Edouard F. Bonneville , Johannes Schetelig , Hein Putter , Liesbeth C. de Wreede
{"title":"Handling missing covariate data in clinical studies in haematology","authors":"Edouard F. Bonneville , Johannes Schetelig , Hein Putter , Liesbeth C. de Wreede","doi":"10.1016/j.beha.2023.101477","DOIUrl":null,"url":null,"abstract":"<div><p>Missing data are frequently encountered across studies in clinical haematology. Failure to handle these missing values in an appropriate manner can complicate the interpretation of a study's findings, as estimates presented may be biased and/or imprecise. In the present work, we first provide an overview of current methods for handling missing covariate data, along with their advantages and disadvantages. Furthermore, a systematic review is presented, exploring both contemporary reporting of missing values in major haematological journals, and the methods used for handling them. A principal finding was that the method of handling missing data was explicitly specified in a minority of articles (in 76 out of 195 articles reporting missing values, 39%). Among these, complete case analysis and the missing indicator method were the most common approaches to dealing with missing values, with more complex methods such as multiple imputation being extremely rare (in 7 out of 195 articles). An example analysis (with associated code) is also provided using hematopoietic stem cell transplantation data, illustrating the different approaches to handling missing values. We conclude with various recommendations regarding the reporting and handling of missing values for future studies in clinical haematology.</p></div>","PeriodicalId":8744,"journal":{"name":"Best Practice & Research Clinical Haematology","volume":null,"pages":null},"PeriodicalIF":2.2000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Best Practice & Research Clinical Haematology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1521692623000385","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"HEMATOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Missing data are frequently encountered across studies in clinical haematology. Failure to handle these missing values in an appropriate manner can complicate the interpretation of a study's findings, as estimates presented may be biased and/or imprecise. In the present work, we first provide an overview of current methods for handling missing covariate data, along with their advantages and disadvantages. Furthermore, a systematic review is presented, exploring both contemporary reporting of missing values in major haematological journals, and the methods used for handling them. A principal finding was that the method of handling missing data was explicitly specified in a minority of articles (in 76 out of 195 articles reporting missing values, 39%). Among these, complete case analysis and the missing indicator method were the most common approaches to dealing with missing values, with more complex methods such as multiple imputation being extremely rare (in 7 out of 195 articles). An example analysis (with associated code) is also provided using hematopoietic stem cell transplantation data, illustrating the different approaches to handling missing values. We conclude with various recommendations regarding the reporting and handling of missing values for future studies in clinical haematology.
期刊介绍:
Best Practice & Research Clinical Haematology publishes review articles integrating the results from the latest original research articles into practical, evidence-based review articles. These articles seek to address the key clinical issues of diagnosis, treatment and patient management. Each issue follows a problem-orientated approach which focuses on the key questions to be addressed, clearly defining what is known and not known, covering the spectrum of clinical and laboratory haematological practice and research. Although most reviews are invited, the Editor welcomes suggestions from potential authors.