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. 2023 Sep 1;62(9):3059-3066.
doi: 10.1093/rheumatology/kead002.

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

Murray Baron  1 , Ariane Barbacki  1 , Ada Man  2 , J K de Vries-Bouwstra  3 , Dylan Johnson  4 , Wendy Stevens  5 , Mohammed Osman  4 , Mianbo Wang  1 , Yuqing Zhang  6 , Joanne Sahhar  7 , Gene-Siew Ngian  7 , Susanna Proudman  8   9 , Mandana Nikpour  4   10 ; Australian Scleroderma Interest Group and the Canadian Scleroderma Research Group
Collaborators, Affiliations

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

Murray Baron et al. Rheumatology (Oxford). .

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.

Keywords: SSc; damage; mortality; prediction; subset; trajectory; ‘group-based trajectory modelling’.

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Figures

Figure 1.
Figure 1.
Actual Damage Index trajectories for both diffuse and limited patients: mean with 1.96*Standard Error
Figure 2.
Figure 2.
Trajectory Group Based Models. (A) lcSSC patients; (B) dcSSC patients
Figure 3.
Figure 3.
ROC curves and AUC for full and selected models as predictors of ‘good’ vs ‘bad’ damage index trajectories. Full models used all covariates at baseline and selected models used only damage index at baseline for lcSSc and damage score plus male gender for dcSSc
See this image and copyright information in PMC

References

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