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Evaluating the evidence behind the surrogate measures included in the FDA's table of surrogate endpoints as supporting approval of cancer drugs
BACKGROUND: In July 2018, the FDA first published a table listing all surrogate measures that it has used, and may accept for future use, in regulatory approval. However, the strength of surrogacy for those measures was not formally assessed. Using the case example of breast cancer, we aimed to eval...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7201012/ https://www.ncbi.nlm.nih.gov/pubmed/32382717 http://dx.doi.org/10.1016/j.eclinm.2020.100332 |
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author | Gyawali, Bishal Hey, Spencer P. Kesselheim, Aaron S. |
author_facet | Gyawali, Bishal Hey, Spencer P. Kesselheim, Aaron S. |
author_sort | Gyawali, Bishal |
collection | PubMed |
description | BACKGROUND: In July 2018, the FDA first published a table listing all surrogate measures that it has used, and may accept for future use, in regulatory approval. However, the strength of surrogacy for those measures was not formally assessed. Using the case example of breast cancer, we aimed to evaluate the strength of correlation of surrogate measures listed in the FDA's Table with overall survival. METHODS: This cross-sectional study of the FDA's Table of Surrogate Endpoints was conducted in May 2019. All surrogate measures listed in the FDA table as appropriate for accelerated or regular approval for breast cancer were extracted. We identified studies evaluating the correlation of treatment benefit in the surrogate with treatment benefit in overall survival and extracted results from the correlation analysis. FINDINGS: Five surrogate endpoints were listed for breast cancer in the FDA website: pathological complete response rates (pCR), event-free survival (EFS), disease-free survival (DFS), objective response rates (ORR), and progression-free survival (PFS), of which pCR was listed as appropriate only for accelerated approval, while the rest were considered appropriate for accelerated or regular approval. No correlation study evaluated the correlation of treatment effects on EFS with that on OS. The results from correlation studies evaluating pCR, DFS, ORR, and PFS suggest that the treatment effects on none of these surrogate measures were strongly correlated with treatment effects on OS (r<0.85 or R(2) < 0.7, except for DFS in HER2 positive early breast cancer (R(2) = 0.75) INTERPRETATION: Using breast cancer as an example, we evaluated the underlying evidence for the surrogate endpoints for solid tumors listed in the FDA's Table of Surrogate Endpoints and found weak or missing correlations of treatment effects on these surrogates with treatment effects on OS . Surrogate measures should be predictive of clinical benefit to be useful in supporting regular FDA approval. FUNDING: Work on this project was funded by the Arnold Ventures. Dr. Kesselheim is also supported by the Harvard-MIT Center for Regulatory Science. The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. |
format | Online Article Text |
id | pubmed-7201012 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-72010122020-05-07 Evaluating the evidence behind the surrogate measures included in the FDA's table of surrogate endpoints as supporting approval of cancer drugs Gyawali, Bishal Hey, Spencer P. Kesselheim, Aaron S. EClinicalMedicine Research paper BACKGROUND: In July 2018, the FDA first published a table listing all surrogate measures that it has used, and may accept for future use, in regulatory approval. However, the strength of surrogacy for those measures was not formally assessed. Using the case example of breast cancer, we aimed to evaluate the strength of correlation of surrogate measures listed in the FDA's Table with overall survival. METHODS: This cross-sectional study of the FDA's Table of Surrogate Endpoints was conducted in May 2019. All surrogate measures listed in the FDA table as appropriate for accelerated or regular approval for breast cancer were extracted. We identified studies evaluating the correlation of treatment benefit in the surrogate with treatment benefit in overall survival and extracted results from the correlation analysis. FINDINGS: Five surrogate endpoints were listed for breast cancer in the FDA website: pathological complete response rates (pCR), event-free survival (EFS), disease-free survival (DFS), objective response rates (ORR), and progression-free survival (PFS), of which pCR was listed as appropriate only for accelerated approval, while the rest were considered appropriate for accelerated or regular approval. No correlation study evaluated the correlation of treatment effects on EFS with that on OS. The results from correlation studies evaluating pCR, DFS, ORR, and PFS suggest that the treatment effects on none of these surrogate measures were strongly correlated with treatment effects on OS (r<0.85 or R(2) < 0.7, except for DFS in HER2 positive early breast cancer (R(2) = 0.75) INTERPRETATION: Using breast cancer as an example, we evaluated the underlying evidence for the surrogate endpoints for solid tumors listed in the FDA's Table of Surrogate Endpoints and found weak or missing correlations of treatment effects on these surrogates with treatment effects on OS . Surrogate measures should be predictive of clinical benefit to be useful in supporting regular FDA approval. FUNDING: Work on this project was funded by the Arnold Ventures. Dr. Kesselheim is also supported by the Harvard-MIT Center for Regulatory Science. The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Elsevier 2020-04-13 /pmc/articles/PMC7201012/ /pubmed/32382717 http://dx.doi.org/10.1016/j.eclinm.2020.100332 Text en © 2020 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research paper Gyawali, Bishal Hey, Spencer P. Kesselheim, Aaron S. Evaluating the evidence behind the surrogate measures included in the FDA's table of surrogate endpoints as supporting approval of cancer drugs |
title | Evaluating the evidence behind the surrogate measures included in the FDA's table of surrogate endpoints as supporting approval of cancer drugs |
title_full | Evaluating the evidence behind the surrogate measures included in the FDA's table of surrogate endpoints as supporting approval of cancer drugs |
title_fullStr | Evaluating the evidence behind the surrogate measures included in the FDA's table of surrogate endpoints as supporting approval of cancer drugs |
title_full_unstemmed | Evaluating the evidence behind the surrogate measures included in the FDA's table of surrogate endpoints as supporting approval of cancer drugs |
title_short | Evaluating the evidence behind the surrogate measures included in the FDA's table of surrogate endpoints as supporting approval of cancer drugs |
title_sort | evaluating the evidence behind the surrogate measures included in the fda's table of surrogate endpoints as supporting approval of cancer drugs |
topic | Research paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7201012/ https://www.ncbi.nlm.nih.gov/pubmed/32382717 http://dx.doi.org/10.1016/j.eclinm.2020.100332 |
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