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Estimating cancer incidence based on claims data from medical insurance systems in two areas lacking cancer registries in China

BACKGROUND: We aimed to establish a Medical-Insurance-System-based Cancer Surveillance System (MIS-CASS) in China and evaluate the completeness and timeliness of this system through reporting cancer incidence rates using claims data in two regions in northern and southern China. METHODS: We extracte...

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Autores principales: Tian, Hongrui, Yang, Wei, Hu, Yanjun, Liu, Zhen, Chen, Lei, Lei, Liang, Zhang, Fan, Cai, Fen, Xu, Huawen, Liu, Mengfei, Guo, Chuanhai, Chen, Yun, Xiao, Ping, Chen, Junhui, Ji, Ping, Fang, Zhengyu, Liu, Fangfang, Liu, Ying, Pan, Yaqi, dos-Santos-Silva, Isabel, He, Zhonghu, Ke, Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7090368/
https://www.ncbi.nlm.nih.gov/pubmed/32215367
http://dx.doi.org/10.1016/j.eclinm.2020.100312
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author Tian, Hongrui
Yang, Wei
Hu, Yanjun
Liu, Zhen
Chen, Lei
Lei, Liang
Zhang, Fan
Cai, Fen
Xu, Huawen
Liu, Mengfei
Guo, Chuanhai
Chen, Yun
Xiao, Ping
Chen, Junhui
Ji, Ping
Fang, Zhengyu
Liu, Fangfang
Liu, Ying
Pan, Yaqi
dos-Santos-Silva, Isabel
He, Zhonghu
Ke, Yang
author_facet Tian, Hongrui
Yang, Wei
Hu, Yanjun
Liu, Zhen
Chen, Lei
Lei, Liang
Zhang, Fan
Cai, Fen
Xu, Huawen
Liu, Mengfei
Guo, Chuanhai
Chen, Yun
Xiao, Ping
Chen, Junhui
Ji, Ping
Fang, Zhengyu
Liu, Fangfang
Liu, Ying
Pan, Yaqi
dos-Santos-Silva, Isabel
He, Zhonghu
Ke, Yang
author_sort Tian, Hongrui
collection PubMed
description BACKGROUND: We aimed to establish a Medical-Insurance-System-based Cancer Surveillance System (MIS-CASS) in China and evaluate the completeness and timeliness of this system through reporting cancer incidence rates using claims data in two regions in northern and southern China. METHODS: We extracted claims data from medical insurance systems in Hua County of Henan Province, and Shantou City in Guangdong Province in China from Jan 1, 2012 to Jun 30, 2019. These two regions have been considered to be high risk regions for oesophageal cancer. We developed a rigorous procedure to establish the MIS-CASS, which includes data extraction, cleaning, processing, case ascertainment, privacy protection, etc. Text-based diagnosis in conjunction with ICD-10 codes were used to determine cancer diagnosis. FINDINGS: In 2018, the overall age-standardised (Segi population) incidence rates (ASR World) of cancer in Hua County and Shantou City were 167·39/100,000 and 159·78/100,000 respectively. In both of these areas, lung cancer and breast cancer were the most common cancers in males and females respectively. Hua County is a high-risk region for oesophageal cancer (ASR World: 25·95/100,000), whereas Shantou City is not a high-risk region for oesophageal cancer (ASR World: 11·43/100,000). However, Nanao island had the highest incidence of oesophageal cancer among all districts and counties in Shantou (ASR World: 36·39/100,000). The age-standardised male-to-female ratio for oesophageal cancer was lower in Hua County than in Shantou (1·69 vs. 4·02). A six-month lag time was needed to report these cancer incidences for the MIS-CASS. INTERPRETATION: MIS-CASS efficiently reflects cancer burden in real-time, and has the potential to provide insight for improvement of cancer surveillance in China. FUNDING: The National Key R&D Program of China (2016YFC0901404), the Digestive Medical Coordinated Development Center of Beijing Municipal Administration of Hospitals (XXZ0204), the Sanming Project of Shenzhen (SZSM201612061), and the Shantou Science and Technology Bureau (190829105556145, 180918114960704).
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spelling pubmed-70903682020-03-25 Estimating cancer incidence based on claims data from medical insurance systems in two areas lacking cancer registries in China Tian, Hongrui Yang, Wei Hu, Yanjun Liu, Zhen Chen, Lei Lei, Liang Zhang, Fan Cai, Fen Xu, Huawen Liu, Mengfei Guo, Chuanhai Chen, Yun Xiao, Ping Chen, Junhui Ji, Ping Fang, Zhengyu Liu, Fangfang Liu, Ying Pan, Yaqi dos-Santos-Silva, Isabel He, Zhonghu Ke, Yang EClinicalMedicine Research paper BACKGROUND: We aimed to establish a Medical-Insurance-System-based Cancer Surveillance System (MIS-CASS) in China and evaluate the completeness and timeliness of this system through reporting cancer incidence rates using claims data in two regions in northern and southern China. METHODS: We extracted claims data from medical insurance systems in Hua County of Henan Province, and Shantou City in Guangdong Province in China from Jan 1, 2012 to Jun 30, 2019. These two regions have been considered to be high risk regions for oesophageal cancer. We developed a rigorous procedure to establish the MIS-CASS, which includes data extraction, cleaning, processing, case ascertainment, privacy protection, etc. Text-based diagnosis in conjunction with ICD-10 codes were used to determine cancer diagnosis. FINDINGS: In 2018, the overall age-standardised (Segi population) incidence rates (ASR World) of cancer in Hua County and Shantou City were 167·39/100,000 and 159·78/100,000 respectively. In both of these areas, lung cancer and breast cancer were the most common cancers in males and females respectively. Hua County is a high-risk region for oesophageal cancer (ASR World: 25·95/100,000), whereas Shantou City is not a high-risk region for oesophageal cancer (ASR World: 11·43/100,000). However, Nanao island had the highest incidence of oesophageal cancer among all districts and counties in Shantou (ASR World: 36·39/100,000). The age-standardised male-to-female ratio for oesophageal cancer was lower in Hua County than in Shantou (1·69 vs. 4·02). A six-month lag time was needed to report these cancer incidences for the MIS-CASS. INTERPRETATION: MIS-CASS efficiently reflects cancer burden in real-time, and has the potential to provide insight for improvement of cancer surveillance in China. FUNDING: The National Key R&D Program of China (2016YFC0901404), the Digestive Medical Coordinated Development Center of Beijing Municipal Administration of Hospitals (XXZ0204), the Sanming Project of Shenzhen (SZSM201612061), and the Shantou Science and Technology Bureau (190829105556145, 180918114960704). Elsevier 2020-03-20 /pmc/articles/PMC7090368/ /pubmed/32215367 http://dx.doi.org/10.1016/j.eclinm.2020.100312 Text en © 2020 Published by Elsevier Ltd. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research paper
Tian, Hongrui
Yang, Wei
Hu, Yanjun
Liu, Zhen
Chen, Lei
Lei, Liang
Zhang, Fan
Cai, Fen
Xu, Huawen
Liu, Mengfei
Guo, Chuanhai
Chen, Yun
Xiao, Ping
Chen, Junhui
Ji, Ping
Fang, Zhengyu
Liu, Fangfang
Liu, Ying
Pan, Yaqi
dos-Santos-Silva, Isabel
He, Zhonghu
Ke, Yang
Estimating cancer incidence based on claims data from medical insurance systems in two areas lacking cancer registries in China
title Estimating cancer incidence based on claims data from medical insurance systems in two areas lacking cancer registries in China
title_full Estimating cancer incidence based on claims data from medical insurance systems in two areas lacking cancer registries in China
title_fullStr Estimating cancer incidence based on claims data from medical insurance systems in two areas lacking cancer registries in China
title_full_unstemmed Estimating cancer incidence based on claims data from medical insurance systems in two areas lacking cancer registries in China
title_short Estimating cancer incidence based on claims data from medical insurance systems in two areas lacking cancer registries in China
title_sort estimating cancer incidence based on claims data from medical insurance systems in two areas lacking cancer registries in china
topic Research paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7090368/
https://www.ncbi.nlm.nih.gov/pubmed/32215367
http://dx.doi.org/10.1016/j.eclinm.2020.100312
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