Monday, March 7, 2016

An Empiric HIV Risk Scoring Tool to Predict HIV-1 Acquisition in African Women

To develop and validate an HIV risk assessment tool to predict HIV acquisition among African women.

Data were analyzed from three randomized trials of biomedical HIV prevention interventions among African women (VOICE, HPTN 035 and FEM-PrEP).

We implemented standard methods for the development of clinical prediction rules to generate a risk-scoring tool to predict HIV acquisition over the course of one year. Performance of the score was assessed through internal and external validation.

The final risk score resulting from multivariable modeling included age, married/living with a partner, partner provides financial or material support, partner has other partners, alcohol use, detection of a curable sexually transmitted infection, and herpes simplex virus-2 serostatus. Point values for each factor ranged from 0 to 2, with a maximum possible total score of 11. Scores ≥5 were associated with HIV incidence >5 per 100 person-years and identified 91% of incident HIV infections from among only 64% of women. The area under the curve (AUC) for predictive ability of the score was 0.71 (95% confidence interval [CI] 0.68, 0.74), indicating good predictive ability. Risk score performance was generally similar with internal cross-validation (AUC=0.69; 95% CI 0.66, 0.73), and external validation in HPTN 035 (AUC=0.70; 95% CI 0.65, 0.75) and FEM-PrEP (AUC=0.58; 95% CI 0.51, 0.65).

A discrete set of characteristics that can be easily assessed in clinical and research settings were predictive of HIV acquisition over one year. Use of a validated risk score could improve efficiency of recruitment into HIV prevention research and inform scale-up of HIV prevention strategies in women at highest risk.

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  • Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center; Seattle, WA, USA 
  • 2 Department of Global Health, University of Washington; Seattle, WA, USA 
  • 3 Department of Epidemiology, University of Washington; Seattle, WA, USA 
  • 4 Department of Biostatistics, University of Washington; Seattle, WA, USA 
  • 5 Department of Medicine, University of Washington; Seattle, WA, USA 
  • 6 Wits Reproductive Health and HIV Institute, University of the Witswatersrand; Johannesburg, South Africa 
  • 7 Centre for AIDS Programme of Research in South Africa, University of KwaZulu Natal; Durban, South Africa 
  • 8 HIV Prevention Research Unit, South African Medical Research Council; Durban, South Africa 
  • 9 Department of Obstetrics and Gynecology, University of Zimbabwe; Harare, Zimbabwe.
  •  2016 Feb 25 

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