The tumor objective response rate(ORR)is an important parameter to demonstrate the efficacy of a treatment in oncology.The ORR is valuable for clinical decision making in routine practice and a significant end-point f...The tumor objective response rate(ORR)is an important parameter to demonstrate the efficacy of a treatment in oncology.The ORR is valuable for clinical decision making in routine practice and a significant end-point for reporting the results of clinical trials.World Health Organization and Response Evaluation Criteria in Solid Tumors(RECIST)are anatomic response criteria developed mainly for cytotoxic chemotherapy.These criteria are based on the visual assessment of tumor size in morphological images provided by computed tomography(CT)or magnetic resonance imaging.Anatomic response criteria may not be optimal for biologic agents,some disease sites,and some regional therapies.Consequently,modifications of RECIST,Choi criteria and Morphologic response criteria were developed based on the concept of the evaluation of viable tumors.Despite its limitations,RECIST v1.1 is validated in prospective studies,is widely accepted by regulatory agencies and has recently shown good performance for targeted cancer agents.Finally,some alternatives of RECIST were developed as immune-specific response criteria for checkpoint inhibitors.Immune RECIST criteria are based essentially on defining true progressive disease after a confirmatory imaging.Some graphical methods may be useful to show longitudinal change in the tumor burden over time.Tumor tissue is a tridimensional heterogenous mass,and tumor shrinkage is not always symmetrical;thus,metabolic response assessments using positron emission tomography(PET)or PET/CT may reflect the viability of cancer cells or functional changes evolving after anticancer treatments.The metabolic response can show the benefit of a treatment earlier than anatomic shrinkage,possibly preventing delays in drug approval.Computer-assisted automated volumetric assessments,quantitative multimodality imaging in radiology,new tracers in nuclear medicine and finally artificial intelligence have great potential in future evaluations.展开更多
文摘The tumor objective response rate(ORR)is an important parameter to demonstrate the efficacy of a treatment in oncology.The ORR is valuable for clinical decision making in routine practice and a significant end-point for reporting the results of clinical trials.World Health Organization and Response Evaluation Criteria in Solid Tumors(RECIST)are anatomic response criteria developed mainly for cytotoxic chemotherapy.These criteria are based on the visual assessment of tumor size in morphological images provided by computed tomography(CT)or magnetic resonance imaging.Anatomic response criteria may not be optimal for biologic agents,some disease sites,and some regional therapies.Consequently,modifications of RECIST,Choi criteria and Morphologic response criteria were developed based on the concept of the evaluation of viable tumors.Despite its limitations,RECIST v1.1 is validated in prospective studies,is widely accepted by regulatory agencies and has recently shown good performance for targeted cancer agents.Finally,some alternatives of RECIST were developed as immune-specific response criteria for checkpoint inhibitors.Immune RECIST criteria are based essentially on defining true progressive disease after a confirmatory imaging.Some graphical methods may be useful to show longitudinal change in the tumor burden over time.Tumor tissue is a tridimensional heterogenous mass,and tumor shrinkage is not always symmetrical;thus,metabolic response assessments using positron emission tomography(PET)or PET/CT may reflect the viability of cancer cells or functional changes evolving after anticancer treatments.The metabolic response can show the benefit of a treatment earlier than anatomic shrinkage,possibly preventing delays in drug approval.Computer-assisted automated volumetric assessments,quantitative multimodality imaging in radiology,new tracers in nuclear medicine and finally artificial intelligence have great potential in future evaluations.
