6-Year Risk of Developing Lung Cancer in Spain: Analysis by Autonomous Communities

Publication date

2026-01-12T16:23:21Z

2026-01-12T16:23:21Z

2020-05-11

2026-01-12T16:23:21Z



Abstract

Introduction: Lung cancer screening with low-dose computed tomography (LDCT) has been proposed as a strategy to reduce lung cancer mortality. Since LDCT has side effects there is a need to carefully select the target population for screening programmes. Because in Spain health competences are transferred to the seventeen Autonomous Communities (ACs), the present paper aims to identify individuals at high risk of developing lung cancer in the different ACs. Methods: We used the 2011-2012 data of the Spanish National Interview Health Survey (n=21,006) to estimate the proportion of individuals at high risk of developing lung cancer using a 6-year prediction model (PLCOm2012). This proportion was then extrapolated into absolute figures for the Spanish population, using the population census data of 2018 from the National Institute of Statistics. Results: The proportion of individuals aged 50-74 with a risk of lung cancer ≥2% was 9.5% (15.9% in men, 3.5% in women). This proportion ranged from 6.6% in Región de Murcia to 12.7% in Andalucía and 13.0% in Extremadura. When extrapolated to the Spanish population, it was estimated that a total of 1,341,483 individuals may have a 6-year risk of lung cancer ≥2%. Conclusions: The present study is the first one that evaluated the number of individuals at high risk of developing lung cancer in the different Spanish ACs using a prediction model and selecting people with a 6-year risk ≥2%. Further studies should assess the cost and effectiveness associated to the implementation of a lung cancer screening programme to such population.

Document Type

Article


Accepted version

Language

English

Publisher

Elsevier

Related items

Versió postprint del document publicat a: https://doi.org/10.1016/j.arbr.2020.03.033

Archivos de Bronconeumologia, 2020, vol. 57, num.8, p. 521-527

https://doi.org/10.1016/j.arbr.2020.03.033

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cc-by-nc-nd (c) Elsevier, 2020

http://creativecommons.org/licenses/by-nc-nd/4.0/

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