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Comparative Effects of CT Imaging Measurement on RECIST End Points and Tumor Growth Kinetics Modeling
Quantitative assessments of tumor burden and modeling of longitudinal growth could improve phase II oncology trials. To identify obstacles to wider use of quantitative measures we obtained recorded linear tumor measurements from three published lung cancer trials. Model‐based parameters of tumor bur...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4760886/ https://www.ncbi.nlm.nih.gov/pubmed/26790562 http://dx.doi.org/10.1111/cts.12384 |
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author | Li, CH Bies, RR Wang, Y Sharma, MR Karovic, S Werk, L Edelman, MJ Miller, AA Vokes, EE Oto, A Ratain, MJ Schwartz, LH Maitland, ML |
author_facet | Li, CH Bies, RR Wang, Y Sharma, MR Karovic, S Werk, L Edelman, MJ Miller, AA Vokes, EE Oto, A Ratain, MJ Schwartz, LH Maitland, ML |
author_sort | Li, CH |
collection | PubMed |
description | Quantitative assessments of tumor burden and modeling of longitudinal growth could improve phase II oncology trials. To identify obstacles to wider use of quantitative measures we obtained recorded linear tumor measurements from three published lung cancer trials. Model‐based parameters of tumor burden change were estimated and compared with similarly sized samples from separate trials. Time‐to‐tumor growth (TTG) was computed from measurements recorded on case report forms and a second radiologist blinded to the form data. Response Evaluation Criteria in Solid Tumors (RECIST)‐based progression‐free survival (PFS) measures were perfectly concordant between the original forms data and the blinded radiologist re‐evaluation (intraclass correlation coefficient = 1), but these routine interrater differences in the identification and measurement of target lesions were associated with an average 18‐week delay (range, −20 to 55 weeks) in TTG (intraclass correlation coefficient = 0.32). To exploit computational metrics for improving statistical power in small clinical trials will require increased precision of tumor burden assessments. |
format | Online Article Text |
id | pubmed-4760886 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-47608862017-02-01 Comparative Effects of CT Imaging Measurement on RECIST End Points and Tumor Growth Kinetics Modeling Li, CH Bies, RR Wang, Y Sharma, MR Karovic, S Werk, L Edelman, MJ Miller, AA Vokes, EE Oto, A Ratain, MJ Schwartz, LH Maitland, ML Clin Transl Sci Research Quantitative assessments of tumor burden and modeling of longitudinal growth could improve phase II oncology trials. To identify obstacles to wider use of quantitative measures we obtained recorded linear tumor measurements from three published lung cancer trials. Model‐based parameters of tumor burden change were estimated and compared with similarly sized samples from separate trials. Time‐to‐tumor growth (TTG) was computed from measurements recorded on case report forms and a second radiologist blinded to the form data. Response Evaluation Criteria in Solid Tumors (RECIST)‐based progression‐free survival (PFS) measures were perfectly concordant between the original forms data and the blinded radiologist re‐evaluation (intraclass correlation coefficient = 1), but these routine interrater differences in the identification and measurement of target lesions were associated with an average 18‐week delay (range, −20 to 55 weeks) in TTG (intraclass correlation coefficient = 0.32). To exploit computational metrics for improving statistical power in small clinical trials will require increased precision of tumor burden assessments. John Wiley and Sons Inc. 2016-01-21 2016-02 /pmc/articles/PMC4760886/ /pubmed/26790562 http://dx.doi.org/10.1111/cts.12384 Text en © 2016 The Authors. Clinical and Translational Science published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs (http://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Research Li, CH Bies, RR Wang, Y Sharma, MR Karovic, S Werk, L Edelman, MJ Miller, AA Vokes, EE Oto, A Ratain, MJ Schwartz, LH Maitland, ML Comparative Effects of CT Imaging Measurement on RECIST End Points and Tumor Growth Kinetics Modeling |
title | Comparative Effects of CT Imaging Measurement on RECIST End Points and Tumor Growth Kinetics Modeling |
title_full | Comparative Effects of CT Imaging Measurement on RECIST End Points and Tumor Growth Kinetics Modeling |
title_fullStr | Comparative Effects of CT Imaging Measurement on RECIST End Points and Tumor Growth Kinetics Modeling |
title_full_unstemmed | Comparative Effects of CT Imaging Measurement on RECIST End Points and Tumor Growth Kinetics Modeling |
title_short | Comparative Effects of CT Imaging Measurement on RECIST End Points and Tumor Growth Kinetics Modeling |
title_sort | comparative effects of ct imaging measurement on recist end points and tumor growth kinetics modeling |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4760886/ https://www.ncbi.nlm.nih.gov/pubmed/26790562 http://dx.doi.org/10.1111/cts.12384 |
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