{"title":"测量肝硬化患者个体累积发病率的疾病负担。","authors":"Mitchell Paukner , Daniela P. Ladner , CAPriCORN Team, Lihui Zhao","doi":"10.1016/j.jbi.2025.104883","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective:</h3><div>Introduce a new method for evaluating the health history of a patient through the use of multi-type recurrent events data that can aid in the assessment of disease progression and quality of life in a healthcare setting.</div></div><div><h3>Methods:</h3><div>The Disease Burden Score (DBS) is characterized as the area under the Disease Burden Curve (DBC), a monotone, increasing stepwise graph, that measures the weighted or unweighted number of health events that occur during a patient’s follow-up period (i.e. cardiovascular events or decompensation events).</div></div><div><h3>Results:</h3><div>The performance of our method, evaluated in simulation studies, demonstrated that our modeling method produces unbiased results and can improve power over alternatives in common biomedical research settings. The method was also applied to real data from a collection of Electronic Health Records.</div></div><div><h3>Conclusion:</h3><div>A DBS can be computed for all patients present in the data and thus can be used as a means of comparing subgroups and as the outcome variable in regression. This measure is not only a valuable tool in cases where death data is not available or reliable but also as an interim measurement when death is infrequent.</div></div>","PeriodicalId":15263,"journal":{"name":"Journal of Biomedical Informatics","volume":"169 ","pages":"Article 104883"},"PeriodicalIF":4.5000,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Measuring disease burden with individual cumulative incidence in patients with cirrhosis\",\"authors\":\"Mitchell Paukner , Daniela P. Ladner , CAPriCORN Team, Lihui Zhao\",\"doi\":\"10.1016/j.jbi.2025.104883\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objective:</h3><div>Introduce a new method for evaluating the health history of a patient through the use of multi-type recurrent events data that can aid in the assessment of disease progression and quality of life in a healthcare setting.</div></div><div><h3>Methods:</h3><div>The Disease Burden Score (DBS) is characterized as the area under the Disease Burden Curve (DBC), a monotone, increasing stepwise graph, that measures the weighted or unweighted number of health events that occur during a patient’s follow-up period (i.e. cardiovascular events or decompensation events).</div></div><div><h3>Results:</h3><div>The performance of our method, evaluated in simulation studies, demonstrated that our modeling method produces unbiased results and can improve power over alternatives in common biomedical research settings. The method was also applied to real data from a collection of Electronic Health Records.</div></div><div><h3>Conclusion:</h3><div>A DBS can be computed for all patients present in the data and thus can be used as a means of comparing subgroups and as the outcome variable in regression. This measure is not only a valuable tool in cases where death data is not available or reliable but also as an interim measurement when death is infrequent.</div></div>\",\"PeriodicalId\":15263,\"journal\":{\"name\":\"Journal of Biomedical Informatics\",\"volume\":\"169 \",\"pages\":\"Article 104883\"},\"PeriodicalIF\":4.5000,\"publicationDate\":\"2025-07-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Biomedical Informatics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1532046425001121\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Biomedical Informatics","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1532046425001121","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Measuring disease burden with individual cumulative incidence in patients with cirrhosis
Objective:
Introduce a new method for evaluating the health history of a patient through the use of multi-type recurrent events data that can aid in the assessment of disease progression and quality of life in a healthcare setting.
Methods:
The Disease Burden Score (DBS) is characterized as the area under the Disease Burden Curve (DBC), a monotone, increasing stepwise graph, that measures the weighted or unweighted number of health events that occur during a patient’s follow-up period (i.e. cardiovascular events or decompensation events).
Results:
The performance of our method, evaluated in simulation studies, demonstrated that our modeling method produces unbiased results and can improve power over alternatives in common biomedical research settings. The method was also applied to real data from a collection of Electronic Health Records.
Conclusion:
A DBS can be computed for all patients present in the data and thus can be used as a means of comparing subgroups and as the outcome variable in regression. This measure is not only a valuable tool in cases where death data is not available or reliable but also as an interim measurement when death is infrequent.
期刊介绍:
The Journal of Biomedical Informatics reflects a commitment to high-quality original research papers, reviews, and commentaries in the area of biomedical informatics methodology. Although we publish articles motivated by applications in the biomedical sciences (for example, clinical medicine, health care, population health, and translational bioinformatics), the journal emphasizes reports of new methodologies and techniques that have general applicability and that form the basis for the evolving science of biomedical informatics. Articles on medical devices; evaluations of implemented systems (including clinical trials of information technologies); or papers that provide insight into a biological process, a specific disease, or treatment options would generally be more suitable for publication in other venues. Papers on applications of signal processing and image analysis are often more suitable for biomedical engineering journals or other informatics journals, although we do publish papers that emphasize the information management and knowledge representation/modeling issues that arise in the storage and use of biological signals and images. System descriptions are welcome if they illustrate and substantiate the underlying methodology that is the principal focus of the report and an effort is made to address the generalizability and/or range of application of that methodology. Note also that, given the international nature of JBI, papers that deal with specific languages other than English, or with country-specific health systems or approaches, are acceptable for JBI only if they offer generalizable lessons that are relevant to the broad JBI readership, regardless of their country, language, culture, or health system.