Transcript Discovery of Misconduct at Clinical Sites

Fraud & Misconduct
at Investigator Sites
Paul Below
Clinical Research Consultant
P. Below Consulting, Inc.
SoCRA 15th Annual Conference
Chicago, IL
September 23, 2006
Disclosure & Disclaimer


I have a consulting relationship with the
following companies:

MGI Pharma

Medical Research Management

Minneapolis Heart Institute Foundation
The views expressed here are my own and I
am solely responsible for the content of this
presentation
Presentation Topics
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Definition of fraud

Prevalence

Famous cases
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Consequences
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Reasons why fraud occurs
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Warning signs/identifiers
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Detection strategies
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Fraud prevention
FDA Definition of Fraud

Falsification of data in proposing, designing,
performing, recording, supervising or reviewing
research, or in reporting research results
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Falsification includes both acts of omission
(consciously not revealing all data) and
commission (consciously altering or fabricating
data)
Fraud Definition (cont.)
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Fraud does not include honest error or honest
differences in opinion

Deliberate or repeated noncompliance with the
protocol and GCP can be considered fraud, but
is considered secondary to falsification of data
Who Commits Fraud?
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Investigators
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Study coordinators
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Data management personnel
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Lab personnel
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IRB staff
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CRAs and sponsor personnel
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FDA
Who Gets Blamed?
4% 4%
9%
39%
9%
9%
Study Coordinator
Nurse
Hospital
Sponsor
Investigator
Office Staff
Sub-investigator
CRA
9%
17%
Source: FDA Presentation, DIA 2000
Prevalence of Fraud
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Difficult to determine but still considered rare
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Reported to significantly impact 1-5% of
pharmaceutical clinical trials – F. Wells, Reuters
Health, January 2002

Only ~3% of FDA inspections uncover serious
GCP violations resulting in Warning Letters
Famous Cases - Investigators
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Robert Fiddes, MD
Private practice, Whittier, CA – 1997
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Richard Borison, MD and Bruce Diamond, PhD
Medical College of Georgia – 1998
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Michael McGee, MD
University of Oklahoma, Tulsa – 2000
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Maria Kirkman (aka Ann Campbell), MD
Private practice, Alabama – 2003
Famous Cases - Coordinators
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Anne Butkovitz
Pediatric private practice, Newton, MA – 2005
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Paul Kornak
Stratton VA Medical Center, Albany – 2005
Robert Fiddes, MD – “Of Mice and Men”, 60 Minutes, April 1, 2001
Richard Borison, MD – “Drug Money,” 48 hours, July 31, 2000
Richard Borison, MD – “Drug Money,” 48 hours, July 31, 2000
Bruce Diamond, PhD – “Drug Money,” 48 hours, July 31, 2000
Bruce Diamond, PhD – “The Lessons of Greed,” PharmaVOICE, July 2004
Paul Kornak – “Abuses Endangered Veterans in Cancer Drug Experiments,”
New York Times, February 6, 2005
Consequences of Fraud
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Sponsor – data validity compromised,
submission jeopardized, additional costs
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Investigator – fines, legal expenses,
disqualification/debarment, license revocation,
incarceration, ruined career
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Institution – lawsuits
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Subject – safety at risk, loss of trust in clinical
trial process
Consequences (cont.)
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Fraudulent investigators are often used by
multiple sponsors on multiple trials
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A small number of investigators can have a
broad impact on many NDA submissions

One fraudulent investigator, Dr. Fiddes, was
involved in 91 submissions with 47 different
sponsors
Dr. Fiddes and staff on the FDA Debarment List
Federal Register Notice for
Study Coordinator Debarment
Why Does Fraud Occur?
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Lack of resources (staff, time, subjects)
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Lack of GCP training
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Lack of regulatory oversight
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Laziness
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Loss of interest
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Pressure to perform or to publish
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Money, greed
General Warning Signs
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High staff turnover
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Staff are disgruntled, fearful, anxious,
depressed, defensive
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High pressure work environment
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Obsession with study payments
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Absent investigators
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Lack of GCP training
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Unusually fast recruitment
Data Identifiers of Fraud
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Implausible trends/patterns:
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100% drug compliance
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Identical lab/ECG results
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No SAEs reported
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Subjects adhering perfectly to a visit
schedule
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Perfect efficacy responses for all
subjects
Layout the primary efficacy data for all subjects
at a site to look for trends
Data Identifiers (cont.)
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Site data not consistent with other centers
(statistical outlier)
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Source records lack an audit trail - no
signatures and dates of persons completing
documentation
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All source records & CRFs completed with the
same pen
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Perfect diary cards, immaculate CRFs
Source: British Medical Journal, 2002; 324; 1193-1194
Data Identifiers (cont.)
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Subject handwriting and signatures are
inconsistent across documents (consents,
diaries)
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Questionable subject visit dates (Sundays,
holidays, staff vacations)
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Impossible events (eg, subject randomized
before IP even available at the site)
Data Identifiers (cont.)
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Subject visits cannot be verified in the medical
chart or appointment schedule
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Data contains “digit preference” – some digits
used more frequently than others (0, 5, and
even digits)

“Halo” around the date or test value indicating
the original was obliterated with correction fluid
Detection Strategies

Expect fraud – start from the assumption that
records are bogus and work backwards
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Question missing, altered, and/or inconsistent
data – offer to retrieve records yourself, keep
pulling on loose ends and see what unravels
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Don’t be intimidated – challenge to explain
suspicious data
Detection Strategies (cont.)
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Be suspicious of blame shifting –remind the
investigator that he/she is responsible for study
conduct

Cultivate whistleblowers – pay attention to staff
complaints, listen to grievances, establish
rapport, and be approachable
Whistleblowers
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Many fraud cases uncovered by staff
whistleblowers
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Ethical commitment to report fraud (SoCRA):

I recognize my right and responsibility as a clinical research
professional to question suspected falsified data, and if
necessary, proceed with appropriate reporting procedures
as mandated by the appropriate regulatory agencies.

Many institutions have an Office of Compliance
with reporting hotlines

US government encourages whistleblowers
through False Claims Act awards
False Claims Act
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Unlawful to submit a false or fraudulent claim
for payment to the United States government
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Private citizens who know of people or
companies defrauding the government may sue
on the government's behalf (qui tam relator)
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Plaintiff shares in the proceeds of the suit
(15-30% of amount recovered by government)

Contains protections for whistleblowers who are
harassed, threatened, discharged or otherwise
discriminated against in their employment
Recent False Claims
Act settlement with
the Mayo Clinic
(Rochester, MN)
Cherlynn Mathias - University of Oklahoma
Melanoma Trial Whistle Blower
Fraud Prevention
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During pre-study evaluation, sponsors should
carefully scrutinize sites for interest in the study,
stability of the staff, investigator/staff
interactions, workload, and level of training

Everyone involved in the clinical trial process
should complete regular GCP training

CRAs should be expert on the protocol
particularly with parameters that determine
eligibility (inclusion/exclusion criteria) and
primary efficacy endpoints
Fraud Prevention (cont.)
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Sponsors should emphasize their policy on
fraud at the initiation visit

Institutions should set-up systems to
encourage fraud reporting and protect
whistleblowers
This presentation and related references
are posted on my corporate website at:
www.pbelow-consulting.com/fraud.html
Thanks

Kerrin Young, Study Manager, Takeda, and
Jeri Weigand, Quality Assurance Auditor, 3M
Pharmaceuticals, for their collaboration in the
development of this presentation
Contact Information

Office: (952) 882-4083

E-mail: [email protected]