R
Ruitao Lin
Researcher at University of Texas MD Anderson Cancer Center
Publications - 64
Citations - 735
Ruitao Lin is an academic researcher from University of Texas MD Anderson Cancer Center. The author has contributed to research in topics: Medicine & Computer science. The author has an hindex of 10, co-authored 42 publications receiving 367 citations. Previous affiliations of Ruitao Lin include University of Texas at Austin & Northeast Normal University.
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A phase 3 randomized study of 5-azacitidine maintenance vs observation after transplant in high-risk AML and MDS patients.
Betul Oran,Marcos de Lima,Guillermo Garcia-Manero,Peter F. Thall,Ruitao Lin,Uday R. Popat,Amin M. Alousi,Chitra Hosing,Sergio Giralt,Gabriela Rondon,Glenda Woodworth,Richard E. Champlin +11 more
TL;DR: This randomized trial with azacitidine maintenance showed that a prospective trial in the posttransplant setting was feasible and safe but challenging, and it is believed the strategy of maintenance therapy merits further study with a goal to reduce the risk of relapse in patients with AML/MDS.
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Bayesian optimal interval design for dose finding in drug-combination trials:
Ruitao Lin,Guosheng Yin +1 more
TL;DR: A Bayesian optimal interval design for dose finding in drug-combination trials is developed and enjoys convergence properties for large samples and the entire dose-finding procedure is nonparametric (model-free), which is thus robust and also does not require the typical “nonparametric” prephase used in model-based designs for drug- Combination trials.
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Time-to-Event Bayesian Optimal Interval Design to Accelerate Phase I Trials.
TL;DR: Numerical studies show that the TITE-BOIN design supports continuous accrual without sacrificing patient safety or the accuracy of identifying the MTD, and therefore has great potential to accelerate early-phase drug development.
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Inter-Ethnic/Racial Facial Variations: A Systematic Review and Bayesian Meta- Analysis of Photogrammetric Studies
TL;DR: A comprehensive database for angular and linear facial measurements was established from existing studies using the statistical model and inter-ethnic/racial variations of facial features were observed.
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BOIN12: Bayesian Optimal Interval Phase I/II Trial Design for Utility-Based Dose Finding in Immunotherapy and Targeted Therapies
TL;DR: A simple and flexible Bayesian optimal interval phase I/II (BOIN12) trial design to find the OBD that optimizes the risk-benefit trade-off and provides a useful design to optimize the dose of immunotherapy and targeted therapy.