Renin-angiotensin system blockers (RAS), including angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs), are common first-line medications in the management of chronic hypertension (CHT),1 used in 0.1–0.5% of pregnancies,2–4 increasing in recent years.2 Given the rising prevalence of CHT in women of childbearing age, as well as delay in chilbearing to ages when CH is more common,5 and the fact that up to half of all pregnancies are unplanned, the use of RAS blockers in pregnancy is likely to increase. These medications, associated with severe neonatal harm including fetal hypotension, anuria, oligo-hydramnios, renal tubule dysplasia and hypocalvaria,6 are clearly contraindicated in the second and third trimesters.7 The risks associated with their use in the first trimester, the subject of this commentary, are less well defined. Early studies report an association of ACEI use with congenital malformations. Published in 2006, a study based on Tennessee Medicaid enrollees (29 507) reported a substantial, increased risk of major congenital malformations: 3.7-fold [95% confidence interval (CI): 1.8-7.3] for congenital heart defects and 4.3-fold (95% CI: 1.3-14.1) for central nervous system (CNS) malformations. The comparison group comprised 29 096 non-hypertensive women.8 More recently, the risk of congenital heart defects was found to be increased (odds ratio, 1.5; 95% CI: 1.1–2.6) among 381 women exposed to ACEIs compared with 400 402 non-hypertensive women. However, when compared with unexposed women with CHT (n = 29 735), no such association was observed (odds ratio, 1.1; 95% CI: 0.6–1.9).9 Similarly, taking into account underlying CHT and a wide range of other confounders (in a study involving more than 2500 women with CHT), exposure to ACEIs was not associated with an increased risk of any major congenital malformations (relative risk, 0.8; 95% CI: 0.7–1.1).10 Robust evidence on the possible teratogenicity of first trimester use of ARBs is, on the other hand, still lacking. Given that ACEIs and ARBs work through the same mechanism of RAS inhibition, and the benefits and harms of medications during pregnancy are directly related to their mechanism of action,11 ACEIs and ARBs are likely to have the same benefits and risks. Little is known about other outcomes associated with RAS blockers. Given that these medications interfere with the overall renin-angiotensin system of the developing fetus, mainly within the first 90 days of gestation,12 RAS inhibition could lead to renal hypoperfusion and ischaemia.13 It is, therefore, biologically plausible that they could cause fetal growth restriction and poor perinatal outcomes, such as preterm birth, small size (for gestational age) or low Apgar scores. Poor prenatal health might also manifest in adverse maternal outcomes like caesarean section. Fetal RAS blockade can also have long-term complications, including neurodevelopmental delay and failure to thrive.14 By contrast, some animal-based data15 and anecdotal human data16 suggest that the use of RAS blockers might reduce maternal blood pressure and the risk of pre-eclampsia. Reducing proteinuria is a distinct characteristic of RAS blockers; other antihypertensives, for which the safety during pregnancy is already established, do not have this capacity.3 Given that women with CHT are at increased risk of pre-eclampsia,17 early pregnancy use of these medications might improve maternal and perinatal outcomes. This possibility, however, remains to be proven. Data regarding the effects of RAS blockers on a comprehensive range of maternal and perinatal outcomes, as well as long-term consequences, are required for a fair assessment of the risks and benefits. Such outcomes have been examined to only a limited extent. To the best of our knowledge, no studies have been conducted on ARBs. One population-based study, of 83 pregnant women, reported associations between exposure to ACEIs and preterm birth (odds ratio, 3.2; 95% CI 1.6–6.4),18 but did not account for potential confounding by underlying CHT. As non-hypertensive women were used as controls, the observed increased risk of preterm birth is likely to have been inflated by the underlying CHT of the women treated with ACEIs. Maternal CHT, with or without treatment, is an independent risk factor for adverse perinatal outcomes.9,10,17,19 Due to practical and ethical concerns, randomized controlled trials are not feasible. Although spontaneous reporting can provide guidance on the types of outcomes to be measured in pharmaco-vigilance studies, they do not, because of under-reporting and the absence of information on the number of exposed pregnancies, reveal reliable rates of adverse outcomes. Prospective cohort studies, including pregnancy registries, can be undertaken when regulatory agencies, pharmaceutical companies and/or researchers assemble cohorts of women exposed to potentially teratogenic medications, and then study outcomes in the offspring. These efforts are crucially important for the detection of major teratogens among new medications, but data collection is resource-intensive, resulting in small samples. Studies based on data from prospectively assembled cohorts are also subject to biases resulting from the voluntary nature of participation, sometimes selective recruitment, and loss to follow-up.20 In order to circumvent many of the potential biases, as well as costs, when facing prospectively collected data, pharmaco-epidemiological studies have used individual-level computerized health and pharmacy records of large, in some cases national, populations. However, because few pregnant women receive RAS blockers (<1% of pregnancies), many of these data collections lack sufficient RAS blocker- treated mothers to adequately and precisely measure the relationship between RAS blockers and perinatal outcomes. Rare exceptions include data collections covering large populations and long time periods, such as the Medicaid claims data from almost all states in the USA, used to measure the relationship between RAS blockers and congenital malformations.11 Accordingly, multijurisdictional collaboration, in which data are pooled across several large administrative databases with the ability to link CHT mothers and infants, is needed. Promising efforts in this direction, examining medications other than RAS blockers, include Sentinel,21 CNODES (the Canadian Network for Observational Drug Effect Studies)22 and InPreSS (International Pregnancy Safety Study Consortium).23 Despite the advantages of large-scale administrative data, it is crucial to note the inherent limitations of observational study designs. Controlling for confounding by indication, in this case CHT, is of major importance when studying the outcomes of using RAS blockers. Large-scale administrative data might contain diagnostic codes, used to account for the underlying indication for the treatment, but seldom indicate severity. Similarly, health care databases might lack refined information on other confounders of any association between RAS blockers and, for example, pre-pregnancy body mass index (BMI), weight gain during pregnancy and undiagnosed diabetes. We therefore recommend that studies examining the outcomes of RAS blockers adopt techniques which deal with, or determine the effect of, unmeasured confounding. Techniques beginning to be adopted in studies of medication safety during-pregnancy include propensity score calibration and probabilistic bias analysis. Propensity score calibration requires an external validation dataset, one which contains the same information as the main study (although information on the outcome is not required), as well as data on potential confounders unobserved in the main study. These validation data are used to determine the error in the main study propensity scores. Once the error in these propensity scores is estimated, regression calibration is used to adjust the main study propensity scores for that error.24 As an example, this technique was applied in a study of the perinatal outcomes of different opioid agonist therapies. The main dataset lacked information on the severity of addiction, which was assumed to be associated with both the type of opioid agonist therapy received and perinatal outcomes. Interviews were administered to an external cohort to obtain information on the severity of addiction, and propensity scores incorporating this information were estimated. Risk estimates based on the main study data were then adjusted for these propensity scores, to produce risk estimates adjusted for confounders observed in the main data as well as external confounder information.25 In the context of establishing RAS blocker safety during pregnancy, where the key unmeasured confounders include lifestyle factors and related morbidities, data relating to biomarkers and physical measurements, already collected in some prospective cohort studies (e.g. MoBa,26 Baby Biobank27), could serve as a valuable source of external data to be used in propensity score calibration. Alternatively, unmeasured confounders can be simulated and probabilistic bias analysis used to assess the sensitivity of the findings to the effects of an unmeasured confounder.28 For example, when examining the relationship between epidural labour analgesia and risk of caesarean delivery, a variable representing labour pain intensity was simulated. Probabilistic bias analysis indicated that the observed association between epidural analgesia and caesarean delivery risk was not sensitive to labour pain intensity unless extremely strong confounding was present.29 In conclusion, robust and recent evidence suggests that there might not be an association between early pregnancy exposure to ACEIs and congenital malformations, including heart and neurovascular defects, as had been suggested by earlier studies. This needs confirmation. Furthermore, whether or not the lack of relationship extends to other perinatal outcomes and ARBs also needs to be determined. The potential benefits of early pregnancy RAS blockers also need to be addressed. To reduce the current challenges that women and clinicians face in weighing the risks and benefits of RAS blocker treatment in early pregnancy, future work needs to be directed towards broader perinatal and maternal outcomes, involving multijurisdictional collaboration and using pooled high-quality, large-scale data and carefully selected observational methods. Conflict of interest: None declared. References 1 James PA, Oparil S, Carter BL, Cushman WC, Dennison-Himmelfarb C, Handler J. 2014 evidence-based guideline for the management of high blood pressure in adults: report from the panel members appointed to the Eighth Joint National Committee (JNC 8). JAMA 2014; 311: 507– 20. Google Scholar CrossRef Search ADS PubMed 2 Bowen ME, Ray WA, Arbogast PG, Ding H, Cooper WO. Increasing exposure to angiotensin-converting enzyme inhibitors in pregnancy. Am J Obstet Gynecol 2008; 198: 291.e1–5. Google Scholar CrossRef Search ADS PubMed 3 Bateman BT, Hernandez-Diaz S, Huybrechts KF et al. Patterns of outpatient antihypertensive medication use during pregnancy in a Medicaid population. Hypertension 2012; 60: 913– 20. Google Scholar CrossRef Search ADS PubMed 4 Cleary BJ, Butt H, Strawbridge JD, Gallagher PJ, Fahey T, Murphy DJ. Medication use in early pregnancy‐prevalence and determinants of use in a prospective cohort of women. Pharmacoepidemiol Drug Saf 2010; 19: 408– 17. Google Scholar PubMed 5 Bateman BT, Shaw KM, Kuklina EV, Callaghan WM, Seely EW, Hernández-Díaz S. Hypertension in women of reproductive age in the United States: NHANES 1999-2008. PLoS One 2012; 7: e36171. Google Scholar CrossRef Search ADS PubMed 6 Hanssens M, Keirse MJ, Vankelecom F, Van Assche FA. Fetal and neonatal effects of treatment with angiotensin-converting enzyme inhibitors in pregnancy. Obstet Gynecol 1991; 78: 128– 35. Google Scholar PubMed 7 Seely EW, Ecker J. Chronic hypertension in pregnancy. Circulation 2014; 129: 1254– 61. Google Scholar CrossRef Search ADS PubMed 8 Cooper WO, Hernandez-Diaz S, Arbogast PG et al. Major congenital malformations after first-trimester exposure to ACE inhibitors. N Engl J Med 2006; 354: 2443– 51. Google Scholar CrossRef Search ADS PubMed 9 Li DK, Yang C, Andrade S, Tavares V, Ferber JR. Maternal exposure to angiotensin converting enzyme inhibitors in the first trimester and risk of malformations in offspring: a retrospective cohort study. BMJ 2011; 343: d5931. Google Scholar CrossRef Search ADS PubMed 10 Bateman BT, Patorno E, Desai RJ et al. Angiotensin-converting enzyme inhibitors and the risk of congenital malformations. Obstet Gynecol 2017; 129: 174– 84. Google Scholar CrossRef Search ADS PubMed 11 Cragan JD, Friedman J, Holmes LB, Uhl K, Green NS, Riley L. Ensuring the safe and effective use of medications during pregnancy: planning and prevention through preconception care. Matern Child Health J 2006; 10: 129– 35. Google Scholar CrossRef Search ADS 12 Darby M, Martin JNJr, LaMarca B. A complicated role for the renin-angiotensin system during pregnancy: highlighting the importance of drug discovery. Expert Opin Drug Saf 2013; 12: 857– 64. Google Scholar CrossRef Search ADS PubMed 13 Andreoli SP. Acute renal failure in the newborn. Semin Perinatol 2004; 28: 112– 23. Google Scholar CrossRef Search ADS PubMed 14 Bullo M, Tschumi S, Bucher BS, Bianchetti MG, Simonetti GD. Pregnancy outcome following exposure to angiotensin-converting enzyme inhibitors or angiotensin receptor antagonists: a systematic review. Hypertension 2012; 60: 444– 50. Google Scholar CrossRef Search ADS PubMed 15 Colafella KMM, Danser AJ. Recent advances in angiotensin research. Hypertension 2017; 69: 994– 99. Google Scholar CrossRef Search ADS PubMed 16 Chung NA, Lip GY, Beevers M, Beevers DG. Angiotensin-II-receptor inhibitors in pregnancy. Lancet 2001; 357: 1620– 21. Google Scholar CrossRef Search ADS PubMed 17 Orbach H, Matok I, Gorodischer R et al. Hypertension and antihypertensive drugs in pregnancy and perinatal outcomes. Am J Obstet Gynecol 2013; 208: 301.e1– 6. Google Scholar CrossRef Search ADS 18 Lyn Colvin BNW, Andrew WG., Linda Slack-Smith. The use of angiotensin converting enzyme inhibitors during the first trimester of pregnancy. J Pharmacovigil 2014; 2: 129. 19 Ramakrishnan A, Lee LJ, Mitchell LE, Agopian A. Maternal hypertension during pregnancy and the risk of congenital heart defects in offspring: a systematic review and meta-analysis. Pediatr Cardiol 2015; 36: 1442– 51. Google Scholar CrossRef Search ADS PubMed 20 Sinclair S, Cunnington M, Messenheimer J et al. Advantages and problems with pregnancy registries: observations and surprises throughout the life of the International Lamotrigine Pregnancy Registry. Pharmacoepidemiol Drug Saf 2014; 23: 779– 86. Google Scholar PubMed 21 Behrman RE, Benner JS, Brown JS, McClellan M, Woodcock J, Platt R. Developing the Sentinel System—a national resource for evidence development. N Engl J Med 2011; 364: 498– 99. Google Scholar CrossRef Search ADS PubMed 22 Suissa S, Henry D, Caetano P et al. CNODES: the Canadian network for observational drug effect studies. Open Med 2012; 6: e134. Google Scholar PubMed 23 Huybrechts KF, Bröms G, Christensen L et al. Association between methylphenidate and amphetamine use in pregnancy and risk of congenital malformations: a cohort study from the international pregnancy safety study consortium. JAMA Psychiatry 2018; 75: 167– 75. Google Scholar CrossRef Search ADS PubMed 24 Stürmer T, Schneeweiss S, Avorn J, Glynn RJ. Adjusting effect estimates for unmeasured confounding with validation data using propensity score calibration. Am J Epidemiol 2005; 162: 279– 89. Google Scholar CrossRef Search ADS PubMed 25 Brogly SB, Hernández-Diaz S, Regan E, Fadli E, Hahn KA, Werler MM. Neonatal outcomes in a medicaid population with opioid dependence. Am J Epidemiol 2017, Nov 16. doi: 10.1093/aje/kwx341. 26 Magnus P, Irgens LM, Haug K, Nystad W, Skjaerven R, Stoltenberg C. Cohort Profile: The Norwegian mother and child cohort study (MoBa). Int J Epidemiol 2006; 35: 1146– 50. Google Scholar CrossRef Search ADS PubMed 27 Leon LJ, Solanky N, Stalman SE et al. A new biological and clinical resource for research into pregnancy complications: the Baby Bio Bank. Placenta 2016; 46: 31– 37. Google Scholar CrossRef Search ADS PubMed 28 Hunnicutt JN, Ulbricht CM, Chrysanthopoulou SA, Lapane KL. Probabilistic bias analysis in pharmacoepidemiology and comparative effectiveness research: a systematic review. Pharmacoepidemiol Drug Saf 2016; 25: 1343– 53. Google Scholar CrossRef Search ADS PubMed 29 Bannister-Tyrrell M, Ford JB, Morris JM, Roberts CL. Epidural analgesia in labour and risk of caesarean delivery. Paediatr Perinat Epidemiol 2014; 28: 400– 11. Google Scholar CrossRef Search ADS PubMed © The Author(s) 2018; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)
International Journal of Epidemiology – Oxford University Press
Published: Apr 26, 2018
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