RResearched esearched AAbuse, Diversion, andbuse, Diversion, andAAddiction-ddiction-RRelated elated SSurveillanceurveillance
Sidney H. Schnoll, M.D., Ph.D.Sidney H. Schnoll, M.D., Ph.D.
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RADARSRADARS® System Need for Surveillance System
• Increasing reports of abuse and diversion of OxyContin®
• Lack of data to support or refute media reports
• National data sets (DAWN, NHSDA) reporting increasing problems with prescription opioids
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Narcotic Analgesics ED Mentions as a Percent of Total Drug Abuse Mentions
0%
2%
4%
6%
8%
10%
12%
1995 1996 1997 1998 1999 2000 2001 2002
Drug Abuse Warning Network (DAWN), 1995-2002
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National Household Survey of Drug Abuse Any Lifetime Use of Hydromorphone
Lifetime Drug Use Behaviors: 1999 2000 2001
%Nonmedical Use of Multiple (2 or more) Prescription Analgesics (not hydromorphone)
88.6 93.1 93.3
% Use of Cocaine 95.4 87.7 92.2
% Use of Heroin 64.2 55.5 54.8
% Use of Cocaine or Heroin 95.4 88.8 94.0
% Nonmedical Use of Multiple Analgesics AND Cocaine or Heroin
84.1 84.2 88.2
% Needle Use 53.4 57.7 65.2
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RADARSRADARS® System Need for Surveillance System
• National data sets reported data 18-24 months after collection
• Those abusing and diverting were not necessarily patients
• Traditional drug safety/pharmacovigilance not the answer
• Needed rapid implementation
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RADARSRADARS® System Design Considerations
• Develop advisory board of experts in addiction, drug policy, law enforcement and epidemiology
• Use existing models if possible, i.e. tramadol independent steering committee
• Expand and use different models as needed• Keep pipeline in mind
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RADARSRADARS® System External Advisory Board (EAB)
Edgar Adams, Ph.D. Harris InteractiveCmdr. John Burke NADDITheodore Cicero, Ph.D. Washington Univ.Richard Dart, M.D. Rocky Mountain PCCDanna Droz, R.Ph., J.D. NASCSAAnn Geller, M.D. Columbia UniversityJames Inciardi, Ph.D. Univ. of DelawareHerbert Kleber, M.D. Columbia UniversityAlvaro Muñoz, Ph.D. Johns Hopkins Univ.Mark Parrino, M.P.A. AATODEdward Senay, M.D. Univ. of ChicagoGeorge Woody, M.D. Univ. of Pennsylvania
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RADARSRADARS® System Goals
• Prospectively study the nature and extent of abuse of scheduled prescription opioid medications
• Suggest interventions to reduce diversion and abuse that are related to problems identified
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The RADARSThe RADARS® System Drugs System Drugs
1. buprenorphine2. fentanyl 3. hydrocodone 4. hydromorphone5. methadone6. morphine 7. oxycodone
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RADARS® System Levels of Activity
Other Purdue Signals
Signal Detection
Signal Verification
Focused Studies
Interventions
Outcomes
Relative Rate Determination
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Signal Detection Components Rationale
Serves as an early warning system
• Timely collection (quarterly)
• Geographically sensitive (3-digit ZIP code)
– Calculation of local rates
• Useful for monitoring newly approved drugs
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Our Early Detection System in Action
The RADARS® System Signal Detection Studies began picking up abuse and diversion of “generic OxyContin”
one week after launch.
4/53/30/04 5/30/04
4/12 4/19 4/26 5/3 5/10 5/17 5/24
Media Signal 5/21/04"Drug dealers in eastern Kentucky beat pharmacists to new form of OxyContin"
By ROGER ALFORDAssociated Press Writer
PCC Signal3 casesTEVA launches 80 mg
generic OxyContin
PCC Signal20 cases
(Wash, DC)Dealer attempted to
sell generic to undercoveragent (LE Drug Diversion Study)
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Signal Detection Studies
• Funded by Purdue Pharma L.P.
• Studies conducted at major research organizations and universities under direction of Principal Investigators
• Data independently housed
• Data reports presented to the EAB and Purdue on a quarterly basis
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Denominator CandidatesPros Cons
1. Population Readily available Uniform exposure assumed
2. Prescriptions filled Readily available; Easily understood
One Rx One person; no adjustment for dosage strength, days of therapy, quantity, acute vs. chronic use
3. Kg distributed Readily available; Easily understood
No adjustment for potency; rate for high potency drugs will be over-estimated
4. Delivery units Provides closer estimate to drug available than prescriptions alone
No adjustment for dosage strength
5. Patients dispensed medications
Provides estimate of those benefiting from medication
Based on projected figures that have high error rate in low population areas
6. Dosage units Used by DEA and familiar to regulatory agencies
Bases calculation on injectable dosages of buprenorphine and fentanyl, assumes incorrect minimum dosage strength for oxycodone
7. Minimum divertible dosage units
Modifies DEA approach to correct for dosage units and delivery type
Harder to understand, not intuitive; New metric
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Comparison of Abuse Rates Using Different Denominators
Rates based on median rate of abuse according to denominator total exposure using Poison Control Center data from 1Q03
0
50
100
150
200
250
300
350
400
100,000Population
Prescriptions Delivery Units MinimumDivertable Units
Denominator
Ra
te
Fentanyl
Hydrocodone
Hydromorphone
Methadone
Morphine
Other oxycodone
OxyContin®
16 CONFIDENTIAL
CONFIDENTIAL % of reporting zip codes with cases and > 100 Pts
me
dia
n o
f ra
tes p
er
10
0,0
00
Pts
0 20 40 60
01
00
20
03
00
40
0
Oc
Fe
Hc
Hm
Me
Mo
oO
OcFe
Hc
Hm
Me
Mo
oO
OcFe
Hc
Hm
Me
Mo
oO
KI
Div
PCC
Median National Rates by Signal Detection Study in ZIP Codes with Greater Than 100
Patients
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Quarter 3 Digit Zip Codes: state
(Numerator, Denominator)
2002Q4 048: ME
(1, 48.83)
246: VA
(2, 263.20)
597: MT
(2, 266.59)
403: KY
(2, 327.43)
811: CO
(1, 227.23)
2003Q1 408: KY
(3, 71.07)
412: KY
(2, 59.73)
416: KY
(2, 98.10)
415: KY
(2, 144.75)
426: KY
(1, 110.31)
2003Q2 413: KY
(1, 20.41)
408: KY
(2, 61.23)
050: VT
(1, 89.83)
229: VA
(5, 511.45)
426: KY
(1, 103.35)
2003Q3 418: KY
(1, 20.99)
413: KY
(1, 22.33)
408: KY
(2, 59.83)
415:KY
(2, 116.54)
409: KY
(4, 241.57)
2003Q4 413: KY
(2, 19.01)
412: KY
(2, 35.64)
256: WV
(4, 80.08)
408: KY
(2, 47.13)
409: KY
(6, 228.90)
2004Q1 412: KY
(2, 10.50)
408: KY
(4, 42.82)
413: KY
(1, 11.72)
248: WV
(3, 37.17)
418: KY
(1, 19.80)
2004Q2 048: ME
(2, 33.05)
268: WV
(1, 31.79)
246: VA
(6, 206.75)
247: WV
(4, 158.07)
808: CO
(1, 45.17)
5 Highest Rates of Abuse for Oxycodone Extended-Release and the Corresponding 3 Digit Zip Codes
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Drug Evaluation Network System(DENS)
Thomas McLellan, PhD, Principal InvestigatorTRI & University of Pennsylvania
Rationale• Collect data on abuse of prescription drugs by those
entering drug abuse treatment programs and track
trends over time
Objectives• Gather data on prescription drug abuse in admissions
to treatment programs• Track trends in prescription drugs abused over timeDENS has lost federal funding – no further data will be collected. TRI is
not interested in collecting data for individual companies
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Law Enforcement Drug DiversionJames Inciardi, PhD, Principal Investigator
University of DelawareRationale• Monitor diversion of RADARS® System Drugs
compared to other drugs in a specific geographic locale
Objectives• Monitor the extent of diversion from a national
convenience sample of police diversion units • Identify “signal sites” for these drugs over time• Identify “epicenters of diversion” (3-digit zip code
locations where a signal is detected > 1Q per year)
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Key Informant NetworkTheodore Cicero, PhD, Principal Investigator
Washington UniversityRationale• Monitor an extensive network of specialists to proactively
seek out documented cases of abuse
Objectives• Use key informants to proactively count the cases of abuse
& addiction to RADARS® System Drugs in specific geographic locations
• Monitor the number of cases of abuse and addiction of the RADARS® System Drugs over time
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Poison Control Centers (PCCs)Richard Dart, MD, PhD, Principal Investigator
University of Colorado
Rationale• Monitor calls to PCCs regarding abuse of
RADARS® System Drugs
Objectives • Prospectively monitor exposure and
information calls• Monitor the changes in these calls over
time
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Opioid Abuse in Methadone Treatment Enrollees
Mark Parrino, MPA and Andrew Rosenblum, Ph.D.,Principal Investigators, AATOD and NDRI
Rationale• Collect admission data on new enrollees at 75 MTPs regarding abuse and addiction
involving RADARS® System Drugs
Objectives• Monitor drugs used by new admissions• Monitor need for pain medication • Monitor trends over time
Pilot study completed February 2005. Full study implemented March 2005.
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Field ResearchStructured Interview Process
• Law Enforcement • Drug Treatment Center • Physician • Pharmacist • Other
– Indian Health Services – Hospital – Board of Pharmacy – State Agencies
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Limitations and Concerns
• Not 100% coverage for all studies
• Not all sites report each quarter
• No universally accepted method defined for calculating rates/denominator issues
• Potential double counting
• No access to raw data
• Adverse event reporting
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