A Predictive Model for Graves' Disease Recurrence After Antithyroid Drug Therapy: A Retrospective Multi-Center Cohort Study

Omar El Kawkgi; David Toro-Tobon; Freddy J K Toloza; Sebastian Vallejo; Cristian Soto Jacome; Ivan N Ayala; Bryan A Vallejo; Camila Wenczenovicz; Olivia Tzeng; Horace J Spencer; Jeff D Thostenson; Dingfeng Li; Jacob Kohlenberg; Eddy Lincango; Sneha Mohan; Jessica Castellanos-Diaz; Spyridoula Maraka; Naykky Singh Ospina; Juan P Brito

doi:10.1016/j.eprac.2024.12.011

A Predictive Model for Graves' Disease Recurrence After Antithyroid Drug Therapy: A Retrospective Multi-Center Cohort Study

Endocr Pract. 2024 Dec 16:S1530-891X(24)00869-3. doi: 10.1016/j.eprac.2024.12.011. Online ahead of print.

Authors

Omar El Kawkgi¹, David Toro-Tobon², Freddy J K Toloza³, Sebastian Vallejo⁴, Cristian Soto Jacome⁵, Ivan N Ayala⁴, Bryan A Vallejo⁶, Camila Wenczenovicz⁴, Olivia Tzeng⁷, Horace J Spencer⁸, Jeff D Thostenson⁸, Dingfeng Li⁹, Jacob Kohlenberg¹⁰, Eddy Lincango⁴, Sneha Mohan², Jessica Castellanos-Diaz¹¹, Spyridoula Maraka¹², Naykky Singh Ospina¹¹, Juan P Brito¹³

Affiliations

¹ Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA; Department of Endocrinology, Mayo Clinic Health System, Eau Claire, Wisconsin, USA.
² Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA.
³ Division of Endocrinology and Metabolism, Department of Internal Medicine, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA; Knowledge and Evaluation Research Unit, Division of Endocrinology, Diabetes, Metabolism and Nutrition, Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA; Diabetes and Endocrinology and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Disorders, National Institutes of Health, Bethesda, Maryland, USA.
⁴ Knowledge and Evaluation Research Unit, Division of Endocrinology, Diabetes, Metabolism and Nutrition, Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA.
⁵ Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA; Knowledge and Evaluation Research Unit, Division of Endocrinology, Diabetes, Metabolism and Nutrition, Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA.
⁶ Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA.
⁷ College of Medicine, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA.
⁸ Department of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA.
⁹ Department of Endocrinology, Endocrinology and Metabolism Institute, Cleveland Clinic, Cleveland, Ohio, USA.
¹⁰ Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, University of Minnesota Medical School, Minneapolis, Minnesota, USA.
¹¹ Division of Endocrinology, Department of Medicine, University of Florida, Gainesville, Florida, USA.
¹² Knowledge and Evaluation Research Unit, Division of Endocrinology, Diabetes, Metabolism and Nutrition, Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA; Section of Endocrinology, Medicine Service, Central Arkansas Veterans Healthcare System, Little Rock, Arkansas, USA; Division of Endocrinology and Metabolism, Department of Internal Medicine, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA.
¹³ Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA; Knowledge and Evaluation Research Unit, Division of Endocrinology, Diabetes, Metabolism and Nutrition, Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA. Electronic address: [email protected].

PMID: 39694327
DOI: 10.1016/j.eprac.2024.12.011

Abstract

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 three U.S. academic centers. Demographic, clinical characteristics and GD recurrence within one 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 (SD 16.31) and baseline free T4 (FT4) levels averaging 3.39 ng/dl (SD 2.25). Additionally, 79/211 patients (37.44%) experienced recurrence within one year. Multivariable analysis indicated a 31% increased risk of GD recurrence per additional decade of age (OR 1.31, 95% CI 1.03-1.66, p = 0.0258), and a 65% increased risk of GD recurrence for every 2.0 ng/dL rise in baseline FT4 (OR 1.65, 95% CI 1.08-2.50, p = 0.0192). The recurrence predictive model's AUC 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 one year of ATD therapy. Further research is needed to identify other factors affecting risk of recurrence and develop more precise predictive models.

Keywords: Graves’ disease; anti-thyroid drug; hyperthyroidism; recurrence.