741Life expectancy among persons with a disease: the Life Years Lost method and R-package 'lillies'. (2nd September 2021)

• Record Type: Journal Article
• Authors: Plana-Ripoll, Oleguer; McGrath, John J
• Is Part Of: International journal of epidemiology. Volume 50(2021)Supplement 1
• Publication Date: 2021-09-02
• Subjects: Epidemiology -- Periodicals; 614.4
• DOI: 10.1093/ije/dyab168.538
• Languages: English
• ISSNs: 0300-5771

Abstract

Abstract: Focus of Presentation: Life Years Lost represent the reduction in life expectancy for a group of persons, e.g. those with a disease. Calculation of life expectancy among those with a disease is not straightforward for diseases that are not present at birth, and previous studies considered a fixed age-of-onset, e.g. 15 years. A recently-introduced method takes into account the real age-of-onset, and allows to decompose differences according to different causes of death. The aim of this communication is to introduce the Life Years Lost method and the associated R package 'lillies'. Findings: The method uses age at onset for each person with a disease as its starting point and estimates the expected residual lifetime at that age using age-specific mortality rates among the diseased. The number of excess Life Years Lost is estimated by comparing the expected residual lifetime with that of the reference population of same age. A single estimate of excess Life Years Lost is estimated as the average of all the person-specific Life Years Lost, and is interpreted as the average number of Life Years Lost that patients with a given disease experience in excess to those experienced by a reference population of same age. Conclusions/Implications: The Life Years Lost method provides accurate estimates of reduced life expectancy in persons with a disease and allows to decompose the total reduction into specific causes of death. Key messages: The implementation of the Life Years Lost method – which can be used with individual-level data (e.g. electronic healthcare records) or summary data – overcomes past limitations in the estimation of life expectancy for time-varying conditions.