Sumithra J Mandrekar, Axel Grothey, Matthew P Goetz, Daniel J Sargent
{"title":"生物标志物前瞻性验证的临床试验设计。","authors":"Sumithra J Mandrekar, Axel Grothey, Matthew P Goetz, Daniel J Sargent","doi":"10.2165/00129785-200505050-00004","DOIUrl":null,"url":null,"abstract":"<p><p>Traditionally, anatomic staging systems have been used to determine predictions of individual patient outcome and, to a lesser extent, guide the choice of treatment in patients with cancer. With new targeted therapies, the role of biomarkers is increasingly promising, suggesting an integrated approach using the genetic make-up of the tumor and the genotype of the patient for treatment selection and patient management. Specifically, biomarkers can aid in patient stratification (risk assessment), treatment response identification (surrogate markers), or in differential diagnosis (identifying individuals who are likely to respond to specific drugs). To be clinically useful, a marker must favorably affect clinical outcomes such as decreased toxicity, increased overall and/or disease-free survival, or improved quality of life. This paper focuses on possible clinical trial designs for assessing the utility of a predictive marker(s) for toxicity or clinical efficacy. We consider the scenario of single and multiple markers as well as present alternative solutions based on the prevalence of a marker. Our designs rest on the assumption that the methods for assessment of the biomarker are established and the initial results show promise with regard to the predictive ability of a marker. Additional research is clearly warranted to achieve the goal of 'predictive oncology'.</p>","PeriodicalId":72171,"journal":{"name":"American journal of pharmacogenomics : genomics-related research in drug development and clinical practice","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2005-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2165/00129785-200505050-00004","citationCount":"52","resultStr":"{\"title\":\"Clinical trial designs for prospective validation of biomarkers.\",\"authors\":\"Sumithra J Mandrekar, Axel Grothey, Matthew P Goetz, Daniel J Sargent\",\"doi\":\"10.2165/00129785-200505050-00004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Traditionally, anatomic staging systems have been used to determine predictions of individual patient outcome and, to a lesser extent, guide the choice of treatment in patients with cancer. With new targeted therapies, the role of biomarkers is increasingly promising, suggesting an integrated approach using the genetic make-up of the tumor and the genotype of the patient for treatment selection and patient management. Specifically, biomarkers can aid in patient stratification (risk assessment), treatment response identification (surrogate markers), or in differential diagnosis (identifying individuals who are likely to respond to specific drugs). To be clinically useful, a marker must favorably affect clinical outcomes such as decreased toxicity, increased overall and/or disease-free survival, or improved quality of life. This paper focuses on possible clinical trial designs for assessing the utility of a predictive marker(s) for toxicity or clinical efficacy. We consider the scenario of single and multiple markers as well as present alternative solutions based on the prevalence of a marker. Our designs rest on the assumption that the methods for assessment of the biomarker are established and the initial results show promise with regard to the predictive ability of a marker. Additional research is clearly warranted to achieve the goal of 'predictive oncology'.</p>\",\"PeriodicalId\":72171,\"journal\":{\"name\":\"American journal of pharmacogenomics : genomics-related research in drug development and clinical practice\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.2165/00129785-200505050-00004\",\"citationCount\":\"52\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American journal of pharmacogenomics : genomics-related research in drug development and clinical practice\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2165/00129785-200505050-00004\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American journal of pharmacogenomics : genomics-related research in drug development and clinical practice","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2165/00129785-200505050-00004","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Clinical trial designs for prospective validation of biomarkers.
Traditionally, anatomic staging systems have been used to determine predictions of individual patient outcome and, to a lesser extent, guide the choice of treatment in patients with cancer. With new targeted therapies, the role of biomarkers is increasingly promising, suggesting an integrated approach using the genetic make-up of the tumor and the genotype of the patient for treatment selection and patient management. Specifically, biomarkers can aid in patient stratification (risk assessment), treatment response identification (surrogate markers), or in differential diagnosis (identifying individuals who are likely to respond to specific drugs). To be clinically useful, a marker must favorably affect clinical outcomes such as decreased toxicity, increased overall and/or disease-free survival, or improved quality of life. This paper focuses on possible clinical trial designs for assessing the utility of a predictive marker(s) for toxicity or clinical efficacy. We consider the scenario of single and multiple markers as well as present alternative solutions based on the prevalence of a marker. Our designs rest on the assumption that the methods for assessment of the biomarker are established and the initial results show promise with regard to the predictive ability of a marker. Additional research is clearly warranted to achieve the goal of 'predictive oncology'.