Prediction of damage trajectories in systemic sclerosis using group-based trajectory modelling.

Area of Science:

• Rheumatology
• Clinical Epidemiology
• Biostatistics

Background:

• Systemic sclerosis (SSc) is a chronic autoimmune disease characterized by progressive damage accrual.
• The Scleroderma Clinical Trials Consortium Damage Index (DI) is a validated tool for tracking damage in SSc.
• Predicting future damage accrual in early SSc is crucial for timely therapeutic interventions.

Purpose of the Study:

• To develop and validate a predictive model for damage accrual in patients with early systemic sclerosis.
• To identify distinct trajectories of damage accumulation in limited cutaneous SSc (lcSSc) and diffuse cutaneous SSc (dcSSc).

Main Methods:

• Group-based trajectory modelling (GBTM) was used to identify latent damage trajectories in derivation and validation cohorts.
• Prediction models were developed using baseline data including the Scleroderma Clinical Trials Consortium Damage Index (DI) and sex.
• Model performance was evaluated using receiver operating characteristic area under the curve (ROC AUC).

Main Results:

• Distinct damage accrual trajectories were identified for lcSSc (two trajectories) and dcSSc (three trajectories).
• A simple prediction model incorporating baseline DI and sex demonstrated excellent performance (ROC AUC 0.9313 for lcSSc, 0.9027 for dcSSc).
• The model accurately predicted patient trajectories into 'good' or 'bad' groups, with clear differentiation in actual damage accumulation.

Conclusions:

• A straightforward model utilizing baseline DI and sex can effectively predict damage accumulation in early SSc.
• This predictive model can differentiate between patients with good and poor prognoses regarding damage accrual.
• The findings support the use of this model for risk stratification in early systemic sclerosis management.