{"title":"了解临床预测模型研究中的决策曲线分析。","authors":"Luqing Zhao, Yueshuang Leng, Yongbin Hu, Juxiong Xiao, Qingling Li, Chuyi Liu, Yitao Mao","doi":"10.1093/postmj/qgae027","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Many medical graduate students lack a thorough understanding of decision curve analysis (DCA), a valuable tool in clinical research for evaluating diagnostic models.</p><p><strong>Methods: </strong>This article elucidates the concept and process of DCA through the lens of clinical research practices, exemplified by its application in diagnosing liver cancer using serum alpha-fetoprotein levels and radiomics indices. It covers the calculation of probability thresholds, computation of net benefits for each threshold, construction of decision curves, and comparison of decision curves from different models to identify the one offering the highest net benefit.</p><p><strong>Results: </strong>The paper provides a detailed explanation of DCA, including the creation and comparison of decision curves, and discusses the relationship and differences between decision curves and receiver operating characteristic curves. It highlights the superiority of decision curves in supporting clinical decision-making processes.</p><p><strong>Conclusion: </strong>By clarifying the concept of DCA and highlighting its benefits in clinical decisionmaking, this article has improved researchers' comprehension of how DCA is applied and interpreted, thereby enhancing the quality of research in the medical field.</p>","PeriodicalId":20374,"journal":{"name":"Postgraduate Medical Journal","volume":null,"pages":null},"PeriodicalIF":3.6000,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Understanding decision curve analysis in clinical prediction model research.\",\"authors\":\"Luqing Zhao, Yueshuang Leng, Yongbin Hu, Juxiong Xiao, Qingling Li, Chuyi Liu, Yitao Mao\",\"doi\":\"10.1093/postmj/qgae027\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Many medical graduate students lack a thorough understanding of decision curve analysis (DCA), a valuable tool in clinical research for evaluating diagnostic models.</p><p><strong>Methods: </strong>This article elucidates the concept and process of DCA through the lens of clinical research practices, exemplified by its application in diagnosing liver cancer using serum alpha-fetoprotein levels and radiomics indices. It covers the calculation of probability thresholds, computation of net benefits for each threshold, construction of decision curves, and comparison of decision curves from different models to identify the one offering the highest net benefit.</p><p><strong>Results: </strong>The paper provides a detailed explanation of DCA, including the creation and comparison of decision curves, and discusses the relationship and differences between decision curves and receiver operating characteristic curves. It highlights the superiority of decision curves in supporting clinical decision-making processes.</p><p><strong>Conclusion: </strong>By clarifying the concept of DCA and highlighting its benefits in clinical decisionmaking, this article has improved researchers' comprehension of how DCA is applied and interpreted, thereby enhancing the quality of research in the medical field.</p>\",\"PeriodicalId\":20374,\"journal\":{\"name\":\"Postgraduate Medical Journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2024-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Postgraduate Medical Journal\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1093/postmj/qgae027\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MEDICINE, GENERAL & INTERNAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Postgraduate Medical Journal","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/postmj/qgae027","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
Understanding decision curve analysis in clinical prediction model research.
Background: Many medical graduate students lack a thorough understanding of decision curve analysis (DCA), a valuable tool in clinical research for evaluating diagnostic models.
Methods: This article elucidates the concept and process of DCA through the lens of clinical research practices, exemplified by its application in diagnosing liver cancer using serum alpha-fetoprotein levels and radiomics indices. It covers the calculation of probability thresholds, computation of net benefits for each threshold, construction of decision curves, and comparison of decision curves from different models to identify the one offering the highest net benefit.
Results: The paper provides a detailed explanation of DCA, including the creation and comparison of decision curves, and discusses the relationship and differences between decision curves and receiver operating characteristic curves. It highlights the superiority of decision curves in supporting clinical decision-making processes.
Conclusion: By clarifying the concept of DCA and highlighting its benefits in clinical decisionmaking, this article has improved researchers' comprehension of how DCA is applied and interpreted, thereby enhancing the quality of research in the medical field.
期刊介绍:
Postgraduate Medical Journal is a peer reviewed journal published on behalf of the Fellowship of Postgraduate Medicine. The journal aims to support junior doctors and their teachers and contribute to the continuing professional development of all doctors by publishing papers on a wide range of topics relevant to the practicing clinician and teacher. Papers published in PMJ include those that focus on core competencies; that describe current practice and new developments in all branches of medicine; that describe relevance and impact of translational research on clinical practice; that provide background relevant to examinations; and papers on medical education and medical education research. PMJ supports CPD by providing the opportunity for doctors to publish many types of articles including original clinical research; reviews; quality improvement reports; editorials, and correspondence on clinical matters.