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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2016
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.
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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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