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Urszula Smyczyńska Department of Automatics and Biomedical Engineering, AGH University of Science and Technology, Krakow, Poland

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Joanna Smyczyńska Department of Endocrinology and Metabolic Diseases, Polish Mother’s Memorial Hospital – Research Institute, Lodz, Poland

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Maciej Hilczer Department of Endocrinology and Metabolic Diseases, Polish Mother’s Memorial Hospital – Research Institute, Lodz, Poland
Department of Paediatric Endocrinology, Medical University of Lodz, Lodz, Poland

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Renata Stawerska Department of Endocrinology and Metabolic Diseases, Polish Mother’s Memorial Hospital – Research Institute, Lodz, Poland

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Ryszard Tadeusiewicz Department of Automatics and Biomedical Engineering, AGH University of Science and Technology, Krakow, Poland

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Andrzej Lewiński Department of Endocrinology and Metabolic Diseases, Polish Mother’s Memorial Hospital – Research Institute, Lodz, Poland
Department of Endocrinology and Metabolic Diseases, Medical University of Lodz, Lodz, Poland

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, 12 ). In one model, the total pubertal growth has been predicted ( 14 ). Previously published models have been included as input variables – either only the data available before GH therapy onset or also the information gathered during treatment ( 6

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-17-0277
Volume/Issue:
Volume 7: Issue 1
Open access
Rongpeng Gong Medical College of Qinghai University, Xining, People’s Republic of China

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Yuanyuan Liu Medical College of Qinghai University, Xining, People’s Republic of China

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Gang Luo Medical College of Qinghai University, Xining, People’s Republic of China

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Jiahui Yin College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China

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Zuomiao Xiao Department of Clinical Laboratory, The Affiliated Ganzhou Hospital of Nanchang University, Ganzhou, China

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Tianyang Hu Precision Medicine Center, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China

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identify subjects with IR early. At present, several predictive models for IR have been established. For example, in 2018, Boursier et al. used triglycerides and glycated hemoglobin to predict IR in an obese population ( 15 ). Yeh et al. proposed a

Article Type:
Research Article
Collections:
Metabolic Syndrome and Diabetes
DOI:
https://doi.org/10.1530/EC-22-0066
Volume/Issue:
Volume 11: Issue 7
Open access
Hongyan Wang Department of Urology, Shengjing Hospital of China Medical University, Shenyang, China

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Bin Wu Department of Urology, Shengjing Hospital of China Medical University, Shenyang, China

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Zichuan Yao Department of Urology, Shengjing Hospital of China Medical University, Shenyang, China

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Xianqing Zhu Department of Urology, Shengjing Hospital of China Medical University, Shenyang, China

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Yunzhong Jiang Department of Urology, Shengjing Hospital of China Medical University, Shenyang, China

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Song Bai Department of Urology, Shengjing Hospital of China Medical University, Shenyang, China

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). At present, risk factors related to surgery-associated morbidity remain unclear due to the limited number of studies about this issue and the inconsistency of the conclusions. A nomogram derived from predictive model is accepted as a reliable tool

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-20-0004
Volume/Issue:
Volume 9: Issue 4
Open access
Nidan Qiao Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
Neuroendocrine Unit, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA

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author’s last name, publication time), cohort selection (sample size, diagnosis), predictors (variables fed into the machine learning models), outcomes (the outcomes as well as the controls, including the distributions between them), model selection

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-19-0156
Volume/Issue:
Volume 8: Issue 7
Open access
Yaqian Mao Shengli Clinical Medical College of Fujian Medical University, Fujian, China
Department of Endocrinology, Fujian Provincial Hospital, Fujian, China

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Lizhen Xu Shengli Clinical Medical College of Fujian Medical University, Fujian, China

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Ting Xue Shengli Clinical Medical College of Fujian Medical University, Fujian, China

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Jixing Liang Department of Endocrinology, Fujian Provincial Hospital, Fujian, China

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Wei Lin Department of Endocrinology, Fujian Provincial Hospital, Fujian, China

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Junping Wen Department of Endocrinology, Fujian Provincial Hospital, Fujian, China

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Huibin Huang Department of Endocrinology, Fujian Provincial Hospital, Fujian, China

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Liantao Li Department of Endocrinology, Fujian Provincial Hospital, Fujian, China

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Gang Chen Shengli Clinical Medical College of Fujian Medical University, Fujian, China
Department of Endocrinology, Fujian Provincial Hospital, Fujian, China
Fujian Provincial Key Laboratory of Medical Analysis, Fujian Academy of Medical, Fujian, China

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the occurrence of a disease and to construct a clinical prediction model. Among the various models for predicting disease risk, the nomogram transforms the complex regression equation into a simple and visual graph. Its prediction results are highly

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-21-0330
Volume/Issue:
Volume 10: Issue 9
Open access
Giorgio Bedogni Liver Research Center, Basovizza, Trieste, Italy

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Andrea Mari Institute of Neuroscience, National Research Council, Padova, Italy

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Alessandra De Col Istituto Auxologico Italiano, IRCCS, Experimental Laboratory for Auxo-Endocrinological Research, Piancavallo (VB), Italy

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Sofia Tamini Istituto Auxologico Italiano, IRCCS, Experimental Laboratory for Auxo-Endocrinological Research, Piancavallo (VB), Italy

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Amalia Gastaldelli Institute of Clinical Physiology, National Research Council, Pisa, Italy

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Alessandro Sartorio Istituto Auxologico Italiano, IRCCS, Experimental Laboratory for Auxo-Endocrinological Research, Piancavallo (VB), Italy
Istituto Auxologico Italiano, IRCCS, Division of Metabolic Diseases and Auxology, Piancavallo (VB), Italy

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95% confidence intervals of the four multivariable median regression models using IGI as measure of insulin secretion (ISEC). Standardization was obtained by dividing each continuous predictor by its interquartile range. BMI SDS, standard deviation

Article Type:
Research Article
DOI:
https://doi.org/10.1530/EC-19-0333
Volume/Issue:
Volume 8: Issue 10
Open access
Lu Yang Department of Nuclear Medicine, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China

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Xingguo Jing Department of Nuclear Medicine, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China

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Hua Pang Department of Nuclear Medicine, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China

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Lili Guan Department of Nuclear Medicine, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China

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Mengdan Li Department of Nuclear Medicine, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China

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4D-CT MGD score, and the composite MGD score ( Table 1 ). These MGD clinical models emphasize the value of high specificity. Table 1 Preoperative scoring models. Model Predictive factors Points/categories CaPTHUS

Article Type:
Review Article
Collections:
Bone and Mineral Metabolism
DOI:
https://doi.org/10.1530/EC-23-0492
Volume/Issue:
Volume 13: Issue 5
Open access
Yuegui Wang Department of Ultrasound, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian, China

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Liwei Hong Department of Nuclear Medicine, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian, China

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Caiyun Yang Department of Ultrasound, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian, China
School of Clinical Medicine, Fujian Medical University, Fuzhou, Fujian, China

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Guorong Lv School of Clinical Medicine, Fujian Medical University, Fuzhou, Fujian, China
Quanzhou Medical College, Quanzhou, Fujian, China

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Kangjian Wang Department of Ultrasound, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian, China

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Xuepeng Huang Department of Nuclear Medicine, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian, China

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Haolin Shen Department of Ultrasound, Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian, China

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this study were two-fold: first, to investigate the predictive value of Ki-67 and ultrasound in determining the outcomes of RAI therapy for GD patients and, second, to construct a prediction model. This endeavor seeks to establish a more evidence

Article Type:
Research Article
Collections:
Thyroid
DOI:
https://doi.org/10.1530/EC-23-0429
Volume/Issue:
Volume 13: Issue 2
Open access
Huguette S Brink Department of Endocrinology, Maasstad Hospital, Rotterdam, The Netherlands

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Aart Jan van der Lely Department of Endocrinology, Erasmus University MC, Rotterdam, The Netherlands

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Joke van der Linden Department of Endocrinology, Maasstad Hospital, Rotterdam, The Netherlands

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GD pathogenesis. Combining biomarkers and risk factors into a predictive model may add to early prediction of GD, evoke effective prevention strategies and may ultimately reduce complications associated with GD. The aim of this review is to ( 1

Article Type:
Review Article
DOI:
https://doi.org/10.1530/EC-16-0033
Volume/Issue:
Volume 5: Issue 5
Open access
Maria Luisa Garo Mathsly Research, Roma, Italy

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Désirée Deandreis Division of Nuclear Medicine, Department of Medical Sciences, AOU Città della Salute e della Scienza, University of Turin, Turin, Italy

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Alfredo Campennì Nuclear Medicine Unit, Department of Biomedical and Dental Sciences and Morpho-Functional Imaging, University of Messina, Messina, Italy

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Alexis Vrachimis Department of Nuclear Medicine, German Oncology Center, University Hospital of the European University, Limassol, Cyprus

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Petra Petranovic Ovcaricek Department of Oncology and Nuclear Medicine, University Hospital Center Sestre Milosrdnice, Zagreb, Croatia

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Luca Giovanella Clinic for Nuclear Medicine and Molecular Imaging, Imaging Institute of Southern Switzerland, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
Clinic for Nuclear Medicine, University Hospital of Zürich, Zürich, Switzerland

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stratification ( 31 ). Nomograms are pictorial representations of a mathematical model that incorporates multiple factors to predict a specific endpoint based on statistical methods. By including significant factors, usually determined by logistic or Cox

Article Type:
Research Article
Collections:
Thyroid
DOI:
https://doi.org/10.1530/EC-22-0457
Volume/Issue:
Volume 12: Issue 4
Open access