Purpose Target lesion selection is known to be a major factor for inter-reader discordance in RECIST 1.1. The purpose of this study was to assess whether volumetric measurements of target… Click to show full abstract
Purpose Target lesion selection is known to be a major factor for inter-reader discordance in RECIST 1.1. The purpose of this study was to assess whether volumetric measurements of target lesions result in different response categorization, as opposed to standard unidimensional measurements, and to evaluate the impact on inter-reader agreement for response categorization when different readers select different sets of target lesions. Material and methods Fifty patients with measurable disease from solid tumours, in which 3 readers had blindly and independently selected different sets of target lesions and subsequently reached clinically significant discordant response categorizations (progressive disease [PD] vs. non-progressive disease [non-PD]) based on RECIST 1.1 analyses were included in this study. Additional volumetric measurements of all target lesions were performed by the same readers in a second read. Intra-reader agreement between standard unidimensional measurements (uRECIST) and volumetric measurements (vRECIST) was assessed using Cohen’s k statistics. Fleiss k statistics was used to analyse the inter-reader agreement for uRECIST and vRECIST results. Results The 3 readers assigned the same response classifications based on uRECIST and vRECIST in 33/50 (66%), 42/50 patients (84%), and 44/50 patients (88%), respectively. Inter-reader agreement improved from 0% when using uRECIST to 36% when using vRECIST. Conclusions Volumetric measurement of target lesions may improve inter-reader variability for response assessment as opposed to standard unidimensional measurements. However, in about two-thirds of patients, readers disagreed regardless of the measurement method, indicating that a limited set of target lesions may not be sufficiently representative of the whole-body tumour burden.
               
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