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1. Biomarker-guided tuberculosis preventive therapy (CORTIS): a randomised controlled trial

Author

Baepanye, Kesenogile, Baepanye, Tshepiso, Clarke, Ken, Collignon, Marelize, Dlamini, Audrey, Eyre, Candice, Feni, Tebogo, Fikizolo, Moogo, Galane, Phinda, Goliath, Thelma, Gangat, Alia, Malefo-Grootboom, Shirley, Janse van Rensburg, Elba, Janse van Rensburg, Bonita, Kekana, Sophy, Zietsman, Marietjie, Kock, Adrianne, Kunene, Israel, Lakhi, Aneessa, Langa, Nondumiso, Ledwaba, Hilda, Luphoko, Marillyn, Mabasa, Immaculate, Mabe, Dorah, Mabuza, Nkosinathi, Majola, Molly, Makhetha, Mantai, Makoanyane, Mpho, Makhubalo, Blossom, Malay, Vernon, Market, Juanita, Matshego, Selvy, Mbipa, Nontsikelelo, Mmotsa, Tsiamo, Modipa, Sylvester, Mopati, Samuel, Moswegu, Palesa, Mothaga, Primrose, Muller, Dorothy, Nchwe, Grace, Nel, Maryna, Nhlangulela, Lindiwe, Ntamo, Bantubonke, Ntoahae, Lawerence, Ntshauba, Tedrius, Sanyaka, Nomsa, Seabela, Letlhogonolo, Selepe, Pearl, Senne, Melissa, Serake, MG, Thlapi, Maria, Tshikovhi, Vincent, Tswaile, Lebogang, van Aswegen, Amanda, Mbata, Lungile, Takavamanya, Constance, Pinho, Pedro, Mdlulu, John, Taljaard, Marthinette, Slabbert, Naydene, Sayed, Sharfuddin, Nielson, Tanya, Ni Sein, Ni, Govender, Dhineshree, Chinappa, Tilagavathy, Zulu, Mbali Ignatia, Maphanga, Nonhle Bridgette, Hlathi, Senzo Ralph, Gumede, Goodness Khanyisile, Shezi, Thandiwe Yvonne, Maphanga, Jabulisiwe Lethabo, Jali, Zandile Patrica, Cwele, Thobelani, Gwamanda, Nonhlanhla Zanele Elsie, Dlamini, Celaphiwe, Sing, Zibuyile Phindile Penlee, Ntanjana, Ntombozuko Gloria, Nzimande, Sphelele Simo, Mbatha, Siyabonga, Maharaj, Bhavna, Moosa, Atika, Corris, Cara-Mia, Kafaar, Fazlin, Geldenhuys, Hennie, Luabeya, Angelique Kany Kany, Shenje, Justin, Botes, Natasja, Rossouw, Susan, Africa, Hadn, Diamond, Bongani, Braaf, Samentra, Stryers, Sonia, Carstens, Alida, Jansen, Ruwiyda, Mabwe, Simbarashe, Mulenga, Humphrey, Herling, Roxane, Veldsman, Ashley, Makhete, Lebohgang, Steyn, Marcia, Buhlungu, Sivuyile, Erasmus, Margareth, Davids, Ilse, Plaatjie, Patiswa, Companie, Alessandro, Ratangee, Frances, Veldtsman, Helen, Petersen, Christel, Abrahams, Charmaine, Moses, Miriam, Kelepu, Xoliswa, Gregg, Yolande, Swanepoel, Liticia, Magawu, Nomsitho, Cetywayo, Nompumelelo, Mactavie, Lauren, Valley, Habibullah, Filander, Elizabeth, Nqakala, Nambitha, Maasdorp, Elizna, Khoury, Justine, Kriel, Belinda, Smith, Bronwyn, Muller, Liesel, Tonsing, Susanne, Loxton, Andre, Hiemstra, Andriette, Ahlers, Petri, Flinn, Marika, Chung, Eva, Chung, Michelle, Sato, Alicia, Scriba, Thomas J, Fiore-Gartland, Andrew, Penn-Nicholson, Adam, Kimbung Mbandi, Stanley, Borate, Bhavesh, Mendelsohn, Simon C, Hadley, Katie, Hikuam, Chris, Kaskar, Masooda, Musvosvi, Munyaradzi, Bilek, Nicole, Self, Steven, Sumner, Tom, White, Richard G, Erasmus, Mzwandile, Jaxa, Lungisa, Raphela, Rodney, Innes, Craig, Brumskine, William, Hiemstra, Andriëtte, Malherbe, Stephanus T, Hassan-Moosa, Razia, Tameris, Michèle, Walzl, Gerhard, Naidoo, Kogieleum, Churchyard, Gavin, and Hatherill, Mark

Published
2021
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2. Age-specific risk scores do not improve HIV-1 prediction among women in South Africa

Author

Peebles, Kathryn, Palanee-Phillips, Thesla, Balkus, Jennnifer E., Beesham, Ivana, Makkan, Heeran, Deese, Jennifer, Smit, Jennifer, Heffron, Renee, Morrison, Charles S., Philip, Neena M., Malahleha, Mookho, Kasaro, Margaret, Naidoo, Yuthika, Nielson, Tanya, Reddy, Krishnaveni, Kotze, Philip, Ahmed, Khatija, Rees, Helen, Baeten, Jared M., and Barnabas, Ruanne V.

Published
2020
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3. Biomarker-guided tuberculosis preventive therapy (CORTIS): a randomised controlled trial

Author

Scriba, Thomas J, primary, Fiore-Gartland, Andrew, additional, Penn-Nicholson, Adam, additional, Mulenga, Humphrey, additional, Kimbung Mbandi, Stanley, additional, Borate, Bhavesh, additional, Mendelsohn, Simon C, additional, Hadley, Katie, additional, Hikuam, Chris, additional, Kaskar, Masooda, additional, Musvosvi, Munyaradzi, additional, Bilek, Nicole, additional, Self, Steven, additional, Sumner, Tom, additional, White, Richard G, additional, Erasmus, Mzwandile, additional, Jaxa, Lungisa, additional, Raphela, Rodney, additional, Innes, Craig, additional, Brumskine, William, additional, Hiemstra, Andriëtte, additional, Malherbe, Stephanus T, additional, Hassan-Moosa, Razia, additional, Tameris, Michèle, additional, Walzl, Gerhard, additional, Naidoo, Kogieleum, additional, Churchyard, Gavin, additional, Hatherill, Mark, additional, Baepanye, Kesenogile, additional, Baepanye, Tshepiso, additional, Clarke, Ken, additional, Collignon, Marelize, additional, Dlamini, Audrey, additional, Eyre, Candice, additional, Feni, Tebogo, additional, Fikizolo, Moogo, additional, Galane, Phinda, additional, Goliath, Thelma, additional, Gangat, Alia, additional, Malefo-Grootboom, Shirley, additional, Janse van Rensburg, Elba, additional, Janse van Rensburg, Bonita, additional, Kekana, Sophy, additional, Zietsman, Marietjie, additional, Kock, Adrianne, additional, Kunene, Israel, additional, Lakhi, Aneessa, additional, Langa, Nondumiso, additional, Ledwaba, Hilda, additional, Luphoko, Marillyn, additional, Mabasa, Immaculate, additional, Mabe, Dorah, additional, Mabuza, Nkosinathi, additional, Majola, Molly, additional, Makhetha, Mantai, additional, Makoanyane, Mpho, additional, Makhubalo, Blossom, additional, Malay, Vernon, additional, Market, Juanita, additional, Matshego, Selvy, additional, Mbipa, Nontsikelelo, additional, Mmotsa, Tsiamo, additional, Modipa, Sylvester, additional, Mopati, Samuel, additional, Moswegu, Palesa, additional, Mothaga, Primrose, additional, Muller, Dorothy, additional, Nchwe, Grace, additional, Nel, Maryna, additional, Nhlangulela, Lindiwe, additional, Ntamo, Bantubonke, additional, Ntoahae, Lawerence, additional, Ntshauba, Tedrius, additional, Sanyaka, Nomsa, additional, Seabela, Letlhogonolo, additional, Selepe, Pearl, additional, Senne, Melissa, additional, Serake, MG, additional, Thlapi, Maria, additional, Tshikovhi, Vincent, additional, Tswaile, Lebogang, additional, van Aswegen, Amanda, additional, Mbata, Lungile, additional, Takavamanya, Constance, additional, Pinho, Pedro, additional, Mdlulu, John, additional, Taljaard, Marthinette, additional, Slabbert, Naydene, additional, Sayed, Sharfuddin, additional, Nielson, Tanya, additional, Ni Sein, Ni, additional, Govender, Dhineshree, additional, Chinappa, Tilagavathy, additional, Zulu, Mbali Ignatia, additional, Maphanga, Nonhle Bridgette, additional, Hlathi, Senzo Ralph, additional, Gumede, Goodness Khanyisile, additional, Shezi, Thandiwe Yvonne, additional, Maphanga, Jabulisiwe Lethabo, additional, Jali, Zandile Patrica, additional, Cwele, Thobelani, additional, Gwamanda, Nonhlanhla Zanele Elsie, additional, Dlamini, Celaphiwe, additional, Sing, Zibuyile Phindile Penlee, additional, Ntanjana, Ntombozuko Gloria, additional, Nzimande, Sphelele Simo, additional, Mbatha, Siyabonga, additional, Maharaj, Bhavna, additional, Moosa, Atika, additional, Corris, Cara-Mia, additional, Kafaar, Fazlin, additional, Geldenhuys, Hennie, additional, Luabeya, Angelique Kany Kany, additional, Shenje, Justin, additional, Botes, Natasja, additional, Rossouw, Susan, additional, Africa, Hadn, additional, Diamond, Bongani, additional, Braaf, Samentra, additional, Stryers, Sonia, additional, Carstens, Alida, additional, Jansen, Ruwiyda, additional, Mabwe, Simbarashe, additional, Herling, Roxane, additional, Veldsman, Ashley, additional, Makhete, Lebohgang, additional, Steyn, Marcia, additional, Buhlungu, Sivuyile, additional, Erasmus, Margareth, additional, Davids, Ilse, additional, Plaatjie, Patiswa, additional, Companie, Alessandro, additional, Ratangee, Frances, additional, Veldtsman, Helen, additional, Petersen, Christel, additional, Abrahams, Charmaine, additional, Moses, Miriam, additional, Kelepu, Xoliswa, additional, Gregg, Yolande, additional, Swanepoel, Liticia, additional, Magawu, Nomsitho, additional, Cetywayo, Nompumelelo, additional, Mactavie, Lauren, additional, Valley, Habibullah, additional, Filander, Elizabeth, additional, Nqakala, Nambitha, additional, Maasdorp, Elizna, additional, Khoury, Justine, additional, Kriel, Belinda, additional, Smith, Bronwyn, additional, Muller, Liesel, additional, Tonsing, Susanne, additional, Loxton, Andre, additional, Hiemstra, Andriette, additional, Ahlers, Petri, additional, Flinn, Marika, additional, Chung, Eva, additional, Chung, Michelle, additional, and Sato, Alicia, additional

Published
2021
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4. Pregnancy Incidence and Correlates during the HVTN 503 Phambili HIV Vaccine Trial Conducted among South African Women.

Author

Latka, Mary H., Fielding, Katherine, Gray, Glenda E., Bekker, Linda-Gail, Nchabeleng, Maphoshane, Mlisana, Koleka, Nielson, Tanya, Roux, Surita, Mkhize, Baningi, Mathebula, Matsontso, Naicker, Nivashnee, Bruyn, Guy de, Kublin, James, and Churchyard, Gavin J.

Subjects
PREGNANCY, AIDS vaccines, POISSON processes, CONDOMS
Abstract

Background: HIV prevention trials are increasingly being conducted in sub-Saharan Africa. Women at risk for HIV are also at risk of pregnancy. To maximize safety, women agree to avoid pregnancy during trials, yet pregnancies occur. Using data from the HVTN 503/"Phambili" vaccine trial, we report pregnancy incidence during and after the vaccination period and identify factors, measured at screening, associated with incident pregnancy. Methods: To enrol in the trial, women agreed and were supported to avoid pregnancy until 1 month after their third and final vaccination ("vaccination period"), corresponding to the first 7 months of follow-up. Unsterilized women, pooled across study arms, were analyzed. Poisson regression compared pregnancy rates during and after the vaccination period. Cox proportional hazards regression identified associations with first pregnancy. Results: Among 352 women (median age 23 yrs; median follow-up 1.5 yrs), pregnancy incidence was 9.6/100 women-years overall and 6.8/100 w-yrs and 11.3/100 w-yrs during and after the vaccination period, respectively [Rate Ratio = 0.60 (0.32-1.14), p = 0.10]. In multivariable analysis, pregnancy was reduced among women who: enrolled at sites providing contraception on-site [HR = 0.43, 95% CI (0.22-0.86)]; entered the trial as injectable contraceptive users [HR = 0.37 (0.21-0.67)] or as consistent condom users (trend) [HR = 0.54 (0.28-1.04)]. Compared with women with a single partner of HIV-unknown status, pregnancy rates were increased among women with: a single partner whose status was HIV-negative [HR = 2.34(1.16-4.73)] and; 2 partners both of HIV-unknown status [HR = 4.42(1.59-12.29)]. Women with 2 more of these risk factors: marijuana use, heavy drinking, or use of either during sex, had increased pregnancy incidence [HR = 2.66 (1.24-5.72)]. Conclusions: It is possible to screen South African women for pregnancy risk at trial entry. Providing injectable contraception for free on-site and supporting consistent condom use may reduce incident pregnancy. Screening should determine the substance use, partnering, and HIV status of both members of the couple for both pregnancy and HIV prevention. [ABSTRACT FROM AUTHOR]

Published
2012
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5. Age-Specific Risk Scores Do Not Improve HIV-1 Prediction Among Women in South Africa.

Author

Peebles K, Palanee-Phillips T, Balkus JE, Beesham I, Makkan H, Deese J, Smit J, Heffron R, Morrison CS, Philip NM, Malahleha M, Kasaro M, Naidoo Y, Nielson T, Reddy K, Kotze P, Ahmed K, Rees H, Baeten JM, and Barnabas RV

Subjects
Adolescent, Adult, Age Factors, Female, HIV Infections etiology, Humans, Risk Assessment, Risk Factors, South Africa epidemiology, Young Adult, HIV Infections epidemiology, HIV-1
Abstract

Background: HIV-1 risk scoring tools could help target provision of prevention modalities such as pre-exposure prophylaxis. Recent research suggests that risk scores for women aged 18-45 may not predict risk well among young women aged 18-24. We evaluated the predictive performance of age-specific risk scores compared with the existing non-age-specific VOICE risk score, developed for women aged 18-45., Methods: We conducted a secondary analysis of the Evidence for Contraceptive Options and HIV Outcomes Trial to develop and internally validate HIV-1 risk scores for women aged 18-24 and 25-35 in South Africa. Candidate predictors included baseline demographic, clinical, behavioral, and contextual characteristics readily available in clinical settings. The VOICE risk score was applied to women aged 18-35. We evaluated predictive performance of each risk score by area under the receiver operating characteristic curve (AUC)., Results: Predictive performance of all risk scores was moderate, with AUC (95% confidence interval) of 0.64 (0.60 to 0.67) among women aged 18-24, 0.68 (0.62 to 0.73) among those aged 25-35, and 0.61 (0.58 to 0.65) for the VOICE risk score applied to women aged 18-35; The AUC was similar in internal validation. Among women aged 18-24, HIV-1 incidence was high even at low risk scores, at 3.9 per 100 person-years (95% confidence interval: 3.2 to 4.7)., Conclusions: All risk scores were moderately predictive of HIV-1 acquisition, and age-specific risk scores performed only marginally better than the VOICE non-age-specific risk score. Approaches for targeted pre-exposure prophylaxis provision to women in South Africa may require more extensive data than are currently available to improve prediction.

Published
2020
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