Standards should be applied in the prevention and handling of missing data for patient-centered outcomes research: a systematic review and expert consensus

被引:53
作者
Li, Tianjing [1 ]
Hutfless, Susan [2 ]
Scharfstein, Daniel O. [3 ]
Daniels, Michael J. [4 ,5 ]
Hogan, Joseph W. [6 ]
Little, Roderick J. A. [7 ]
Roy, Jason A. [8 ]
Law, Andrew H. [9 ]
Dickersin, Kay [1 ]
机构
[1] Johns Hopkins Bloomberg Sch Publ Hlth, Ctr Clin Trials, Dept Epidemiol, Baltimore, MD 21205 USA
[2] Johns Hopkins Sch Med, Div Gastroenterol, Baltimore, MD USA
[3] Johns Hopkins Bloomberg Sch Publ Hlth, Dept Biostat, Baltimore, MD 21205 USA
[4] Univ Texas Austin, Sect Integrat Biol, Austin, TX 78712 USA
[5] Univ Texas Austin, Div Stat & Sci Computat, Austin, TX 78712 USA
[6] Brown Univ, Dept Biostat, Providence, RI 02912 USA
[7] Univ Michigan, Dept Biostat, Ann Arbor, MI 48109 USA
[8] Univ Penn, Dept Biostat & Epidemiol, Perelman Sch Med, Philadelphia, PA 19104 USA
[9] Johns Hopkins Sch Med, Epidemiol Res Grp Organ Transplantat, Baltimore, MD USA
关键词
Preventing missing data; Handling missing data; Patient-centered outcomes research; Methodology standards; Systematic review; Consensus survey; SECONDARY DATA SOURCES; ISPOR TASK-FORCE; RETROSPECTIVE DATABASE; SENSITIVITY-ANALYSIS; TRIALS; IMPUTATION; DESIGN;
D O I
10.1016/j.jclinepi.2013.08.013
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Objectives: To recommend methodological standards in the prevention and handling of missing data for primary patient-centered outcomes research (PCOR). Study Design and Setting: We searched National Library of Medicine Bookshelf and Catalog as well as regulatory agencies' and organizations' Web sites in January 2012 for guidance documents that had formal recommendations regarding missing data. We extracted the characteristics of included guidance documents and recommendations. Using a two-round modified Delphi survey, a multidisciplinary panel proposed mandatory standards on the prevention and handling of missing data for PCOR. Results: We identified 1,790 records and assessed 30 as having relevant recommendations. We proposed 10 standards as mandatory, covering three domains. First, the single best approach is to prospectively prevent missing data occurrence. Second, use of valid statistical methods that properly reflect multiple sources of uncertainty is critical when analyzing missing data. Third, transparent and thorough reporting of missing data allows readers to judge the validity of the findings. Conclusion: We urge researchers to adopt rigorous methodology and promote good science by applying best practices to the prevention and handling of missing data. Developing guidance on the prevention and handling of missing data for observational studies and studies that use existing records is a priority for future research. (C) 2014 Elsevier Inc. All rights reserved.
引用
收藏
页码:15 / 32
页数:18
相关论文
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