Patterns of care and cost profiles of women with breast cancer in Italy: EPICOST study based on real world data



To estimate total direct health care costs associated to diagnosis and treatment of women with breast cancer in Italy, and to investigate their distribution by service type according to the disease pathway and patient characteristics.


Data on patients provided by population-based Cancer Registries are linked at individual level with data on health-care services and corresponding claims from administrative databases. A combination of cross-sectional approach and a threephase of care decomposition model with initial, continuing and final phases-of-care defined according to time occurred since diagnosis and disease outcome is adopted. Direct estimation of cancer-related costs is obtained.


Study cohort included 49,272 patients, 15.2% were in the initial phase absorbing 42% of resources, 79.7% in the continuing phase absorbing 44% of resources and 5.1% in the final phase absorbing 14% of resources. Hospitalization was the most important cost driver, accounting for over 55% of the total costs.


This paper represents the first attempt in Italy to estimate the economic burden of cancer at population level taking into account the entire disease pathway and using multiple current health care databases. The evidence produced by the study can be used to better plan resources allocation. The model proposed is replicable to countries with individual health care information on services and claims.

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We thank Giuseppe Traversa and Roberto Da Cas, pharmaco-epidemiologists, for their useful suggestions.


The study was supported by the National Centre for Disease Prevention and Control of the Italian Ministry of Health, Grant 2014.

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Correspondence to Stefano Guzzinati.

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Francisci, S., Guzzinati, S., Capodaglio, G. et al. Patterns of care and cost profiles of women with breast cancer in Italy: EPICOST study based on real world data. Eur J Health Econ 21, 1003–1013 (2020).

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  • Breast cancer
  • Health care utilization
  • Administrative data
  • Real world data
  • Cost analysis

JEL Classification

  • H750 State and Local Government: Health; Education; Welfare; Public Pensions
  • H510 National Government Expenditures and Health
  • I180 Health: Government Policy; Regulation; Public Health