{"title":"Describing and analyzing complex disease history in retrospective studies","authors":"Ariane Boumendil , Myriam Labopin","doi":"10.1016/j.beha.2023.101483","DOIUrl":null,"url":null,"abstract":"<div><p><span>Blood-related diseases<span><span> are complex diseases with diverse origins, treatments and prognosis. In </span>haematology studies, investigators are interested in multiple outcomes and multiple prognostic variables that may change value over the course of follow-up. These time-dependent variables can be of different nature. Time-dependent events such as treatment with haematopoeitic </span></span>stem cell transplant<span> (HCT) and acute or chronic graft-versus-host disease (GVHD) typically interact with outcomes respectively after diagnosis or HCT. Longitudinal measurement such as immune response do influence survival after HCT. Effect of these time-dependent variables on outcomes can be investigated using different approaches, such as time-dependent Cox regression, landmark analysis, multi-state models or joint modelisation. In this paper we review basic principles of these different approaches using examples from haematological studies.</span></p></div>","PeriodicalId":8744,"journal":{"name":"Best Practice & Research Clinical Haematology","volume":"36 3","pages":"Article 101483"},"PeriodicalIF":2.2000,"publicationDate":"2023-09-01","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/S1521692623000440","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
Blood-related diseases are complex diseases with diverse origins, treatments and prognosis. In haematology studies, investigators are interested in multiple outcomes and multiple prognostic variables that may change value over the course of follow-up. These time-dependent variables can be of different nature. Time-dependent events such as treatment with haematopoeitic stem cell transplant (HCT) and acute or chronic graft-versus-host disease (GVHD) typically interact with outcomes respectively after diagnosis or HCT. Longitudinal measurement such as immune response do influence survival after HCT. Effect of these time-dependent variables on outcomes can be investigated using different approaches, such as time-dependent Cox regression, landmark analysis, multi-state models or joint modelisation. In this paper we review basic principles of these different approaches using examples from haematological studies.
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.
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