Meta-analysis of the difference of medians

被引:127
|
作者
McGrath, Sean [1 ,3 ]
Sohn, Hojoon [2 ]
Steele, Russell [1 ]
Benedetti, Andrea [3 ,4 ]
机构
[1] McGill Univ, Dept Math & Stat, Montreal, PQ, Canada
[2] Johns Hopkins Univ, Bloomberg Sch Publ Hlth, Dept Epidemiol, Baltimore, MD USA
[3] McGill Univ, Resp Epidemiol & Clin Res Unit, Hlth Ctr, Montreal, PQ, Canada
[4] McGill Univ, Dept Med, Montreal, PQ, Canada
关键词
median; meta-analysis; quantile estimation; skewed data; two-group; RANDOM-EFFECTS MODELS; TUBERCULOSIS; DIAGNOSIS; FEASIBILITY; MULTICENTER; PNEUMONIA; ACCURACY; OUTCOMES; CANCER; INDIA;
D O I
10.1002/bimj.201900036
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
We consider the problem of meta-analyzing two-group studies that report the median of the outcome. Often, these studies are excluded from meta-analysis because there are no well-established statistical methods to pool the difference of medians. To include these studies in meta-analysis, several authors have recently proposed methods to estimate the sample mean and standard deviation from the median, sample size, and several commonly reported measures of spread. Researchers frequently apply these methods to estimate the difference of means and its variance for each primary study and pool the difference of means using inverse variance weighting. In this work, we develop several methods to directly meta-analyze the difference of medians. We conduct a simulation study evaluating the performance of the proposed median-based methods and the competing transformation-based methods. The simulation results show that the median-based methods outperform the transformation-based methods when meta-analyzing studies that report the median of the outcome, especially when the outcome is skewed. Moreover, we illustrate the various methods on a real-life data set.
引用
收藏
页码:69 / 98
页数:30
相关论文
共 50 条
  • [41] Accurate confidence intervals for risk difference in meta-analysis with rare events
    Tao Jiang
    Baixin Cao
    Guogen Shan
    BMC Medical Research Methodology, 20
  • [42] A Bayesian Meta-analysis Method for Estimating Risk Difference of Rare Events
    Tang, Yuanyuan
    Tang, Qi
    Yu, Yao
    Wen, Shihua
    JOURNAL OF BIOPHARMACEUTICAL STATISTICS, 2018, 28 (03) : 550 - 561
  • [43] A Risk-Difference Meta-Analysis for the Prophylactic Treatments of Chronic Migraine
    Kodounis, Michalis
    Constantinidis, Theodoros S.
    Rizonaki, Konstantina
    Drakou, Eleni
    Zintzaras, Elias
    Stefanidis, Ioannis
    Mitsikostas, Dimos-Dimitrios
    Dardiotis, Efthimios
    CUREUS JOURNAL OF MEDICAL SCIENCE, 2024, 16 (06)
  • [44] Diagnostic value of mesothelinin pancreatic cancer: a meta-analysis
    Zhu, Lin
    Liu, Yiling
    Chen, Guangyuan
    INTERNATIONAL JOURNAL OF CLINICAL AND EXPERIMENTAL MEDICINE, 2014, 7 (11): : 4000 - 4007
  • [45] Diagnostic value of microRNA for pancreatic cancer: a meta-analysis
    Wan, Chun
    Shen, Yongchun
    Yang, Ting
    Wang, Tao
    Chen, Lei
    Wen, Fuqiang
    ARCHIVES OF MEDICAL SCIENCE, 2012, 8 (05) : 749 - 755
  • [46] Circular RNA as a biomarker for cancer: A systematic meta-analysis
    Li, Yulong
    Zeng, Xiaoli
    He, Jianxun
    Gui, Yuan
    Zhao, Song
    Chen, Hua
    Sun, Qi
    Jia, Nan
    Yuan, Hui
    ONCOLOGY LETTERS, 2018, 16 (03) : 4078 - 4084
  • [47] Accurate confidence intervals for risk difference in meta-analysis with rare events
    Jiang, Tao
    Cao, Baixin
    Shan, Guogen
    BMC MEDICAL RESEARCH METHODOLOGY, 2020, 20 (01)
  • [48] Quality of life in "chronic" cancer survivors: a meta-analysis
    Firkins, Jenny
    Hansen, Lissi
    Driessnack, Martha
    Dieckmann, Nathan
    JOURNAL OF CANCER SURVIVORSHIP, 2020, 14 (04) : 504 - 517
  • [49] Corticosteroids and Intravenous Immunoglobulin in Pediatric Myocarditis: A Meta-Analysis
    Li, Yining
    Yu, Yuqing
    Chen, Selena
    Liao, Ying
    Dui, Junbao
    FRONTIERS IN PEDIATRICS, 2019, 7
  • [50] Critical prognostic factors for poststroke dysphagia: a meta-analysis
    Liu, C. H.
    Huo, M.
    Qin, H. H.
    Zhao, B. L.
    EUROPEAN REVIEW FOR MEDICAL AND PHARMACOLOGICAL SCIENCES, 2022, 26 (02) : 610 - 622