Gabapentin in pregnancy and the risk of adverse neonatal and maternal outcomes: A population-based cohort study nested in the US Medicaid Analytic eXtract dataset

English version

Autoři: Elisabetta Patorno ^aff001; Sonia Hernandez-Diaz ^aff002; Krista F. Huybrechts ^aff001; Rishi J. Desai ^aff001; Jacqueline M. Cohen ^aff002; Helen Mogun ^aff001; Brian T. Bateman ^aff001
Působiště autorů: Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States of America ^aff001; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America ^aff002; Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America ^aff003
Vyšlo v časopise: Gabapentin in pregnancy and the risk of adverse neonatal and maternal outcomes: A population-based cohort study nested in the US Medicaid Analytic eXtract dataset. PLoS Med 17(9): e32767. doi:10.1371/journal.pmed.1003322
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pmed.1003322

Souhrn

Background

Despite the widespread use, only sparse information is available on the safety of gabapentin during pregnancy. We sought to evaluate the association between gabapentin exposure during pregnancy and risk of adverse neonatal and maternal outcomes.

Methods and findings

Using the United States Medicaid Analytic eXtract (MAX) dataset, we conducted a population-based study of 1,753,865 Medicaid-eligible pregnancies between January 2000 and December 2013. We examined the risk of major congenital malformations and cardiac defects associated with gabapentin exposure during the first trimester (T1), and the risk of preeclampsia (PE), preterm birth (PTB), small for gestational age (SGA), and neonatal intensive care unit admission (NICUa) associated with gabapentin exposure early, late, or both early and late in pregnancy. Gabapentin-unexposed pregnancies served as the reference. We estimated relative risks (RRs) and 95% confidence intervals (CIs) using fine stratification on the propensity score (PS) to control for over 70 confounders (e.g., maternal age, race/ethnicity, indications for gabapentin, other pain conditions, hypertension, diabetes, use of opioids, and specific morphine equivalents). We identified 4,642 pregnancies exposed in T1 (mean age = 28 years; 69% white), 3,745 exposed in early pregnancy only (28 years; 67% white), 556 exposed in late pregnancy only (27 years; 60% white), and 1,275 exposed in both early and late pregnancy (29 years; 75% white). The reference group consisted of 1,744,447 unexposed pregnancies (24 years; 40% white). The adjusted RR for major malformations was 1.07 (95% CI 0.94–1.21, p = 0.33) and for cardiac defects 1.12 (0.89–1.40, p = 0.35). Requiring ≥2 gabapentin dispensings moved the RR to 1.40 (1.03–1.90, p = 0.03) for cardiac defects. There was a higher risk of preterm birth among women exposed to gabapentin either late (RR, 1.28 [1.08–1.52], p < 0.01) or both early and late in pregnancy (RR, 1.22 [1.09–1.36], p < 0.001), SGA among women exposed to gabapentin early (1.17 [1.02–1.33], p = 0.02), late (1.39 [1.01–1.91], p = 0.05), or both early and late in pregnancy (RR, 1.32 [1.08–1.60], p < 0.01), and NICU admission among women exposed to gabapentin both early and late in pregnancy (RR, 1.35 [1.20–1.52], p < 0.001). There was no higher risk of preeclampsia among women exposed to gabapentin after adjustment. Study limitations include the potential for residual confounding and exposure misclassification.

Conclusions

In this large population-based study, we did not find evidence for an association between gabapentin exposure during early pregnancy and major malformations overall, although there was some evidence of a higher risk of cardiac malformations. Maternal use of gabapentin, particularly late in pregnancy, was associated with a higher risk of PTB, SGA, and NICUa.

Klíčová slova:

Epilepsy – Medical risk factors – Neonates – Neuropathic pain – Pain – Preeclampsia – Pregnancy – Preterm birth

Zdroje

1. Gabapentin. Clinical Pharmacology. Tampa (FL): Elsevier. 2012.

2. Neurontin (gabapentin) package insert. New York: Pfizer, NY. 2017.

3. Online L. Gabapentin: Drug Information. Hudson, Ohio: Lexi-Comp, Inc.

4. Montouris G. Gabapentin exposure in human pregnancy: results from the Gabapentin Pregnancy Registry. Epilepsy & behavior: E&B. 2003;4 : 310–7.

5. Morrow J, Russell A, Guthrie E, et al. Malformation risks of antiepileptic drugs in pregnancy: a prospective study from the UK Epilepsy and Pregnancy Register. Journal of neurology, neurosurgery, and psychiatry. 2006;77 : 193–8. doi: 10.1136/jnnp.2005.074203 16157661

6. Guttuso T Jr., Robinson LK, Amankwah KS. Gabapentin use in hyperemesis gravidarum: a pilot study. Early human development. 2010;86 : 65–6. doi: 10.1016/j.earlhumdev.2009.11.003 20015600

7. Molgaard-Nielsen D, Hviid A. Newer-generation antiepileptic drugs and the risk of major birth defects. JAMA. 2011;305 : 1996–2002. doi: 10.1001/jama.2011.624 21586715

8. Hernandez-Diaz S, Smith CR, Shen A, et al. Comparative safety of antiepileptic drugs during pregnancy. Neurology. 2012;78 : 1692–9. doi: 10.1212/WNL.0b013e3182574f39 22551726

9. Fujii H, Goel A, Bernard N, et al. Pregnancy outcomes following gabapentin use: results of a prospective comparative cohort study. Neurology. 2013;80 : 1565–70. doi: 10.1212/WNL.0b013e31828f18c1 23553472

10. Veiby G, Daltveit AK, Engelsen BA, Gilhus NE. Fetal growth restriction and birth defects with newer and older antiepileptic drugs during pregnancy. Journal of neurology. 2014;261 : 579–88. doi: 10.1007/s00415-013-7239-x 24449062

11. Mostacci B, Poluzzi E, D'Alessandro R, Cocchi G, Tinuper P, Group ES. Adverse pregnancy outcomes in women exposed to gabapentin and pregabalin: data from a population-based study. Journal of neurology, neurosurgery, and psychiatry. 2018;89 : 223–4. doi: 10.1136/jnnp-2017-316143 28716783

12. Centers for Medicare and Medicaid Services. Medicaid Analytic eXtract (MAX) General Information [cited 2020 Apr 8]. Available from: https://www.cms.gov/Research-Statistics-Data-and-Systems/Computer-Data-and-Systems/MedicaidDataSourcesGenInfo/MAXGeneralInformation

13. Palmsten K, Huybrechts KF, Mogun H, et al. Harnessing the Medicaid Analytic eXtract (MAX) to Evaluate Medications in Pregnancy: Design Considerations. PLoS ONE. 2013;8:e67405. doi: 10.1371/journal.pone.0067405 23840692

14. Margulis AV, Setoguchi S, Mittleman MA, Glynn RJ, Dormuth CR, Hernandez-Diaz S. Algorithms to estimate the beginning of pregnancy in administrative databases. Pharmacoepidemiology and drug safety. 2013;22 : 16–24. doi: 10.1002/pds.3284 22550030

15. Centers for Medicare & Medicaid Services. Medicaid Analytic eXtract (MAX) general information. MAX 1999–2005 state claims anomalies from the “2005 files” zipped file within the “MAX Data 2005 to 2008 general information, data dictionaries, data element lists, data anomalies, validation table measures and SAS loads zipped file [cited 2018 Dec 23]. Available from: http://www.cms.gov/research-statistics-data-and-systems/computer-data-and-systems/medicaiddatasourcesgeninfo/maxgeneralinformation.html

16. Palmsten K, Huybrechts KF, Kowal MK, Mogun H, Hernandez-Diaz S. Validity of maternal and infant outcomes within nationwide Medicaid data. Pharmacoepidemiology and drug safety. 2014;23 : 646–55. doi: 10.1002/pds.3627 24740606

17. He M, Huybrechts KF, Dejene SZ, et al. Validation of algorithms to identify adverse perinatal outcomes in the Medicaid Analytic Extract database. Pharmacoepidemiology and drug safety. 2020 Mar 2. doi: 10.1002/pds.4967 [Epub ahead of print] 32124511

18. Bateman BT, Mhyre JM, Hernandez-Diaz S, et al. Development of a comorbidity index for use in obstetric patients. Obstetrics and gynecology. 2013;122 : 957–65. doi: 10.1097/AOG.0b013e3182a603bb 24104771

19. Schneeweiss S, Seeger JD, Maclure M, Wang PS, Avorn J, Glynn RJ. Performance of comorbidity scores to control for confounding in epidemiologic studies using claims data. American journal of epidemiology. 2001;154 : 854–64. doi: 10.1093/aje/154.9.854 11682368

20. Austin PC. Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples. Statistics in medicine. 2009;28 : 3083–107. doi: 10.1002/sim.3697 19757444

21. Desai RJ, Rothman KJ, Bateman BT, Hernandez-Diaz S, Huybrechts KF. A Propensity-score-based Fine Stratification Approach for Confounding Adjustment When Exposure Is Infrequent. Epidemiology. 2017;28 : 249–57. doi: 10.1097/EDE.0000000000000595 27922533

22. Wasserstein RL, Lazar NA. The ASA’s statement on p-values: Context, process, and purpose. The American Statistician. 2016;70 : 129–133.

23. Schneeweiss S, Rassen JA, Glynn RJ, Avorn J, Mogun H, Brookhart MA. High-dimensional propensity score adjustment in studies of treatment effects using health care claims data. Epidemiology. 2009;20 : 512–22. doi: 10.1097/EDE.0b013e3181a663cc 19487948

24. Rassen JA, Glynn RJ, Brookhart MA, Schneeweiss S. Covariate selection in high-dimensional propensity score analyses of treatment effects in small samples. American journal of epidemiology. 2011;173 : 1404–13. doi: 10.1093/aje/kwr001 21602301

25. Huybrechts KF, Palmsten K, Avorn J, et al. Antidepressant use in pregnancy and the risk of cardiac defects. The New England journal of medicine. 2014;370 : 2397–407. doi: 10.1056/NEJMoa1312828 24941178

26. Shah NR, Bracken MB. A systematic review and meta-analysis of prospective studies on the association between maternal cigarette smoking and preterm delivery. American journal of obstetrics and gynecology. 2000;182 : 465–72. doi: 10.1016/s0002-9378(00)70240-7 10694353

27. Ko TJ, Tsai LY, Chu LC, et al. Parental smoking during pregnancy and its association with low birth weight, small for gestational age, and preterm birth offspring: a birth cohort study. Pediatrics and neonatology. 2014;55 : 20–7. doi: 10.1016/j.pedneo.2013.05.005 23850094

28. Wei J, Liu CX, Gong TT, Wu QJ, Wu L. Cigarette smoking during pregnancy and preeclampsia risk: a systematic review and meta-analysis of prospective studies. Oncotarget. 2015;6 : 43667–78. doi: 10.18632/oncotarget.6190 26498356

29. Schneeweiss S. Sensitivity analysis and external adjustment for unmeasured confounders in epidemiologic database studies of therapeutics. Pharmacoepidemiology and drug safety. 2006;15 : 291–303. doi: 10.1002/pds.1200 16447304

30. Patorno E, Huybrechts KF, Bateman BT, et al. Lithium Use in Pregnancy and the Risk of Cardiac Malformations. The New England journal of medicine. 2017;376 : 2245–54. doi: 10.1056/NEJMoa1612222 28591541

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