Assay validation for left-censored data

• Published in: Statistics in medicine Vol. 24; no. 21; pp. 3347 - 3360
• Main Authors: Barnhart, Huiman X., Song, Jingli, Lyles, Robert H.
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Ltd 15.11.2005; Wiley Subscription Services, Inc
• Subjects: agreement; assay validation; Computer Simulation; generalized estimating equations; HIV; HIV - growth & development; HIV Infections - diagnosis; Human immunodeficiency virus; Humans; left censoring; Likelihood Functions; limit of detection; Reproducibility of Results; Reverse Transcriptase Polymerase Chain Reaction; Ribonucleic acid; RNA; RNA, Viral - blood; Sensitivity and Specificity; Validation studies
• ISSN: 0277-6715; 1097-0258
• DOI: 10.1002/sim.2225

In laboratory validation studies, it is often important to assess agreement between two assays, based on different techniques. Oftentimes, both assays have lower limits of detection and thus measurements are left censored. For example, in studies of Human Immunodeficiency Virus (HIV), the branched DNA (bDNA) assay was developed to quantify HIV‐1 RNA concentrations in plasma. Validation of newer assays, such as the RT‐PCR (reverse transcriptase polymerase chain reaction) involves assessing agreement of measurements obtained using the two techniques. Both bDNA and RT‐PCR assays have lower limits of detection and thus new statistical methods are needed for assessing agreement between two left‐censored variables. In this paper, we present maximum likelihood and generalized estimating equations approaches to evaluate agreement between two assays that are subject to lower limits of detection. The concordance correlation coefficient is used as an agreement index. The methodology is illustrated using HIV RNA assay data collected as part of a long‐term HIV cohort study. Copyright © 2005 John Wiley & Sons, Ltd.