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DOI 10.1093/rheumatology/kead002

Медицинская библиотека · Rheumatology (Oxford, England) · 2023

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, Australian Scleroderma Interest Group and the Canadian Scleroderma Research Group

СтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

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.

Для цитирования: 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, Australian Scleroderma Interest Group and the Canadian Scleroderma Research Group. Prediction of damage trajectories in systemic sclerosis using group-based trajectory modelling.. Rheumatology (Oxford, England). 2023. DOI: 10.1093/rheumatology/kead002.

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