Software Application Profile: dynamicLM-a tool for performing dynamic risk prediction using a landmark supermodel for survival data under competing risks.
Int J Epidemiol
; 52(6): 1984-1989, 2023 Dec 25.
Article
en En
| MEDLINE
| ID: mdl-37670428
ABSTRACT
MOTIVATION Providing a dynamic assessment of prognosis is essential for improved personalized medicine. The landmark model for survival data provides a potentially powerful solution to the dynamic prediction of disease progression. However, a general framework and a flexible implementation of the model that incorporates various outcomes, such as competing events, have been lacking. We present an R package, dynamicLM, a user-friendly tool for the landmark model for the dynamic prediction of survival data under competing risks, which includes various functions for data preparation, model development, prediction and evaluation of predictive performance. IMPLEMENTATION dynamicLM as an R package. GENERAL FEATURES The package includes options for incorporating time-varying covariates, capturing time-dependent effects of predictors and fitting a cause-specific landmark model for time-to-event data with or without competing risks. Tools for evaluating the prediction performance include time-dependent area under the ROC curve, Brier Score and calibration. AVAILABILITY:
Available on GitHub [https//github.com/thehanlab/dynamicLM].Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Programas Informáticos
/
Modelos Estadísticos
Tipo de estudio:
Etiology_studies
/
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
Int J Epidemiol
Año:
2023
Tipo del documento:
Article
País de afiliación:
Estados Unidos