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

医学 队列 弹道 硬皮病(真菌) 增加物 统计 内科学 数学 病理 天文 物理 会计 业务 接种 收益
作者
Murray Baron,Ariane Barbacki,Ada Man,Jeska K de Vries-Bouwstra,Dylan Johnson,Wendy Stevens,Mohammed Osman,Mianbo Wang,Yuqing Zhang,Joanne Sahhar,Gene‐Siew Ngian,Susanna Proudman,Mandana Nikpour,Murray Baron,Geneviève Gyger,Sophie Ligier,Marie Hudson,Maggie Larché,Nader Khalidi,A Massetto,Emily Sutton,Ada Man,T.S. Rodríguez-Reyna,Carter Thorne,Paul R. Fortin,Alena Ikic,David Robinson,Mohammed Osman,Natalie Jones,Sharon LeClercq,Paul D. Docherty,Douglas P. Smith,Maysan Abu-Hakima,Elżbieta Kamińska,Marvin J. Fritzler,Mandana Nikpour,Susanna Proudman,Wendy Stevens,Joanne Sahhar,Nava Ferdowsi,Kathleen Morrisroe,Laura Ross,Gene‐Siew Ngian,Jenny Walker,Janet Roddy,Lauren Host,Gabor Major
出处
期刊:Rheumatology [Oxford University Press]
卷期号:62 (9): 3059-3066 被引量:2
标识
DOI:10.1093/rheumatology/kead002
摘要

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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