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Abstract
Background
Many studies evaluating the performance of in vitro diagnostic kits have been criticized for the lack of reliability. To attain reliability those evaluation studies should be preceded by sample size calculation ensuring statistical power. This study was intended to develop a web-based system to estimate the sample size, which was often neglected because it would require expert knowledge in statistics.
Methods
For sample size calculation, we extracted essential parameters from the performance studies on the 3rd generation anti-hepatitis C virus (HCV) kits reported in the literature. We developed a system with PHP web-script language and MySQL. The statistical models used in this system were as follows; one sample without power consideration (model 1), one sample with power consideration (model 2), and two samples with power consideration (model 3).
Results
Among the articles published between 1989 and 2005, 13 articles that evaluated the performance of anti-HCV kits were identified by searching with Medical Subject Headings (MeSH). The diagnostic sensitivity was 83–100% with a median of 145 samples (range; 12–1,091) and the specificity was 97–100% with a median of 1,025 samples (range; 33–4,381). The estimated sample size would be 280 in the model 1, 817 in the model 2, and 1,510 in the model 3, when we set 2% prevalence of HCV infection, 95% sensitivity of a conventional kit, 97% sensitivity of a new kit, 95% significance level (two-sided test), 2% allowable error, and 80% power.
References
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Fig. 1.
The screenshot of the main input menu. The statistical parameters including sensitivity, specificity and allowable error limit were assigned. Significant level, power, and statistical models can be chosen via a select box or a check box, respectively.
Fig. 2.
Output screenshot of the program. (A) Sample size was estimated by giving prevalence of HCV=2%, sensitivity of the reference test=95%, sensitivity of a new test=97%, significant level (two-sided)=95%, allowable error=2%, and power=80%. (B) When the power and significant level were selected, the estimation of sample size for comparison of two in vitro diagnostic devices was tabulated by the statistical models.
Fig. 3.
Estimates from the studies of sensitivity and specificity of anti-HCV antibody tests. Points indicate estimates of sensitivity (A) and specificity (B). Horizontal lines are 95% confidence intervals for the estimates.
Table 1.
Performance evaluation studies of hepatitis C virus serological assays
Table 2.
Comparison of confidence intervals and P value for the assessment of a case-control difference (confidence interval of control; −4, 4)
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