Novel methods for pregnancy drug safety surveillance in the FDA Sentinel System.
TreeScan
neonatal outcomes
pregnancy
Journal
Pharmacoepidemiology and drug safety
ISSN: 1099-1557
Titre abrégé: Pharmacoepidemiol Drug Saf
Pays: England
ID NLM: 9208369
Informations de publication
Date de publication:
Feb 2023
Feb 2023
Historique:
revised:
14
07
2022
received:
11
04
2022
accepted:
21
07
2022
pubmed:
26
7
2022
medline:
26
1
2023
entrez:
25
7
2022
Statut:
ppublish
Résumé
It is a priority of the US Food and Drug Administration (FDA) to monitor the safety of medications used during pregnancy. Pregnancy exposure registries and cohort studies utilizing electronic health record data are primary sources of information but are limited by small sample sizes and limited outcome assessment. TreeScan™, a statistical data mining tool, can be applied within the FDA Sentinel System to simultaneously identify multiple potential adverse neonatal and infant outcomes after maternal medication exposure. We implemented TreeScan using the Sentinel analytic tools in a cohort of linked live birth deliveries and infants nested in the IBM MarketScan® Research Database. As a case study, we compared first trimester fluoroquinolone use and cephalosporin use. We used the Bernoulli and Poisson TreeScan statistics with compatible propensity score-based study designs for confounding control (matching and stratification) and used multiple propensity score models with various strategies for confounding control to inform best practices. We developed a hierarchical outcome tree including major congenital malformations and outcomes of gestational length and birth weight. A total of 1791 fluoroquinolone-exposed and 8739 cephalosporin-exposed mother-infant pairs were eligible for analysis. Both TreeScan analysis methods resulted in single alerts that were deemed to be due to uncontrolled confounding or otherwise not warranting follow-up. In this implementation of TreeScan using Sentinel analytic tools, we did not observe any new safety signals for fluoroquinolone use in the first trimester. TreeScan, with tailored or high-dimensional propensity scores for confounding control, is a valuable tool in addition to current safety surveillance methods for medications used during pregnancy.
Substances chimiques
Pharmaceutical Preparations
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
126-136Subventions
Organisme : FDA HHS
ID : HHSF223201400030I
Pays : United States
Organisme : US Food and Drug Administration (FDA)
ID : HHSF22301012T
Informations de copyright
© 2022 John Wiley & Sons Ltd.
Références
Kulldorff M, Dashevsky I, Avery TR, et al. Drug safety data mining with a tree-based scan statistic. Pharmacoepidemiol Drug Saf. 2013;22(5):517-523. doi:10.1002/pds.3423
Kulldorff M, Fang Z, Walsh SJ. A tree-based scan statistic for database disease surveillance. Biometrics. 2003;59(2):323-331. doi:10.1111/1541-0420.00039
Yih WK, Maro JC, Nguyen M, et al. Assessment of Quadrivalent human papillomavirus vaccine safety using the self-controlled tree-temporal scan statistic signal-detection method in the sentinel system. Am J Epidemiol. 2018;187(6):1269-1276. doi:10.1093/aje/kwy023
Yih WK, Kulldorff M, Dashevsky I, Maro JC. Using the self-controlled tree-temporal scan statistic to assess the safety of live attenuated herpes zoster vaccine. Am J Epidemiol. 2019;188(7):1383-1388. doi:10.1093/aje/kwz104
Liu CH, Huang WT, Chie WC, Arnold CK. Safety surveillance of varicella vaccine using tree-temporal scan analysis. Vaccine. 2021;39(43):6378-6384. doi:10.1016/j.vaccine.2021.09.035
Kim JH, Lee H, Shin JY. Bacillus Calmette-Guérin (BCG) vaccine safety surveillance in the Korea adverse event reporting system using the tree-based scan statistic and conventional disproportionality-based algorithms. Vaccine. 2020;38(21):3702-3710. doi:10.1016/j.vaccine.2020.04.007
Li R, Weintraub E, McNeil MM, et al. Meningococcal conjugate vaccine safety surveillance in the vaccine safety datalink using a tree-temporal scan data mining method. Pharmacoepidemiol Drug Saf. 2018;27(4):391-397. doi:10.1002/pds.4397
Yih WK, Kulldorff M, Dashevsky I, Maro JC. A broad safety assessment of the recombinant herpes zoster vaccine. Am J Epidemiol. 2022;191(5):957-964. doi:10.1093/aje/kwac030
Wintzell V, Svanström H, Melbye M, Ludvigsson JF, Pasternak B, Kulldorff M. Data Mining for Adverse Events of tumor necrosis factor-alpha inhibitors in pediatric patients: tree-based scan statistic analyses of Danish Nationwide health data. Clin Drug Investig. 2020;40(12):1147-1154. doi:10.1007/s40261-020-00977-5
Fralick M, Kulldorff M, Redelmeier D, et al. A novel data mining application to detect safety signals for newly approved medications in routine care of patients with diabetes. Endocrinol Diabetes Metab. 2021;4(3):e00237. doi:10.1002/edm2.237
Huybrechts KF, Kulldorff M, Hernandez-Diaz S, et al. Active Surveillance of the Safety of Medications Used in Pregnancy. Published Online; 2021.
Dinatale M, Roca C, Sahin L, et al. The importance of clinical research in pregnant women to inform prescription drug labeling. J Clin Pharmacol. 2020;60(S2):S18-S25. doi:10.1002/jcph.1761
Illamola SM, Bucci-Rechtweg C, Costantine MM, Tsilou E, Sherwin CM, Zajicek A. Inclusion of pregnant and breastfeeding women in research - efforts and initiatives. Br J Clin Pharmacol. 2018;84(2):215-222. doi:10.1111/bcp.13438
Wesley BD, Sewell CA, Chang CY, Hatfield KP, Nguyen CP. Prescription medications for use in pregnancy-perspective from the US Food and Drug Administration. Am J Obstet Gynecol. 2021;225(1):21-32. doi:10.1016/j.ajog.2021.02.032
Gelperin K, Hammad H, Leishear K, et al. A systematic review of pregnancy exposure registries: examination of protocol-specified pregnancy outcomes, target sample size, and comparator selection. Pharmacoepidemiol Drug Saf. 2017;26(2):208-214. doi:10.1002/pds.4150
Bird ST, Gelperin K, Taylor L, et al. Enrollment and retention in 34 United States pregnancy registries contrasted with the Manufacturer's capture of spontaneous reports for exposed pregnancies. Drug Saf. 2018;41(1):87-94. doi:10.1007/s40264-017-0591-5
Huybrechts KF, Bateman BT, Hernández-Díaz S. Use of real-world evidence from healthcare utilization data to evaluate drug safety during pregnancy. Pharmacoepidemiol Drug Saf. 2019;28(7):906-922. doi:10.1002/pds.4789
Suarez EA, Haug N, Hansbury A, Stojanovic D, Corey C. Prescription medication use and baseline health status of women with live-birth deliveries in a national data network. Am J Obstet Gynecol MFM. 2022;4(1):100512. doi:10.1016/j.ajogmf.2021.100512
US Food and Drug Administration. PDUFA Reauthorization Performance Goals and Prodecures Fiscal Years 2023 Through 2027. Published Online August 23, 2021. Accessed January 9, 2022. https://www.fda.gov/industry/prescription-drug-user-fee-amendments/pdufa-vii-fiscal-years-2023-2027
Bookstaver PB, Bland CM, Griffin B, Stover KR, Eiland LS, McLaughlin M. A review of antibiotic use in pregnancy. Pharmacother J Hum Pharmacol Drug Ther. 2015;35(11):1052-1062. doi:10.1002/phar.1649
Ziv A, Masarwa R, Perlman A, Ziv D, Matok I. Pregnancy outcomes following exposure to quinolone antibiotics - a systematic-review and meta-analysis. Pharm Res. 2018;35(5):109. doi:10.1007/s11095-018-2383-8
Yefet E, Schwartz N, Chazan B, Salim R, Romano S, Nachum Z. The safety of quinolones and fluoroquinolones in pregnancy: a meta-analysis. R Coll Obstet Gynaecol. 2018;125:8-1076.
Acar S, Keskin-Arslan E, Erol-Coskun H, Kaya-Temiz T, Kaplan YC. Pregnancy outcomes following quinolone and fluoroquinolone exposure during pregnancy: a systematic review and meta-analysis. Reprod Toxicol. 2019;85:65-74. doi:10.1016/j.reprotox.2019.02.002
American College of Obstetricians and Gynecologists. Committee opinion No. 717: sulfonamides, nitrofurantoin, and risk of birth defects. Obstet Gynecol. 2017;130:e150-e152.
Muanda FT, Sheehy O, Bérard A. Use of antibiotics during pregnancy and the risk of major congenital malformations: a population based cohort study. Br J Clin Pharmacol. 2017;83:2557-2571.
Czeizel AE, Rockenbauer M, Sørensen HT, Olsen J. Use of cephalosporins during pregnancy and in the presence of congenital abnormalities: a population-based, case-control study. Am J Obstet Gynecol. 2001;184(6):1289-1296. doi:10.1067/mob.2001.113905
Crider K, Cleves M, Reefhuis J, Berry R, Hobbs CA, Hu D. Antibacterial medication use during pregnancy and risk of birth defects: National Birth Defects Prevention Study. Arch Pediatr Adolesc Med. 2009;163(11):8.
Ailes EC, Gilboa SM, Gill SK, et al. Association between antibiotic use among pregnant women with urinary tract infections in the first trimester and birth defects, National Birth Defects Prevention Study 1997 to 2011. Birt Defects Res A Clin Mol Teratol. 2016;106(11):940-949. doi:10.1002/bdra.23570
McClure DL, Raebel MA, Yih WK, et al. Mini-sentinel methods: framework for assessment of positive results from signal refinement. Pharmacoepidemiol Drug Saf. 2014;23(1):3-8. doi:10.1002/pds.3547
WHO/CDC/ICBDSR. Birth defects surveillance: a manual for Programme managers. World health Organization; 2014.
MacDonald SC, Cohen JM, Panchaud A, TF ME, Huybrechts KF, Hernández-Díaz S. Identifying Pregnancies in Insurance Claims Data: Methods and Application to Retinoid Teratogenic Surveillance. Pharmacoepidemiol Drug Saf. 2019;22:1211-1221. doi:10.1002/pds.4794
Suarez EA, Nguyen MD, Zhang D, et al. Use of the tree-based scan statistic for surveillance of infant outcomes following maternal perinatal medication use: protocol. Accessed February 9, 2021. https://www.sentinelinitiative.org/sites/default/files/Methods/Sentinel_Protocol_TreeScan_Pregnancy_V3.pdf
Wang SV, Maro JC, Gagne JJ, et al. A general propensity score for signal identification using tree-based scan statistics. Am J Epidemiol. 2021;22:1424-1433. doi:10.1093/aje/kwab034
Bateman BT, Mhyre JM, Hernandez-Diaz S, et al. Development of a comorbidity index for use in obstetric patients. Obstet Gynecol. 2013;122(5):957-965. doi:10.1097/AOG.0b013e3182a603bb
Chua KP, Fischer MA, Linder JA. Appropriateness of outpatient antibiotic prescribing among privately insured US patients: ICD-10-CM based cross sectional study. BMJ. 2019;364:8.
Sentinel Operations Center. Sentinel modular program report: use of the tree-based scan statistic for surveillance of infant outcomes following maternal perinatal medication use (Aim 2). Accessed August 19, 2021. https://www.sentinelinitiative.org/sites/default/files/documents/Sentinel_Report_tspreg_mpl2p_wp001-002.pdf
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(4):512-522. doi:10.1097/EDE.0b013e3181a663cc
Wang SV, Maro JC, Baro E, et al. Data Mining for Adverse Drug Events with a propensity score-matched tree-based scan statistic. Epidemiology. 2018;29(6):895-903. doi:10.1097/EDE.0000000000000907
Maro JC, Nguyen MD, Dashevsky I, Baker MA, Kulldorff M. Statistical power for Postlicensure medical product safety data mining. eGEMs. 2017;5(1):6. doi:10.5334/egems.225
Kaur P, Panneerselvam D. Bicornuate Uterus. In StatPearls. StatPearls Publishing; 2021. http://www.ncbi.nlm.nih.gov/books/NBK560859/
Austin PC. The relative ability of different propensity score methods to balance measured covariates between treated and untreated subjects in observational studies. Med Decis Making. 2009;29(6):661-677. doi:10.1177/0272989X09341755
Suarez EA, Nguyen M, Zhang D, et al. Statistical power for use of tree-based scan statistics for surveillanceof infant outcomes following maternal perinatal medication use. Pharmacoepidemiol Drug Saf. 2021;30(S1):67.
Wang S, Gagne J, Maro J, et al. A general propensity score for signal detection using tree-based scan statistics. Pharmacoepidemiol Drug Saf. 2019;28(S2):29.