Dataset Information

Application of futility analysis to refine jitter recordings in myasthenia gravis.

ABSTRACT: The current practice of single-fiber electromyography (SFEMG) requires that 20 fiber pairs with normal jitter be collected to exclude myasthenia gravis (MG). We applied principles of futility analysis from clinical trials in an attempt to reduce that requirement.We utilized conditional power futility analysis to assess the probability of an abnormal 20-pair SFEMG based on ongoing analysis of jitter as each pair is collected. Rules for early test termination in the presence of 0, 1, or 2 abnormal pairs were identified. These rules were then applied to previously collected SFEMG data.SFEMG could be stopped at just 12 pairs if all are normal and at 17 pairs if 1 is abnormal. The rules successfully determined when SFEMG could be stopped in 104 of 106 (98%) studies originally reported to be normal.If the first 12 SFEMG pairs have normal jitter, the study can be terminated and interpreted as normal.

SUBMITTER: Narayanaswami P

PROVIDER: S-EPMC3313075 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature

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Application of futility analysis to refine jitter recordings in myasthenia gravis.

Narayanaswami Pushpa P Pantoja-Galicia Norberto N Betensky Rebecca A RA Rutkove Seward B SB

Muscle & nerve 20120401 4

<h4>Introduction</h4>The current practice of single-fiber electromyography (SFEMG) requires that 20 fiber pairs with normal jitter be collected to exclude myasthenia gravis (MG). We applied principles of futility analysis from clinical trials in an attempt to reduce that requirement.<h4>Methods</h4>We utilized conditional power futility analysis to assess the probability of an abnormal 20-pair SFEMG based on ongoing analysis of jitter as each pair is collected. Rules for early test termination i ...[more]

PMID: 22431080

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Project description:Myasthenia gravis (MG) is an autoimmune disease affecting the neuromuscular junction, whose clinical hallmark is muscle weakness and early fatigability. Azathioprine (AZA) is commonly used in Myasthenia Gravis therapy. AZA is a purine antagonist, which inhibits the cell cycle in the resting and DNA synthesis phases. It is usually used as an immunosuppressant to block T- and B-cell proliferation. AZA, bioconverted to 6-mercaptopurine by glutathione S-transferase (GST), can be metabolized either through the hypoxanthine phosphoribosyl transferase pathway to active 6-thioguanine nucleotides (6-TGN) or through the thiopurine S-methyltransferase (TPMT) pathway to inactive methyl-thiopurine metabolites. The incorporation of active 6-TGNs into DNA, causing breaks in DNA strands resulting in interference with RNA production and thereby protein synthesis, is responsible for the drug effect. The response to AZA is determined by which metabolic pathway is being favored. While balanced use of both HPRT and TPMT pathways results in responsiveness to AZA, hyperactivity of TPMT skews the balance towards the TPMT pathway and results in unresponsiveness to AZA with no pharmacological effect. In contrast, low TPMT activity skews the balance towards the HPRT pathway, resulting in increasing side-effects due to the accumulation of 6-TGNs. Current treatments for MG therapy are often inadequate because less than 40% of patients achieve complete remission with available drugs. This reflects the lack of drugs acting on target sites for which there is strong evidence of pathogenicity and the inability to identify responder patients. No criteria for responsiveness are available, exposing patients to unpredictable failures and unpredictable side effects. These individuals are at particular risk for adverse drug reaction (ADRs) or therapeutic failure. Genetic profiling with the Affymetrix drug metabolizing enzymes and transports genotyping array offers the ability to determine 1,931 variants and 225 genes involved in drug metabolism and disposition. Accordingly, the study of well-known drug-metabolizing genes can be involved in the specific metabolic pathway of a drug, which is more likely to define genotype-phenotype association and thereby genotype profiles relevant to drug response that can be applied as predictive biomarkers for pharmacological treatment.

Dataset Information

Application of futility analysis to refine jitter recordings in myasthenia gravis.

Publications

Application of futility analysis to refine jitter recordings in myasthenia gravis.

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