Would Guidelines for Maturity Onset Diabetes in Youth (MODY) Be Useful in Clinical Practice?




Wilson, Don
Crenshaw, Aubrey
Hamilton, Luke
Hamby, Tyler


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Purpose: Maturity Onset Diabetes in Youth (MODY) is a rare form of diabetes mellitus (DM) caused by a single gene mutation inherited in an autosomal dominant fashion. There are approximately 13 different gene mutations that can cause the MODY phenotype. MODY is typically diagnosed in Caucasian adolescents; the incidence is similar in males and females. Approximately 80-95% of MODY cases are misdiagnosed as T1D or T2D. Currently no algorithm is available to facilitate clinic decision making to assure proper diagnosis and treatment of affected youth. Methods: An online survey was conducted to better understand common approaches in the diagnosis of DM in youth and the need for a clinical algorithm to help guide testing for MODY. The survey was sent via email to PESTOLA providers (Pediatric Endocrinologists of Texas, Oklahoma, Louisiana, and Arkansas). Results: The survey was sent out to 188 providers; 32 responded (17% response rate). In establishing a diagnosis of MODY, a majority of providers agreed or strongly agreed that they needed more education (53%) and that they needed and algorithm (64%). Responses to the survey allowed us to construct a cost-effective diagnostic algorithm to assist in clinical decision-making in youth with diabetes. Conclusion: Confirming a diagnosis of MODY requires proper knowledge of the key features of the disease and its genetic mode of inheritance, a reliable family history, and predilection of race and phenotype. Because treatment options, outcomes, and genetic counseling differ in MODY compared to T1D and T2D, whenever appropriate clinicians should consider performing genetic testing. Using a diagnostic algorithm for children presenting with dysglycemia will provide physicians a cost-effective way to decide which patients may benefit from genetic testing and, hopefully, reduce the frequent misdiagnosis of MODY. Further studies are needed to determine the utility of the proposed model.