Reflex Algorithm For Improving Accuracy Of Myasthenia Gravis Autoantibody Testing

NEUROLOGY(2020)

引用 14|浏览34
暂无评分
摘要
ObjectiveTo improve myasthenia gravis (MG) autoantibody testing.MethodsMG serologic tests with confirmatory or refuting clinical-electrodiagnostic (EDX) testing and cancer evaluations were reviewed over 4 years (2012-2015). All patients had acetylcholine receptor-binding (AChR-Bi), modulating (AChR-Mo), and striational (STR) autoantibody testing, and negatives reflexed to muscle-specific kinase (MuSK). Thymoma and cancer occurrences were correlated with STR and reflexed glutamic acid decarboxylase 65 (GAD65), ganglionic acetylcholine receptor (alpha 3), collapsin response mediating protein-5, and voltage-gated potassium channel complex autoantibodies.ResultsOf 433 samples tested, 133 (31%) met clinical-EDX criteria for MG. Best sensitivity (90%) occurred at AChR-Bi >0.02 nmol/L, leaving 14 negative (6 ocular MG, 7 generalized MG, 1 MuSK MG) with specificity 90% (31 false-positives). Using AChR-Mo antibodies (>20% loss), specificity was better (92%, 24 false-positives), but sensitivity dropped (85%). Specificity improved (95%) by testing AChR-Mo when AChR-Bi are positive, resulting in 45% reduction of false-positives (31-17), maintaining AChR-Bi 90% sensitivity. Cutoff values recommended by area under the curve analysis did not outperform this approach. AChR-Bi and AChR-Mo values were significantly higher in true-positives. CT evaluations in 121 MG samples revealed 16 thymomas. Historical or subsequent cancers occurred in 22. STR and reflexed autoantibodies were not more common in MG with thymoma or other cancers. Full-body CT (n = 34) was performed in those with STR and reflex autoantibody positivity, but without additional cancers found.ConclusionAccuracy of MG serologic testing is improved by reflexing AChR-Bi-positive cases to AChRMo. STR and other reflexed cancer evaluation autoantibodies did not provide value beyond standard CT chest imaging at the time of MG diagnosis. Diagnostic certainty is informed by AChR-Bi and AChR-Mo with higher values increasing specificity.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要