Objective： Response Evaluation Criteria in Solid Tumors （RECIST） guideline version 1.0 （RECIST 1.0） was proposed as a new guideline for evaluating tumor response and has been widely accepted as a standardized mea...Objective： Response Evaluation Criteria in Solid Tumors （RECIST） guideline version 1.0 （RECIST 1.0） was proposed as a new guideline for evaluating tumor response and has been widely accepted as a standardized measure. With a number of issues being raised on RECIST 1.0, however, a revised RECIST guideline version 1.1 （RECIST 1.1） was proposed by the RECIST Working Group in 2009. This study was conducted to compare CT tumor response based on RECIST 1.1 vs. RECIST 1.0 in patients with advanced gastric cancer （AGC）. Methods： We reviewed 61 AGC patients with measurable diseases by RECIST 1.0 who were enrolled in other clinical trials between 2008 and 2010. These patients were retrospectively re-analyzed to determine the concordance between the two response criteria using the κ statistic. Results： The number and sum of tumor diameters of the target lesions by RECIST 1.1 were significantly lower than those by RECIST 1.0 （P〈0.0001）. However, there was excellent agreement in tumor response between RECIST 1.1 and RECIST 1.0 0（κ=0.844）. The overall response rates （ORRs） according to RECIST 1.0 and RECIST 1.1 were 32.7% （20/61） and 34.5% （20/58）, respectively. One patient with partial response （PR） based on RECIST 1.0 was reclassified as stable disease （SD） by RECIST 1.1. Of two patients with SD by RECIST 1.0, one was downgraded to progressive disease and the other was upgraded to PR by RECIST 1.1. Conclusions： RECIST 1.1 provided almost perfect agreement with RECIST 1.0 in the CT assessment of tumor response of AGC.展开更多
The global energy cycle is a diagnostic metric widely used to gauge the quality of datasets. In this paper, the "Mixed Space-Time Domain" method for diagnosis of energy cycle is evaluated by using newly deve...The global energy cycle is a diagnostic metric widely used to gauge the quality of datasets. In this paper, the "Mixed Space-Time Domain" method for diagnosis of energy cycle is evaluated by using newly developed datasets-the Chinese Reanalysis Interim (CRAI) and ECMWF Reanalysis version 5 (ERA5), over a 7-yr period (2010-16) on seasonal and monthly timescales. The results show that the energy components calculated from the two reanalysis datasets are highly consistent;however, some components in the global energy integral from CRAI are slightly larger than those from ERA5. The main discrepancy in the energy components stems from the conversion of baroclinic process, whereas the dominant difference originates from the conversion from stationary eddy available potential energy to stationary eddy kinetic energy (CES), which is caused by systematic differences in the temperature and vertical velocity in low-mid latitudes of the Northern Hemisphere and near the Antarctic, where there exist complex terrains. Furthermore, the monthly analysis reveals that the general discrepancy in the temporal variation between the two datasets also lie mainly in the CES as well as corresponding generation and dissipation rates.展开更多
文摘Objective： Response Evaluation Criteria in Solid Tumors （RECIST） guideline version 1.0 （RECIST 1.0） was proposed as a new guideline for evaluating tumor response and has been widely accepted as a standardized measure. With a number of issues being raised on RECIST 1.0, however, a revised RECIST guideline version 1.1 （RECIST 1.1） was proposed by the RECIST Working Group in 2009. This study was conducted to compare CT tumor response based on RECIST 1.1 vs. RECIST 1.0 in patients with advanced gastric cancer （AGC）. Methods： We reviewed 61 AGC patients with measurable diseases by RECIST 1.0 who were enrolled in other clinical trials between 2008 and 2010. These patients were retrospectively re-analyzed to determine the concordance between the two response criteria using the κ statistic. Results： The number and sum of tumor diameters of the target lesions by RECIST 1.1 were significantly lower than those by RECIST 1.0 （P〈0.0001）. However, there was excellent agreement in tumor response between RECIST 1.1 and RECIST 1.0 0（κ=0.844）. The overall response rates （ORRs） according to RECIST 1.0 and RECIST 1.1 were 32.7% （20/61） and 34.5% （20/58）, respectively. One patient with partial response （PR） based on RECIST 1.0 was reclassified as stable disease （SD） by RECIST 1.1. Of two patients with SD by RECIST 1.0, one was downgraded to progressive disease and the other was upgraded to PR by RECIST 1.1. Conclusions： RECIST 1.1 provided almost perfect agreement with RECIST 1.0 in the CT assessment of tumor response of AGC.
基金Supported by the China Meteorological Administration(CMA)Special Public Welfare Research Fund(GYHY201506002)National Key Research and Development Program of China(2017YFA0604500)+1 种基金CMA Special Project for Developing Key Techniques for Operational Meteorological Forecast(YBGJXM201706)National Natural Science Foundation of China(41305091)
文摘The global energy cycle is a diagnostic metric widely used to gauge the quality of datasets. In this paper, the "Mixed Space-Time Domain" method for diagnosis of energy cycle is evaluated by using newly developed datasets-the Chinese Reanalysis Interim (CRAI) and ECMWF Reanalysis version 5 (ERA5), over a 7-yr period (2010-16) on seasonal and monthly timescales. The results show that the energy components calculated from the two reanalysis datasets are highly consistent;however, some components in the global energy integral from CRAI are slightly larger than those from ERA5. The main discrepancy in the energy components stems from the conversion of baroclinic process, whereas the dominant difference originates from the conversion from stationary eddy available potential energy to stationary eddy kinetic energy (CES), which is caused by systematic differences in the temperature and vertical velocity in low-mid latitudes of the Northern Hemisphere and near the Antarctic, where there exist complex terrains. Furthermore, the monthly analysis reveals that the general discrepancy in the temporal variation between the two datasets also lie mainly in the CES as well as corresponding generation and dissipation rates.
