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A perfect correlate does not a surrogate make
BACKGROUND: There is common belief among some medical researchers that if a potential surrogate endpoint is highly correlated with a true endpoint, then a positive (or negative) difference in potential surrogate endpoints between randomization groups would imply a positive (or negative) difference i...
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2003
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC212489/ https://www.ncbi.nlm.nih.gov/pubmed/12962545 http://dx.doi.org/10.1186/1471-2288-3-16 |
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author | Baker, Stuart G Kramer, Barnett S |
author_facet | Baker, Stuart G Kramer, Barnett S |
author_sort | Baker, Stuart G |
collection | PubMed |
description | BACKGROUND: There is common belief among some medical researchers that if a potential surrogate endpoint is highly correlated with a true endpoint, then a positive (or negative) difference in potential surrogate endpoints between randomization groups would imply a positive (or negative) difference in unobserved true endpoints between randomization groups. We investigate this belief when the potential surrogate and unobserved true endpoints are perfectly correlated within each randomization group. METHODS: We use a graphical approach. The vertical axis is the unobserved true endpoint and the horizontal axis is the potential surrogate endpoint. Perfect correlation within each randomization group implies that, for each randomization group, potential surrogate and true endpoints are related by a straight line. In this scenario the investigator does not know the slopes or intercepts. We consider a plausible example where the slope of the line is higher for the experimental group than for the control group. RESULTS: In our example with unknown lines, a decrease in mean potential surrogate endpoints from control to experimental groups corresponds to an increase in mean true endpoint from control to experimental groups. Thus the potential surrogate endpoints give the wrong inference. Similar results hold for binary potential surrogate and true outcomes (although the notion of correlation does not apply). The potential surrogate endpointwould give the correct inference if either (i) the unknown lines for the two group coincided, which means that the distribution of true endpoint conditional on potential surrogate endpoint does not depend on treatment group, which is called the Prentice Criterion or (ii) if one could accurately predict the lines based on data from prior studies. CONCLUSION: Perfect correlation between potential surrogate and unobserved true outcomes within randomized groups does not guarantee correct inference based on a potential surrogate endpoint. Even in early phase trials, investigators should not base conclusions on potential surrogate endpoints in which the only validation is high correlation with the true endpoint within a group. |
format | Text |
id | pubmed-212489 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2003 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-2124892003-10-11 A perfect correlate does not a surrogate make Baker, Stuart G Kramer, Barnett S BMC Med Res Methodol Research Article BACKGROUND: There is common belief among some medical researchers that if a potential surrogate endpoint is highly correlated with a true endpoint, then a positive (or negative) difference in potential surrogate endpoints between randomization groups would imply a positive (or negative) difference in unobserved true endpoints between randomization groups. We investigate this belief when the potential surrogate and unobserved true endpoints are perfectly correlated within each randomization group. METHODS: We use a graphical approach. The vertical axis is the unobserved true endpoint and the horizontal axis is the potential surrogate endpoint. Perfect correlation within each randomization group implies that, for each randomization group, potential surrogate and true endpoints are related by a straight line. In this scenario the investigator does not know the slopes or intercepts. We consider a plausible example where the slope of the line is higher for the experimental group than for the control group. RESULTS: In our example with unknown lines, a decrease in mean potential surrogate endpoints from control to experimental groups corresponds to an increase in mean true endpoint from control to experimental groups. Thus the potential surrogate endpoints give the wrong inference. Similar results hold for binary potential surrogate and true outcomes (although the notion of correlation does not apply). The potential surrogate endpointwould give the correct inference if either (i) the unknown lines for the two group coincided, which means that the distribution of true endpoint conditional on potential surrogate endpoint does not depend on treatment group, which is called the Prentice Criterion or (ii) if one could accurately predict the lines based on data from prior studies. CONCLUSION: Perfect correlation between potential surrogate and unobserved true outcomes within randomized groups does not guarantee correct inference based on a potential surrogate endpoint. Even in early phase trials, investigators should not base conclusions on potential surrogate endpoints in which the only validation is high correlation with the true endpoint within a group. BioMed Central 2003-09-09 /pmc/articles/PMC212489/ /pubmed/12962545 http://dx.doi.org/10.1186/1471-2288-3-16 Text en Copyright © 2003 Baker and Kramer; licensee BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL. |
spellingShingle | Research Article Baker, Stuart G Kramer, Barnett S A perfect correlate does not a surrogate make |
title | A perfect correlate does not a surrogate make |
title_full | A perfect correlate does not a surrogate make |
title_fullStr | A perfect correlate does not a surrogate make |
title_full_unstemmed | A perfect correlate does not a surrogate make |
title_short | A perfect correlate does not a surrogate make |
title_sort | perfect correlate does not a surrogate make |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC212489/ https://www.ncbi.nlm.nih.gov/pubmed/12962545 http://dx.doi.org/10.1186/1471-2288-3-16 |
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