1. Causality Assessment for Drug-
Induced Liver Injury
Leonard B. Seeff, M.D.
NIDDK, NIH
Joint Meeting of the Anti-Infective Drugs
Advisory Committee and the Drug Safety
and Risk Management Advisory Committee
Silver Spring, Maryland
December 14-15, 2006

2. Leonard B. Seeff, M.D. National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health
I have no financial relationship(s) to disclose within the past 12 months relevant to my presentation.
AND
My presentation does not include discussion of off-label or investigational use.
Joint Meeting of the Anti-Infective Drugs Advisory Committee and the Drug Safety and Risk Management Committee Meeting
December 14 & 15, 2006

3. Classification of Hepatotoxicity
Intrinsic Toxicity:
 Direct
 Indirect
Host Idiosyncrasy:
 Immunologic
 Metabolic
Zimmerman HJ. Hepatotoxicity 2nd Ed.

4. Background Idiosyncratic hepatotoxicity can manifest as three
broad categories of liver injury:
- hepatocellular liver disease
- cholestatic liver disease
- mixed hepatocellular/cholestatic liver disease
There is no form of liver disease, acute or chronic,
that is not mimicked by drug injury

5. How is Hepatotoxicity Diagnosed?
Presently, there is no biomarker for the
diagnosis of hepatotoxicity
Because hepatotoxicity can simulate all
known causes of liver disease, drug-
induced liver disease is largely a
diagnosis of exclusion
What instrument is currently available or
needs to be developed to improve diagnosis?

6. Early Efforts to Develop Causality Assessment for Hepatotoxicity
1989 RUCAM (Roussel Uclaf Causality
Assessment Method)
- points awarded in 7 categories
1997 M & V Scale (Maria and Victorino)
- subsequently found less effective
than RUCAM

7. Other Approaches to Assessment of Hepatotoxicity
Expert opinion
(Bayesian Adverse Reactions
Diagnostic Instrument)

8. Drug-Induced Liver Injury Network: DILIN
A Cooperative Agreement funded by the
Liver Disease Research Branch,
DDDN, NIDDK

9. Drug Induced Liver Injury Network Participants
Investigators:
Paul Watkins – University of North Carolina
Herbert Bonkovsky – Univ. Massachusetts
Naga Chalasani – Indiana University
Timothy Davern – UC, San Francisco
Robert Fontana – Michigan University
James Rochon (DCC) – Duke University
NIDDK, NIH:
Jose Serrano, Project Officer
Leonard Seeff; Jay Hoofnagle
FDA Advisors:
John Senior; Mark Avigan

10. Drug Induced Liver Injury Network
 Limited retrospective study focusing upon four
well-established causes of Dili: Isoniazid,
Valproic Acid, Phenytoin, and Augmentin
(amoxacillin/clavulanic acid)
Prospective study enrolling all cases of drug-
induced liver disease seen at the clinical
centers and their catchment areas

11. Drug-Induced Liver Disease Network
(DILIN): Objectives
 To provide a prospective clinical database on
unselected cases of hepatotoxicity
 To obtain biological samples for studies on the
pathogenesis of hepatotoxicity using biochemical,
molecular, immunologic and genetic techniques
 To evaluate susceptibility and genetics of drug-
induced liver injury

12. Drug-Induced Liver Disease Network
(DILIN): Objectives-2
 To provide the foundation for development of
molecular screening tools to prevent or predict
drug-induced liver injury
 To provide a stimulus and resource for research
and clinical investigation of all forms of drug-
induced liver disease
 To develop standardized definitions, grading
systems and clinical instruments to identify
and assign causality to cases of suspected

13. Drug-Induced Liver Injury (DILIN) Network Study
Causality Adjudication Process
Highly refined evaluation using expert opinion vs
RUCAM

14. Protocol for Evaluation
Drug Induced Liver Injury Network
Protocol for Evaluation
 Each case is evaluated in a standardized and
formalized fashion with collection of medical
history and all laboratory test results
 Serum, urine, PBMCs and DNA are obtained from
each patients and sent to an NIDDK repository
 Each cases is evaluated by a panel of experts to
establish an assessment of causality
 At least six-month follow-up is obtained

15. DILIN Causality Assessment
Causality Committee, subcommittee of the Steering Committee
Composed of: PI or designate from each of the 5 clinical sites
Member from Data Coordinating Center (DCC)
Member from NIDDK
Cases adjudicated by 3 members – NIDDK/DCC member and PIs
or designees selected on rotation to serve for 3 months
Causality Committee meets monthly or bimonthly to discuss cases
and reconcile differences
If the 3 members cannot agree, the full committee convenes and
votes on the case

16. Sequence of DILIN Causality Assessment
PI downloads CRF from
DILIN website
and completes CRF
CRF forwarded
to DCC
Potential case of
DILI identified by PI
Committee of 3 download
the data forms as well as
forms they must complete:
Data Completeness Checklist
Clinical Assess/Severity Forms
RUCAM
DCC cleans the data and extracts a
pre-defined subset from the CRF, inserts
the information into specially designed
data forms to distribute through the
DILIN website to the Causality Committee
The completed forms are
returned to the DCC who then
arrange for a teleconference
to discuss the cases
Causal Comm reviews
and, if necessary,
reconciles scores
in teleconference
Results recorded by
the DCC and the PI
notified for later
selection of controls

17. Causality Committee Assessment Forms
1. Data Completeness Checklist: Consists of 24 yes/no
questions for the retrospective and 41 for the prospective;
1 question asking about degree of completeness of data;
and 1 question asking if more information is needed
2. Clinical Assessment Form: Assesses causality relationship
3. Clinical Severity Form: Addresses liver disease severity
4. RUCAM

18. DILIN Causality Assessment Form
Definite > 95%
Highly likely %
Probable %
Possible %
Unlikely < 25%

19. DILIN Clinical Severity Index Form
Grade Definition
1 Raised ALT, AST or AP levels, total
serum bilirubin <2.5 mg/dl, INR <1.5
not hospitalized for DILI
2 Raised ALT, AST or AP levels, total
serum bilirubin >2.5 mg/dl, or INR >1.5
3 Hospitalized for DILI or hospitalization
prolonged because of DILI
4 Death or liver transplantation due to DILI

20. Adjudication Process for
Multiple Drugs
 Is it DILI?
 If yes, which drug likeliest culprit?
 If more than one drug possible, each
is adjudicated separately

21. Current Assessment of the Effectiveness of RUCAM
Causality assessment in DILI is complex and not well
standardized. The RUCAM system, although widely used,
exhibits substantial inter-individual variability, and
correlates rather poorly in either retrospective or
prospective identified cases with scores assigned by experts.
We conclude that in routine clinical practice, expert opinion
is likely to be more reliable than RUCAM, but requires
standardization in definitions and scales of likelihood.
Don Rockey for the DILI Group
the

22. Telithromycin

23. Approach Used to Evaluate Telithromycin for Potential Hepatotoxicity-1
Potential cases received by FDA via MedWatch
Fifty three cases selected for review by FDA
Drug Safety and Risk Management Group
Cases sent for evaluation for potential hepato-
toxicity by adjudication committee (Mark Avigan,
Allen Brinker, William Lee, Jose Serrano,
Leonard Seeff) working independently

24. Approach Used to Evaluate Telithromycin for Potential Hepatotoxicity-2
DILIN probability assessment and severity scales
used in adjudicating cases
Results of evaluation, undertaken independently,
submitted to FDA
Reconciliation of cases, if needed, reached through
several conference calls

25. Scoring for Hepatotoxicity of Adjudicated
Cases of Telithromycin (n=53)
Initial Final
Very likely 11 (20.8%) 9 (17.0%)
Probable 19 (35.9%) (35.9%)
Possible 14 (26.4%) (32.1%)
Insufficient evidence 8 (15.1%) 8 (15.1%)
Unlikely (1.9%) 0

26. Scoring for Severity of Liver disease
of Adjudicated Cases of Telithromycin
(n=53)
Grade (15%)
Grade (2%)
Grade (70%)
Grade (13%)

27. Mandatory Requirement for
Assessing Causality
Complete information to permit exclusion of
competing causes for liver injury

28. Some Questions Regarding Causality Assessment - 1
Is expert opinion preferable to the existing
causality instruments, i.e., RUCAM or M & V?
Can these existing instruments be improved?
Might the Bayesian approach be useful?

29. Some Questions Regarding Causality Assessment - 2
Distinguish enzyme adaptation from true hepatotoxicity?
Single out an implicated drug among many received when
there is underlying liver disease? Should there be 2
causality assessments: first, is it Dili, second which drug?
Will pharmacogenetics, proteomics, metabolomics
be helpful in the future?
Will other specific biomarkers be identified?
This is a work in progress!!!

30. Criteria for Considering the Diagnosis of DILI
Temporal receipt of a drug or herbal
associated with:
- ALT > 5X ULN or baseline X 2
- AP > 2X ULN or baseline X 2
- Any in ALT, AST or AP with T.Bil > 2.5

31. Return
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