{"title":"Simple Methods for Evaluating 4 Types of Biomarkers: Surrogate Endpoint, Prognostic, Predictive, and Cancer Screening.","authors":"Stuart G Baker, Barnett S Kramer","doi":"10.1177/1177271920946715","DOIUrl":null,"url":null,"abstract":"<p><p>We review simple methods for evaluating 4 types of biomarkers. First, we discuss the evaluation of surrogate endpoint biomarkers (to shorten a randomized trial) using 2 statistical and 3 biological criteria. Second, we discuss the evaluation of prognostic biomarkers (to predict the risk of disease) by comparing data collection costs with the anticipated net benefit of risk prediction. Third, we discuss the evaluation of predictive markers (to search for a promising subgroup in a randomized trial) using a multivariate subpopulation treatment effect pattern plot involving a risk difference or responders-only benefit function. Fourth, we discuss the evaluation of cancer screening biomarkers (to predict cancer in asymptomatic persons) using methodology to substantially reduce the sample size with stored specimens.</p>","PeriodicalId":47060,"journal":{"name":"Biomarker Insights","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2020-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1177271920946715","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biomarker Insights","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/1177271920946715","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2020/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
引用次数: 3
Abstract
We review simple methods for evaluating 4 types of biomarkers. First, we discuss the evaluation of surrogate endpoint biomarkers (to shorten a randomized trial) using 2 statistical and 3 biological criteria. Second, we discuss the evaluation of prognostic biomarkers (to predict the risk of disease) by comparing data collection costs with the anticipated net benefit of risk prediction. Third, we discuss the evaluation of predictive markers (to search for a promising subgroup in a randomized trial) using a multivariate subpopulation treatment effect pattern plot involving a risk difference or responders-only benefit function. Fourth, we discuss the evaluation of cancer screening biomarkers (to predict cancer in asymptomatic persons) using methodology to substantially reduce the sample size with stored specimens.
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