Deferral of MSM:
Policy Analysisby Andrew I. Dayton
“U” (Undetectable Strains)
“E” (Blood Bank Error)
“F” (Test Failure)
“W” (Window Period)
“P” (Prevalence)
“I” (Incidence)
Quantitation of Errors I:How many infectious units will “get through?”
Infectious Units in Potential Donors
Infectious Units in Blood Supply
Contribution to Errors*
= P x U
= P x E
= P x F
= I x W/365
Total Errors = P x (U + E + F ) + I x (WP/365)} x Population
Errors = P x (U + E + F ) + I x (WP/365)} x Population
Quantitation of Errors II:How many Additional infectious units will “get through?”
Total Errors = P x (U + E + F ) + I x (WP/365)} x Population
Quantitation of Errors III: Population
FDA is considering changing donor suitability criteria to defer for MSM behavior only within the last 5 years prior to donation.
How many new individuals will join the set of donors who are not deferred by the questionnaire and thus have their units enter into the blood bank for testing?
We need to know the size of the MSM population that has abstained from MSM behavior for 5 years or more.
We need to know the frequency at which MSM can be expected to donate.
Quantitation of Errors III: Population
We need to know the size of the MSM population that has abstained from MSM behavior for 5 years or more.
1.4x106 MSM in U.S.A. with 5 years abstention (Lynda Doll, CDC)
We need to know the frequency at which MSM can be expected to donate.
Quantitation of Errors IV: Population
We need to know the frequency at which MSM with deferrable risk will donate.
Given an MSM (5 yr.) population size of 1.4x106 and assuming a donation rate equivalent to the general population, 5%, a change to a 5 year deferral policy would result in 5% x 1.4x106, or 70, 000 new MSM “presenting to donate.”
However, some of these will already have been donating. How many?
0.57% of men who present to donate have deferrable MSM history (REDS).
{ (0.57%) x (4.5x106) } / 4.7x106 = 0.55%
Of approximately 9x106 donors per year, about half, 4.5x106 are male.
The MSM population with deferrable risk = 4.7x106
The donor frequency of MSM having deferrable risk therefore =
(number showing up to donate) / (population size) =
Quantitation of Errors V: Population
We need to know the frequency at which MSM with deferrable risk will donate.
Of the 1.4x106 who are newly eligible to donate, 0.55% or ~7,700 will have already been donating. Therefore, of the 70,000 MSM who would be expected to newly present, 7,700 have already been donating.
Thus, changing the deferral policy to a 5 yr. Deferral for MSM behavior would result in approximately 62,300 new MSM presenting to donate blood.
Quantitation of HIV in newly-donating population: Prevalence Issues I
Prevalence Errors = P x (U + E + F ) x Population
HIV Prevalence in MSM varies from 6% to 36%, depending on the population sampled. Average US prevalence is approx. 8%. Given that about 75% of these already know their seropositive status and can be expected to self defer, the average effective prevalence is about 2%.
Undetectable Strains are ignored for lack of evidence that they represent a predictable threat..
Blood Bank Errors involving release of HIV positive units have not been reported. Errors, where they have occurred, have been pipetting errors and have occurred at the rate of 0.5-1.3 x 10-3.
Primary test failure, F is essentially 0.
Quantitation of HIV in newly-donating population: Prevalence Issues I
Prevalence Errors = P x (U + E + F ) x Population
2% 0 1.3x10-1 0 62,300
2x10-2 x 1.3x10-3 x 62,300 = 1.6
NAT provides a minimum 20 fold of redundancy.
Therefore, NAT reduces the introduced prevalence errors to: 0.081
Quantitation of HIV in newly-donating population: Prevalence Issues II
Even this low number of 0.081 unit per year would decrease as HIV tests eliminate the effective prevalence amongst repeat donors from this category.
•However, this estimate was made assuming errors only came from performing tests (e.g., pipetting errors).
•Double testing (e.g. EIA & NAT) confers no protection against release errors.
•Release errors are difficult to quantify.
Prevalence Issues III :Release Errors
HCV Anti-HBV-core
Donations(‘99-’00)
Hospital 1 4 70,000BloodCenter
0 1 630,000
From ARCNET (7/1/98-6/30/99):
anti-HCV+ 5013
anti-HBV-core + 26,854
# donations 5.9e6
Inappropriate release, New York State (out of 700,000 donations)
HCV Anti-HBV-core0.0133.5e-4
0.017
Reported Incidents Release Rate
Prevalence Issues III :Release Errors
How many HIV-positive units could be inappropriately released by changing to a 5 year MSM deferral policy?
Hospitals (8%)
Blood Centers (92%)
HIV+ (MSM x I)
100
1,146
Rate
0.013
3.5e-4
# released
1.3
0.4
Quantitation of HIV in newly-donating population: Incidence Issues I
Average incidence in MSM = approx. 3x10-2 /PY
Although the typical window period = 11- 16 days, in needlestick accidents followed post-exposure, 5% (2/50) seroconvert after the first 6 months.
If we assume that there is 95% conversion (or 5% failure to convert) every 6 months, there should be an exponential drop of the probability of of a seroconversion that we can calculate.
convert in 6 months (%)
fail to convert in 6 months (%)
WP units introduced into U.S. blood banks, from 62,300 MSM (#)
95% 5% 3x10-5 Units
80% 20% 0.11 Unit
75% 25% 0.42 Unit
Quantitation of HIV in newly-donating population: Incidence Issues I
convert in 6 months (%)
fail to convert in 6 months (%)
WP units introduced into U.S. blood banks, from 62,300 MSM (#)
95% 5% 3x10-5 Units
80% 20% 0.11 Unit
75% 25% 0.42 Unit
These calculations took into account the possibility of donor confusion or poor memory by assuming that a 5 yr. query was entirely ineffective except for the behavior within the last 3 years (i.e. A 3 yr. Deferral policy).
Analysis of 1 year deferral.
A 1 year deferral policy would result in approximately 112,000 new MSM donors, or about 1.8 times as many as a 5 year deferral policy. This would result in about 0.15 new sero-positive units “escaping interdiction” per year from errors in performing tests and possibly as many as 3 units from errors in unit release.
Also, a 1 year deferral policy poses potential “window period problems.”
Analysis of 1 year deferral (continued)
If there is only 95% seroconversion every 6 months post HIV exposure, then 0.25% will seroconvert after the first year.
Incidence X risk of conversion X population = # infected units*
2% X 0.25% X 112,000 = 3.1
*No correction factor for the window period is used in this calculation, because it is assumed that any delayed seroconverters are infectious for the entire time between HIV infection and seroconversion.
Summary of HIV
Thus, for HIV, changing to a 5 year deferral policy for MSM behavior would result in minimal numbers of infectious unit slipping through the blood screening system in the first year, and probably less in subsequent years.
Inappropriate release, primarily due to non-automated blood handling systems, remains the biggest risk factor.
HCV
The prevalence of HCV in Non-IVDU MSM (~4%) is only about twice that of the general population (1.8%). Given the high sensitivity of anti-HCV EIA and the redundancy of HCV NAT, deferral of MSM would be only marginally effective in preventing HCV transmission.
HBV:Prevalence Issues I
As with HIV, essentially all of the infectees who are going to seroconvert will have done so well before 3 - 5 years. Therefore “incidence” issues are of minor concern.
The real danger is chronically infected donors.
The prevalence of HBsAg-positivity in MSM is ~1%.
Therefore 623 new HBsAg-positive units would present.
However, Anti-HBV-core provides redundancy.
HBV:Prevalence Issues II
How many HBsAg-positive units could be inappropriately released by changing to a 5 year MSM deferral policy?
Hospitals (8%)
Blood Centers (92%)
HBsAg+ (MSM x PI)
50
573
Rate
0.013
3.5e-4
# released
0.64
0.2
Therefore changing to a 5-year MSM deferral would introduce minimal risk of HBV morbidity from blood transmission.
Residual Risk
Estimated risk of viral infections in the USper 10 million donations by sources of risk.*
Virus WindowPeriod
ViralVariants
ChronicSeronegative
Carriers
TestingError
Total
HIV 24 < 0.6 < 0.1 0.4 25HCV 80 < 1 0 - 20 11 91 -
111
Agent WindowPeriod
ViralVariants
ChronicAntibody-Negative Carriers
TestError
Total
HIV 12 - 13 < 0.6 0 0 13 -14
HCV 16 - 32 0 0 0 16 -32
PRE-NAT
POST-NAT
*Busch
Estimated Incidence of HIV in MSM, San Francisco
Percent per Year
____Year____1997 2000
• All MSM 1.1 1.9
• MSM/IDU 2.0 4.6
• MSM, non-IDU 1.0 1.7
HHH- 30
Acknowledgments
SeattleConnie CelumTarquin CollisShirley DesmonDwyn DithmerBarbara KrekelerWil WhittingtonBob Wood
CaliforniaKyle BernsteinGail BolanDuli KodagodaRoger Tulloch
San FranciscoJeff KlausnerWilli McFarlandSandy Schwarcz
Los AngelesPeter Kerndt
San DiegoBob Gunn
ChicagoCarol Ciesielski
PhiladelphiaMarty Goldberg
HHH- 31
Acknowledgments
CDCSevgi AralGeorge CountsLyn FinelliBill LevineKristin MertzSusan Wang
Great BritainJane JonesAngus McNichol
CONCLUSION
We have quantitatively analyzed the risks to the blood supply of changing the deferral of MSM from “…since 1977…” to “.. Within the last five years …”
This analysis has taken into account prevalence and incidence issues, test sensitivity and testing errors and release errors..
This analysis has not summarized projected improvements in blood banking from improved automation, but does demonstrate that inappropriate release remains a significant risk.
CONCLUSION
Introduction of a 5 year floating deferral for MSM behavior, even using conservative estimates, would result in minimal increased morbidity from the blood supply by HIV, HCV or HBV.
CONCLUSION
There is scientific data to support relaxation of the current MSM deferral policy which defers male donors who have had sex with another male, even one time, since 1977.
A 5 year MSM deferral policy for blood donation would harmonize with the 5 year deferral policy for tissue donation.
Questions for the Committee:
1. Does the BPAC recommend that Men who have Sex with other Men (MSM) be deferred from donating blood for a period of five years following MSM activity, rather than being deferred for any MSM behavior since 1977?
Acknowledgements
ARCAlan WilliamsSue StramerRoger Dodd
AABB(NBDRC)Marion Sullivan
CDC Lynda DollIan Williams
NIHHarvey Alter
NYS Dept. of HelathJeanne Linden
UCSFMike Busch
FDAAndrew DaytonJay EpsteinRobin BiswasIndira HewlettHira NakhasiMartin RutaEd TaborPaul Mied