Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Sample Size Calculations with Dropouts in Clinical Trials

임상시험에서 중도탈락을 고려한 표본크기의 결정

  • Published : 2008.05.30
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Abstract

The sample size in a clinical trial is determined by the hypothesis, the variance of observations, the effect size, the power and the significance level. Dropouts in clinical trials are inevitable, so we need to consider dropouts on the determination of sample size. It is common that some proportion corresponding to the expected dropout rate would be added to the sample size calculated from a mathematical equation. This paper proposes new equations for calculating sample size dealing with dropouts. Since we observe data longitudinally in most clinical trials, we can use a last observation to impute for missing one in the intention to treat (ITT) trials, and this technique is called last observation carried forward(LOCF). But LOCF might make deviations on the assumed variance and effect size, so that we could not guarantee the power of test with the sample size obtained from the existing equation. This study suggests the formulas for sample size involving information about dropouts and shows the properties of the proposed method in testing equality of means.

임상시험에서 피험자수는 검정가설, 변수값의 분산과 유효차이, 검정력과 유의수준 등에 의해 결정되어진다. 일반적으로 수학적으로 계산된 피험자수에 중도탈락 예상치를 고려한 피험자수를 추가하여 최종적인 실험참가자수를 결정하는데 본 논문에서는 이론적인 계산식에서부터 중도탈락을 고려하여 피험자수를 결정하는 방법을 제안한다. 임상시험에서 많은 자료는 경시적(longitudinal) 형태를 갖고, ITT(intention to treat) 실험의 경우 중도탈락이 생기면 결측값으로 처리하지 않고 탈락직전에 관측된 값을 최종값으로 대체하는 LOCF(last observation carried forward) 방법을 주로 사용한다. 이러한 LOCF 방법은 피험자수 계산에 사용했던 분산과 유효차이 값의 가정에 왜곡을 가져오기 때문에 우리가 원하는 검정력을 보장 받지 못할 수 있다. 본 연구에서는 중도탈락률에 관한 정보를 포함하는 피험자수의 결정식을 제안하고 평균의 동일성 검정 경우에 검정력을 비교하여 이러한 산출방식이 합리적임을 실증하였다.

Keywords

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