Original articleConsiderations in the Evaluation of Surrogate Endpoints in Clinical Trials: Summary of a National Institutes of Health Workshop☆
Section snippets
Design and Analysis of Clinical Trials amid Rapid Advances in Biotechnology and Genomics
Research in biosciences and technology is yielding promising new ways of understanding and measuring human disease processes. Genome sequencing, DNA microarrays, proteomics, and magnetic resonance imaging are giving rise to new tools of biostatistics and epidemiology that are making their way into clinical investigation and are producing vastly more information than was obtained through previous methods. This emerging field of bioinformatics contends with the explosion of data in molecular
An evolving framework: bridging empirical and mechanism-based knowledge
Biostatistics uses quantitative data to estimate biologic parameters and to test hypotheses. The use of a surrogate endpoint would represent a prediction or extrapolation from past information about the relationship of treatment, surrogate, and clinical endpoint to a new similar treatment. The more that is known about the biological mechanism underlying the disease and mechanism of action of the treatment, the more accurate the prediction is likely to be. The current revolution in bioscience
Summary of workshop goals and recommendations
An overarching aim of the workshop was to develop recommendations to guide NIH and the research community at large in the design and analysis of methods for evaluating the uses of biomarkers as surrogate endpoints in clinical trials. In doing so, participants recognized that many successful clinical trials use neither biomarkers nor surrogate endpoints. Information derived from trials of clinical outcomes, including adverse effects, is extremely important in assessing the clinical utility of an
References (18)
- et al.
Relationships between antiviral treatment effects and biphasic viral decay rates in modeling HIV dynamics
Math Biosci
(1999) - et al.
Short-course zidovudine for perinatal HIV-1 transmission in Bangkok, ThailandA randomized controlled trial. Bangkok Collaborative Perinatal HIV Transmission Study Group
Lancet
(1999) Biomarkers and surrogate endpointsPreferred definitions and conceptual framework
Clinical Pharmacol Ther
(2001)Surrogate endpoints in clinical trialsDefinition and operational criteria
Stat Med
(1998)- et al.
Statistical validation of intermediate endpoints for chronic diseases
Stat Med
(1992) - et al.
Modeling the relationship of survival to longitudinal data measured with error. Applications to survival and CD4 counts in patients with AIDS
J Am Stat Assoc
(1995) - et al.
Meta-analysis for the evaluation of potential surrogate markers
Stat Med
(1997) - et al.
Surrogate end points in clinical trialsAre we being misled?
Ann Intern Med
(1996) - et al.
Estimating the proportion of treatment effect explained by a surrogate marker
Stat Med
(1997)
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NIH Workshop: Research Needs for the Design and Analysis of Surrogate Endpoints in Clinical Trials, December 1–2, 1998 (<<http:\www.od.nih.gov/osp/ospp.biomarkers/coverpage.htm).