Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists · 2024
A Predictive Model for Graves' Disease Recurrence After Antithyroid Drug Therapy: A Retrospective Multicenter Cohort Study.
СтатьяМногоцентровое исследованиеНаблюдательное исследованиеНазвание и аннотация: Перевод в очереди
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El Kawkgi Omar, Toro-Tobon David, Toloza Freddy J K, Vallejo Sebastian, Jacome Cristian Soto, Ayala Ivan N, Vallejo Bryan A, Wenczenovicz Camila, Tzeng Olivia, Spencer Horace J, Thostenson Jeff D, Li Dingfeng, Kohlenberg Jacob, Lincango Eddy, Mohan Sneha, Castellanos-Diaz Jessica, Maraka Spyridoula, Ospina Naykky Singh, Brito Juan P
Аннотация
OBJECTIVES: Predicting recurrence after antithyroid drug (ATD) cessation is crucial for optimal treatment decision-making in patients with Graves' disease (GD). We aimed to identify factors associated with GD recurrence and to develop a model using routine pretherapeutic clinical parameters to predict GD recurrence risk during the first year following ATD discontinuation.
METHODS: This electronic health records-based observational cohort study analyzed patients with GD treated with ATDs at 3 U.S. academic centers. Demographic, clinical characteristics, and GD recurrence within 1 year following ATD discontinuation were assessed. Univariable and multivariable analyses were performed. A predictive model for GD recurrence was developed and visualized as a nomogram.
RESULTS: Among the 523 patients included in the study, 211 (40.34%) discontinued treatment. Of these, the 142 (67.29%) that had a follow-up period exceeding 12 months after stopping ATD were used for the development of the predictive model. Among the patients included in the model, the majority were women (n = 111, 78.16%), with a mean age of 49.29 years (standard deviation 16.31) and baseline free thyroxine (FT4) levels averaging 3.39 ng/dl (standard deviation 2.25). Additionally, 79 of 211 patients (37.44%) experienced recurrence within 1 year. Multivariable analysis indicated a 31% increased risk of GD recurrence per additional decade of age (odds ratio 1.31, 95% confidence interval 1.03-1.66, P = .0258), and a 65% increased risk of GD recurrence for every 2.0 ng/dL rise in baseline FT4 (odds ratio 1.65, 95% confidence interval 1.08-2.50, P = .0192). The recurrence predictive model's area under the curve was 0.69 in the derivation dataset and 0.65 in cross-validation.
CONCLUSIONS: This study introduced a practical model that can be used during the initial therapeutic decision-making process. It utilizes easily accessible baseline clinical data to predict the likelihood of GD recurrence after 1 year of ATD therapy. Further research is needed to identify other factors affecting risk of recurrence and develop more precise predictive models.
METHODS: This electronic health records-based observational cohort study analyzed patients with GD treated with ATDs at 3 U.S. academic centers. Demographic, clinical characteristics, and GD recurrence within 1 year following ATD discontinuation were assessed. Univariable and multivariable analyses were performed. A predictive model for GD recurrence was developed and visualized as a nomogram.
RESULTS: Among the 523 patients included in the study, 211 (40.34%) discontinued treatment. Of these, the 142 (67.29%) that had a follow-up period exceeding 12 months after stopping ATD were used for the development of the predictive model. Among the patients included in the model, the majority were women (n = 111, 78.16%), with a mean age of 49.29 years (standard deviation 16.31) and baseline free thyroxine (FT4) levels averaging 3.39 ng/dl (standard deviation 2.25). Additionally, 79 of 211 patients (37.44%) experienced recurrence within 1 year. Multivariable analysis indicated a 31% increased risk of GD recurrence per additional decade of age (odds ratio 1.31, 95% confidence interval 1.03-1.66, P = .0258), and a 65% increased risk of GD recurrence for every 2.0 ng/dL rise in baseline FT4 (odds ratio 1.65, 95% confidence interval 1.08-2.50, P = .0192). The recurrence predictive model's area under the curve was 0.69 in the derivation dataset and 0.65 in cross-validation.
CONCLUSIONS: This study introduced a practical model that can be used during the initial therapeutic decision-making process. It utilizes easily accessible baseline clinical data to predict the likelihood of GD recurrence after 1 year of ATD therapy. Further research is needed to identify other factors affecting risk of recurrence and develop more precise predictive models.