PrEP has high efficacy for HIV-1 prevention among higher-risk HIV-1 serodiscordant couples: a subgroup analysis from the Partners PrEP Study Erin Kahle.

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Presentation transcript:

PrEP has high efficacy for HIV-1 prevention among higher-risk HIV-1 serodiscordant couples: a subgroup analysis from the Partners PrEP Study Erin Kahle 1, Deborah Donnell 2, James Hughes 1, Katherine Thomas 1, Grace John-Stewart 1, Edith Nakku-Joloba 3, Elizabeth Bukusi 4, Jairam Lingappa 1, Connie Celum 1, Jared Baeten 1 for the Partners PrEP Study Team 1 University of Washington, Seattle, WA, USA; 2 Fred Hutchinson Cancer Research Center, Seattle,WA, USA; 3 Makerere University, Kampala, Uganda; 4 Kenya Medical Research Institute, Nairobi, Kenya;

PrEP Pre-exposure prophylaxis (PrEP) is effective in reducing HIV-1 acquisition in multiple populations AP/Paul Sakuma

Oral PrEP efficacy trial results Study NamePopulationN Placebo incidence Results Partners PrEP Kenya, Uganda Heterosexual couples 47582/100 p-y TDF: 67% efficacy FTC/TDF: 75% efficacy TDF2 Study Botswana Men and women 12193/100 p-yFTC/TDF: 62% efficacy iPrEx Brazil, Ecuador, Peru, South Africa, Thailand, US MSM24994/100 p-yFTC/TDF: 44% efficacy FEM-PrEP Kenya, S Africa, Tanzania Women19515/100 p-yFTC/TDF: futility VOICE South Africa, Uganda, Zimbabwe Women50296/100 p-y TDF: futility Vaginal TFV gel: futility FTC/TDF: ongoing

Oral PrEP efficacy trial results Study NamePopulationN Placebo incidence Results Partners PrEP Kenya, Uganda Heterosexual couples 47582/100 p-y TDF: 67% efficacy FTC/TDF: 75% efficacy TDF2 Study Botswana Men and women 12193/100 p-yFTC/TDF: 62% efficacy iPrEx Brazil, Ecuador, Peru, South Africa, Thailand, US MSM24994/100 p-yFTC/TDF: 44% efficacy FEM-PrEP Kenya, S Africa, Tanzania Women19515/100 p-yFTC/TDF: futility VOICE South Africa, Uganda, Zimbabwe Women50296/100 p-y TDF: futility Vaginal TFV gel: futility FTC/TDF: ongoing

Oral PrEP efficacy trial results Study NamePopulationN Placebo incidence Results Partners PrEP Kenya, Uganda Heterosexual couples 47582/100 p-y TDF: 67% efficacy FTC/TDF: 75% efficacy TDF2 Study Botswana Men and women 12193/100 p-yFTC/TDF: 62% efficacy iPrEx Brazil, Ecuador, Peru, South Africa, Thailand, US MSM24994/100 p-yFTC/TDF: 44% efficacy FEM-PrEP Kenya, S Africa, Tanzania Women19515/100 p-yFTC/TDF: futility VOICE South Africa, Uganda, Zimbabwe Women50296/100 p-y TDF: futility Vaginal TFV gel: futility FTC/TDF: ongoing

PrEP in serodiscordant couples Serodiscordant couples are common and contribute a high proportion of new HIV-1 cases in sub-Saharan Africa HIV acquisition risk is high for uninfected partners in discordant relationships but level of risk varies between couples Limited data on PrEP efficacy in highest risk serodiscordant couples

Objectives Identify and assess efficacy of PrEP among a subgroup of higher-risk heterosexual HIV-1 serodiscordant couples from the Partners PrEP Study

Partners PrEP study design 4758 HIV serodiscordant couples (HIV+ partner not yet medically eligible for ART) TDF once dailyPlacebo once daily Randomize HIV- partners (normal liver, renal, hematologic function) 1° endpoint: HIV infection in HIV- partner Co- 1° endpoint: Safety Follow couples for up to 36 months FTC/TDF once daily

Partners PrEP Study Sites Kenya Eldoret, Kisumu, Nairobi Thika Uganda Jinja, Kabwohe Kampala, Mbale, Tororo

HIV-1 risk score for serodiscordant couples We developed a novel risk scoring tool, made up of a discrete combination of baseline clinical and behavioral factors, that would define HIV- 1 transmission risk (Kahle, CROI 2012 Abstract 1102)

Risk score worksheet Kahle CROI 2012

Risk score worksheet Kahle CROI 2012

Risk score worksheet Kahle CROI 2012 Risk score = 7

HIV-1 incidence by risk score- PrEP placebo arm

High risk subgroup Comparable incidence to FemPrEP (5/100) and VOICE (6/100)

High risk couples subgroup 4758 PrEP couples 1087 higher risk couples (risk score ≥6) 346 TDF 354 FTC/TDF 380 placebo

High risk couples (risk score ≥6) Risk score characteristicsHigh risk group, N=1087 Full cohort, N=4503 Age29 (24-35)33 (28-40) Number of children1 (0-2)2 (1-4) Male HIV-1 uninfected partner uncircumcised874 (80.4%)1312 (29.1%) Unprotected sex within partnership, prior 30 days 678 (62.4%)1245 (27.8%) HIV-1 plasma viral load, HIV-1 infected partner 50,000 copies/mL or higher560 (51.5%)804 (17.8%) 10,000-49,999 copies/mL295 (27.1%)1237 (27.5%) Less than 10,000 copies/mL232 (21.3%)2462 (54.7%)

PrEP efficacy results Partners PrEP primary mITT analysis TDFFTC/TDFPlacebo Number of HIV-1 infections HIV-1 incidence, per 100 person-years HIV-1 protection efficacy, vs. placebo (95%CI) 67% (44-81%) 75% (55-87%) p-value <0.001

PrEP efficacy results Partners PrEP primary mITT analysis TDFFTC/TDFPlacebo Number of HIV-1 infections HIV-1 incidence, per 100 person-years HIV-1 protection efficacy, vs. placebo (95%CI) 67% (44-81%) 75% (55-87%) p-value <0.001 High risk subgroup analysis mITT TDFFTC/TDFPlacebo Number of HIV-1 infections 7628 HIV-1 incidence, per 100 person-years HIV-1 protection efficacy, vs. placebo (95%CI) 72% (35-88%) 78% (46-91%) p-value 0.001<0.001

PrEP efficacy results Partners PrEP primary mITT analysis TDFFTC/TDFPlacebo Number of HIV-1 infections HIV-1 incidence, per 100 person-years HIV-1 protection efficacy, vs. placebo (95%CI) 67% (44-81%) 75% (55-87%) p-value <0.001 High risk subgroup analysis mITT TDFFTC/TDFPlacebo Number of HIV-1 infections 7628 HIV-1 incidence, per 100 person-years HIV-1 protection efficacy, vs. placebo (95%CI) 72% (35-88%) 78% (46-91%) p-value 0.001<0.001

PrEP efficacy results Partners PrEP primary mITT analysis TDFFTC/TDFPlacebo Number of HIV-1 infections HIV-1 incidence, per 100 person-years HIV-1 protection efficacy, vs. placebo (95%CI) 67% (44-81%) 75% (55-87%) p-value <0.001 High risk subgroup analysis mITT TDFFTC/TDFPlacebo Number of HIV-1 infections 7628 HIV-1 incidence, per 100 person-years HIV-1 protection efficacy, vs. placebo (95%CI) 72% (35-88%) 78% (46-91%) p-value 0.001<0.001

PrEP efficacy results Partners PrEP primary mITT analysis TDFFTC/TDFPlacebo Number of HIV-1 infections HIV-1 incidence, per 100 person-years HIV-1 protection efficacy, vs. placebo (95%CI) 67% (44-81%) 75% (55-87%) p-value <0.001 High risk subgroup analysis mITT TDFFTC/TDFPlacebo Number of HIV-1 infections 7628 HIV-1 incidence, per 100 person-years HIV-1 protection efficacy, vs. placebo (95%CI) 72% (35-88%) 78% (46-91%) p-value 0.001<0.001

PrEP efficacy results Partners PrEP primary mITT analysis TDFFTC/TDFPlacebo Number of HIV-1 infections HIV-1 incidence, per 100 person-years HIV-1 protection efficacy, vs. placebo (95%CI) 67% (44-81%) 75% (55-87%) p-value <0.001 High risk subgroup analysis mITT TDFFTC/TDFPlacebo Number of HIV-1 infections 7628 HIV-1 incidence, per 100 person-years HIV-1 protection efficacy, vs. placebo (95%CI) 72% (35-88%) 78% (46-91%) p-value 0.001<0.001

PrEP efficacy results Partners PrEP primary mITT analysis TDFFTC/TDFPlacebo Number of HIV-1 infections HIV-1 incidence, per 100 person-years HIV-1 protection efficacy, vs. placebo (95%CI) 67% (44-81%) 75% (55-87%) p-value <0.001 High risk subgroup analysis mITT TDFFTC/TDFPlacebo Number of HIV-1 infections 7628 HIV-1 incidence, per 100 person-years HIV-1 protection efficacy, vs. placebo (95%CI) 72% (35-88%) 78% (46-91%) p-value 0.001<0.001

Summary A high risk subgroup of heterosexual HIV-1 serodiscordant couples can be identified using a composite risk scoring tool, and HIV-1 incidence is significantly higher in that high risk subgroup of HIV-1 serodiscordant couples, but Oral PrEP provides substantial protection against HIV-1 acquisition in higher risk serodiscordant couples, comparable to that seen in all couples in the Partners PrEP Study

Conclusion Although Fem-PrEP and VOICE had a higher incidence, reflecting a higher risk population, our data do not support the hypothesis that the futility of PrEP in those studies was a result of higher HIV-1 transmission risk Ongoing demonstration projects of PrEP that target the highest risk populations will maximize the potential to reduce HIV-1 transmissions

Acknowledgements Study participants and staff Funding: Bill and Melinda Gates Foundation and NIH/NIMH R01 MH Partners PrEP Study Team Sites: –Eldoret, Kenya (Moi U, Indiana U): Edwin Were (PI), Ken Fife (PI), Cosmas Apaka –Jinja, Uganda (Makarere U, UW); Patrick Ndase (PI), Elly Katabira (PI), Fridah Gabona –Kabwohe, Uganda (KCRC): Elioda Tumwesigye (PI), Rogers Twesigye –Kampala, Uganda (Makarere U): Elly Katabira (PI), Allan Ronald (PI), Edith Nakku-Joloba –Kisumu, Kenya (KEMRI, UCSF): Elizabeth Bukusi (PI), Craig Cohen (PI), Josephine Odoyo –Mbale, Uganda (TASO, CDC): Jonathan Wangisi (PI), Akasiima Mucunguzi –Nairobi, Kenya (KNH/U Nairobi, UW): James Kiarie (PI), Carey Farquhar (PI), Grace John-Stewart (PI), Harrison Tamooh –Thika, Kenya (KNH/U Nairobi, UW): Nelly Mugo (PI), Kenneth Ngure –Tororo, Uganda (CDC, TASO): Jim Campbell (PI), Jordan Tappero (PI), Aloysious Kakia University of Washington Coordinating Center: Connie Celum (PI and Co-Chair), Jared Baeten (Co-Chair and Medical Director), Deborah Donnell (Statistician), Justin Brantley, Tami Cloutier, Robert Coombs, Amy Dao, Shauna Durbin, Mira Emmanuel-Ogier, Lisa Frenkel, Carlos Flores, Harald Haugen, Renee Heffron, Ting Hong, Jim Hughes, Erin Kahle, Johanna Karas, Becky Karschney, Lara Kidoguchi, Meighan Krows, Matt Leidholm, Jai Lingappa, Toni Maddox, Angela McKay, Julie McElrath, Allison Mobley, Susan Morrison, Nelly Mugo, Andrew Mujugira, Vikram Nayani, Patrick Ndase, Apollo Odika, Hilda O’Hara, Dana Panteleeff, Jennifer Revall, Marothodi Semenya, John Sparkman, Kathy Thomas, Ellen Wilcox Adherence Ancillary Study: David Bangsberg, Jessica Haberer, Norma Ware, Monique Wyatt, Steve Safren, Christina Psaros, Craig Hendrix, Namandjé Bumpus DF/Net (data center): Lisa Ondrejcek, Darryl Pahl, Jae Chong CLS (laboratory oversight): Wendy Stevens, Charlotte Ingram, Ute Jentsch, Mukthar Kader, Nombulelo Gqomane, Feroza Bulbulia, Jan van den Heuvel ClinPhone/Perceptive Informatics (randomization)