Impact of changing donor demographics on HIV transmission risk: A ten year analysis of individual donation NAT screening

Transcription

1 Impact of changing donor demographics on HIV transmission risk: A ten year analysis of individual donation NAT screening IPFA Lisbon 216 Marion Vermeulen

2 Disclaimer Race classifications are described as per the South African government classifications and are not meant to be discriminatory nor pejorative.

3 Background on HIV epidemic Antenatal Survey % 35 Blood donors %,35 3,26 29,5, ,8,23,25 2,22,2 15,15 1 5,6 1,74,5 RR 26/Million,1,5, Antenatal survey DoH blood donors SANBS

4 Collections by race and donor type 7 over 1 years White Indian Coloured African New Rejoin Repeat

5 x/1 yields x/1 Concordants 12 1 HIV rate NAT yields serology yields Concordants

6 % Collections % HIV Collections and HIV rate in repeat donors 1% 9% 8% 7% 6% 5% 4% 3% 2% 1% % African Non African African HIV+ Non African HIV +,3,25,2,15,1,5,

7 % Collection % HIV Collections and HIV rate in new donors 1% 9% 8% 7% 6% 5% 4% 3% 2% 1% % African Non African African HIV+ Non African HIV + 3,5 3, 2,5 2, 1,5 1,,5,

8 x/1 x/1 HIV rates by donor type and classification NAT yield rate HIV concordants New Rejoin Repeat New Re-Join Repeat

9 Number (%) of HIV infection category New Rejoin Repeat Inter-don interval days (p)# Total NAT yields* 137 (1.3) 44 (1.9) 31 (12.) 11 (p<.5) 482 (3.1) Serology* Yields 186 (1.7) 17 (.7) 3 (.1) 781 (p<.5) 26 (1.3) Concordant 1545 (97.) 2285 (97.4) 228 (87.9) (95.6) Total 1868 (1) 2346 (1) 2512 (1) (1) *p value <.5 when comparing proportion of repeat and rejoin donors with new donors # p value <.5 when comparing interdonation intervals of NAT and serology yields with concordants (student t test)

10 Donor Type Non African 4,5 4, 3,5 3, 2,5 2, 1,5 1,,5, Repeat Rejoin New Repeat Rejoin New Risk factors NAT yield/1 Ethnicity African White Indian Colour African Repeat Rejoin New

11 x/1 HIV NAT yield/1 by age and gender to 19 2 to to 3 31 to 4 41 to 5 51 to 6 16 to 19 2 to to 3 31 to 4 41 to 5 51 to 6

12 % HIV by ethnicity and donor type Donor type Category Race New Rejoin Repeat p value (new vs repeat) HIV positives White <.5 Indian <.5 Coloured <.5 African <.5 Total <.5 NAT yields White Indian Coloured African Total <.5

13 p24 antigen reactivity (%) of NAT yields Negative Positive Total 26 8 (53) 7 (47) (38) 18 (62) (73) 9 (27) (68) 12 (32) (68) 13 (32) (63) 23 (37) (55) 25 (45) (67) 25 (33) (63) 22 (37) (53) 24 (43) 56 Total 285 (62) 178 (38) 463

14 Early dynamics of HIV markers and estimates of lengths of WPs rd gen Western blot 2 nd gen Weusten J et al. Transfusion 211;51:23-15 Zaaijer et al. Lancet 1992;34:77-2 Fiebig EW et al. AIDS. 23;17: Apertrei AIDS 1996;1:F57-6 Vermeulen et al, Transfusion 213;53: days Source of data Weusten 5.3 Vermeulen Clade B seroconversion panel data 2.8 Fiebig Zaaijer 5. 38% p24ag+ Apetrei 3rd gen rd gen Non clade B (A, E, G) seroconversion data Clade C NAT vs p24 Ag yield ratio data

15 Residual risk methodology Incidence rate-wp risk day equivalent model 1 No Repeat donations No. Seroconverting donors Harmonic mean of interdonation interval MID 5 = 1 95% LOD = 18.4 copies/ml* 5% LOD = 2.7 copies/ml* 2 copies/virion NAT WP 4.3 days NAT Yield WP ratio model 1,2 No of NAT yields No of donations NAT WP = 4.3 days NAT+ Ab- = 15.4 days (clade B) NAT+ Ab- = 16.4 days (clade C) NAT+,p24Ag- = 1.1 days NAT+, p24 Ag+=6.3 days RR = R Days N seroconverting repeat T between N repeat donations RR = WP NAT T1 (WP HIV Ab WP NAT)(T2) NNAT yields N all donations 1. Weusten Transfusion 211;51: Busch Transfusion 25;45:254-64

16 Comparison of models to determine residual risk per million WP Incidence rate-risk day equivalent model WP ratio model Lengths of WP used Repeat Lapsed Repeat + Lapsed Repeat + Lapsed Pre-NAT WP Clade B Pre-NAT WP Clade C Pre-p24 Ag WP Clade C MID 5 =1 virion

17 Residual risk per million Number of HIV seroconversions Trend of residual HIV transmission risk HIV seroconversion Risk days model WP ratio Model (MID 5 =1 virion, Clade C parameters)

18 Residual risk per million Trend residual HIV transmission risk by donor type New Lapsed + Repeat All (WP ratio model, MID 5 =1 virion, Clade C parameters)

19 Residual risk per milion Trend residual HIV transmission risk by race Non African African WP ratio model, MID 5 =1 virion, Clade C parameters)

20 Residual HIV transmission risk by donor type and ethnicity RR x:million (MID 5 =1) African Non African All New Repeat & Lapsed All New 1:12,548 1:323,438 1:26,264 RR 1:x Repeat & Lapsed 1:15,174 1:37,342 1:75,47 All 1:14,349 1:371,776 1:61,557 WP ratio model, MID 5 =1 virion, Clade C parameters)

21 HIV ID-NAT breakthrough infection Donor Recipient Transfused unit Index donation Recipient Date Bled 19/9/214 4/12/214 14/2/215 Unit number Transfused date 28/9/214 Started ARV 28/1/215 Prism HIV S/CO NAT S/CO Viral load 936 copies/ml CD4 578 Lookback investigation HIV-1 Subtype C 1% boot strap in phylogenetic sequencing Observed risk 1:7.7 million

22 HIV NAT breakthrough cases Country Blood Product Storage Screening time Assay days 5% LOD cps/ml 95% LOD cps/ml Pool size Test Failure Break-Through Cases Approx Estimated Cps/mL Viral load plasma copies etimate method ml transfused Recipient Infected Reference Germany RBC In-house 96 64TaqMan 2 128, Yes Schmidt M et al. Transfusion 29;49: Germany RBC In-house TaqMan 2 256, Yes Chudy M et al. Transfusion x Viral Load Below Detectable Level Germany PLT In-house 24 TaqMan 24 No Kalus U et al., Transfusion 29;49: Germany RBC Gfe Blut No Muller B. Transfusion. 213;53: France RBC Nuclisens- Ampliscreen % LOD Yes Najiouallah F et al. J Med Virol 24;73: USA FFP Duplex % LOD Yes Phelps R et al. Transfusion 24;44: USA RBC Duplex % LOD Yes Phelps R et al. Transfusion 24;44: USA FFP Duplex % LOD Yes Stramer S et al. Transfusion 23;43:Supplement :4-41A USA RBC Duplex % LOD No Stramer S et al. Transfusion 23;43:Supplement :4-41A USA RBC In-house 24 18NGI b 2 36 Yes Delwart ELet al. Vox Sang 24;86: Singapore PLT No NAT 5Probit Yes Ling AE et al. JAMA 2; 28:4: Singapore RBC No NAT 5Probit 2 1 Yes Ling AE et al. JAMA 2; 28:4: S. Africa RBC No NAT 31Probit 2 62 No Ferriera MCet al. Transfusion 26;46: S. Africa PLT No NAT 31Probit 2 62 Yes Ferriera MCet al. Transfusion 26;46: Italy RBC No NAT 98TaqMan No Zanetti et al. Transfusion 27;47: Denmark PLT In-house Abbott RT Yes Harritshoj Let al. Transfusion 28;48: Denmark RBC In-house Abbott RT Yes Harritshoj Let al. Transfusion 28;48: Japan RBC AmpliNAT % LOD 2 14 Yes Satake M et al. Journal of Hematology 24;8:36-1 USA RBC Duplex % LOD Yes Laffoon et al, MMWR 21;59: Greece RBC No NAT % LOD Yes Hatzakis et al. (personal communication, 26) Spain RBC 28Ampliscreen Ampl Monitor 2 27 No Alvarez et al. Transfusion 216;56; Spain PLT 2Ampliscreen Ampl Monitor Yes Alvarez et al. Transfusion 216;56; Spain FFP-MB Ampliscreen Amp Mon Yes Alvarez et al. Transfusion 216;56; Japan RBC TaqScreen % LOD 2 82 No Shinohar N. Transfusion 214;54: Japan FFP TaqScreen % LOD Yes Shinohar N. Transfusion 214;54: Brazil RBC 11in house probit 2 87 Yes Salles NA. Transfusion 213;53: Thailand RBC TaqScreen % LOD Rujirojindakul P. Vox Sang 215:19 Suppl P Yes (abstract) SANBS RBC Ultrio Plus % LOD 2 54 Yes Vermeulen M personal communication

23 probability HIV transmissibility in NAT breakthrough cases 1% 9% 8% 7% 6% 5% 4% 3% 2% 1% % FFP PLT RBC transmission MID 5 =96 copies= 48 virions Non transmission copies/ml

24 Impact of MID 5 on overall residual HIV transmission risk MID 5 x/million 1:x :61, :9, :36, :2,4,816 Observed rate.13 1:7,692,37 Possible reasons for lower observed rate: 5% mortality rate 18% adult population already infected Poor ability to contact patients post discharge

25 Conclusions Yield ratio and incidence rate models were comparable when using same WP (risk day) estimates No difference in residual risk between repeat and lapsed blood donors No difference in NAT yield rate and in residual risk in new, repeat or lapsed donors within African donors (and within non African donors) Difference and trends in NAT yield rate and residual risk depends on donor demographics Estimated residual risk is >1 fold than observed rate The implementation of ID-NAT has enabled SANBS to increase the African donor base and maintain the RR 18/million window period donations compared to 26/million in 25 (Pre-NAT)

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