Comparative Safety of Non-Insulin Agents in Pregnant Women with Pregestational Diabetes

在普通人群中，非胰岛素药物已被广泛接受用于治疗2型糖尿病， 考虑到它们的有效性和耐受性，与皮下注射胰岛素相比。最常见的一种 妊娠期间的医学并发症是妊娠期糖尿病，其处理目前主要集中在 通过饮食、运动和胰岛素治疗(如果需要的话)实现血糖控制。两位美国人的糖尿病 协会和妇产科学院建议计划怀孕的妇女和 妊娠者口服降糖药替代胰岛素治疗，待进一步数据公布 关于安全的问题变得可用。然而，孕妇通常会接触到这些制剂，因为 1)指南没有得到普遍遵守，2)一些妇女拒绝使用胰岛素，3)50%的怀孕妇女 计划外，如果女性已经在使用口服制剂，之前没有时间改用胰岛素 器官发生。此外，在怀孕期间，口服药物对患者有潜在的好处 可接受性和依从性，因此改善了血糖控制和妊娠结局。即使是对那些 仅口服降糖药不足以达到血糖控制的患者，可以使用它们 减少胰岛素用量。由于妊娠期随机对照试验有足够的样本量来确定 这些特工的安全稳健是不现实的，我们需要在及时的信息基础上仔细进行 观察性研究。在此之前，信息的缺乏将继续是使用它们的关键障碍。 怀孕了。我们的主要目标是量化与以下因素相关的母婴不良事件的风险 妊娠期特定的非胰岛素抗糖尿病治疗与单独使用胰岛素和二甲双胍的比较。 我们已经建立了一个与婴儿有关的300万例怀孕的队列，这些婴儿的纵向信息 两个基于人群的医疗保健数据库中的处方和临床情况：医疗补助分析 提取(MAX)和Truven Health MarketScan(Truven)。这项研究将确定超过18,000人(最多)的队列 和15,000名患有孕前2型糖尿病的妇女，她们在2000-2018年间分娩。药物暴露 将根据药房配药记录确定，结果将基于住院和门诊 诊断和程序，使用经过验证的定义。为了控制糖尿病的严重程度和其他混杂因素， 我们将(I)将人群限制为患有2型糖尿病的女性；(Ii)使用积极的参照组；(Iii)使用 倾向评分分层以平衡糖尿病严重程度的各个方面；以及(Iv)使用新的倾向评分 一种校准方法，通过合并来自具有以下任一项的子样本的血糖控制数据来进一步调整 实验室记录或链接的电子病历。将使用具有全国代表性的调查数据 以确保对美国人口的普适性。广义线性模型将估计相对风险及其 95%的可信区间。将进行敏感性分析，以测试调查结果的稳健性。前期工作 由调查人员和试点数据支持了拟议研究的可行性。

In the general population, non-insulin agents have gained wide acceptance for the treatment of type 2 diabetes, given their efficacy and tolerability when compared to subcutaneous insulin injections. One of the most common medical complications in pregnancy is pre-gestational diabetes and its management currently focuses on achieving glucose control with diet, exercise and, if needed, insulin treatment. Both the American Diabetes Association and the College of Obstetrics and Gynecology recommend to women planning pregnancy and for those who are pregnant that oral antidiabetic agents be substituted with insulin therapy until further data regarding safety become available. However, pregnant women are commonly exposed to these agents because 1) guidelines are not universally followed, 2) some women refuse to use insulin, and 3) 50% of pregnancies are unplanned and if a woman is already using an oral agent there is no time to switch to insulin before organogenesis. Furthermore, in pregnancy, oral agents have potential benefits with respect to patient acceptability and adherence, and therefore improved glycemic control and pregnancy outcomes. Even for those patients for whom oral antidiabetic agents alone are inadequate to achieve glycemic control, they can be used to reduce insulin dose. Since randomized controlled trials in pregnancy with sufficient sample size to define the safety of these agents robustly are not realistic, we need timely information based on carefully conducted observational studies. Until then, the lack of information will continue to be a critical barrier to their use in pregnancy. Our primary objective is to quantify the risk of maternal and fetal adverse events associated with specific non-insulin antidiabetic therapies during pregnancy in comparison to insulin alone and metformin alone. We have established a cohort of 3 million pregnancies linked to infants with longitudinal information on prescriptions and clinical conditions within two population-based healthcare databases: the Medicaid Analytic eXtract (MAX) and Truven Health MarketScan (Truven). This study will identify cohorts of over 18,000 (MAX) and 15,000 (Truven) women with pre-gestational type 2 diabetes who delivered in 2000-2018. Drug exposure will be determined based on pharmacy dispensing records, and outcomes will be based on in- and outpatient diagnoses and procedures, using validated definitions. To control for diabetes severity and other confounders, we will (i) restrict the population to women with type 2 diabetes; (ii) use an active reference group; (iii) use propensity score stratification to balance aspects of diabetes severity; and (iv) use a novel propensity score calibration approach to further adjust by incorporating data on glycemic control from subsamples with either laboratory records or linked electronic medical records. Data from nationally-representative surveys will be used to ensure generalizability to the US population. Generalized linear models will estimate relative risks and their 95% confidence intervals. Sensitivity analyses will be conducted to test the robustness of the findings. Prior work by the investigators and pilot data support the feasibility of the proposed study.