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针对疾病患病率未知的前瞻性癌症筛查试验的内部试点设计。

An internal pilot design for prospective cancer screening trials with unknown disease prevalence.

作者信息

Brinton John T, Ringham Brandy M, Glueck Deborah H

机构信息

Denver Health Medical Center, 777 Bannock St., MC 6551, Denver, Colorado, 80204, USA.

Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, 13001 E. 17th Place, Aurora, Colorado, 80045, USA.

出版信息

Trials. 2015 Oct 13;16:458. doi: 10.1186/s13063-015-0951-3.

Abstract

BACKGROUND

For studies that compare the diagnostic accuracy of two screening tests, the sample size depends on the prevalence of disease in the study population, and on the variance of the outcome. Both parameters may be unknown during the design stage, which makes finding an accurate sample size difficult.

METHODS

To solve this problem, we propose adapting an internal pilot design. In this adapted design, researchers will accrue some percentage of the planned sample size, then estimate both the disease prevalence and the variances of the screening tests. The updated estimates of the disease prevalence and variance are used to conduct a more accurate power and sample size calculation.

RESULTS

We demonstrate that in large samples, the adapted internal pilot design produces no Type I inflation. For small samples (N less than 50), we introduce a novel adjustment of the critical value to control the Type I error rate. We apply the method to two proposed prospective cancer screening studies: 1) a small oral cancer screening study in individuals with Fanconi anemia and 2) a large oral cancer screening trial.

CONCLUSION

Conducting an internal pilot study without adjusting the critical value can cause Type I error rate inflation in small samples, but not in large samples. An internal pilot approach usually achieves goal power and, for most studies with sample size greater than 50, requires no Type I error correction. Further, we have provided a flexible and accurate approach to bound Type I error below a goal level for studies with small sample size.

摘要

背景

对于比较两种筛查试验诊断准确性的研究,样本量取决于研究人群中疾病的患病率以及结果的方差。在设计阶段,这两个参数可能都是未知的,这使得确定准确的样本量变得困难。

方法

为了解决这个问题,我们建议采用一种内部预试验设计。在这种改进的设计中,研究人员将积累计划样本量的一定比例,然后估计疾病患病率和筛查试验的方差。疾病患病率和方差的更新估计值用于进行更准确的效能和样本量计算。

结果

我们证明,在大样本中,改进的内部预试验设计不会产生第一类错误膨胀。对于小样本(N小于50),我们引入了一种对临界值的新颖调整方法来控制第一类错误率。我们将该方法应用于两项拟议的前瞻性癌症筛查研究:1)一项针对范可尼贫血患者的小型口腔癌筛查研究,以及2)一项大型口腔癌筛查试验。

结论

在不调整临界值的情况下进行内部预试验研究,在小样本中可能会导致第一类错误率膨胀,但在大样本中不会。内部预试验方法通常能达到目标效能,并且对于大多数样本量大于50的研究,不需要进行第一类错误校正。此外,对于小样本量的研究,我们提供了一种灵活且准确的方法,可将第一类错误限制在目标水平以下。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cef3/4604650/227fb4bef638/13063_2015_951_Fig1_HTML.jpg

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