Prediction of damage trajectories in systemic sclerosis using group-based trajectory modelling.
Rheumatology (Oxford)
; 62(9): 3059-3066, 2023 09 01.
Article
en En
| MEDLINE
| ID: mdl-36625513
ABSTRACT
OBJECTIVES:
Damage accrual in SSc can be tracked using the Scleroderma Clinical Trials Consortium Damage Index (DI). Our goal was to develop a prediction model for damage accrual in SSc patients with early disease.METHODS:
Using patients with <2 years disease duration from Canada and Australia as a derivation cohort, and from the Netherlands as a validation cohort, we used group-based trajectory modelling (GBTM) to determine 'good' and 'bad' latent damage trajectories. We developed a prediction model from this analysis and applied it to patients from derivation and validation cohorts. We plotted the actual DI trajectories of the patients predicted to be in 'good' or 'bad' groups.RESULTS:
We found that the actual trajectories of damage accumulation for lcSSc and dcSSc were very different, so we studied each subset separately. GBTM found two distinct trajectories in lcSSc and three in dcSSc. We collapsed the two worse trajectories in the dcSSc into one group and developed a prediction model for inclusion in either 'good' or 'bad' trajectories. The performance of models using only baseline DI and sex was excellent with ROC AUC of 0.9313 for lcSSc and 0.9027 for dcSSc. Using this model, we determined whether patients would fall into 'good' or 'bad' trajectory groups and then plotted their actual trajectories which showed clear differences between the predicted 'good' and 'bad' cases in both derivation and validation cohorts.CONCLUSIONS:
A simple model using only cutaneous subset, baseline DI and sex can predict damage accumulation in early SSc.Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Esclerodermia Localizada
/
Esclerodermia Sistémica
/
Esclerodermia Difusa
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
País/Región como asunto:
America do norte
Idioma:
En
Revista:
Rheumatology (Oxford)
Asunto de la revista:
REUMATOLOGIA
Año:
2023
Tipo del documento:
Article
País de afiliación:
Canadá