ArticleGastroenterology and hepatology from bed to bench2017
Bayesian correction model for over-estimation and under-estimation of liver cancer incidence in Iranian neighboring provinces.
Article in Gastroenterology and hepatology from bed to bench, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- Incidence and mortality trend of liver cancer in Iran from 1990 to 2021: an epidemiological investigation using the Global Burden of Disease study.Annals of medicine and surgery (2012) · 2025Article
- The spatial distribution of colorectal cancer relative risk in Iran: a nationwide spatial study.Gastroenterology and hepatology from bed to bench · 2020Article
- Bayesian adjustment for trend of colorectal cancer incidence in misclassified registering across Iranian provinces.PloS one · 2018Article
- Iranian high risk regions due to esophageal cancer: spatial analysis of cancer registry data.Gastroenterology and hepatology from bed to bench · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimThe aim of this study was to obtain more accurate estimates of the liver cancer incidence rate after correcting for misclassification error in cancer registry across Iranian provinces.
backgroundNowadays having a thorough knowledge of geographic distribution of disease incidence has become essential for identifying the influential factors on cancer incidence.
methodsData of liver cancer incidence was extracted from Iranian annual of national cancer registration report 2008. Expected coverage of cancer cases for each province was calculated. Patients of each province that had covered fewer cancer cases than 100% of its expectation, were supposed to be registered at an adjacent province which had observed more cancer cases than 100% of its expected coverage. For estimating the rate of misclassification in registering cancer incidence, a Bayesian method was implemented. Beta distribution was considered for misclassified parameter since its expectation converges to the misclassification rate. Parameters of beta distribution were selected based on the expected coverage of cancer cases in each province. After obtaining the misclassification rate, the incidence rates were re-estimated.
resultsThere was misclassification error in registering new cancer cases across the provinces of Iran. Provinces with more medical facilities such as Tehran which is the capital of the country, Mazandaran in north of the Iran, East Azerbaijan in north-west, Razavi Khorasan in north-east, Isfahan in central part, and Fars and Khozestan in south of Iran had significantly higher rates of liver cancer than their neighboring provinces. On the other hand, their neighboring provinces with low medical facilities such as Ardebil, West Azerbaijan, Golestan, South and north Khorasans, Qazvin, Markazi, Arak, Sistan & balouchestan, Kigilouye & boyerahmad, Bushehr, Ilam and Hormozgan, had observed fewer cancer cases than their expectation.
conclusionAccounting and correcting the regional misclassification are necessary for identifying high risk areas of the country and effective policy making to cope with cancer.
Indexed as
Identifiers
29511473PMC5838182What OpenQuestion holds
Registered trials
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.