Use of SERTS (Socio-Economic,health Resources and Technologic Supplies) models to estimate cancer survival at provincial geographical level |
| |
| Authors: | Marina Vercelli Roberto Lillini Riccardo Capocaccia Alberto Quaglia |
| |
| Affiliation: | 1. Liguria Region Cancer Registry, Descriptive Epidemiology Unit, IRCCS Azienda Ospedaliera Universitaria San Martino – IST Istituto Nazionale per la Ricerca sul Cancro, Genoa, Italy;2. Department of Health Sciences, University of Genoa, Italy;3. “Vita – Salute” San Raffaele University, Milan, Italy;4. National Center of Epidemiology, Surveillance and Promotion of Health, National Institute of Health, Rome, Italy;1. Institute for Maternal and Child Health, IRCCS Burlo Garofolo, Trieste, Italy;2. Department of Biomedical Sciences and Advanced Therapies, Section of Hematology, University of Ferrara-Arcispedale S. Anna, Ferrara, Italy;3. Department of Experimental and Diagnostic Medicine, Section of Pathologic Anatomy, University of Ferrara-Arcispedale S. Anna, Ferrara, Italy;4. Department of Morphology and Embryology and LTTA Centre, University of Ferrara, Ferrara, Italy;5. Department of Internal Medicine and Hematology, Maggiore General Hospital, University of Trieste, Trieste, Italy;1. Dipartimento di Ingegneria, Università degli Studi di Ferrara, Via Saragat, 1, 44100 Ferrara;2. Haestad Methods Solution Center, Bentley Systems, Incorporated, 27 Siemon Co Dr. Suite 200W, Watertown, CT 06795;1. Health Agency of Tuscany, 50141 Firenze, Italy;2. Department of Experimental and Clinical Medicine, University of Florence, Firenze, Italy;3. Laboratory Unit, Health District of Prato, Prato, Italy;4. Infectious Disease Unit, Health District of Prato, Prato, Italy;5. Epidemiological Unit, Health District of Prato, Prato, Italy |
| |
| Abstract: | AimThe main aim of this work is to compute expected cancer survival for Italian provinces by Socio-Economic and health Resources and Technologic Supplies (SERTS) models, based on demographic, socioeconomic variables and information describing the health care system (SEH).MethodsFive-year age-standardised relative survival rates by gender for 11 cancer sites and all cancers combined of patients diagnosed in 1995–1999, were obtained from the Italian Association of Cancer Registries (CRs) database. The SEH variables describe at provincial level macro-economy, demography, labour market, health resources in 1995–2005. A principal components factor analysis was applied to the SEH variables to control their strong mutual correlation. For every considered cancer site, linear regression models were estimated considering the 5-RS% as dependent variable and the principal components factors of the SEH variables as independent variables.ResultsThe model composition was correlated to the characteristics of take in charge of patients. SEH factors were correlated with the observed survival for all cancer combined and colon-rectum in both sexes, prostate, kidney and non Hodgkin's lymphomas in men, breast, corpus uteri and melanoma in women (R2 from 40% to 85%). In the provinces without any CR the survival was very similar with that of neighbouring provinces with analogous social, economic and health characteristics.ConclusionsThe SERTS models allowed us to interpret the survival outcome of oncologic patients with respect to the role of the socio-economic and health related system characteristics, stressing how the peculiarities of the take in charge at the province level could address the decisions regarding the allocation of resources. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
