infectivity based risk modeling

16
Infectivity based risk modeling Nico Lelie Chiron, France

Upload: ronald

Post on 12-Feb-2016

25 views

Category:

Documents


0 download

DESCRIPTION

Infectivity based risk modeling. Nico Lelie. Chiron, France. 1:133 dilution iatrogen serum (CF titre 1:1280) in 130L plasma pool (CF titre1:10). LF Barker and R Murray AJMS, 1972: 263;27-33. ~ 10 geq?. 2/5(40%). 3/5(60%). 2/5(40%). ~ 10 4 geq?. 1/5(20%). 3/5(60%). 2/5(20%). - PowerPoint PPT Presentation

TRANSCRIPT

Page 1: Infectivity based risk modeling

Infectivity based risk modeling

Nico Lelie

Chiron, France

Page 2: Infectivity based risk modeling

LF Barker and R Murray AJMS, 1972: 263;27-33

22/37(59%)

2/5(20%)

1/5(20%)

25/37(68%)

3/5(60%)

3/5(60%)

2/5(40%)

3/5(60%)

2/5(40%)

1:133 dilutioniatrogen serum (CF

titre 1:1280) in 130L plasma pool

(CF titre1:10)

~ 10 geq?

~ 104 geq?

Page 3: Infectivity based risk modeling

HBV (NAT)HBV (NAT) HBsAgHBsAg

Analytical standardsRelation IU to genome equivalents and infectious dose

1 IU ~ 0,5 ng (PEI) ~ 1,9 ng (AFSSAPS)

1 IU ~ 7,5 geq1 ~ 5 cps2

Pictures Prof. Gerlich

1 CID50 ~ 10 geq33Yoshizawa et al

1VQC standard,2 Bayer Versant bDNA3.0

HBV Analytical Standards

Page 4: Infectivity based risk modeling

0

20

40

60

80

100

120

0 1 2 3 4 5

HIV-RNAHCV-RNAHBV-DNA

Increase of virus concentration (C) in early ramp up phase of window

days

geq/ml

. . .

C=Co 2t/l

= 0.45 days

= 0.85 days

= 2.56 days

doubling times: Glynn et al, Transfusion, 2005;45:994, Fiebig et al, AIDS 2003;17:1871 Biswas et al, Transfusion 2003,43:788

Early viral dynamics

Page 5: Infectivity based risk modeling

0%

20%

40%

60%

80%

100%

ID-TMA

MP-TMA (1:16)

delta days

Probability of HIV-RNA detection during onset viraemia

~ 4 days

HIV window phase

Page 6: Infectivity based risk modeling

Probability non RNA/DNA detection during window phase (Weusten et al, Transfusion 2002, 42, 537)

100 copies

1 copy

Mathematical model

Page 7: Infectivity based risk modeling

Relation between viral nucleic acid concentration and infectivity titre

Virus plasma source immune genomes per ref. complex infectious dosea

HBV chronic carrier - 10-100 1,2,8

HCV acute phase,H-strain - 10-100 3,4,7

chronic phase + >1000 3 F-strain + >10000 4

HIV window - 1000-100000 5,6

a) infectious dose HBV : CID50 , HCV: CID50,, HIV : 1 CID50= 1-10 TCID50

References1. Berninger et al, J. Med. Virol. (1982) 9:57-682. Ulrich et al J Infect Dis. (1989) 160: 37-433. Hijikata et al. J. Virol. (1993) 67:19534. Alter et al. J. Viral Hep. (1995) 2:121-1325. Piatak et al, Science (1993) 259:1749-17546. Prince et al. PNAS (1988) 85:6944-69487. Katayma K. Intervirology 2004;47:57-648. Yoshizawa et al, to be published

Viral load and infectivity

Page 8: Infectivity based risk modeling

HIV transmission cases by transfusion after introduction mini-pool NAT

Study Country Blood product

loadcps/ml

geq transfused1

Transmission

Delwart et al, Vox Sang 2004, 86,171-177

USA RC 180 5000 yes

Ling et al, JAMA 2000; 284:210-214

Singapore RC 5-391 3000 yes

SANBS, to be published

SouthAfrica

RC/PC 145 5000 no/yes

Zanetti, personalcommunication

Italy RC 80 2500 no

1)1) Assuming ~30 ml plasma in red cell concentrateAssuming ~30 ml plasma in red cell concentrate2)2) 120 geq/ml in limiting dilution analysis with VQC genotype E standard.120 geq/ml in limiting dilution analysis with VQC genotype E standard.

HIV MP NAT breakthrough

Page 9: Infectivity based risk modeling

Proportion of HIV-RNA positives in dilutions of differential infectious window phase plasma (South

Africa) Window plasma2 % Ampliscreen

pos (n = 3)% Ultrio

pos (n= 24)neat 100% 100%1:2 100%1:4 100% 100%1:6 67%1:8 66,7%

1:16 0% 33,3%1:24 33%1:32 20,8%1:64 16,7%

borderline infectious HIV

Page 10: Infectivity based risk modeling

HIV: production of defective virus?

virus

capsidcell

RNA

HIV infectivity

Page 11: Infectivity based risk modeling

[geq/ml]10 100 1000

HBV

HCVHIV

Probability of infection HCV / HBV

Probability of infection in window

Probability of infection

HIV

risk100%

50%

HIV infection risk

Page 12: Infectivity based risk modeling

Residual HIV window phase ‘risk days’

1 copy/20 mlday 0

ID-NATday 5,6

MP-NATday 9

p24 Agday 15

Anti-HIVday 22

3,2 ‘risk days’

Busch et al, Transfusion 2005;45:254

Weusten et al, Transfusion 2002;42:537

Anti-HIVday 22

p24 Agday 15

MP-NATday 9

ID-NATday 5,6

1 copy/20 mlday 0

0,2 ‘risk days’ 6,5 ‘risk days’

15 days

7 days

7 days9 days5,6 days

Page 13: Infectivity based risk modeling

Residual window phase ‘risk days’ of viral transmission by NAT screened red cell transfusions

based on mathematical model Weusten et al (Transfusion 2002, 42, 537) on PeliCheck analytical sensitivity data in geq/ml

published by Koppelman et al, Transfusion 2005;45:1258-66 and Vox Sang 2005;89: 193-200 20 ml plasma in red cell concentrate

Pool Size HBV HCV HIV

500 ul Ultio neat 15,3 1,4 0,2

1 ml Ampliprep Ampliscreen

minipools 1:24

23,1 4,5 3,2

No NAT, only serology

30,51 58,33 16,7 (6,5)2

1) based on HBsAg sensitivity of 2000 geg/ml2) based on anti-HIV screening 22 days, based on HIV-Ag testing with 10.000 geq/ml sensitivity 6,5 days3) Based on anti-HCV screening

40 x2 x 80 x

ID-NAT risk reduction

Page 14: Infectivity based risk modeling

Infectivity of blood

T = 0high medium low

NAT detection limit

antibody

virus

relative concentration

infectivity

neutralized

infectivity threshold

infectivity threshold

loweclipse

NAT

serologyantigen antibody

antigen detection limit

Page 15: Infectivity based risk modeling

+

-

-+

311 (94,0%) 8 (2,4%)

12 (3,6%)

Ultrio/dHIV reactive

Diagnostic Sensitivity Tigris and PRISM in 312,033 donations in RSA

PRISM anti-HIV reactive

311,702

non specific?non infectious?

infectious windowphase

HIV yield in RSA

Page 16: Infectivity based risk modeling

Infectivity based risk modeling with ID-NAT

(red cell transfusions)• rest infectious window period:– HIV ~ 0-0,5 days – HCV ~ 1-2 days– HBV ~ 1-2 weeks

• window phase risk reduction factor to serology:– HBV ~ 2 x– HCV ~ 40 x– HIV ~ 80 x

• significant risk reduction occult HBV transmission• infectivity ID-NAT negative ‘serology yield’

questionable• ID-NAT negative low infectious transfusions may not

have clinical consequences

ID-NAT risk reduction