Cinacalcet use in secondary hyperparathyroidism: a machine learning-based systematic review

被引:4
|
作者
Li, Xiaosong [1 ]
Ding, Wei [1 ]
Zhang, Hong [1 ]
机构
[1] Jilin Univ, Hosp 2, Dept Thyroid Surg, Changchun, Jilin, Peoples R China
来源
FRONTIERS IN ENDOCRINOLOGY | 2023年 / 14卷
关键词
calcimimetics; FGF-23; bibliometrics; LDA analysis; machine learning; CARDIOVASCULAR-DISEASE; VASCULAR CALCIFICATION; HEMODIALYSIS-PATIENTS; HCL THERAPY; EVENTS; ETELCALCETIDE; MANAGEMENT; FGF-23;
D O I
10.3389/fendo.2023.1146955
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
IntroductionThis study aimed to systematically review research on cinacalcet and secondary hyperparathyroidism (SHPT) using machine learning-based statistical analyses. MethodsPublications indexed in the Web of Science Core Collection database on Cinacalcet and SHPT published between 2000 and 2022 were retrieved. The R package "Bibliometrix," VOSviewer, CiteSpace, meta, and latent Dirichlet allocation (LDA) in Python were used to generate bibliometric and meta-analytical results. ResultsA total of 959 articles were included in our bibliometric analysis. In total, 3753 scholars from 54 countries contributed to this field of research. The United States, Japan, and China were found to be among the three most productive countries worldwide. Three Japanese institutions (Showa University, Tokai University, and Kobe University) published the most articles on Cinacalcet and SHPT. Fukagawa, M.; Chertow, G.M.; Goodman W.G. were the three authors who published the most articles in this field. Most articles were published in Nephrology Dialysis Transplantation, Kidney International, and Therapeutic Apheresis and Dialysis. Research on Cinacalcet and SHPT has mainly included three topics: 1) comparative effects of various treatments, 2) the safety and efficacy of cinacalcet, and 3) fibroblast growth factor-23 (FGF-23). Integrated treatments, cinacalcet use in pediatric chronic kidney disease, and new therapeutic targets are emerging research hotspots. Through a meta-analysis, we confirmed the effects of Cinacalcet on reducing serum PTH (SMD = -0.56, 95% CI = -0.76 to -0.37, p = 0.001) and calcium (SMD = -0.93, 95% CI = -1.21to -0.64, p = 0.001) and improving phosphate (SMD = 0.17, 95% CI = -0.33 to -0.01, p = 0.033) and calcium-phosphate product levels (SMD = -0.49, 95% CI = -0.71 to -0.28, p = 0.001); we found no difference in all-cause mortality (RR = 0.97, 95% CI = 0.90 to 1.05, p = 0.47), cardiovascular mortality (RR = 0.69, 95% CI = 0.36 to 1.31, p = 0.25), and parathyroidectomy (RR = 0.36, 95% CI = 0.09 to 1.35, p = 0.13) between the Cinacalcet and non-Cinacalcet users. Moreover, Cinacalcet was associated with an increased risk of nausea (RR = 2.29, 95% CI = 1.73 to 3.05, p = 0.001), hypocalcemia (RR = 4.05, 95% CI = 2.33 to 7.04, p = 0.001), and vomiting (RR = 1.90, 95% CI = 1.70 to 2.11, p = 0.001). DiscussionThe number of publications indexed to Cinacalcet and SHPT has increased rapidly over the past 22 years. Literature distribution, research topics, and emerging trends in publications on Cinacalcet and SHPT were analyzed using a machine learning-based bibliometric review. The findings of this meta-analysis provide valuable insights into the efficacy and safety of cinacalcet for the treatment of SHPT, which will be of interest to both clinical and researchers.
引用
收藏
页数:16
相关论文
共 50 条
  • [1] Review of cinacalcet hydrochloride in the management of secondary hyperparathyroidism
    Yousaf, Farhanah
    Charytan, Chaim
    RENAL FAILURE, 2014, 36 (01) : 131 - 138
  • [2] Cinacalcet A Pharmacoeconomic Review of its Use in Secondary Hyperparathyroidism in End-Stage Renal Disease
    Plosker, Greg L.
    PHARMACOECONOMICS, 2011, 29 (09) : 807 - 821
  • [3] Machine learning-based computation offloading in edge and fog: a systematic review
    Taheri-abed, Sanaz
    Moghadam, Amir Masoud Eftekhari
    Rezvani, Mohammad Hossein
    CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2023, 26 (05): : 3113 - 3144
  • [4] Machine learning-based computation offloading in edge and fog: a systematic review
    Sanaz Taheri-abed
    Amir Masoud Eftekhari Moghadam
    Mohammad Hossein Rezvani
    Cluster Computing, 2023, 26 : 3113 - 3144
  • [5] Machine Learning-Based Opinion Spam Detection: A Systematic Literature Review
    Qazi, Atika
    Hasan, Najmul
    Mao, Rui
    Elhag Mohamed Abo, Mohamed
    Kumar Dey, Samrat
    Hardaker, Glenn
    IEEE ACCESS, 2024, 12 : 143485 - 143499
  • [6] Machine learning-based farm risk management: A systematic mapping review
    Ghaffarian, Saman
    van der Voort, Mariska
    Valente, Joao
    Tekinerdogan, Bedir
    de Mey, Yann
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2022, 192
  • [7] Machine learning-based heart disease diagnosis: A systematic literature review
    Ahsan, Md Manjurul
    Siddique, Zahed
    ARTIFICIAL INTELLIGENCE IN MEDICINE, 2022, 128
  • [8] Machine and Deep Learning-based XSS Detection Approaches: A Systematic Literature Review
    Thajeel, Isam Kareem
    Samsudin, Khairulmizam
    Hashim, Shaiful Jahari
    Hashim, Fazirulhisyam
    JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES, 2023, 35 (07)
  • [9] Machine Learning-Based Edge Placement Error Analysis and Optimization: A Systematic Review
    Ngo, Anh Tuan
    Dey, Bappaditya
    Halder, Sandip
    De Gendt, Stefan
    Wang, Changhai
    IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING, 2023, 36 (01) : 1 - 13
  • [10] Machine Learning-Based Predictive Models for Patients with Venous Thromboembolism: A Systematic Review
    Danilatou, Vasiliki
    Dimopoulos, Dimitrios
    Kostoulas, Theodoros
    Douketis, James
    THROMBOSIS AND HAEMOSTASIS, 2024, 124 (11) : 1040 - 1052