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1.  Analysis of randomized comparative clinical trial data for personalized treatment selections 
Biostatistics (Oxford, England)  2010;12(2):270-282.
Suppose that under the conventional randomized clinical trial setting, a new therapy is compared with a standard treatment. In this article, we propose a systematic, 2-stage estimation procedure for the subject-level treatment differences for future patient's disease management and treatment selections. To construct this procedure, we first utilize a parametric or semiparametric method to estimate individual-level treatment differences, and use these estimates to create an index scoring system for grouping patients. We then consistently estimate the average treatment difference for each subgroup of subjects via a nonparametric function estimation method. Furthermore, pointwise and simultaneous interval estimates are constructed to make inferences about such subgroup-specific treatment differences. The new proposal is illustrated with the data from a clinical trial for evaluating the efficacy and toxicity of a 3-drug combination versus a standard 2-drug combination for treating HIV-1–infected patients.
doi:10.1093/biostatistics/kxq060
PMCID: PMC3062150  PMID: 20876663
Cross-validation; HIV infection; Non-parametric function estimation; Personalized medicine; Subgroup analysis
2.  Exact and efficient inference procedure for meta-analysis and its application to the analysis of independent 2 × 2 tables with all available data but without artificial continuity correction 
Biostatistics (Oxford, England)  2008;10(2):275-281.
Recently, meta-analysis has been widely utilized to combine information across comparative clinical studies for evaluating drug efficacy or safety profile. When dealing with rather rare events, a substantial proportion of studies may not have any events of interest. Conventional methods either exclude such studies or add an arbitrary positive value to each cell of the corresponding 2×2 tables in the analysis. In this article, we present a simple, effective procedure to make valid inferences about the parameter of interest with all available data without artificial continuity corrections. We then use the procedure to analyze the data from 48 comparative trials involving rosiglitazone with respect to its possible cardiovascular toxicity.
doi:10.1093/biostatistics/kxn034
PMCID: PMC2648899  PMID: 18922759
Continuity correction for zero events; Exact inference procedure; Odds ratio; Risk difference

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