Iran.
Maryam NasirianDepartment of Epidemiology and Biostatistics, Faculty of Health, Isfahan University of Medical Sciences, Isfahan, Iran.
Maryam ZamaniDepartment of Biostatistics, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.
Akbar HassanzadehDepartment of Epidemiology and Biostatistics, Faculty of Health, Isfahan University of Medical Sciences, Isfahan, Iran.
Isfahan University of Medical Sciences · IRHamedan University of Medical Sciences · IRKermanshah University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Spatial disease mapping is a widespread tool in ecological analysis to obtain accurate estimates for incidence, relative risks (RRs), prevalence, or mortality rates regarding to increase the incidence of gastrointestinal (GI) cancer in Isfahan in recent years. This study aimed to inspect the RR of GI cancer in Isfahan counties using empirical and full Bayesian model. Materials and Methods: Data of this ecological study were GI cancer cases which registered in health-care system of Isfahan University of Sciences during 2005-2010. We applied shared component model to model the spatial variation incidence rates of the GI cancers. We compared three models such as Gamma-Poisson, lognormal, and Besag, York, and Mollie (BYM) Bayesian. WinBUGS and GIS 10.1 software were used. Results: According to the fitted model, BYM model had best fit to the data. However, in general, ranks of RRs in most counties are identical; counties with higher RR in one map have higher RR in other maps. Geographical maps for three cancers in women were smoother than men. Isfahan has high RR in women, whereas this point is slightly different in men. Daran, FreidoonShahr, and Isfahan are cities which have high RR in esophagus, stomach, and colon cancer, respectively. Conclusions: Lognormal and BYM maps had very similar results. Despite some differences in estimation values, in nearly all maps arias Isfahan had high RR in GI cancer. It is recommended to promote the use of screening programs and increase awareness of people in high RR areas to reduce the incidence of GI cancer.

Indexed as

Gastrointestinal neoplasmsGeographic Mappingrelative risk

Identifiers

PMID35386540
PMCPMC8977617
OpenAlexW4214633659

What OpenQuestion holds

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LicenceCC BY-NC-SA
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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.