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Full-Text Articles in Social and Behavioral Sciences
Prognostic Impact Of P53 Status, Tls-Chop Fusion Transcript Structure, And Histological Grade In Myxoid Liposarcoma: A Molecular And Clinicopathologic Study Of 82 Cases, C. R. Antonescu, S. J. Tschernyavsky, R. Decuseara, Denis H. Y. Leung, J. M. Woodruff, M. F. Brennan, J. A. Bridge, J. R. Neff, J. R. Goldblum, M. Ladanyi
Prognostic Impact Of P53 Status, Tls-Chop Fusion Transcript Structure, And Histological Grade In Myxoid Liposarcoma: A Molecular And Clinicopathologic Study Of 82 Cases, C. R. Antonescu, S. J. Tschernyavsky, R. Decuseara, Denis H. Y. Leung, J. M. Woodruff, M. F. Brennan, J. A. Bridge, J. R. Neff, J. R. Goldblum, M. Ladanyi
Research Collection School Of Economics
Purpose: A specific TLS-CHOP fusion gene resulting from the t(12;16) is present in at least 95% of myxoid liposarcomas (MLS). Three common forms of the TLS-CHOP fusion have been described, differing by the presence or absence of TLS exons 6-8 in the fusion product. Type 5-2 (also known as type II) consists of TLS exons 1-5 fused to CHOP exon 2; type 7-2 (also known as type I) also includes TLS exons 6 and 7 in the fusion, whereas type 8-2 (also known as type III) fuses TLS exons 1-8 to CHOP exon 2. We sought to determine the impact …
Validation Of Tissue Microarrays For Immunohistochemical Profiling Of Cancer Specimens Using The Example Of Human Fibroblastic Tumors, Axel Hoos, M. J. Urist, A. Stojadinovic, S. Mastorides, M. Dudas, Denis H. Y. Leung
Validation Of Tissue Microarrays For Immunohistochemical Profiling Of Cancer Specimens Using The Example Of Human Fibroblastic Tumors, Axel Hoos, M. J. Urist, A. Stojadinovic, S. Mastorides, M. Dudas, Denis H. Y. Leung
Research Collection School Of Economics
Tissue microarrays allow high-throughput molecular profiling of cancer specimens by immunohistochemistry. Phenotype information of sections from arrayed biopsies on a multitissue block needs to be representative of full sections, as protein expression varies throughout the entire tumor specimen. To validate the use of tissue microarrays for immunophenotyping, we studied a group of 59 fibroblastic tumors with variable protein expression patterns by immunohistochemistry for Ki-67, p53, and the retinoblastoma protein (pRB). Data on full tissue sections were compared to the results of one, two, and three 0.6-mm core biopsies per tumor on a tissue array. Ki-67 and p53 staining was read …
Optimal Designs For Evaluating A Series Of Treatments, Denis H. Y. Leung, You Gan Wang
Optimal Designs For Evaluating A Series Of Treatments, Denis H. Y. Leung, You Gan Wang
Research Collection School Of Economics
Several articles in this journal have studied optimal designs for testing a series of treatments to identify promising ones for further study. These designs formulate testing as an ongoing process until a promising treatment is identified. This formulation is considered to be more realistic but substantially increases the computational complexity. In this article, we show that these new designs, which control the error rates for a series of treatments, can be reformulated as conventional designs that control the error rates for each individual treatment. This reformulation leads to a more meaningful interpretation of the error rates and hence easier specification …
A Bayesian Decision Approach For Sample Size Determination In Phase Ii Trials, Denis H. Y. Leung, You-Gan Wang
A Bayesian Decision Approach For Sample Size Determination In Phase Ii Trials, Denis H. Y. Leung, You-Gan Wang
Research Collection School Of Economics
Stallard (1998, Biometrics54, 279–294) recently used Bayesian decision theory for sample-size determination in phase II trials. His design maximizes the expected financial gains in the development of a new treatment. However, it results in a very high probability (0.65) of recommending an ineffective treatment for phase III testing. On the other hand, the expected gain using his design is more than 10 times that of a design that tightly controls the false positive error (Thall and Simon, 1994, Biometrics50, 337–349). Stallard's design maximizes the expected gain per phase II trial, but it does not maximize the rate of gain or …