Sample size calculation and re-estimation based on the prevalence in a single-arm confirmatory diagnostic accuracy study
Sample size calculation and re-estimation based on the prevalence in a single-arm confirmatory diagnostic accuracy study
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DOI：
10.1177/0962280220913588
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发表时间：
2020-04-16
影响因子：
2.3
通讯作者：
Zapf, Antonia
中科院分区：
文献类型：
--
作者：
Stark, Maria;Zapf, Antonia
在确证性诊断准确性研究中，敏感性和特异性被认为是共同的主要终点。对于样本量的计算，必须考虑目标人群的患病率，以获得具有代表性的样本。在这方面，出现了一个普遍的问题。在低患病率或高患病率的情况下，该研究可能在一个亚群中被压倒。另一个问题是正确地预先说明真实的流行程度。如果对患病率的假设不正确，就会导致样本量过高或过低。方法为了获得与患病率无关的所需功率，提出了一种计算最佳样本量的方法，用于对具有预定最小灵敏度和特异性的诊断实验测试进行比较。针对预估患病率不正确的问题，通过仿真研究评估了基于患病率的单盲样本量重估计设计和基于患病率的单盲样本量重复重估计设计。两种设计都与固定设计进行比较，并且彼此之间进行比较。结果两种盲法重估计设计的I型误差率均不存在虚高现象。它们的经验总功率等于期望的理论功率，并且两种设计都提供了对患病率的无偏估计。与一次性重新估计设计相比，重复重新估计设计在重新估计的患病率或样本量的均方误差方面没有优势。在一次性重新估计设计中，内部试点研究的适当规模是初始计算样本量的50%。结论在单臂诊断准确性研究中，建议采用基于最佳样本量计算的患病率一次性重估设计。
IntroductionIn a confirmatory diagnostic accuracy study, sensitivity and specificity are considered as co-primary endpoints. For the sample size calculation, the prevalence of the target population must be taken into account to obtain a representative sample. In this context, a general problem arises. With a low or high prevalence, the study may be overpowered in one subpopulation. One further issue is the correct pre-specification of the true prevalence. With an incorrect assumption about the prevalence, an over- or underestimated sample size will result.MethodsTo obtain the desired power independent of the prevalence, a method for an optimal sample size calculation for the comparison of a diagnostic experimental test with a prespecified minimum sensitivity and specificity is proposed. To face the problem of an incorrectly pre-specified prevalence, a blinded one-time re-estimation design of the sample size based on the prevalence and a blinded repeated re-estimation design of the sample size based on the prevalence are evaluated by a simulation study. Both designs are compared to a fixed design and additionally among each other.ResultsThe type I error rates of both blinded re-estimation designs are not inflated. Their empirical overall power equals the desired theoretical power and both designs offer unbiased estimates of the prevalence. The repeated re-estimation design reveals no advantages concerning the mean squared error of the re-estimated prevalence or sample size compared to the one-time re-estimation design. The appropriate size of the internal pilot study in the one-time re-estimation design is 50% of the initially calculated sample size.ConclusionsA one-time re-estimation design of the prevalence based on the optimal sample size calculation is recommended in single-arm diagnostic accuracy studies.