Bayesian adjustment for trend of colorectal cancer incidence in misclassified registering across Iranian provinces.

Misclassification error is a common problem of cancer registries in developing countries that leads to biased cancer rates. The purpose of this research is to use Bayesian method for correcting misclassification in registered cancer incidence of eighteen provinces in Iran. Incidence data of patients...

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Bibliographic Details
Main Authors: Sajad Shojaee, Nastaran Hajizadeh, Hadis Najafimehr, Luca Busani, Mohamad Amin Pourhoseingholi, Ahmad Reza Baghestani, Maryam Nasserinejad, Sara Ashtari, Mohammad Reza Zali
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2018-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0199273
Description
Summary:Misclassification error is a common problem of cancer registries in developing countries that leads to biased cancer rates. The purpose of this research is to use Bayesian method for correcting misclassification in registered cancer incidence of eighteen provinces in Iran. Incidence data of patients with colorectal cancer were extracted from Iranian annual of national cancer registration reports from 2005 to 2008. A province with proper medical facilities can always be compared to its neighbors. Almost 28% of the misclassification was estimated between the province of East Azarbaijan and West Azarbaijan, 56% between Fars and Hormozgan, 43% between Isfahan and Charmahal and Bakhtyari, 46% between Isfahan and Lorestan, 58% between Razavi Khorasan and North Khorasan, 50% between Razavi Khorasan and South Khorasan, 74% between Razavi Khorasan and Sistan and Balochestan, 43% between Mazandaran and Golestan, 37% between Tehran and Qazvin, 45% between Tehran and Markazi, 42% between Tehran and Qom, 47% between Tehran and Zanjan. Correcting the regional misclassification and obtaining the correct rates of cancer incidence in different regions is necessary for making cancer control and prevention programs and in healthcare resource allocation.
ISSN:1932-6203