Department of Molecular Medicine and Medical Biotechnologies, University of Naples "Federico II", Naples, Italy.
PLoS One. 2013 Nov 11;8(11):e79933. doi: 10.1371/journal.pone.0079933. eCollection 2013.
MODY2 is the most prevalent monogenic form of diabetes in Italy with an estimated prevalence of about 0.5-1.5%. MODY2 is potentially indistinguishable from other forms of diabetes, however, its identification impacts on patients' quality of life and healthcare resources. Unfortunately, DNA direct sequencing as diagnostic test is not readily accessible and expensive. In addition current guidelines, aiming to establish when the test should be performed, proved a poor detection rate. Aim of this study is to propose a reliable and easy-to-use tool to identify candidate patients for MODY2 genetic testing. We designed and validated a diagnostic flowchart in the attempt to improve the detection rate and to increase the number of properly requested tests. The flowchart, called 7-iF, consists of 7 binary "yes or no" questions and its unequivocal output is an indication for whether testing or not. We tested the 7-iF to estimate its clinical utility in comparison to the clinical suspicion alone. The 7-iF, in a prospective 2-year study (921 diabetic children) showed a precision of about the 76%. Using retrospective data, the 7-iF showed a precision in identifying MODY2 patients of about 80% compared to the 40% of the clinical suspicion. On the other hand, despite a relatively high number of missing MODY2 patients, the 7-iF would not suggest the test for 90% of the non-MODY2 patients, demonstrating that a wide application of this method might 1) help less experienced clinicians in suspecting MODY2 patients and 2) reducing the number of unnecessary tests. With the 7-iF, a clinician can feel confident of identifying a potential case of MODY2 and suggest the molecular test without fear of wasting time and money. A Qaly-type analysis estimated an increase in the patients' quality of life and savings for the health care system of about 9 million euros per year.
MODY2 是意大利最常见的单基因糖尿病形式，估计患病率约为 0.5-1.5%。MODY2 与其他形式的糖尿病可能无法区分，但其鉴定会影响患者的生活质量和医疗资源。不幸的是，DNA 直接测序作为诊断测试并不可用且昂贵。此外，目前的指南旨在确定何时应进行测试，但检测率却很低。本研究旨在提出一种可靠且易于使用的工具，以确定 MODY2 基因检测的候选患者。我们设计并验证了一个诊断流程图，试图提高检测率并增加适当要求的测试数量。该流程图称为 7-iF，由 7 个二进制“是或否”问题组成，其明确输出是进行测试或不进行测试的指示。我们测试了 7-iF，以估计其与单独临床怀疑相比的临床实用性。在一项为期 2 年的前瞻性研究（921 名糖尿病儿童）中，7-iF 的准确率约为 76%。使用回顾性数据，7-iF 显示在识别 MODY2 患者方面的准确率约为 80%，而临床怀疑的准确率为 40%。另一方面，尽管漏诊了相当数量的 MODY2 患者，但 7-iF 不会建议对 90%的非 MODY2 患者进行测试，这表明该方法的广泛应用可能 1）帮助经验较少的临床医生怀疑 MODY2 患者，2）减少不必要的测试数量。通过 7-iF，临床医生可以有信心识别潜在的 MODY2 病例，并建议进行分子测试，而不必担心浪费时间和金钱。质量调整生命年 (QALY) 分析估计每年可提高患者的生活质量并为医疗保健系统节省约 900 万欧元。
