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Breaking down the RECIST 1.1 double read variability in lung trials: What do baseline assessments tell us?

BACKGROUND: In clinical trials with imaging, Blinded Independent Central Review (BICR) with double reads ensures data blinding and reduces bias in drug evaluations. As double reads can cause discrepancies, evaluations require close monitoring which substantially increases clinical trial costs. We so...

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Autores principales: Iannessi, Antoine, Beaumont, Hubert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10060958/
https://www.ncbi.nlm.nih.gov/pubmed/37007064
http://dx.doi.org/10.3389/fonc.2023.988784
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author Iannessi, Antoine
Beaumont, Hubert
author_facet Iannessi, Antoine
Beaumont, Hubert
author_sort Iannessi, Antoine
collection PubMed
description BACKGROUND: In clinical trials with imaging, Blinded Independent Central Review (BICR) with double reads ensures data blinding and reduces bias in drug evaluations. As double reads can cause discrepancies, evaluations require close monitoring which substantially increases clinical trial costs. We sought to document the variability of double reads at baseline, and variabilities across individual readers and lung trials. MATERIAL AND METHODS: We retrospectively analyzed data from five BICR clinical trials evaluating 1720 lung cancer patients treated with immunotherapy or targeted therapy. Fifteen radiologists were involved. The variability was analyzed using a set of 71 features derived from tumor selection, measurements, and disease location. We selected a subset of readers that evaluated ≥50 patients in ≥two trials, to compare individual reader’s selections. Finally, we evaluated inter-trial homogeneity using a subset of patients for whom both readers assessed the exact same disease locations. Significance level was 0.05. Multiple pair-wise comparisons of continuous variables and proportions were performed using one-way ANOVA and Marascuilo procedure, respectively. RESULTS: Across trials, on average per patient, target lesion (TL) number ranged 1.9 to 3.0, sum of tumor diameter (SOD) 57.1 to 91.9 mm. MeanSOD=83.7 mm. In four trials, MeanSOD of double reads was significantly different. Less than 10% of patients had TLs selected in completely different organs and 43.5% had at least one selected in different organs. Discrepancies in disease locations happened mainly in lymph nodes (20.1%) and bones (12.2%). Discrepancies in measurable disease happened mainly in lung (19.6%). Between individual readers, the MeanSOD and disease selection were significantly different (p<0.001). In inter-trials comparisons, on average per patient, the number of selected TLs ranged 2.1 to 2.8, MeanSOD 61.0 to 92.4 mm. Trials were significantly different in MeanSOD (p<0.0001) and average number of selected TLs (p=0.007). The proportion of patients having one of the top diseases was significantly different only between two trials for lung. Significant differences were observed for all other disease locations (p<0.05). CONCLUSIONS: We found significant double read variabilities at baseline, evidence of reading patterns and a means to compare trials. Clinical trial reliability is influenced by the interplay of readers, patients and trial design.
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spelling pubmed-100609582023-03-31 Breaking down the RECIST 1.1 double read variability in lung trials: What do baseline assessments tell us? Iannessi, Antoine Beaumont, Hubert Front Oncol Oncology BACKGROUND: In clinical trials with imaging, Blinded Independent Central Review (BICR) with double reads ensures data blinding and reduces bias in drug evaluations. As double reads can cause discrepancies, evaluations require close monitoring which substantially increases clinical trial costs. We sought to document the variability of double reads at baseline, and variabilities across individual readers and lung trials. MATERIAL AND METHODS: We retrospectively analyzed data from five BICR clinical trials evaluating 1720 lung cancer patients treated with immunotherapy or targeted therapy. Fifteen radiologists were involved. The variability was analyzed using a set of 71 features derived from tumor selection, measurements, and disease location. We selected a subset of readers that evaluated ≥50 patients in ≥two trials, to compare individual reader’s selections. Finally, we evaluated inter-trial homogeneity using a subset of patients for whom both readers assessed the exact same disease locations. Significance level was 0.05. Multiple pair-wise comparisons of continuous variables and proportions were performed using one-way ANOVA and Marascuilo procedure, respectively. RESULTS: Across trials, on average per patient, target lesion (TL) number ranged 1.9 to 3.0, sum of tumor diameter (SOD) 57.1 to 91.9 mm. MeanSOD=83.7 mm. In four trials, MeanSOD of double reads was significantly different. Less than 10% of patients had TLs selected in completely different organs and 43.5% had at least one selected in different organs. Discrepancies in disease locations happened mainly in lymph nodes (20.1%) and bones (12.2%). Discrepancies in measurable disease happened mainly in lung (19.6%). Between individual readers, the MeanSOD and disease selection were significantly different (p<0.001). In inter-trials comparisons, on average per patient, the number of selected TLs ranged 2.1 to 2.8, MeanSOD 61.0 to 92.4 mm. Trials were significantly different in MeanSOD (p<0.0001) and average number of selected TLs (p=0.007). The proportion of patients having one of the top diseases was significantly different only between two trials for lung. Significant differences were observed for all other disease locations (p<0.05). CONCLUSIONS: We found significant double read variabilities at baseline, evidence of reading patterns and a means to compare trials. Clinical trial reliability is influenced by the interplay of readers, patients and trial design. Frontiers Media S.A. 2023-03-16 /pmc/articles/PMC10060958/ /pubmed/37007064 http://dx.doi.org/10.3389/fonc.2023.988784 Text en Copyright © 2023 Iannessi and Beaumont https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Iannessi, Antoine
Beaumont, Hubert
Breaking down the RECIST 1.1 double read variability in lung trials: What do baseline assessments tell us?
title Breaking down the RECIST 1.1 double read variability in lung trials: What do baseline assessments tell us?
title_full Breaking down the RECIST 1.1 double read variability in lung trials: What do baseline assessments tell us?
title_fullStr Breaking down the RECIST 1.1 double read variability in lung trials: What do baseline assessments tell us?
title_full_unstemmed Breaking down the RECIST 1.1 double read variability in lung trials: What do baseline assessments tell us?
title_short Breaking down the RECIST 1.1 double read variability in lung trials: What do baseline assessments tell us?
title_sort breaking down the recist 1.1 double read variability in lung trials: what do baseline assessments tell us?
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10060958/
https://www.ncbi.nlm.nih.gov/pubmed/37007064
http://dx.doi.org/10.3389/fonc.2023.988784
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