Bayesian modeling of muscle biopsy contracture testing for malignant hyperthermia susceptibility.

Abstract:

BACKGROUND:Phenotyping malignant hyperthermia (MH) by contracture testing has a low but quantifiable degree of inaccuracy, measured by its sensitivity and specificity. Quantifying the limitations inherent in diagnostic testing for MH can help resolve issues in clinical practice, such as the interpretation of a negative test and the apparent lack of complete genetic linkage to RYR1. METHODS:Bayesian models, mathematical descriptions of the outcome of diagnostic testing, were constructed. The inputs to the model include patient factors, summarized in a single number called pretest probability (PTP), and sensitivity and specificity that specify the accuracy of the entire test process. The outputs of the model include positive predictive value (PPV) and negative predictive value (NPV), which are numeric expressions of diagnostic certainty of positive and negative test results. A special case was constructed for equivocal results. RESULTS:The PPV, NPV, and efficiency of contracture testing for MH are functions of PTP, sensitivity, and specificity. The NPV is high for all clinical PTP, whereas PPV is clinically useful for moderate to high PTP. CONCLUSIONS:Diagnostic contracture testing for MH is clinically useful because of high NPV and can exclude MH with near certainty. For MH probands, the clinical grading scale for MH may guide PTP estimation, whereas for relatives of probands, PTP is a function of kinship to a known MH-susceptible relative. A sequential testing strategy optimizes diagnostic information by maximizing PTP within a pedigree. Incomplete testing of parents of an MH susceptible child can pose a significant risk of false-negative results for the untested parent. Even with optimal pedigree testing strategies, the PPV drift effect results in a considerable source of phenotypic uncertainty for genetic linkage studies.

journal_name

Anesthesiology

journal_title

Anesthesiology

authors

Loke JC,MacLennan DH

doi

10.1097/00000542-199803000-00007

subject

Has Abstract

pub_date

1998-03-01 00:00:00

pages

589-600

issue

3

eissn

0003-3022

issn

1528-1175

journal_volume

88

pub_type

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