• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.161-175
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• 2001

Meta-analysis refers to quantitative methods for combining results from independent studies in order to draw overall conclusions. Hierarchical models including selection models are introduced and shown to be useful in such Bayesian meta-analysis. Semiparametric hierarchical models are proposed using the Dirichlet process prior. These rich class of models combine the information of independent studies, allowing investigation of variability both between and within studies, and weight function. Here we investigate sensitivity of results to unobserved studies by considering a hierachical selection model with including unknown weight function and use Markov chain Monte Carlo methods to develop inference for the parameters of interest. Using Bayesian method, this model is used on a meta-analysis of twelve studies comparing the effectiveness of two different types of flouride, in preventing cavities. Clinical informative prior is assumed. Summaries and plots of model parameters are analyzed to address questions of interest.

• Communications for Statistical Applications and Methods
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• v.24 no.6
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• pp.561-581
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• 2017

Bayesian statistics can play a key role in the design and analysis of clinical trials and this has been demonstrated for medical device trials. By 1995 Bayesian statistics had been well developed and the revolution in computing powers and Markov chain Monte Carlo development made calculation of posterior distributions within computational reach. The Food and Drug Administration (FDA) initiative of Bayesian statistics in medical device clinical trials, which began almost 20 years ago, is reviewed in detail along with some of the key decisions that were made along the way. Both Bayesian hierarchical modeling using data from previous studies and Bayesian adaptive designs, usually with a non-informative prior, are discussed. The leveraging of prior study data has been accomplished through Bayesian hierarchical modeling. An enormous advantage of Bayesian adaptive designs is achieved when it is accompanied by modeling of the primary endpoint to produce the predictive posterior distribution. Simulations are crucial to providing the operating characteristics of the Bayesian design, especially for a complex adaptive design. The 2010 FDA Bayesian guidance for medical device trials addressed both approaches as well as exchangeability, Type I error, and sample size. Treatment response adaptive randomization using the famous extracorporeal membrane oxygenation example is discussed. An interesting real example of a Bayesian analysis using a failed trial with an interesting subgroup as prior information is presented. The implications of the likelihood principle are considered. A recent exciting area using Bayesian hierarchical modeling has been the pediatric extrapolation using adult data in clinical trials. Historical control information from previous trials is an underused area that lends itself easily to Bayesian methods. The future including recent trends, decision theoretic trials, Bayesian benefit-risk, virtual patients, and the appalling lack of penetration of Bayesian clinical trials in the medical literature are discussed.

• Journal of Genetic Medicine
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• v.19 no.1
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• pp.7-13
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• 2022

Purpose: Preimplantation genetic testing for monogenic disorders (PGT-M) has been successfully used to prevent couples with monogenic disorders from passing them on to their child. Charcot-Marie-Tooth Disease (CMT) is a genetic disorder characterized by progressive extremity muscle degeneration and loss of sensory function. For the first time in Korea, we report our experience of applying single nucleotide polymorphism genotyping and karyomapping for PGT-M of CMT disease. Materials and Methods: Prior to clinical PGT-M, preclinical tests were performed using genotypes of affected families to identify informative single-nucleotide polymorphisms associated with mutant alleles. We performed five cycles of in vitro fertilization PGT-M in four couples with CMT1A, CMT2A, and CMT2S in CHA Fertility Center, Seoul Station. Results: From July 2020 through August 2021, five cycles of PGT-M with karyomapping in four cases with CMT1 and CMT2 were analyzed retrospectively. A total of 17 blastocysts were biopsied and 15 embryos were successfully diagnosed (88.2%). Ten out of 15 embryos were diagnosed as unaffected (66.7%). Five cycles of PGT-M resulted in four transfer cycles, in which four embryos were transferred. Three clinical pregnancies were achieved (75%) and the prenatal diagnosis by amniocentesis for all three women confirmed PGT-M of karyomapping. One woman delivered a healthy baby uneventfully and two pregnancies are currently ongoing. Conclusion: This is the first report in Korea on the application of karyomapping in PGT-M for CMT patients. This study shows that karyomapping is an efficient, reliable and accurate diagnostic method for PGT-M in various types of CMT diseases.