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Prediction of damage trajectories in systemic sclerosis using group-based trajectory modelling.
Baron, Murray; Barbacki, Ariane; Man, Ada; de Vries-Bouwstra, J K; Johnson, Dylan; Stevens, Wendy; Osman, Mohammed; Wang, Mianbo; Zhang, Yuqing; Sahhar, Joanne; Ngian, Gene-Siew; Proudman, Susanna; Nikpour, Mandana.
Afiliación
  • Baron M; Lady Davis Institute for Medical Research, Montreal, Quebec, Canada.
  • Barbacki A; Lady Davis Institute for Medical Research, Montreal, Quebec, Canada.
  • Man A; Rheumatology, Faculty of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada.
  • de Vries-Bouwstra JK; Department of Rheumatology, Leiden University, Leiden, The Netherlands.
  • Johnson D; Department of Medicine, University of Alberta, Edmonton, Alberta, Canada.
  • Stevens W; Division of Rheumatology, St. Vincent's Hospital Melbourne, Fitzroy, Victoria, Australia.
  • Osman M; Department of Medicine, University of Alberta, Edmonton, Alberta, Canada.
  • Wang M; Lady Davis Institute for Medical Research, Montreal, Quebec, Canada.
  • Zhang Y; Division of Rheumatology, Allergy, and Immunology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Sahhar J; Monash Health, Clayton, Victoria, Australia.
  • Ngian GS; Monash Health, Clayton, Victoria, Australia.
  • Proudman S; Royal Adelaide Hospital, Adelaide, South Australia, Australia.
  • Nikpour M; Discipline of Medicine, University of Adelaide, Adelaide, South Australia, Australia.
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.
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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

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