Incremental cost-effectiveness of algorithm-driven genetic testing versus no testing for Maturity Onset Diabetes of the Young (MODY) in Singapore
Incremental cost-effectiveness of algorithm-driven genetic testing versus no testing for Maturity Onset Diabetes of the Young (MODY) in Singapore
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DOI：
10.1136/jmedgenet-2017-104670
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发表时间：
2017-11-01
影响因子：
4
通讯作者：
Gardner, Daphne Su-Lyn
中科院分区：
文献类型：
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作者：
Hai Van Nguyen;Finkelstein, Eric Andrew;Gardner, Daphne Su-Lyn
背景：对所有2型糖尿病的年轻患者提供成熟型糖尿病（MODY）的基因检测已被证明不具有成本效益。本研究测试了一种新的算法驱动的MODY基因检测策略是否相对于不检测的设置具有递增的成本效益。方法构建决策树，从支付方角度评估算法驱动的MODY检测策略和30年无基因检测策略的成本和效果。该算法使用谷氨酸脱羧酶（GAD）抗体检测（阴性抗体）、糖尿病发病年龄（< 45岁）和体重指数（< 25 kg/m(2)，如果诊断为bbb30岁）将糖尿病患者人群分为三个亚组，并仅在最有可能发生突变的亚组中检测MODY。从本地研究中获得的新加坡特定成本和MODY患病率以及从文献中获得的效用值用于填充模型。结果：与不检测策略相比，算法驱动的MODY检测策略每个质量调整生命年的增量成本效益比为93 663美元。如果基因检测的价格从1050美元降至530美元（下降50%），它将具有成本效益。基于已建立的基准，我们提出的算法驱动的MODY测试策略尚未具有成本效益。然而，随着基因检测价格的持续下降，这种策略很可能在不久的将来变得具有成本效益。
Background Offering genetic testing for Maturity Onset Diabetes of the Young (MODY) to all young patients with type 2 diabetes has been shown to be not cost-effective. This study tests whether a novel algorithm-driven genetic testing strategy for MODY is incrementally cost-effective relative to the setting of no testing.Methods A decision tree was constructed to estimate the costs and effectiveness of the algorithm-driven MODY testing strategy and a strategy of no genetic testing over a 30-year time horizon from a payer's perspective. The algorithm uses glutamic acid decarboxylase (GAD) antibody testing (negative antibodies), age of onset of diabetes (< 45 years) and body mass index (< 25 kg/m(2) if diagnosed > 30 years) to stratify the population of patients with diabetes into three subgroups, and testing for MODY only among the subgroup most likely to have the mutation. Singaporespecific costs and prevalence of MODY obtained from local studies and utility values sourced from the literature are used to populate the model.Results The algorithm-driven MODY testing strategy has an incremental cost-effectiveness ratio of US$ 93 663 per quality-adjusted life year relative to the no testing strategy. If the price of genetic testing falls from US$ 1050 to US$ 530 (a 50% decrease), it will become cost-effective.Conclusion Our proposed algorithm-driven testing strategy for MODY is not yet cost-effective based on established benchmarks. However, as genetic testing prices continue to fall, this strategy is likely to become costeffective in the near future.