Using Automated Databases to Using Automated Databases to Assess Fetal Effects of Maternal Assess Fetal Effects of Maternal

Medication UseMedication Use

William Cooper, M.D., M.P.H.William Cooper, M.D., M.P.H.Vanderbilt University School of MedicineVanderbilt University School of Medicine

FDA/OWHFDA/OWHPregnancy and Prescription Medication Use SymposiumPregnancy and Prescription Medication Use Symposium

ObjectivesObjectives

Discuss role of automated databases in Discuss role of automated databases in conducting studies of maternal drug conducting studies of maternal drug exposures and fetal effectsexposures and fetal effects

Review findings from OWH funded studiesReview findings from OWH funded studies

Consider future directionsConsider future directions

Lessons Learned from ThalidomideLessons Learned from Thalidomide

Epidemiology played a critical roleEpidemiology played a critical role– Response to signalResponse to signal– Epidemiologic assessmentEpidemiologic assessment

Placenta not protectivePlacenta not protective

Need for regulation and Need for regulation and monitoring of medications monitoring of medications and effects on fetusand effects on fetus

Population-Based StudiesPopulation-Based Studies

Provide estimates of potential exposuresProvide estimates of potential exposuresTest signals with adequate powerTest signals with adequate powerProvide directions for targeted studyProvide directions for targeted study– Maternal differencesMaternal differences– Fetal differencesFetal differences

Opportunities for informing policiesOpportunities for informing policies– Identify medications with low riskIdentify medications with low risk– Identify medications with high riskIdentify medications with high risk

Role of Epidemiologic StudiesRole of Epidemiologic Studies

Assess Risk

Signal Detection

Case-controlStudies

CohortStudies

Administrative Data: TennesseeAdministrative Data: Tennessee

Linked data system dating to 1974Linked data system dating to 1974**

Critical elements validatedCritical elements validated

Used in over 300 research studiesUsed in over 300 research studies

Filled pharmacy claimsFilled pharmacy claims– Validated as measure of drug exposureValidated as measure of drug exposure††

– Avoids maternal recall biasAvoids maternal recall bias

*Ray et al Annals Epidem 1989

Cooper & Kuhlthau Amb Pediatr 2001

††Landry et al Landry et al GertontologistGertontologist 1988; Leister 1988; Leister Med CareMed Care 1981; Johnson 1981; Johnson J Am Ger Soc J Am Ger Soc 19911991

Evaluation: Administrative DataEvaluation: Administrative Data

*Ray et al Am J Epidem 1989; Cooper et al Paediatr Perinatal Epi 2008

MEDICAL RECORDS

DEATHCERTIFICATE

TENNCAREFILES

ALL-PAYERSDATA

CENSUSDATA

BIRTHCERTIFICATE

LINKFILE

Unique Considerations: DatabasesUnique Considerations: Databases

Choosing the right questionChoosing the right question

Cohort identificationCohort identification

Exposure ascertainmentExposure ascertainment

OutcomeOutcome– IdentificationIdentification– ValidationValidation

Choosing the Right QuestionChoosing the Right Question

SignalSignal– Vigilant health care providersVigilant health care providers– FDA adverse event reportsFDA adverse event reports– Registries (HIV-infected women, Accutane)Registries (HIV-infected women, Accutane)– Surveillance (CDC, Teratology Services)Surveillance (CDC, Teratology Services)

Public Health ImportancePublic Health Importance– Bioterrorism Antibiotics and Fetal RisksBioterrorism Antibiotics and Fetal Risks– FDA OWHFDA OWH

Biologic PlausibilityBiologic Plausibility

Choosing the Right QuestionChoosing the Right Question

FeasibilityFeasibility– Timing of exposure (trimester)Timing of exposure (trimester)– Potential outcomes measurablePotential outcomes measurable– Sufficient useSufficient use

Statistical powerStatistical power

Public health guidance needed for safetyPublic health guidance needed for safety

Antidepressant ExposuresAntidepressant Exposures

Cooper, Willy et al, Am J Obstet Gynecol 2007;197

CohortCohort

Selection of pregnanciesSelection of pregnancies– Enrollment throughout pregnancyEnrollment throughout pregnancy**

– Complete informationComplete information

Selection of appropriate comparison groupSelection of appropriate comparison group– Non-usersNon-users– Active comparatorsActive comparators

*Cooper et al, New Engl J Med 2006; 354;23-31

ExposuresExposures

*LMP validated 94% of time (Cooper et al Pharmepi Drug Safety 2008)

1st 2nd 3rdPRE

LMP* DOB

Date of prescription through days supplyDate of prescription through days supplyDrugs with long half-lives (biologics)Drugs with long half-lives (biologics)Drugs in combination Drugs in combination Drugs with overlapDrugs with overlap

Antibiotics and Pregnancy*Antibiotics and Pregnancy*GroupGroup AnyAny

CiproCipro††

Any Any AzithroAzithro

AnyAny

DoxyDoxy

AnyAny

AmoxAmox

AnyAny

ErythEryth

NoneNone

N infantsN infants 588588 1,4591,459 1,8431,843 14,53414,534 2,1282,128 3,4003,400

Mean age at deliveryMean age at delivery 23.223.2 21.621.6 22.622.6 22.622.6 22.022.0 23.123.1

Black race, %Black race, % 46.346.3 68.168.1 63.263.2 41.441.4 54.554.5 56.456.4

Chronic illness, %Chronic illness, % 25.525.5 19.819.8 19.319.3 20.920.9 20.220.2 15.315.3

Smoking, %Smoking, % 35.235.2 17.817.8 25.125.1 30.430.4 29.729.7 25.625.6

Level III hospital, %Level III hospital, % 41.341.3 44.044.0 51.151.1 34.234.2 45.845.8 45.845.8

*Cooper et al, Paed Perinatal Epidemiol 2008; 23:18

††Mutually exclusive categories (i.e. Any cipro, Any azithro (no cipro), etc.Mutually exclusive categories (i.e. Any cipro, Any azithro (no cipro), etc.

OutcomesOutcomes

Major Congenital MalformationsMajor Congenital Malformations– CDCCDC** definitions definitions

– Possible: vital records or claims in first year of lifePossible: vital records or claims in first year of life

– Confirmed: review of medical recordsConfirmed: review of medical records††

Blinded adjudication by two investigatorsBlinded adjudication by two investigators

Malformation-specific confirmation rulesMalformation-specific confirmation rules– e.g. Transposition of the Great Vesselse.g. Transposition of the Great Vessels

Echo, cardiac cath, surgical note, or autopsy findingEcho, cardiac cath, surgical note, or autopsy finding

*Metropolitan Atlanta Congenital Defects Program

† † Cooper et al Pharmacoepidemiol Drug Safety 2008

Confirmed Defects [n=869 (2.9%)]Confirmed Defects [n=869 (2.9%)]N infantsN infants

Cardiovascular (n=304)Cardiovascular (n=304)

Atrial septal defectAtrial septal defect 141141

Patent ductus arteriosus (term infants)Patent ductus arteriosus (term infants) 121121

Ventricular septal defectVentricular septal defect 7676

Central nervous system (n=82)Central nervous system (n=82)

Spina bifidaSpina bifida 88

Microcephaly and eye anomalyMicrocephaly and eye anomaly 1717

HydrocephalusHydrocephalus 2525

Renal/Genitourinary (n=166)Renal/Genitourinary (n=166)

Renal dysplasiaRenal dysplasia 2727

Genital anomaliesGenital anomalies 8989

Musculo-skeletal defects (n=207)Musculo-skeletal defects (n=207)

PolydactylyPolydactyly 147147

Upper limb defectsUpper limb defects 2121

Craniofacial anomaliesCraniofacial anomalies 1010

*Cooper et al, Paed Perinatal Epidemiol 2008; 23:18

Positive Predictive ValuePositive Predictive ValueBirth Birth

certificatescertificatesInpatient Inpatient claimsclaims

Either Either

sourcesource

All defectsAll defects 69.9%69.9% 69.9%69.9% 67.7%67.7%

CardiacCardiac 35.7%35.7% 74.5%74.5% 67.7%67.7%

GIGI 94.1%94.1% 73.6%73.6% 73.5%73.5%

MusculoMusculo 94.1%94.1% 65.0%65.0% 67.8%67.8%

GUGU 65.0%65.0% 68.4%68.4% 67.3%67.3%

CNSCNS 63.3%63.3% 48.9%48.9% 47.1%47.1%

OrofacialOrofacial 93.6%93.6% 93.3%93.3% 90.9%90.9%

*Cooper et al, Pharmacoepi Drug Safety 2008; 17:455

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0.5

1

1.5

2

2.5

3

3.5

Ciprofloxacin Azithromycin Doxycycline Amoxicillin Erytrhomycin No antibiotics

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Antibiotics & MalformationsAntibiotics & Malformations

Cooper et al, Paediatric and Perinatal Epidemiology 2009

Antibiotics: ImplicationsAntibiotics: Implications

Antibiotics that might be needed in the Antibiotics that might be needed in the event of bioterrorism attack should not event of bioterrorism attack should not result in a greater incidence of overall result in a greater incidence of overall congenital malformations in infants whose congenital malformations in infants whose mothers take these medications.mothers take these medications.

Studies of Pregnancy ExposuresStudies of Pregnancy ExposuresDrug(s)Drug(s) OutcomesOutcomes PublicationPublication

MacrolidesMacrolides ↑ ↑ Pyloric stenosisPyloric stenosis Obstet Gynecol Obstet Gynecol 2002; 100:1012002; 100:101

Category XCategory X Risk groups for useRisk groups for use Paed Perinatal Epi Paed Perinatal Epi 20042004; 18:106; 18:106

ACE inhibitorsACE inhibitors ↑↑ Heart, CNSHeart, CNS New Engl J Med New Engl J Med 2006; 354:24432006; 354:2443

SSRI antidep.SSRI antidep. ↑↑ useuse Am J Ob Gyn Am J Ob Gyn 2007; 196:e12007; 196:e1

ACE inhibitorsACE inhibitors ↑↑ useuse Am J Ob Gyn Am J Ob Gyn 2008; 198:e12008; 198:e1

AntibioticsAntibiotics No No ↑↑ malformation risk malformation risk Paed Perinatal Epi Paed Perinatal Epi 2009;2009; 23:1823:18

Harmful drugsHarmful drugs ↑↑ use in Haitiuse in Haiti Acad PediatrAcad Pediatr 2010;10:395 2010;10:395

Ongoing WorkOngoing Work

Immunosuppressives (NIAMS, AHRQ)Immunosuppressives (NIAMS, AHRQ)

HIV Medications (NICHD)HIV Medications (NICHD)

Medication Exposures in Pregnancy Medication Exposures in Pregnancy Research and Evaluation Program Research and Evaluation Program [MEPREP] (FDA)[MEPREP] (FDA)

Immunosuppressives in PregnancyImmunosuppressives in Pregnancy

ImmunosuppressivesImmunosuppressives– Biologics, methotrexate, othersBiologics, methotrexate, others– Used to treat autoimmune conditionsUsed to treat autoimmune conditions– Little or no information to guide pregnancy useLittle or no information to guide pregnancy use

OutcomesOutcomes– Malformations and perinatal outcomesMalformations and perinatal outcomes

Participating sitesParticipating sites– Vanderbilt (lead site)Vanderbilt (lead site)– Kaiser PermanenteKaiser Permanente

Northern CaliforniaNorthern CaliforniaSouthern CaliforniaSouthern California

Distributed Data NetworkDistributed Data Network

Common protocolCommon protocol

VUVU KPSCKPSCKPNKPNCC

Standardized datasets at local sitesStandardized datasets at local sites

Limited use data files sent to lead site - combined for Limited use data files sent to lead site - combined for analysisanalysis

Lead site for each study generates code, sends to Lead site for each study generates code, sends to local siteslocal sites

Case Reviews at local sites sent to lead site for Case Reviews at local sites sent to lead site for confirmationconfirmation

In Utero HIV MedicationsIn Utero HIV Medications

Several treatments, all understudiedSeveral treatments, all understudiedCollaboration with two other sitesCollaboration with two other sites– Harvard School of Public HealthHarvard School of Public Health– Brigham and Women’s Brigham and Women’s

Pharmacoepidemiology UnitPharmacoepidemiology Unit

OutcomesOutcomes– MalformationsMalformations– NICU hospitalizationNICU hospitalization– DeathDeath

Pregnancy Network (MEPREP)Pregnancy Network (MEPREP)

Multiple sitesMultiple sites– HMO Research Network (15 health plans)HMO Research Network (15 health plans)– Kaiser Permanente (2 health plans)Kaiser Permanente (2 health plans)– Vanderbilt (Tennessee Medicaid)Vanderbilt (Tennessee Medicaid)

Standardized data files/distributed dataStandardized data files/distributed data

Increased sample size and distributionIncreased sample size and distribution

Collaboration with FDACollaboration with FDA

What is Needed?What is Needed?

Active surveillanceActive surveillanceFollow-up of signal with studies Follow-up of signal with studies – No study design is perfectNo study design is perfect– Draw on strengths of various designsDraw on strengths of various designs– Consortia to assess signalConsortia to assess signal

Methods for conveying informationMethods for conveying information– Information for policy makersInformation for policy makers– Information for health care providersInformation for health care providers– Information for women of child-bearing ageInformation for women of child-bearing age

AcknowledgmentsAcknowledgmentsCollaboratorsCollaborators

– VanderbiltVanderbiltWayne RayWayne RayGerald HicksonGerald HicksonMike SteinMike Stein

– HarvardHarvardSonia Hernandez-DiazSonia Hernandez-Diaz

– Kaiser PermanenteKaiser PermanenteDe-Kun LiDe-Kun LiCraig CheethamCraig Cheetham

– FDAFDAMary WillyMary WillyJudy StaffaJudy StaffaRita Ouellet-HellstromRita Ouellet-HellstromPam ScottPam ScottKristin PhucasKristin Phucas

BiostatisticsBiostatistics– Patrick ArbogastPatrick Arbogast– Lisa KaltenbachLisa Kaltenbach– Hua DingHua Ding

TraineesTrainees– Michael BowenMichael Bowen– Megan CevascoMegan Cevasco– Brooke ThompsonBrooke Thompson– Stephen PontStephen Pont– Astride JulesAstride Jules

Research StaffResearch Staff

– ProgrammersProgrammers

Judy DudleyJudy Dudley

Kathi HallKathi Hall

Tony MorrowTony Morrow

– Research NursesResearch Nurses

Pat GideonPat Gideon

Leanne BalmerLeanne Balmer

Michelle DeRanieriMichelle DeRanieri

Dee WoodDee Wood

– Research CoordinatorsResearch Coordinators

Shannon StrattonShannon Stratton

Lynne CaplesLynne Caples

FundersFunders

– AHRQ HS 13084AHRQ HS 13084

– NIAMS AR 07001NIAMS AR 07001

– FDA 223-02-3003, 223-05-10100FDA 223-02-3003, 223-05-10100

– NICHD HD 056940NICHD HD 056940