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1000
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Abstract/Summary
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BACKGROUND: The lymphocyte transformation test (LTT) is an in vitro test system for the detection of a sensitization in the context of allergies to drugs. Its reported sensitivity varies largely and seems to be affected by different parameters. In review articles, the average LTT performance was often calculated by combining overall mean sensitivities of various published studies, but without considering different patient characteristics or varying patient numbers per publication.
OBJECTIVE: To investigate the impact of different patient-specific and methodological parameters on the sensitivity of the LTT based on data on the level of the individual patient extracted from single studies.
METHODS: We performed an advanced literature search in PubMed and screened the identified publications according to previously defined inclusion criteria. In total, individual patient data from 721 patients were extracted from 30 studies. Random-effects meta-regression analyses were performed.
RESULTS: The analysis indicate that the enzyme-linked immunosorbent assay–based read-out is more sensitive compared with the classical radioactivity method (enzyme-linked immunosorbent assay: 80% vs radioactivity: 66%; P = .08). Interestingly, drug reaction with eosinophilia and systemic symptoms/drug-induced hypersensitivity syndrome is associated with a higher probability of a positive LTT test result compared with other investigated clinical phenotypes (“drug reaction with eosinophilia and systemic symptoms/drug-induced hypersensitivity syndrome” vs “bullous reaction”; odds ratio, 2.52; P value = .003). Our analysis also revealed an impact of the time to testing period after the occurrence of the allergic event (“< 2 weeks” vs “2 weeks-2 months”; odds ratio, 2.12; P value = .03).
CONCLUSION: The read-out method and relevant clinical parameters affect the sensitivity of the LTT. These findings are based on a meta-analysis providing a higher level of evidence than a single study or previous reviews not considering individual patient data.
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