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Using Automated Databases to Assess Fetal Effects of Maternal Medication Use. FDA/OWH Pregnancy and Prescription Medication Use Symposium. William Cooper, M.D., M.P.H. Vanderbilt University School of Medicine. Objectives.

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using automated databases to assess fetal effects of maternal medication use

Using Automated Databases to Assess Fetal Effects of Maternal Medication Use

FDA/OWHPregnancy and Prescription Medication Use Symposium

William Cooper, M.D., M.P.H.

Vanderbilt University School of Medicine

  • Discuss role of automated databases in conducting studies of maternal drug exposures and fetal effects
  • Review findings from OWH funded studies
  • Consider future directions
lessons learned from thalidomide
Lessons Learned from Thalidomide
  • Epidemiology played a critical role
    • Response to signal
    • Epidemiologic assessment
  • Placenta not protective
  • Need for regulation and monitoring of medications and effects on fetus
population based studies
Population-Based Studies
  • Provide estimates of potential exposures
  • Test signals with adequate power
  • Provide directions for targeted study
    • Maternal differences
    • Fetal differences
  • Opportunities for informing policies
    • Identify medications with low risk
    • Identify medications with high risk
role of epidemiologic studies
Role of Epidemiologic Studies

Signal Detection



Assess Risk

administrative data tennessee
Administrative Data: Tennessee
  • Linked data system dating to 1974*
  • Critical elements validated
  • Used in over 300 research studies
  • Filled pharmacy claims
    • Validated as measure of drug exposure†
    • Avoids maternal recall bias

*Ray et al Annals Epidem 1989

Cooper & Kuhlthau Amb Pediatr 2001

†Landry et al Gertontologist 1988; Leister Med Care 1981; Johnson J Am Ger Soc 1991

evaluation administrative data
Evaluation: Administrative Data













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

unique considerations databases
Unique Considerations: Databases
  • Choosing the right question
  • Cohort identification
  • Exposure ascertainment
  • Outcome
    • Identification
    • Validation
choosing the right question
Choosing the Right Question
  • Signal
    • Vigilant health care providers
    • FDA adverse event reports
    • Registries (HIV-infected women, Accutane)
    • Surveillance (CDC, Teratology Services)
  • Public Health Importance
    • Bioterrorism Antibiotics and Fetal Risks
    • FDA OWH
  • Biologic Plausibility
choosing the right question10
Choosing the Right Question
  • Feasibility
    • Timing of exposure (trimester)
    • Potential outcomes measurable
    • Sufficient use
      • Statistical power
      • Public health guidance needed for safety
antidepressant exposures
Antidepressant Exposures

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

  • Selection of pregnancies
    • Enrollment throughout pregnancy*
    • Complete information
  • Selection of appropriate comparison group
    • Non-users
    • Active comparators

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




  • Date of prescription through days supply
  • Drugs with long half-lives (biologics)
  • Drugs in combination
  • Drugs with overlap





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

antibiotics and pregnancy
Antibiotics and Pregnancy*

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

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

  • Major Congenital Malformations
    • CDC* definitions
    • Possible: vital records or claims in first year of life
    • Confirmed: review of medical records†
      • Blinded adjudication by two investigators
      • Malformation-specific confirmation rules
        • e.g. Transposition of the Great Vessels
          • Echo, 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%)]

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

positive predictive value
Positive Predictive Value

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

antibiotics malformations
Antibiotics & Malformations

Cooper et al, Paediatric and Perinatal Epidemiology 2009

antibiotics implications
Antibiotics: Implications
  • Antibiotics that might be needed in the event of bioterrorism attack should not result in a greater incidence of overall congenital malformations in infants whose mothers take these medications.
ongoing work
Ongoing Work
  • Immunosuppressives (NIAMS, AHRQ)
  • HIV Medications (NICHD)
  • Medication Exposures in Pregnancy Research and Evaluation Program [MEPREP] (FDA)
immunosuppressives in pregnancy
Immunosuppressives in Pregnancy
  • Immunosuppressives
    • Biologics, methotrexate, others
    • Used to treat autoimmune conditions
    • Little or no information to guide pregnancy use
  • Outcomes
    • Malformations and perinatal outcomes
  • Participating sites
    • Vanderbilt (lead site)
    • Kaiser Permanente
      • Northern California
      • Southern California

distributed data network
Distributed Data Network




Common protocol

Standardized datasets at local sites

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

Case Reviews at local sites sent to lead site for confirmation

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

in utero hiv medications
In Utero HIV Medications
  • Several treatments, all understudied
  • Collaboration with two other sites
    • Harvard School of Public Health
    • Brigham and Women’s Pharmacoepidemiology Unit
  • Outcomes
    • Malformations
    • NICU hospitalization
    • Death
pregnancy network meprep
Pregnancy Network (MEPREP)
  • Multiple sites
    • HMO Research Network (15 health plans)
    • Kaiser Permanente (2 health plans)
    • Vanderbilt (Tennessee Medicaid)
  • Standardized data files/distributed data
  • Increased sample size and distribution
  • Collaboration with FDA
what is needed
What is Needed?
  • Active surveillance
  • Follow-up of signal with studies
    • No study design is perfect
    • Draw on strengths of various designs
    • Consortia to assess signal
  • Methods for conveying information
    • Information for policy makers
    • Information for health care providers
    • Information for women of child-bearing age


Wayne Ray

Gerald Hickson

Mike Stein


Sonia Hernandez-Diaz

Kaiser Permanente

De-Kun Li

Craig Cheetham


Mary Willy

Judy Staffa

Rita Ouellet-Hellstrom

Pam Scott

Kristin Phucas


Patrick Arbogast

Lisa Kaltenbach

Hua Ding


Michael Bowen

Megan Cevasco

Brooke Thompson

Stephen Pont

Astride Jules

Research Staff


Judy Dudley

Kathi Hall

Tony Morrow

Research Nurses

Pat Gideon

Leanne Balmer

Michelle DeRanieri

Dee Wood

Research Coordinators

Shannon Stratton

Lynne Caples


AHRQ HS 13084

NIAMS AR 07001

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

NICHD HD 056940