INTRODUCTION: Due to the lack of precise diagnostic criteria, current search strategy for monogenic diabetes is predominantly based on atypical clinical course of diabetes and intuition of the attending physician. Yet another issue is the common view that monogenic diabetes is rare. It discourages from performing deepened diagnostics and makes it difficult to gain experience necessary to select appropriate patients for genetic examination. AIM OF THE STUDY: Estimating the true incidence of patients with a high probability of monogenic background of the disease and compare their search strategies based on clinical practice or structured databases. MATERIAL AND METHODS: The authors compared the current strategy of selecting candidates for screening with a directed search strategy based on immunologic (lack of islet autoantibodies), functional (presence or complete lack of c-peptide at onset and follow-up) and familial (dominant pattern of inheritance) criteria. The number of patients selected for the screening was chosen as efficacy measure selected among 1281 diabetic patients diagnosed and treated between 1983-2009. RESULTS: Screening based on clinical assessment yielded 37 patients (2.9%) chosen for genetic screening. Criteria used by the physicians were based on up-to-date guidelines and unusual clinical course. Active search of the database according to predefined criteria resulted in selecting: 121 patients (9.4%) with likely monogenic background of diabetes (71 - lack of autoantibodies, 8 - normal C-peptide, 6 - lack of both c-peptide and autoantibodies, 36 - diabetes in at least one parent). The difference in screening efficacy was statistically significant (p <0.0001). CONCLUSIONS: Periodic reevaluation of patients' data allows a significant increase in the number of candidates subjected to genetic screening and potentially achieving beneficial therapeutic effects by means of pharmacogenetics.
INTRODUCTION: Due to the lack of precise diagnostic criteria, current search strategy for monogenic diabetes is predominantly based on atypical clinical course of diabetes and intuition of the attending physician. Yet another issue is the common view that monogenic diabetes is rare. It discourages from performing deepened diagnostics and makes it difficult to gain experience necessary to select appropriate patients for genetic examination. AIM OF THE STUDY: Estimating the true incidence of patients with a high probability of monogenic background of the disease and compare their search strategies based on clinical practice or structured databases. MATERIAL AND METHODS: The authors compared the current strategy of selecting candidates for screening with a directed search strategy based on immunologic (lack of islet autoantibodies), functional (presence or complete lack of c-peptide at onset and follow-up) and familial (dominant pattern of inheritance) criteria. The number of patients selected for the screening was chosen as efficacy measure selected among 1281 diabeticpatients diagnosed and treated between 1983-2009. RESULTS: Screening based on clinical assessment yielded 37 patients (2.9%) chosen for genetic screening. Criteria used by the physicians were based on up-to-date guidelines and unusual clinical course. Active search of the database according to predefined criteria resulted in selecting: 121 patients (9.4%) with likely monogenic background of diabetes (71 - lack of autoantibodies, 8 - normal C-peptide, 6 - lack of both c-peptide and autoantibodies, 36 - diabetes in at least one parent). The difference in screening efficacy was statistically significant (p <0.0001). CONCLUSIONS: Periodic reevaluation of patients' data allows a significant increase in the number of candidates subjected to genetic screening and potentially achieving beneficial therapeutic effects by means of pharmacogenetics.
Authors: Andrea Gerard-Gonzalez; Stephen E Gitelman; Peiyao Cheng; Stephanie N Dubose; Kellee M Miller; Beth A Olson; Maria J Redondo; Andrea K Steck; Roy W Beck Journal: J Diabetes Date: 2013-06 Impact factor: 4.006
Authors: B Mianowska; W Fendler; A Szadkowska; A Baranowska; E Grzelak-Agaciak; J Sadon; H Keenan; W Mlynarski Journal: Diabetologia Date: 2010-12-25 Impact factor: 10.122