Research Topics
 Shigeyuki MatsuiSummaryAffiliation: Institute of Statistical Mathematics Country: Japan Publications
 Collaborators

Detail Information
Publications
 Study protocol of the SACURA trial: a randomized phase III trial of efficacy and safety of UFT as adjuvant chemotherapy for stage II colon cancerMegumi Ishiguro
Department of Surgical Oncology, Tokyo Medical and Dental University, Graduate School, 1 5 45 Yushima, Tokyo 113 8519, Japan
BMC Cancer 12:281. 2012..The major Western guidelines recommend adjuvant chemotherapy for "highrisk stage II" cancer, but this is not clearly defined and the efficacy has not been confirmed...  Genomic biomarkers for personalized medicine: development and validation in clinical studiesShigeyuki Matsui
Department of Data Science, The Institute of Statistical Mathematics, 10 3 Midori cho, Tachikawa, Tokyo 190 8562, Japan
Comput Math Methods Med 2013:865980. 2013..A wide variety of biomarkerbased clinical trial designs to assess clinical utility of a biomarker or a new treatment with a companion biomarker are also discussed...  Developing and validating continuous genomic signatures in randomized clinical trials for predictive medicineShigeyuki Matsui
Department of Data Science, The Institute of Statistical Mathematics, Tachikawa, Tokyo, Japan
Clin Cancer Res 18:606573. 2012..Development and validation of genomic signatures in the randomized trial can be a promising solution. Such signatures are required to predict quantitatively the underlying heterogeneity in the magnitude of treatment effects...  Sample sizes for a robust ranking and selection of genes in microarray experimentsShigeyuki Matsui
Department of Data Science, The Institute of Statistical Mathematics, Tokyo, Japan
Stat Med 28:280116. 2009..Application to the data set from a clinical study for lymphoma is given...  Estimation and selection in highdimensional genomic studies for developing molecular diagnosticsShigeyuki Matsui
Department of Data Science, The Institute of Statistical Mathematics, Tokyo, Japan
Biostatistics 12:22333. 2011..We can assess the predictive capability for any gene sets, possibly those selected via incorporation of biological considerations. Applications to 2 gene expression data sets from cancer clinical studies with microarrays are provided...  Estimating effect sizes of differentially expressed genes for power and samplesize assessments in microarray experimentsShigeyuki Matsui
Department of Data Science, The Institute of Statistical Mathematics, 10 3 Midori cho, Tachikawa, Tokyo 190 8562, Japan
Biometrics 67:122535. 2011..Applications to two real datasets from cancer clinical studies are provided...  An empirical Bayes optimal discovery procedure based on semiparametric hierarchical mixture modelsHisashi Noma
Department of Data Science, The Institute of Statistical Mathematics, 10 3 Midori cho, Tachikawa, Tokyo 190 8562, Japan
Comput Math Methods Med 2013:568480. 2013..In addition, we provide a significance rule based on the false discovery rate (FDR) in the empirical Bayes framework. Applications to two clinical studies are presented...  Cancer outlier analysis based on mixture modeling of gene expression dataKeita Mori
Department of Statistical Science, School of Multidisciplinary Sciences, The Graduate University for Advanced Studies, 10 3 Midori cho, Tachikawa, Tokyo 190 8562, Japan
Comput Math Methods Med 2013:693901. 2013..Some efficiency improvement by using our method was demonstrated, even under settings with misspecified, heavytailed tdistributions. An application to a real dataset from hematologic malignancies is provided...  Empirical Bayes ranking and selection methods via semiparametric hierarchical mixture models in microarray studiesHisashi Noma
Department of Data Science, The Institute of Statistical Mathematics, 10 3 Midori cho, Tachikawa, Tokyo, 190 8562, Japan
Stat Med 32:190416. 2013..We present applications to childhood and infant leukemia clinical studies with microarrays for exploring genes related to prognosis or disease progression...  Quantifying indirect evidence in network metaanalysisHisashi Noma
Department of Data Science, The Institute of Statistical Mathematics, Tokyo, Japan
Stat Med . 2016..In addition, the efficiency of the developed method is demonstrated based on simulation studies. Applications to a network metaanalysis of 12 newgeneration antidepressants are presented. Copyright © 2016 John Wiley & Sons, Ltd...