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Published on: January 17, 2018
An LR-based risk stratification framework for assessing interlaboratory variability in HEp-2 IFA pattern
Chaochao Zhang1,2, Yingxin Dai1, Dan Cao3
1Department of Laboratory Medicine, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Objectives:
Interlaboratory variability in HEp-2 indirect immunofluorescence assay (IFA) interpretation remains a major challenge. Conventional agreement metrics quantify disagreement but do not distinguish discrepancies by diagnostic relevance. We aimed to develop a likelihood ratio (LR)-based framework for clinically informed assessment of interpretation variability.
Methods:
Pattern-specific positive LRs were derived from 33,690 routine HEp-2 IFA records and used to classify patterns into four risk tiers. A pattern discrepancy score (PDS) was developed to quantify discrepancies according to risk-tier displacement. Interlaboratory variability was assessed using a standardized 200-specimen panel tested by 18 laboratories, and diagnostic performance was explored in six laboratories.
Results:
Pattern disagreement rates ranged from 17.5 to 50.0 %. PDS strongly correlated with disagreement rate (Spearman's ρ=0.936, p<0.001), but laboratories with similar disagreement rates differed in cross-tier discrepancy distribution. Most discrepancies remained within the same risk tier; among discordant interpretations involving high-risk reference patterns, 20.4 % crossed into another tier. Pattern concordance varied markedly, while titer agreement was moderate to almost perfect (weighted κ, 0.569-0.821). Across six laboratories, diagnostic performance varied (Youden Index, 0.391-0.617), but was not significantly associated with interpretation consistency.
Conclusions:
HEp-2 IFA interpretation variability differs in both frequency and potential diagnostic relevance. The LR-based framework and PDS complement conventional agreement measures by identifying discrepancies that alter diagnostic risk classification, potentially supporting risk-oriented proficiency assessment and targeted quality improvement.