lillies: An R package for the estimation of excess Life Years Lost among patients with a given disease or condition.
PLoS One
; 15(3): e0228073, 2020.
Article
em En
| MEDLINE
| ID: mdl-32142521
Life expectancy at a given age is a summary measure of mortality rates present in a population (estimated as the area under the survival curve), and represents the average number of years an individual at that age is expected to live if current age-specific mortality rates apply now and in the future. A complementary metric is the number of Life Years Lost, which is used to measure the reduction in life expectancy for a specific group of persons, for example those diagnosed with a specific disease or condition (e.g. smoking). However, calculation of life expectancy among those with a specific disease is not straightforward for diseases that are not present at birth, and previous studies have considered a fixed age at onset of the disease, e.g. at age 15 or 20 years. In this paper, we present the R package lillies (freely available through the Comprehensive R Archive Network; CRAN) to guide the reader on how to implement a recently-introduced method to estimate excess Life Years Lost associated with a disease or condition that overcomes these limitations. In addition, we show how to decompose the total number of Life Years Lost into specific causes of death through a competing risks model, and how to calculate confidence intervals for the estimates using non-parametric bootstrap. We provide a description on how to use the method when the researcher has access to individual-level data (e.g. electronic healthcare and mortality records) and when only aggregated-level data are available.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Software
/
Interpretação Estatística de Dados
/
Expectativa de Vida
/
Causas de Morte
Tipo de estudo:
Etiology_studies
/
Prognostic_studies
Limite:
Adolescent
/
Adult
/
Aged
/
Aged80
/
Child
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Child, preschool
/
Female
/
Humans
/
Infant
/
Male
Idioma:
En
Revista:
PLoS One
Assunto da revista:
CIENCIA
/
MEDICINA
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
Dinamarca