Variant CJD risk associated with human plasma derivatives: Introduction and
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Transcript Variant CJD risk associated with human plasma derivatives: Introduction and
Variant CJD risk associated with human
plasma derivatives: Introduction and
overview of risk model for
US manufactured
Factor VIII
Steven Anderson, PhD, MPP
Associate Director for Risk Assessment
Office of Biostatistics & Epidemiology
FDA-CBER
TSE Advisory Committee Meeting
October 31, 2005
Elements of Risk Assessment
NAS (1983)
• Hazard identification
• Establishes causality between hazard and adverse
effects
• Dose response
(Hazard characterization)
• Probability of response – infection or illness
• Exposure assessment
• Frequency and level of exposure
• Estimates potential DOSE vCJD ID50
• Risk characterization
• Probability of occurrence, severity of adverse effects
• Uncertainty
• Sensitivity analysis
Risk Assessment
NAS (1983)
Risk Assessment is conducted when
information is limited and uncertainty high
• Value of Risk Assessment
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Provides estimate of risk
Details the Uncertainties
Determine effectiveness of Mitigations
Identifies data gaps and research priorities
Risk Assessment
Uncertainty
Arises in risk assessment when:
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Only limited information is available
Data are lacking
Use of assumptions / expert opinion
Errors in measurement or data collection
Incorrect specification of model
FDA Risk Assessment:
vCJD risks for US manufactured Factor VIII
Factor VIII assessment under development
Models vCJD risk for Factor VIII made in 2002
• Assessments for additional years possible - 1999
Beginning of process to assess risks for plasma
derivatives – in future may:
• Assess vCJD risks – additional product classes
• Possibly assess risk by specific product, per individual, etc.
Process model – analyzes
• Probability & quantity vCJD agent in plasma pools
• Reduction in levels vCJD ID50 in manufacturing
• Quantity Factor VIII used – exposure vCJD ID50
Overview of vCJD and US
manufactured Factor VIII
Risk Assessment Model
INPUT
UK surveillance data
Predictive modeling
based on UK vCJD
cases
Donor travel history
UK, FR, Europe
Adjustments for duration &
year traveled, donor age
Screening questionnaire
MODULE
Module 1
vCJD
Prevalence
UK
Module 2
vCJD
Prevalence
US Donors
Plasma pool size
Quantity vCJD agent in pool
Reduction of vCJD agent
during manufacture
Module 3
Annual dose Factor VIII
Module 4
FVIII
Processing
Utilization
FVIII
OUTPUT
Estimate of vCJD prevalence in
United Kingdom
Number US vCJD donors
Number vCJD donors postscreening
Total number vCJD donations
Percentage plasma pools / vials
with vCJD agent
Quantity vCJD agent per FVIII
vial
Annual exposure FVIII
recipients to vCJD agent
Module 1
Prevalence of vCJD in United Kingdom
Proposed Modeling Approaches
Two major sources of UK vCJD prevalence data
A. Predictive Modeling based on vCJD cases in UK
B. Surveillance data – examination tonsil/appendix samples
Disparity of approximately 10 to 100 fold between the two
approaches
Module 1
Prevalence of vCJD in United Kingdom
A. Predictive mathematical models
Some of data we may use (select sample – many others!):
(1) Ghani et al 2003
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(2) Boelle, et al 2003
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vCJD estimate median 100 cases (10 – 2,600 - 95% CI)
Median 1 in 500,000
vCJD estimated cases range 183 to 304 cases
(3) Llewyn et al 2004
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vCJD infection 1 in 15,000 to 1 in 30,000
Approximately 1,000 - 2,000 infections
Include all genotypes in estimate - codon 129 PrP – MM, MV, VV
Module 1
Prevalence of vCJD in United Kingdom
B. Surveillance data – tissue samples UK patients
Tonsil/appendix surveillance study (Hilton, et al. 2004)
3 prion positive samples in 12,674 samples tested
Mean of 1 positive in 4,225 individuals
Mostly in 20 – 30 yr old patients
Approximately 13,000 vCJD infected UK individuals
Data would be further age adjusted – using reported UK vCJD
cases age profile
Module 1
Prevalence of vCJD in United Kingdom
Uncertainties of Proposed Modeling Approaches
Predictive Modeling based on vCJD cases in UK
Only estimate clinical cases of MM codon 129 individuals
Use of assumptions – incubation period, time of infection, etc
Surveillance data – examination tonsil/appendix samples
vCJD agent in appendix – may not have agent in blood
May not become symptomatic
Overestimate (Sample size relatively small for rare disease)
Underestimate vCJD prevalence - in one infected case vCJD
agent not in appendix
Generally neither approach adequately address:
Clinical or asymptomatic cases MV codon 129, or VV 129 PrP
vCJD infections that don’t progress to symptomatic disease
Module 1
Prevalence of vCJD in United Kingdom
Estimation of prevalence vCJD in UK population
Critical parameter in model – used to estimate
vCJD prevalence for:
France
Europe
Plasma donors in United States
Module 2
Prevalence vCJD in US plasma donors
Proposed Modeling Approach
Estimate size of US plasma donor population travel history to UK,
France or Europe since 1980
Determine travel characteristics from survey data
Adjust travel data by several factors (duration of stay, year, etc.)
Estimate probability of infection in individual donors
Add up potential number cases for US plasma donor groups
Apply effectiveness of donor deferral policy
Model output – predict number of:
Potential vCJD infected US plasma donors
vCJD infected donors deferred from donation
Potential donations with vCJD agent
Module 2
Prevalence vCJD in US plasma donors
vCJD in US donors possible from dietary exposure to
BSE agent during travel
Current policy – Defers donors with travel history:
UK
> 3 months - 1980 – 1996
France > 5 years
- 1980 – present
Europe > 5 years - 1980 - present (blood donation only)
Estimated 90% - 99% effective eliminating vCJD donors / risk
Residual risk - Two donor groups of interest
1) Deferrable risk
1% - 10% with deferrable travel history risk but donate
2) Short duration travel
UK
< 3 months - 1980 – 1996
France < 5 years - 1980 – present
Europe < 5 years - 1980 - present (blood donation only)
Module 2
Prevalence vCJD in US plasma donors
Concept of Relative Risk
Used to estimate vCJD prevalence France and Europe
relative to UK prevalence
Based on BSE exposure, number vCJD cases, etc.
Relative
Risk
Estimated mean relative
vCJD Prevalence
UK
1
UK vCJD prevalence
France
0.05
0.05
x
UK vCJD prevalence
Europe
0.015
0.015
x
UK vCJD prevalence
Military
0.035
0.035
x
UK vCJD prevalence
Euroblood
0.015
0.015
x
UK vCJD prevalence
( x age adjustment Euro donor)
Module 2
Potential vCJD Prevalence in US Plasma Donors
Relative risk for US plasma donor with travel
history to UK, France or Europe since 1980
FDA model adjusted relative risk for vCJD
over 23 year period (1980 – 2002) based on:
Duration of Travel
Relative risk is adjusted on a per month or per day basis
Specific year(s) of travel
Accounts for variation in BSE epidemic / exposure
Age of donor
To apply age specific rates for vCJD in UK (median age 28yrs)
Module 2
Potential vCJD Prevalence in US Plasma Donors
Propose to model two types of
plasma donors
1. Source Plasma donors (> 80% donations)
Age specific donation rates
2. Recovered Plasma donors (< 20% donations)
Age specific donation rates
Module 2
Estimation Potential vCJD Prevalence
in US Plasma Donors
Plasma Donor travel estimated from
survey data
Survey – random sample of blood donors by
American Red Cross
Conducted Dec 1998 & Jan 1999
Queried travel history and accumulated stay
information for UK, Europe and/or (France) during
period 1980 - 1996
Module 2
Estimation Potential vCJD Prevalence
in US Plasma Donors
Modeling effectiveness of geographic deferral
policy for travel to UK, France and Europe
Data be discussed by Dr. Alan Williams
Potential values that could be used in FDA
model for effectiveness vCJD deferral policies
Reduces 90% to 95% of vCJD risk from first-time
donations
May reduce 99% vCJD risk from repeat donors
Module 2
Estimation Potential vCJD Prevalence
in US Plasma Donors
When is vCJD agent present in blood during
incubation period?
Detailed discussion of data by Dr. David Asher
Two potential approaches could be modeled
During entire incubation period
Assumption used in FDA Factor XI risk assessment
During last half of incubation period?
Brown, et al. 1999 prions in blood later in incubation period
Modeling would be complex
Increased uncertainty
Assumptions would be made about duration incubation periods
Module 2
Estimation Potential vCJD Prevalence
in US Plasma Donors
Uncertainties
Survey conducted on whole blood (recovered plasma
donors)
No survey on travel characteristics Source Plasma donors
Source plasma donors may travel less
Blood donor travel information may overestimate risk for Source Plasma
Estimation deferral effectiveness a challenge – because selfdeferral
Estimation of vCJD agent’s presence in blood – from animal
data may not be accurate for humans
Module 3
Factor VIII Processing
Proposed Modeling Approach
Estimation probability plasma pool contains vCJD donation
Estimation quantity vCJD ID50 per ml plasma and per pool
Efficiency of exposure through i.v. versus i.c. route
Log10 reduction in quantity iv ID50
Model output to predict :
Percentage plasma pools with vCJD agent
Percentage vials with vCJD agent
Quantity vCJD agent per vial
Module 3
Factor VIII Processing
Proposed modeling approaches for estimation
quantity vCJD ID50 per ml plasma and in pool
Data to be discussed by Dr. David Asher
Data: ic ID50 per ml blood
Propose to use triangular distribution with
Minimum
Most likely
Maximum
0.1
10
310
Module 3
Factor VIII Processing
Proposed approaches estimation efficiency of
exposure route to vCJD ID50
FDA Factor XI risk assessment - assumption with range
5 to 10 fold (Kimberlin, et al 1996)
Recent unpublished data suggest adjustment 1 to 5 fold
for efficiency of intracerebral vs. intravenous route
exposure
FDA proposes to use estimate of 1 to 5 fold for
adjustment of efficiency of intracerebral vs.
intravenous route exposure
Module 3
Factor VIII Processing
Proposed approach estimation of
Plasma pool size in FDA model
Number of donations per plasma pool used in
manufacturing ranges from 20,000 donations up to
60,000 donations
FDA needs more accurate information on size of
pools used in manufacturing
FDA proposes to use a bimodal distribution –
indicating plasma pools most likely contain 20,000
donations or 60,000 donations
Module 3
FVIII Processing
Proposed modeling of reduction vCJD ID50
during FVIII processing
Detailed information to be presented by Dr. Dorothy Scott
Some reduction levels vCJD ID50 expected to occur during
processing and manufacture of Factor VIII
Designations for degree FVIII purity (intermediate or high purity)
may have little relationship to level of vCJD ID50 clearance
FDA proposes 3 values for range Log10 reduction ID50 during
processing
2 Log10 , 5 Log10 , 8 Log10,
Distributions about these values – will capture uncertainty
Possible distributions 1-3 Log10, , 4 – 6 Log10, , 7 – 9 Log10, , etc.
Module 3
FVIII Processing
Uncertainties in the data
Only limited amount of data available of TSE
reduction for a small number processing steps
and few products
Levels of reduction achieved with spiked
infectivity may not accurately reflect levels
achieved during manufacturing
Experimental data obtained for other TSE agents
and not specifically for vCJD agent
Does addition of orthogonal reduction steps
reflect actual reduction ID50 during
manufacturing?
Module 4
Utilization of Factor VIII
Proposed Modeling Approach
Inputs:
Percentage vials with vCJD agent
Quantity vCJD agent per vial
Annual utilization / dose Factor VIII per patient
Model output to predict :
Annual potential dose vCJD ID50 per patient
Prediction of risk of vCJD infection based on
animal dose-response information
Module 4
Utilization of FVIII
Utilization to be discussed by Dr. Mark Weinstein
Utilization Factors being considered for model
Severity of Hemophilia A
Severe, Moderate and Mild
Treatment regimens
Prophylaxis and sporadic
Utilization data from CDC Hemophilia Treatment Centers
may be used in model
3000 patients followed 1993 – 1998 utilization based on review of
medical chart
If available – may use additional data sources from medical databases
Module 4
Utilization of FVIII
Uncertainties
Utilization data – not most current and may not accurately reflect
current prescribing practices
Patients on multiple products – utilization not separately
reported for each
Patients may move among categories (prophylaxis to episodic,
etc.) difficult accurately capture in estimate
To reduce uncertainty – FDA is seeking additional sources of
FVIII utilization data
Exposure Assessment
Should the FDA model address apparent
cumulative nonlinear effects of
repeated dosing?
Data to be discussed by Dr. Mark Weinstein
Single Dose
Repeated / Cumulative Doses
(Diringer H, et al. 1998, Jacquemot, et al. 2005)
Modeling the risk of repeated / cumulative doses would be a
challenge and increase uncertainty in risk estimate
Limited data suggest that in some cases there may be an added
nonlinear increase in infection rates with repeated dosing
FDA proposes to model cumulative vCJD exposure per year
assuming a linear ID50 dose-response
Exposure Assessment
Exposure assessment of FDA model will provide estimate of
potential vCJD ID50 dose
Estimated dose from model– coupled with
dose-response relationship for vCJD agent
Model will assume: vCJD ID50 is a linear dose-response
Dose
Probability of infection
1 ID50
50 %
0.1 ID50
5%
etc.
etc.
Estimated RISK = Probability vCJD infection
Exposure Assessment
Exposure to Fractional ID50 or Indivisible ID50
(1) Fractional ID50 infection
20 individuals exposed to 0.1 ID50 then
likely that 1 individual exposed to 0.1 ID50 would become infected
(2) Indivisible ID50 infection
20 individuals exposed to 0.1 ID50 then
Probability of 0.1 or 10% of receiving one ID50
Implies that 19 individuals receive no ID50 and 1 receives 1 ID50
likely that 1 individual exposed to 1 ID50 and infected
Dose response (vCJD)
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Uncertainties
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Factor VIII risk assessment uses Animal ID50 as linear
dose-response to estimate human risk !
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Animal data limited – adding uncertainty to dose-response
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Human data not available
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Development of a human dose response model is not
possible at this time
Risk Characterization
vCJD risk for Factor VIII
Conclusions:
Estimated risk of infection based on level of exposure (dose)
can be predicted using model
Risk Prediction based on animal data and animal dose response
Therefore risk estimates will be highly uncertain
Risk assessment will highlight data gaps and uncertainties
Risk estimates do provide information on relative magnitude of
risk for risk management purposes