An optimization algorithm for designing phase I cancer clinical trials

@article{citeulike:2473617, abstract = {Numerous phase I dose finding clinical trials are conducted everyday to find the "maximum tolerated dose" (MTD) of a cancer treatment. Although various Bayesian designs for Phase I clinical trials have been proposed in the literature, the traditional 3 + 3 design is still widely used because of its algorithm-based simplicity in logistics for the clinical investigators to carry out in comparison with model-based Bayesian methods. In this paper, we propose an optimization algorithm for designing phase I cancer clinical trials. This algorithm does not need assumptions on the true dose-response relationship but can readily incorporate available prior information about the true response probabilities. It searches for an approximately optimal design within a design space, in which the 3 + 3 design is included as a special case. Simulation studies show that the design recommended by this algorithm significantly outperforms the 3 + 3 design.}, author = {Jiang, Hui and Liu, Yifan and Su, Zheng }, citeulike-article-id = {2473617}, doi = {10.1016/j.cct.2007.06.003}, journal = {Contemporary Clinical Trials}, keywords = {algorithm\_based\_design, clinical\_trial, phase\_i}, month = {March}, number = {2}, pages = {102--108}, posted-at = {2008-03-05 16:30:06}, priority = {2}, title = {An optimization algorithm for designing phase I cancer clinical trials}, url = {http://dx.doi.org/10.1016/j.cct.2007.06.003}, volume = {29}, year = {2008} }

TY - JOUR ID - citeulike:2473617 L3 - citeulike-article-id:2473617 TI - An optimization algorithm for designing phase I cancer clinical trials JF - Contemporary Clinical Trials VL - 29 IS - 2 SP - 102 EP - 108 N2 - Numerous phase I dose finding clinical trials are conducted everyday to find the "maximum tolerated dose" (MTD) of a cancer treatment. Although various Bayesian designs for Phase I clinical trials have been proposed in the literature, the traditional 3 + 3 design is still widely used because of its algorithm-based simplicity in logistics for the clinical investigators to carry out in comparison with model-based Bayesian methods. In this paper, we propose an optimization algorithm for designing phase I cancer clinical trials. This algorithm does not need assumptions on the true dose-response relationship but can readily incorporate available prior information about the true response probabilities. It searches for an approximately optimal design within a design space, in which the 3 + 3 design is included as a special case. Simulation studies show that the design recommended by this algorithm significantly outperforms the 3 + 3 design. KW - algorithm_based_design KW - clinical_trial KW - phase_i AU - Jiang, Hui AU - Liu, Yifan AU - Su, Zheng PY - 2008/03// UR - http://dx.doi.org/10.1016/j.cct.2007.06.003 ER -