Maria Teresa Pesce , Paolo Contiero , Carlotta Buzzoni , Sabrina Fabiano , Alessio Gili , Andrea Tittarelli , Viviana Perotti , Riccardo Capocaccia , Fabrizio Stracci , Walter Mazzucco , Maurizio Zarcone , AIRTUM Working Group
{"title":"意大利的癌症发病率、死亡率和生存估计:方法学方法","authors":"Maria Teresa Pesce , Paolo Contiero , Carlotta Buzzoni , Sabrina Fabiano , Alessio Gili , Andrea Tittarelli , Viviana Perotti , Riccardo Capocaccia , Fabrizio Stracci , Walter Mazzucco , Maurizio Zarcone , AIRTUM Working Group","doi":"10.1016/j.canep.2025.102891","DOIUrl":null,"url":null,"abstract":"<div><div>Italy, home to one of the world’s oldest populations, has traditionally shown geographic differences in cancer incidence, with rates decreasing from north to south. The cancer registries that have been accredited by the Italian Cancer Registry Network (AIRTUM), during the last 20 years altogether cover the 90 % of the Italian population, aiming to improve data quality, standardize procedures, and promote research. This study presents the methodological approaches used for data collection, quality control, and analysis to describe current patterns of cancer incidence, mortality, and survival across Italy's three macro-areas (North, Central, South). Estimates of incidence rates and case numbers for 2025 were also produced. Data from 34 accredited cancer registries were analyzed, comprising over 4.6 million cases from 1981 to 2020, with a detailed focus on the 2008–2017 period, which includes over 3 million cases. Cancer incidence and mortality data were collected according to ICD-O-3 and ICD-10 classifications and processed for statistical analysis using tools such as SEER<em>Prep, SEER</em>Stat, and the Joinpoint Regression Program. Age-standardized rates were calculated, and incidence and mortality trends from 2013 to 2017 were modeled. Five-year cumulative net survival was estimated using the Pohar-Perme method to adjust for competing risks. Survival trends were analyzed by geographic areas and cancer sites, revealing regional disparities in cancer outcomes.</div></div>","PeriodicalId":56322,"journal":{"name":"Cancer Epidemiology","volume":"98 ","pages":"Article 102891"},"PeriodicalIF":2.3000,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Cancer incidence, mortality, and survival estimates in Italy: Methodological approaches\",\"authors\":\"Maria Teresa Pesce , Paolo Contiero , Carlotta Buzzoni , Sabrina Fabiano , Alessio Gili , Andrea Tittarelli , Viviana Perotti , Riccardo Capocaccia , Fabrizio Stracci , Walter Mazzucco , Maurizio Zarcone , AIRTUM Working Group\",\"doi\":\"10.1016/j.canep.2025.102891\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Italy, home to one of the world’s oldest populations, has traditionally shown geographic differences in cancer incidence, with rates decreasing from north to south. The cancer registries that have been accredited by the Italian Cancer Registry Network (AIRTUM), during the last 20 years altogether cover the 90 % of the Italian population, aiming to improve data quality, standardize procedures, and promote research. This study presents the methodological approaches used for data collection, quality control, and analysis to describe current patterns of cancer incidence, mortality, and survival across Italy's three macro-areas (North, Central, South). Estimates of incidence rates and case numbers for 2025 were also produced. Data from 34 accredited cancer registries were analyzed, comprising over 4.6 million cases from 1981 to 2020, with a detailed focus on the 2008–2017 period, which includes over 3 million cases. Cancer incidence and mortality data were collected according to ICD-O-3 and ICD-10 classifications and processed for statistical analysis using tools such as SEER<em>Prep, SEER</em>Stat, and the Joinpoint Regression Program. Age-standardized rates were calculated, and incidence and mortality trends from 2013 to 2017 were modeled. Five-year cumulative net survival was estimated using the Pohar-Perme method to adjust for competing risks. Survival trends were analyzed by geographic areas and cancer sites, revealing regional disparities in cancer outcomes.</div></div>\",\"PeriodicalId\":56322,\"journal\":{\"name\":\"Cancer Epidemiology\",\"volume\":\"98 \",\"pages\":\"Article 102891\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2025-07-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cancer Epidemiology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1877782125001511\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Epidemiology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1877782125001511","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ONCOLOGY","Score":null,"Total":0}
Cancer incidence, mortality, and survival estimates in Italy: Methodological approaches
Italy, home to one of the world’s oldest populations, has traditionally shown geographic differences in cancer incidence, with rates decreasing from north to south. The cancer registries that have been accredited by the Italian Cancer Registry Network (AIRTUM), during the last 20 years altogether cover the 90 % of the Italian population, aiming to improve data quality, standardize procedures, and promote research. This study presents the methodological approaches used for data collection, quality control, and analysis to describe current patterns of cancer incidence, mortality, and survival across Italy's three macro-areas (North, Central, South). Estimates of incidence rates and case numbers for 2025 were also produced. Data from 34 accredited cancer registries were analyzed, comprising over 4.6 million cases from 1981 to 2020, with a detailed focus on the 2008–2017 period, which includes over 3 million cases. Cancer incidence and mortality data were collected according to ICD-O-3 and ICD-10 classifications and processed for statistical analysis using tools such as SEERPrep, SEERStat, and the Joinpoint Regression Program. Age-standardized rates were calculated, and incidence and mortality trends from 2013 to 2017 were modeled. Five-year cumulative net survival was estimated using the Pohar-Perme method to adjust for competing risks. Survival trends were analyzed by geographic areas and cancer sites, revealing regional disparities in cancer outcomes.
期刊介绍:
Cancer Epidemiology is dedicated to increasing understanding about cancer causes, prevention and control. The scope of the journal embraces all aspects of cancer epidemiology including:
• Descriptive epidemiology
• Studies of risk factors for disease initiation, development and prognosis
• Screening and early detection
• Prevention and control
• Methodological issues
The journal publishes original research articles (full length and short reports), systematic reviews and meta-analyses, editorials, commentaries and letters to the editor commenting on previously published research.