Development of a Web-based Program to Calculate Sample Size for Evaluating the Performance of In Vitro Diagnostic Kits.
10.3343/kjlm.2006.26.4.299
- Author:
Sang Hyun HWANG
1
;
Heung Bum OH
;
Jeong Min CHAE
;
Min Kwan SEO
;
Soon Young JUNG
;
Sung Eun CHOI
;
Kwan Jeh LEE
Author Information
1. Department of Laboratory Medicine, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Korea.
- Publication Type:Evaluation Studies ; In Vitro ; Original Article
- Keywords:
Sample size calculation;
Performance Evaluation;
Sensitivity;
Specificity In vitro diagnostics;
HCV
- MeSH:
Medical Subject Headings;
Models, Statistical;
Prevalence;
Sample Size*;
Sensitivity and Specificity
- From:The Korean Journal of Laboratory Medicine
2006;26(4):299-306
- CountryRepublic of Korea
- Language:Korean
-
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. CONCLUSIONS: Our study indicates that an insufficient sample size is still a problem in performance evaluation. Our system should be helpful in increasing the reliability of performance evaluation by providing an appropriate sample size.
