Reducing number of target lesions for RECIST1.1 to predict survivals in patients with advanced non-small-cell lung cancer undergoing anti-PD1/PD-L1 monotherapy. (March 2022) - He, Li-Na; Chen, Tao; Fu, Sha; Chen, Chen; Jiang, Yongluo; Zhang, Xuanye; Du, Wei; Li, Haifeng; Wang, Yixing; Ali, Wael Abdullah Sultan; Zhou, Yixin; Lin, Zuan; et al.
Highlights: For RECIST1.1, response using reduced number of lesions versus up to five targets was assessed. Assessing the largest two targets achieved high inter-method concordance. Reduction in the number of lesions assessed did not affect prediction of OS for immunotherapy. Measuring the largest two targets could be proposed to reduce the RECIST workload. Abstract: Objectives: The Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 provides conventional and standardized response assessment for multiple solid tumors. We investigated the smallest number of target lesions that can be measured without compromising response categorization and survival prediction in patients with advanced non-small-cell lung cancer (aNSCLC) undergoing anti-PD-1/PD-L1 monotherapy. Material and methods: 125 aNSCLC patients with at least two measurable lesions undergoing PD-1/PD-L1 inhibitor treatment were retrospectively studied. Tumor measurements allowing up to two lesions per organ and five lesions in total were reviewed. Inter-individual agreement and κ values for inter-method concordance on response status were evaluated based on up to five target lesions versus the largest one through four lesions. C-index was calculated to evaluate the prognostic accuracy of response categorization based on the selected number of target lesions for predicting overall survival (OS). Cox regression analysis was conducted for survival analysis. Results: The highly consistent response assignment (99.2%) could be obtained when measuring the largest two lesions versus up to five lesions. Using the largest two through four lesions produced κ values of 0.986, 1.000 and 1.000 for response assessment, values significantly higher than those obtained when measuring the largest single lesion (κ = 0.850). C-index for overall survival (OS) was similar when assessing the largest one through five lesions, ranging from 0.646 to 0.654. Cox regression analyses showed that radiological response significantly predicted OS, irrespective of the number of target lesions selected. Conclusions: Reducing the number of target lesions does not affect OS prediction in aNSCLC patients treated with anti-PD-1/PD-L1 therapy. Considering the high intra-individual and inter-method concordance, using the largest two lesions in total is proposed to assess response.