The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Comparing the Randomization Methods Considering the Covariates in a Clinical Trial

임상시험에서의 공변량을 고려한 확률화 방법들의 비교

  • Yu, A-Mi (Department of Statistics, Korea University) ;
  • Lee, Jae-Won (Department of Statistics, Korea University)
  • Received : 20091000
  • Accepted : 20100500
  • Published : 2010.12.31
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Abstract

In clinical trials, patients should be randomly allocated to treatment and control groups that consider the balance of their prognostic factors(covariates). There are many randomization methods and stratification is popular in Korea. In stratification, patients are divided into strata based on covariates and then the patients are randomly assigned to the arms of each strata. If the number of covariates increases then the number of strata increases rapidly and the results may not be reliable when the patients are inadequate in each strata. To complement this problem Pocock and Simon (1975) suggested a new randomization method that called for minimization focusing on the balance of covariates. In this study, we compare the advantages and disadvantages, the imbalance of covariates, the power of minimization, and other randomization methods by simulation.

임상시험에서 환자들을 각 처리로 할당할 때 반응변수에 영향을 미치는 공변량이 존재하면 공변량도 함께 고려하여 환자들을 랜덤하게 배치하여야 한다. 확률화(randomization) 방법들에는 여러 가지가 있으나 공변량에 따라 환자들을 배치하는 방법으로 층화(stratification)를 많이 사용한다. 층화는 환자들을 공변량에 따라 여러 층으로 나누고 각 층들 안에서 환자들을 랜덤하게 배치하는 방법인데, 공변량의 수가 많아지면 층의 수가 급격하게 늘어나기 때문에 층마다의 환자수가 충분히 많지 않으면 그 결과를 신뢰할 수 없게 된다. 이를 보완하기 위한 방법으로 Pocock과 Simon (1975)은 최소화(minimization) 방법을 제안하였으며 이 방법은 처리에 대한 공변량의 균형을 맞추는 것에 중점을 두었다. 본 논문에서는 현재 가장 많이 쓰이고 있는 확률화 방법들과 최소화 방법의 장단점, 불균형의 정도 및 검정력을 모의실험 연구를 통해 비교해보고자 한다.

Keywords

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