著者 |
Gonçalves, Bronner P.
Faculty of Health and Medical Sciences, University of Surrey
Suzuki, Etsuji
Department of Epidemiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
Kaken ID
publons
researchmap
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抄録 | Epidemiologic analyses that aim to quantify exposure effects on disease progression are not uncommon. Understanding the implications of these studies, however, is complicated, in part because different causal estimands could, at least in theory, be the target of such analyses. Here, to facilitate interpretation of these studies, we describe different settings in which causal questions related to disease progression can be asked, and consider possible estimands. For clarity, our discussion is structured around settings defined based on two factors: whether the disease occurrence is manipulable or not, and the type of outcome. We describe relevant causal structures and sets of response types, which consist of joint potential outcomes of disease occurrence and disease progression, and argue that settings where interventions to manipulate disease occurrence are not plausible are more common, and that, in this case, principal stratification might be an appropriate framework to conceptualize the analysis. Further, we suggest that the precise definition of the outcome of interest, in particular of what constitutes its permissible levels, might determine whether potential outcomes linked to disease progression are definable in different strata of the population. Our hope is that this paper will encourage additional methodological work on causal analysis of disease progression, as well as serve as a resource for future applied studies.
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キーワード | disease progression
causal inference
principal stratification
controlled direct effects
potential outcomes
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備考 | This is a non-final version of an article published in final form in Gonçalves, Bronner P.a; Suzuki, Etsujib. Causal Approaches to Disease Progression Analyses. Epidemiology 36(6):p 732-740, November 2025. | DOI: 10.1097/EDE.0000000000001893.
This fulltext file will be available in Nov. 2026.
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発行日 | 2025-11
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出版物タイトル |
Epidemiology
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巻 | 36巻
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号 | 6号
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出版者 | Ovid Technologies (Wolters Kluwer Health)
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開始ページ | 732
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終了ページ | 740
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ISSN | 1044-3983
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NCID | AA10832184
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資料タイプ |
学術雑誌論文
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言語 |
英語
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OAI-PMH Set |
岡山大学
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著作権者 | © 2025 Wolters Kluwer Health, Inc.
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論文のバージョン | author
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PubMed ID | |
DOI | |
関連URL | isVersionOf https://doi.org/10.1097/ede.0000000000001893
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Citation | Gonçalves, Bronner P.a; Suzuki, Etsujib. Causal Approaches to Disease Progression Analyses. Epidemiology 36(6):p 732-740, November 2025. | DOI: 10.1097/EDE.0000000000001893
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助成情報 |
19KK0418:
因果分析研究とAIによる健康格差縮小プログラム構築とリアルワールドデータへの応用
( 独立行政法人日本学術振興会 / Japan Society for the Promotion of Science )
23K09740:
因果関係の可視化:メカニズムの観点から描くグラフィカルモデルの開発と実用
( 独立行政法人日本学術振興会 / Japan Society for the Promotion of Science )
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