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Collection of Post-treatment PRO Data in Oncology Clinical Trials
As patient-reported outcome (PRO) measures are being included more frequently in oncology clinical trials, regulatory and health technology assessment agencies have begun to request long-term, post-treatment PRO data to supplement traditional survival/progression endpoints. These data may be collect...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785546/ https://www.ncbi.nlm.nih.gov/pubmed/32643079 http://dx.doi.org/10.1007/s43441-020-00195-3 |
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author | Lundy, J. Jason Coon, Cheryl D. Fu, An-Chen Pawar, Vivek |
author_facet | Lundy, J. Jason Coon, Cheryl D. Fu, An-Chen Pawar, Vivek |
author_sort | Lundy, J. Jason |
collection | PubMed |
description | As patient-reported outcome (PRO) measures are being included more frequently in oncology clinical trials, regulatory and health technology assessment agencies have begun to request long-term, post-treatment PRO data to supplement traditional survival/progression endpoints. These data may be collected as part of cohort extension or registry studies to describe long-term outcomes of study participants after concluding their cancer treatment. While post-treatment PRO data may be expected to satisfy regulatory and payer expectations, significant practical barriers exist for the efficient incorporation of these data into oncology clinical trials, such as subject attrition, protocol deviations, and treatment crossover. The incorporation of post-treatment PRO assessments is a resource-intensive task requiring clear objectives for how the data will be analyzed and interpreted by both sponsors and regulators. Incorporating PRO data collection via electronic modalities (e.g., smartphone, web) may be a less expensive and more feasible option for incorporating long-term follow-up, reducing the frequency of manual study staff follow-up and expensive clinic visits. It is essential to include well-defined estimands for the statistical analysis, as well as to document limitations associated with the long-term follow-up data-collection approach. Analytical techniques will likely rely on descriptive and model-based statistics, and conclusions about treatment differences will likely be limited to preliminary findings of effectiveness (instead of efficacy). Finally, communications with health authorities and regulatory agencies regarding the LTFU study design and analysis should occur as early as possible to ensure that the PRO data to be collected offer an opportunity to properly evaluate the research question(s) of interest. |
format | Online Article Text |
id | pubmed-7785546 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-77855462021-01-11 Collection of Post-treatment PRO Data in Oncology Clinical Trials Lundy, J. Jason Coon, Cheryl D. Fu, An-Chen Pawar, Vivek Ther Innov Regul Sci Commentary As patient-reported outcome (PRO) measures are being included more frequently in oncology clinical trials, regulatory and health technology assessment agencies have begun to request long-term, post-treatment PRO data to supplement traditional survival/progression endpoints. These data may be collected as part of cohort extension or registry studies to describe long-term outcomes of study participants after concluding their cancer treatment. While post-treatment PRO data may be expected to satisfy regulatory and payer expectations, significant practical barriers exist for the efficient incorporation of these data into oncology clinical trials, such as subject attrition, protocol deviations, and treatment crossover. The incorporation of post-treatment PRO assessments is a resource-intensive task requiring clear objectives for how the data will be analyzed and interpreted by both sponsors and regulators. Incorporating PRO data collection via electronic modalities (e.g., smartphone, web) may be a less expensive and more feasible option for incorporating long-term follow-up, reducing the frequency of manual study staff follow-up and expensive clinic visits. It is essential to include well-defined estimands for the statistical analysis, as well as to document limitations associated with the long-term follow-up data-collection approach. Analytical techniques will likely rely on descriptive and model-based statistics, and conclusions about treatment differences will likely be limited to preliminary findings of effectiveness (instead of efficacy). Finally, communications with health authorities and regulatory agencies regarding the LTFU study design and analysis should occur as early as possible to ensure that the PRO data to be collected offer an opportunity to properly evaluate the research question(s) of interest. Springer International Publishing 2020-07-08 2021 /pmc/articles/PMC7785546/ /pubmed/32643079 http://dx.doi.org/10.1007/s43441-020-00195-3 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Commentary Lundy, J. Jason Coon, Cheryl D. Fu, An-Chen Pawar, Vivek Collection of Post-treatment PRO Data in Oncology Clinical Trials |
title | Collection of Post-treatment PRO Data in Oncology Clinical Trials |
title_full | Collection of Post-treatment PRO Data in Oncology Clinical Trials |
title_fullStr | Collection of Post-treatment PRO Data in Oncology Clinical Trials |
title_full_unstemmed | Collection of Post-treatment PRO Data in Oncology Clinical Trials |
title_short | Collection of Post-treatment PRO Data in Oncology Clinical Trials |
title_sort | collection of post-treatment pro data in oncology clinical trials |
topic | Commentary |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785546/ https://www.ncbi.nlm.nih.gov/pubmed/32643079 http://dx.doi.org/10.1007/s43441-020-00195-3 |
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