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Alterations in the gene encoding fibroblast growth factor receptor (In this open-label, phase 2 study, we enrolled patients who had locally advanced and unresectable or metastatic urothelial carcinoma with prespecifiedA total of 99 patients in the selected-regimen group received a median of five cycles of erdafitinib. Of these patients, 43% had received at least two previous courses of treatment, 79% had visceral metastases, and 53% had a creatinine clearance of less than 60 ml per minute. The rate of confirmed response to erdafitinib therapy was 40% (3% with a complete response and 37% with a partial response). Among the 22 patients who had undergone previous immunotherapy, the confirmed response rate was 59%. The median duration of progression-free survival was 5.5 months, and the median duration of overall survival was 13.8 months. Treatment-related adverse events of grade 3 or higher, which were managed mainly by dose adjustments, were reported in 46% of the patients; 13% of the patients discontinued treatment because of adverse events. There were no treatment-related deaths.The use of erdafitinib was associated with an objective tumor response in 40% of previously treated patients who had locally advanced and unresectable or metastatic urothelial carcinoma with

We develop an assimilation method of high horizontal resolution sea surface temperature data, provided from the Moderate Resolution Imaging Spectroradiometer (MODIS-SST) sensors boarded on the Aqua and Terra satellites operated by National Aeronautics and Space Administration (NASA), focusing on the reproducibility of the Kuroshio front variations south of Japan in February 2010. Major concerns associated with the development are (1) negative temperature bias due to the cloud effects, and (2) the representation of error covariance for detection of highly variable phenomena. We treat them by utilizing an advanced data assimilation method allowing use of spatiotemporally varying error covariance: the Local Ensemble Transformation Kalman Filter (LETKF). It is found that the quality control, by comparing the model forecast variable with the MODIS-SST data, is useful to remove the negative temperature bias and results in the mean negative bias within -0.4 °C. The additional assimilation of MODIS-SST enhances spatial variability of analysis SST over 50 km to 25 km scales. The ensemble spread variance is effectively utilized for excluding the erroneous temperature data from the assimilation process., 資料番号: PA1410065000