Type 2 diabetes in adults with sickle cell disease: can we dive deeper? Response to Skinner et al.
Type 2 diabetes in adults with sickle cell disease: can we dive deeper? Response to Skinner et al.
复制标题
镰状细胞病成人 2 型糖尿病：我们可以更深入地研究吗？
DOI：
10.1111/bjh.15949
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发表时间：
2019
影响因子：
6.5
通讯作者：
Calip,GregoryS
中科院分区：
文献类型：
--
作者：
Zhou,Jifang;Han,Jin;Nutescu,EdithA;Galanter,WilliamL;Walton,SurreyM;Gordeuk,VictorR;Saraf,SantoshL;Calip,GregoryS
我们饶有兴趣地阅读了Skinner、Nader和Connes的来信，以及他们对我们最近发表的关于镰状细胞病（SCD）患者2型糖尿病（T2D）负担的研究的评论（Skinner，et al 2019，Zhou，et al 2019）。作者提醒注意不同SCD基因型患者的T2D风险差异。尽管SCD是由单基因疾病引起的，但SCD患者表现出复杂的并发症谱和表型异质性，这可以部分地由胎儿血红蛋白水平的变异性和α地中海贫血的共同遗传来解释。不同遗传基础的SCD患者可能具有不同的病理生理学特征，包括血脂谱和人体测量学特征，这些特征反过来可能影响T2D的诊断。为了回答Skinner博士及其同事提出的问题，我们必须承认行政卫生数据库在进行疾病负担研究方面的固有局限性。在此，我们描述了进一步探索这些当前可用数据的挑战以及此类流行病学研究必要的方法学考虑，特别是可能的信息和选择偏差。
We read with interest the letter from Skinner, Nader and Connes and their comments on our recently published study on the burden of type 2 diabetes (T2D) in patients with sickle cell disease (SCD)(Skinner, et al 2019, Zhou, et al 2019). The authors call attention to variation in T2D risk across patients with different SCD genotypes. Despite the fact that SCD is caused by single gene disorders, patients with SCD demonstrate a complex spectrum of complications and phenotypic heterogeneity that can be partially explained by the variability of fetal hemoglobin levels and co-inheritance of alpha thalassemia. It is plausible to speculate that SCD patients of different genetic foundation could present distinct pathophysiology features including lipid profile and anthropometrics, which in turn could influence the likelihood of being diagnosed with T2D.To answer the questions raised by Dr. Skinner and colleagues, we must acknowledge the inherent limitations of administrative health databases in performing studies of disease burden. Herein we describe the challenges of further exploration of these currently available data and the necessary methodological considerations for such epidemiological studies, particularly possible information and selection biases.