Endocrinology and Metabolism

Original Article

Thyroid
BRAF Mutation and Tumor Growth Kinetics during Active Surveillance of Papillary Thyroid Microcarcinoma: A Single-Center Retrospective Study: Jinyoung Kim, Min Kyoung Lee, Tae-Jung Kim, Dong-Jun Lim, Ki-Hyun Baek; Endocrinol Metab. 2026;41(3):461-469. Published online June 9, 2026; DOI: https://doi.org/10.3803/EnM.2025.2821

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Abstract PDF Supplementary Material PubReader ePub: Background
We investigated tumor volume doubling time (TVDT) during active surveillance of papillary thyroid microcarcinoma (PTMC) and reviewed clinical factors including BRAF mutation associated with tumor progression.
Methods
Patients with PTMC who deferred surgery for more than 1 year after diagnosis between 2014 and 2021 and were followed until 2023 were enrolled. Inclusion criteria were papillary thyroid carcinoma confirmed by fine needle aspiration cytology (Bethesda categories V–VI), maximal tumor diameter ≤1 cm, and available BRAF mutation testing.
Results
A total of 85 patients were included. The median age was 49 years, and 63 patients (74%) were female. The positivity rate for BRAF mutation was 51% in the study cohort, and 16 patients (19%) showed rapid-growing disease, defined by a TVDT of less than 5 years. The median follow-up duration was 4.4 years, and 23 patients (27%) underwent surgery after a median of 3.2 years. When TVDT groups were analyzed using logistic regression, sonographic features with microcalcification were associated with tumor growth in binary regression (odds ratio for the group combining slowly and rapid-growing disease was 4.34; 95% confidence interval [CI], 1.41 to 13.35; P=0.010), and BRAF mutation was associated with rapid-growing disease in multinomial regression (odds ratio for rapid-growing disease was 4.48; 95% CI, 1.08 to 18.51; P=0.038).
Conclusion
BRAF mutation is presumed to be associated with tumor progression and may predict growth of PTMC. Genetic testing including BRAF testing may help distinguishing rapid-growing thyroid cancer.

Review Article

Mineral, Bone & Muscle
Long-Term Efficacy and Safety of Denosumab: Insights beyond 10 Years of Use: Jeonghoon Ha, Youn-Ju Lee, Jinyoung Kim, Chaiho Jeong, Yejee Lim, Jeongmin Lee, Ki-Hyun Baek, on Behalf of the Catholic Medical Center Bone Research Group; Endocrinol Metab. 2025;40(1):47-56. Published online January 13, 2025; DOI: https://doi.org/10.3803/EnM.2024.2125

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Osteoporosis management in post-menopausal women focuses on fracture prevention, with denosumab as a key therapeutic option. Despite its proven efficacy in reducing fracture risk and increasing bone mineral density (BMD) over 10 years, its long-term impact remains uncertain. We evaluated the literature on its efficacy and safety beyond the initial decade. Clinical trials and real-world studies confirm denosumab’s sustained efficacy, especially in lumbar spine BMD, with hip BMD stabilizing. Concerns about adverse events (AEs) like hypocalcemia and osteonecrosis of the jaw necessitate vigilant monitoring. Risks of atypical femoral fractures and malignancies also require attention, despite unclear links to treatment duration. Clinical guidelines for denosumab beyond 10 years are limited, emphasizing the need for careful monitoring. In certain scenarios, such as advanced chronic kidney disease, prolonged denosumab may be required to balance AE risks with fracture prevention benefits. Denosumab shows potential for long-term efficacy in augmenting BMD; however, monitoring for AEs is crucial to guide clinical decision-making effectively.

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Matthias Gunzer
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Original Articles

Thyroid
Deep Learning Technology for Classification of Thyroid Nodules Using Multi-View Ultrasound Images: Potential Benefits and Challenges in Clinical Application: Jinyoung Kim, Min-Hee Kim, Dong-Jun Lim, Hankyeol Lee, Jae Jun Lee, Hyuk-Sang Kwon, Mee Kyoung Kim, Ki-Ho Song, Tae-Jung Kim, So Lyung Jung, Yong Oh Lee, Ki-Hyun Baek; Endocrinol Metab. 2025;40(2):216-224. Published online January 13, 2025; DOI: https://doi.org/10.3803/EnM.2024.2058

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Background
This study aimed to evaluate the applicability of deep learning technology to thyroid ultrasound images for classification of thyroid nodules.
Methods
This retrospective analysis included ultrasound images of patients with thyroid nodules investigated by fine-needle aspiration at the thyroid clinic of a single center from April 2010 to September 2012. Thyroid nodules with cytopathologic results of Bethesda category V (suspicious for malignancy) or VI (malignant) were defined as thyroid cancer. Multiple deep learning algorithms based on convolutional neural networks (CNNs) —ResNet, DenseNet, and EfficientNet—were utilized, and Siamese neural networks facilitated multi-view analysis of paired transverse and longitudinal ultrasound images.
Results
Among 1,048 analyzed thyroid nodules from 943 patients, 306 (29%) were identified as thyroid cancer. In a subgroup analysis of transverse and longitudinal images, longitudinal images showed superior prediction ability. Multi-view modeling, based on paired transverse and longitudinal images, significantly improved the model performance; with an accuracy of 0.82 (95% confidence intervals [CI], 0.80 to 0.86) with ResNet50, 0.83 (95% CI, 0.83 to 0.88) with DenseNet201, and 0.81 (95% CI, 0.79 to 0.84) with EfficientNetv2_ s. Training with high-resolution images obtained using the latest equipment tended to improve model performance in association with increased sensitivity.
Conclusion
CNN algorithms applied to ultrasound images demonstrated substantial accuracy in thyroid nodule classification, indicating their potential as valuable tools for diagnosing thyroid cancer. However, in real-world clinical settings, it is important to aware that model performance may vary depending on the quality of images acquired by different physicians and imaging devices.

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Molecular intelligence and immune reconnaissance in thyroid cancer: a new paradigm for diagnosis, risk stratification, and therapeutic precision
Marcio J. Concepción-Zavaleta, Jenyfer M. Fuentes-Mendoza, Alfredo Cruz-Quintá, Argelia V. Cadena-Guerrero, Ximena Barrón, Luis Concepción-Urteaga, Cristian D. Armas, José Paz-Ibarra, Juan Eduardo Quiroz-Aldave
Expert Review of Anticancer Therapy.2026; 26(5): 585. CrossRef
Deep Learning for Ultrasound Classification to Identify Noninvasive Follicular Thyroid Neoplasms with Papillary–Like Nuclear Features
I-Hung Chien, Yi-Chiung Hsu, Shih-Ping Cheng
Journal of Imaging Informatics in Medicine.2026;[Epub] CrossRef
Knowledge-Prompted Trustworthy Disentangled Learning for Thyroid Ultrasound Segmentation With Limited Annotations
Wenxu Wang, Weizhen Wang, Qianjin Feng, Yu Zhang, Zhenyuan Ning
IEEE Transactions on Image Processing.2026; 35: 983. CrossRef
Integrating Robotic Bilateral Axillo-Breast Approach Thyroidectomy with Molecular Diagnostics and Artificial Intelligence in Thyroid Cancer Care
Qiang Deng, Xiaoping Men, Duo Jin, Yuzhuo Bai
Biomolecules & Therapeutics.2026; 34(1): 45. CrossRef
Improving Non-Invasive Prediction of Thyroid Nodule Malignancy: A Machine Learning-Based Clinical Approach
Maja Reiner, Hanna Drobińska, Michał Miciak, Michał Kisiel, Szymon Biernat, Krzysztof Kaliszewski
Cancer Management and Research.2026; Volume 18: 1. CrossRef
An early evaluation of MedSigLIP in thyroid cytology: a comparative frozen-encoder benchmark against ImageNet-pretrained encoders
Mehmet Poyrazer, Rıdvan Erten
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The Role of Cytology, Histology and Molecular Pathology in the Diagnostic Process of Thyroid Nodules
Mathilde Ribeiro, Sule Canberk, Massimo Bongiovanni
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Classification of Thyroid Nodules from Ultrasound Images Using Deep Learning Methods
Mehmet Emre Özbey, Mehmet Kaplan, Sercan Yalçın, Muhammed Yıldırım
Muş Alparslan Üniversitesi Fen Bilimleri Dergisi.2026; 14(1): 95. CrossRef
Explainable AI for accurate diagnosis of papillary thyroid carcinoma via fine-needle aspiration cytopathology
Ahmet Kilicarslan, Canan Tastimur, Gokhan Gundogdu, Erhan Akin
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Artificial intelligence-assisted risk stratification of thyroid nodules with atypia of undetermined significance
Jinyoung Kim, Jeongmin Lee, Jeonghoon Ha, Ohjoon Kwon, Ki-Hyun Baek, Chang Myeon Song, Hyeon A Lee, Hyemi Kwon, Inyoung Youn, Mi-ri Kwon, Dong-Jun Lim
European Thyroid Journal.2026;[Epub] CrossRef
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Huajie Ding, Lei Na, Meiling Hao, Wanlou Chen, Zhen Zhang
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Jing Zhao, Li-Juan Du, Ying Liu, Dan-Dan Zhu, Hui-Qing Wang, Ming-Kui Shen, Ling-Yue Wang, Hai-Yan Wang
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Dehui Qiao, Weiting Huang, Xiaoyu Chen, Maolin Fang, Linjun Xie, Yongsheng Luo, Xiangyu Zhou
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Haolun Ding, Shuangshuang Zhao, Yanwei Chen, Xin Zhang, Zheng Zhang, Jing Yang, Qi Ren, Baoding Chen
Journal of Imaging Informatics in Medicine.2026;[Epub] CrossRef
Artificial intelligence in thyroid nodules and cancer: clinical validation and real-world performance
Mustafa Sahin, Nikolaos George Angelopoulos, Rodis D Paparodis
Endocrine Connections.2026;[Epub] CrossRef
Transforming the Imaging Assessment of Thyroid Nodules with Artificial Intelligence: Advancements and Clinical Integration
Sanaz Vahdati, Kathryn A. Robinson, M. Regina Castro, Marius N. Stan, Kuan Zhang, Bradley J. Erickson
Journal of Imaging Informatics in Medicine.2026;[Epub] CrossRef
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Sarkheel Sarshar, Noor-ul-Huda Bhatti, Momina Amir, Nida Jaffar, Muhammad Hasnain, Syed Ghazi Ali Kirmani, Raza Hussain, Shayan Khalid Ghaloo
Turkish Journal of Surgery.2026;[Epub] CrossRef
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Rili Gao, Shangqing Mai, Song Wang, Wuqiang Hu, Zhangqi Chang, Guozhi Wu, Haixia Guan
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Artificial Intelligence for Thyroid Ultrasound: Clinical Performance, Pitfalls, and Practice Integration
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Mineral, Bone & Muscle Big Data Articles (National Health Insurance Service Database)
Association between Smoking Status and the Risk of Hip Fracture in Patients with Type 2 Diabetes: A Nationwide Population-Based Study: Se-Won Lee, Jun-Young Heu, Ju-Yeong Kim, Jinyoung Kim, Kyungdo Han, Hyuk-Sang Kwon; Endocrinol Metab. 2023;38(6):679-689. Published online December 6, 2023; DOI: https://doi.org/10.3803/EnM.2023.1760

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Background
Limited longitudinal evidence exists regarding the potential association between smoking status and hip fracture among individuals with type 2 diabetes. We investigated this association using large-scale, nationwide cohort data for the Korean population.
Methods
This nationwide cohort study included 1,414,635 adults aged 40 and older who received Korean National Health Insurance Service health examinations between 2009 and 2012. Subjects with type 2 diabetes were categorized according to their smoking status, amount smoked (pack-years), number of cigarettes smoked per day, and duration of smoking. The results are presented as hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations between smoking status parameters and risk of hip fracture in multivariable Cox proportional hazard regression analysis.
Results
Compared with never-smokers, an increased adjusted HR (aHR) for hip fracture was observed in current smokers (1.681; 95% CI, 1.578 to 1.791), and a comparable aHR for hip fracture was found in former smokers (1.065; 95% CI, 0.999 to 1.136). For former smokers who had smoked 20 pack-years or more, the risk was slightly higher than that for never-smokers (aHR, 1.107; 95% CI, 1.024 to 1.196). The hip fracture risk of female former smokers was similar to that of female current smokers, but the hip fracture risk in male former smokers was similar to that of male never-smokers.
Conclusion
Smoking is associated with an increased risk of hip fracture in patients with type 2 diabetes. Current smokers with diabetes should be encouraged to quit smoking because the risk of hip fracture is greatly reduced in former smokers.

Citations

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Hip fractures and type 2 diabetes in the elderly: Risk factors analysis of the Nedices cohort
Federico Hawkins Carranza, Cristina Martín-Arriscado Arroba, Arturo Corbatón-Anchuelo, Guillermo Martínez Díaz-Guerra, Félix Bermejo Pareja
Diabetes & Metabolism.2025; 51(4): 101656. CrossRef
Bone Health in Type 1 and Type 2 Diabetes: Pathophysiological Mechanisms, Clinical Implications, and Management Strategies
Hermine Carine Pouabe Epse Bodah, Suraiya Rahman Shifa, Sara Saleh, Tuba Abeer Hashmi, Tuleen Al Shawa, Badreshiya Kajal Akshaykumar, Nabeel Sufwan, Rajvinder Kaur, Andrii Shevchuk, Usman Ul Haq, Manju Rai
SN Comprehensive Clinical Medicine.2025;[Epub] CrossRef
Inflammatory impact of cigarette smoking on bone function and structure; a review of evidence
Yashar Shahbaz, Rasoul Shirmohammadi, Shirin Shamsghahfarokhi, Hooman Esfahani, Mobin Forghan, Hojjat Eghbali Jelodar, Leila Ashrafi, Mohammad Mousavi
Journal of Parathyroid Disease.2025; 13: e13302. CrossRef
Influence of quitting smoking on diabetes-related complications: A scoping review with a systematic search strategy
Magdalena Walicka, Arkadiusz Krysiński, Giusy Rita Maria La Rosa, Ang Sun, Davide Campagna, Agostino Di Ciaula, Tabinda Dugal, Andre Kengne, Phuong Le Dinh, Anoop Misra, Riccardo Polosa, Syed Abbas Raza, Cristina Russo, Roberta Sammut, Noel Somasundaram
Diabetes & Metabolic Syndrome: Clinical Research & Reviews.2024; 18(5): 103044. CrossRef

Mineral, Bone & Muscle
Persistence with Denosumab in Male Osteoporosis Patients: A Real-World, Non-Interventional Multicenter Study: Chaiho Jeong, Jeongmin Lee, Jinyoung Kim, Jeonghoon Ha, Kwanhoon Jo, Yejee Lim, Mee Kyoung Kim, Hyuk-Sang Kwon, Tae-Seo Sohn, Ki-Ho Song, Moo Il Kang, Ki-Hyun Baek; Endocrinol Metab. 2023;38(2):260-268. Published online April 27, 2023; DOI: https://doi.org/10.3803/EnM.2023.1663

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Background
Persistence with denosumab in male patients has not been adequately investigated, although poor denosumab persistence is associated with a significant risk of rebound vertebral fractures.
Methods
We retrospectively evaluated 294 Korean male osteoporosis patients treated with denosumab at three medical centers and examined their persistence with four doses of denosumab injection over 24 months of treatment. Persistence was defined as the extent to which a patient adhered to denosumab treatment in terms of the prescribed interval and dose, with a permissible gap of 8 weeks. For patients who missed their scheduled treatment appointment(s) during the follow-up period (i.e., no-shows), Cox proportional regression analysis was conducted to explore the factors associated with poor adherence. Several factors were considered, such as age, prior anti-osteoporotic drug use, the treatment provider’s medical specialty, the proximity to the medical center, and financial burdens of treatment.
Results
Out of 294 male patients, 77 (26.2%) completed all four sequential rounds of the denosumab treatment. Out of 217 patients who did not complete the denosumab treatment, 138 (63.6%) missed the scheduled treatment(s). Missing treatment was significantly associated with age (odds ratio [OR], 1.03), prior bisphosphonate use (OR, 0.76), and prescription by non-endocrinologists (OR, 2.24). Denosumab was stopped in 44 (20.3%) patients due to medical errors, in 24 (11.1%) patients due to a T-score improvement over –2.5, and in five (2.3%) patients due to expected dental procedures.
Conclusion
Our study showed that only one-fourth of Korean male osteoporosis patients were fully adherent to 24 months of denosumab treatment.

Citations

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Follow-on osteoporosis therapy after denosumab discontinuation among Medicare beneficiaries
Selvam R. Sendhil, Suzanne M. Cadarette, Sulbh Aggarwal, Arman Oganisian, Andrew R. Zullo, Sarah D. Berry, Michael A. Adegboye, Kaleen N. Hayes
Osteoporosis International.2026; 37(1): 81. CrossRef
Denosumab safety in men with osteoporosis: a disproportionality analysis of the FAERS database
Hou-hong Li, Li Wan, Si-jie He, Wen-long Xie
Naunyn-Schmiedeberg's Archives of Pharmacology.2026; 399(11): 16915. CrossRef
Denosumab

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Thyroid Big Data Articles (National Health Insurance Service Database)
Repeated Low High-Density Lipoprotein Cholesterol and the Risk of Thyroid Cancer: A Nationwide Population- Based Study in Korea: Jinyoung Kim, Mee Kyoung Kim, Ki-Hyun Baek, Ki-Ho Song, Kyungdo Han, Hyuk-Sang Kwon; Endocrinol Metab. 2022;37(2):303-311. Published online April 6, 2022; DOI: https://doi.org/10.3803/EnM.2021.1332

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Background
High-density lipoprotein cholesterol (HDL-C) plays an important role in the reverse cholesterol transport pathway and prevents atherosclerosis-mediated disease. It has also been suggested that HDL-C may be a protective factor against cancer. However, an inverse correlation between HDL-C and cancer has not been established, and few studies have explored thyroid cancer.
Methods
The study participants received health checkups provided by the Korean National Health Insurance Service from 2009 to 2013 and were followed until 2019. Considering the variability of serum HDL-C level, low HDL-C level was analyzed by grouping based on four consecutive health checkups. The data analysis was performed using univariate and multivariate Cox proportional hazard regression models.
Results
A total of 3,134,278 total study participants, thyroid cancer occurred in 16,129. In the crude model, the hazard ratios for the association between repeatedly measured low HDL-C levels and thyroid cancer were 1.243, 1.404, 1.486, and 1.680 (P for trend <0.01), respectively, which were significant even after adjusting for age, sex, lifestyle factors, and metabolic diseases. The subgroup analysis revealed that low HDL-C levels likely had a greater impact on the group of patients with central obesity (P for interaction= 0.062), high blood pressure (P for interaction=0.057), impaired fasting glucose (P for interaction=0.051), and hyperlipidemia (P for interaction=0.126).
Conclusion
Repeatedly measured low HDL-C levels can be considered a risk factor for cancer as well as vascular disease. Low HDL-C levels were associated with the risk of thyroid cancer, and this correlation was stronger in a metabolically unhealthy population.

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