- Thyroid
- Dynamic Risk Model for the Medical Treatment of Graves’ Hyperthyroidism according to Treatment Duration
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Meihua Jin, Chae A Kim, Min Ji Jeon, Won Bae Kim, Tae Yong Kim, Won Gu Kim
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Endocrinol Metab. 2024;39(4):579-589. Published online May 23, 2024
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DOI: https://doi.org/10.3803/EnM.2024.1918
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 Abstract
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- Background
Changes in thyrotropin receptor antibody (TRAb) levels are associated with the clinical outcomes of Graves’ hyperthyroidism. However, the effects of the patterns of TRAb changes on patient prognosis according to the treatment duration of antithyroid drugs (ATDs) are not well established.
Methods
In this retrospective cohort study, 1,235 patients with Graves’ hyperthyroidism who were treated with ATDs for more than 12 months were included. Patients were divided into two groups according to treatment duration: group 1 (12–24 months) and group 2 (>24 months). Risk prediction models comprising age, sex, and either TRAb levels at ATD withdrawal (model A) or patterns of TRAb changes (model B) were compared.
Results
The median treatment duration in groups 1 (n=667, 54%) and 2 (n=568, 46%) was 17.3 and 37.1 months, respectively. The recurrence rate was significantly higher in group 2 (47.9%) than in group 1 (41.4%, P=0.025). Group 2 had significantly more goiter, thyroid eye disease, and fluctuating and smoldering type of TRAb pattern compared with group 1 (all P<0.001). The patterns of TRAb changes were an independent risk factor for recurrence after adjusting for other confounding factors in all patients, except in group 1. Integrated discrimination improvement and net reclassification improvement analyses showed that model B performed better than model A in all patients, except in group 1.
Conclusion
The dynamic risk model, including the patterns of TRAb changes, was more suitable for predicting prognosis in patients with Graves’ hyperthyroidism who underwent longer ATD treatment duration.
- Thyroid
- Prognostic Roles of Inflammatory Biomarkers in Radioiodine-Refractory Thyroid Cancer Treated with Lenvatinib
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Chae A Kim, Mijin Kim, Meihua Jin, Hee Kyung Kim, Min Ji Jeon, Dong Jun Lim, Bo Hyun Kim, Ho-Cheol Kang, Won Bae Kim, Dong Yeob Shin, Won Gu Kim
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Endocrinol Metab. 2024;39(2):334-343. Published online April 4, 2024
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DOI: https://doi.org/10.3803/EnM.2023.1854
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Abstract
PDFSupplementary MaterialPubReader ePub
- Background
Inflammatory biomarkers, such as the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR), serve as valuable prognostic indicators in various cancers. This multicenter, retrospective cohort study assessed the treatment outcomes of lenvatinib in 71 patients with radioactive iodine (RAI)-refractory thyroid cancer, considering the baseline inflammatory biomarkers.
Methods
This study retrospectively included patients from five tertiary hospitals in Korea whose complete blood counts were available before lenvatinib treatment. Progression-free survival (PFS) and overall survival (OS) were evaluated based on the median value of inflammatory biomarkers.
Results
No significant differences in baseline characteristics were observed among patients grouped according to the inflammatory biomarkers, except for older patients with a higher-than-median NLR (≥2) compared to their counterparts with a lower NLR (P= 0.01). Patients with a higher-than-median NLR had significantly shorter PFS (P=0.02) and OS (P=0.017) than those with a lower NLR. In multivariate analysis, a higher-than-median NLR was significantly associated with poor OS (hazard ratio, 3.0; 95% confidence interval, 1.24 to 7.29; P=0.015). However, neither the LMR nor the PLR was associated with PFS. A higher-than-median LMR (≥3.9) was significantly associated with prolonged OS compared to a lower LMR (P=0.036). In contrast, a higher-than-median PLR (≥142.1) was associated with shorter OS compared to a lower PLR (P=0.039).
Conclusion
Baseline inflammatory biomarkers can serve as predictive indicators of PFS and OS in patients with RAI-refractory thyroid cancer treated with lenvatinib.
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