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AME循证杂谈022|诊断准确性研究的样本量计算——基于PASS软件实现

Published at: 2015年第1卷第S1期

周支瑞
关键词:

样本量计算第三弹如约而至,今天我们探讨下诊断准确性研究的样本量计算。最常见的诊断准确性研究的设计类型是横断面设计的诊断试验,该类型的诊断试验设计模式如图1所示。

图1 基于横断面设计的诊断试验模式图

下面我们就以此类型的诊断准确性研究为案例,介绍横断面设计的诊断试验样本量计算方法在PASS软件中的实现。

【案例】一研究者计划研究超声诊断胆囊结石的准确度,手术探查为金标准,预实验结果见表1,取alpha=0.05,power=90%,双侧检验,总计需要多少样本?

表1. 超生波诊断胆囊结石预实验数据

 

第一步,首先计算预实验中的敏感度、特异度

敏感度=64/(64+16)=64/80=0.8

特异度=42/(28+42)=42/70=0.6

人群患病率=64/150≈0.4(此处应该为先验概率,理论上应该是人群总体的胆囊结石的患病率,本例用样本的胆囊结石的患病率代替先验概率)

第二步,如图依次点击:    

图2 依次选择Diagnostic Test (ROC)----Test For One-Sample Sensitivity and Specificity

第三步,如图填入参数

图3 设置参数

参数的具体含义及解释如下:

n(Specificity)表示待计算的样本量,按Specificity计算样本量,此处为选择项;power=90%表示把握度为0.9,alpha=0.05表示检验水准为0.05;P ( Prevalence)=0.4,此处应该为先验概率,理论上应该是人群总体的胆囊结石的患病率,本例用样本的胆囊结石的患病率代替先验概率;Se0 (Null Sensitivity)=0.5,Se1 (Alternative Sensitivity)=0.8,Sp0 (Null Specificity)=0.5,Sp1 (Alternative Specificity)=0.6,此处敏感度及特异度基线值设置为0.5,也可以根据实际情况设置为一个更大的数值,一般来说应不小于0.5。

样本量计算结果及报道如下:

One-Sample Sensitivity and Specificity Power Analysis

Numeric Results for testing H0: Se = Se0 vs. H1: Se ≠ Se0 and H0: Sp = Sp0 vs. H1: Sp ≠ Sp0

Test Statistic: Binomial Test

 

References

Obuchowski, N.A., Zhou, X.H. 2002. 'Prospective studies of diagnostic test accuracy when disease prevalence is low,' Biostatistics, Volume 3, No. 4, pages 477-492.

Li, J., Fine, J. 2004. 'On sample size for sensitivity and specificity in prospective diagnostic accuracy studies,' Statistics in Medicine, Volume 23, pages 2537-2550.

Machin, D., Campbell, M.J., Tan, S.B., Tan, S.H. 2008. Sample Size Tables for Clinical Studies, Third Edition. Wiley-Blackwell, Chichester, United Kingdom.

Zhou, X.H., Obuchowski, N.A., McClish, D.K. 2002. Statistical Methods in Diagnostic Medicine. Wiley-Interscience, New York.

Report Definitions

Sens. Power is the power of the sensitivity test. It is based on the N1 observations.

Spec. Power is the power of the specificity test. It is based on the N-N1 observations.

N is the total sample size of the study. It is equal to N1 + N2.

Se0 is the sensitivity under H0. The sensitivity is the proportion of diseased subjects that yield a positive test result.

Se1 is the sensitivity under H1. The sensitivity is the proportion of diseased subjects that yield a positive test result.

Sp0 is the specificity under H0. The specificity is the proportion of non-diseased subjects that yield a negative test result.

Sp1 is the specificity under H1. The specificity is the proportion of non-diseased subjects that yield a negative test result.

Target Alpha is the alpha (probability of rejecting H0 when H0 is true) that was desired.

Actual Sens. Alpha is the alpha that was actually achieved by the sensitivity test, calculated from the binomial distribution.

Actual Spec. Alpha is the alpha that was actually achieved by the specificity test, calculated from the binomial distribution.

P is proportion of the population that actually has the condition (disease) of interest, called the prevalence.

Summary Statements

A total sample size of 438 (which includes 175 subjects with the disease) achieves 100% power to detect a change in sensitivity from 0.5 to 0.8 using a two-sided binomial test and 90% power to detect a change in specificity from 0.5 to 0.6 using a two-sided binomial test. The target significance level is 0.05. The actual significance level achieved by the sensitivity test is 0.0491 and achieved by the specificity test is 0.0483. The prevalence of the disease is 0.4.

至此,关于诊断准确性试验的样本量计算演示完毕,共需要438例样本。

 

笔者|周支瑞 ,复旦大学附属肿瘤医院放射治疗科在读博士

 

下期预告

样本量计算第四弹预告

生存资料研究的样本量计算----基于PASS软件实现

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doi:10.3978/kysj.2014.1.1462

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