Balkus Jennifer E, Brown Elizabeth, Palanee Thesla, Nair Gonasagrie, Gafoor Zakir, Zhang Jingyang, Richardson Barbra A, Chirenje Zvavahera M, Marrazzo Jeanne M, Baeten Jared M
*Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA; Departments of †Global Health; ‡Epidemiology; §Biostatistics University of Washington, Seattle, WA; ‖Wits Reproductive Health and HIV Institute, University of the Witswatersrand, Johannesburg, South Africa; ¶Centre for AIDS Programme of Research in South Africa, University of KwaZulu Natal, Durban, South Africa; #HIV Prevention Research Unit, South African Medical Research Council, Durban, South Africa; **Department of Obstetrics and Gynecology, University of Zimbabwe, Harare, Zimbabwe; and ††Department of Medicine, University of Washington, Seattle, WA.
J Acquir Immune Defic Syndr. 2016 Jul 1;72(3):333-43. doi: 10.1097/QAI.0000000000000974.
To develop and validate an HIV risk assessment tool to predict HIV acquisition among African women.
Data were analyzed from 3 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 1 year. Performance of the score was assessed through internal and external validations.
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 to 0.74), indicating good predictive ability. Risk score performance was generally similar with internal cross-validation (AUC = 0.69; 95% CI: 0.66 to 0.73) and external validation in HPTN 035 (AUC = 0.70; 95% CI: 0.65 to 0.75) and FEM-PrEP (AUC = 0.58; 95% CI: 0.51 to 0.65).
A discrete set of characteristics that can be easily assessed in clinical and research settings was predictive of HIV acquisition over 1 year. The 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.
开发并验证一种用于预测非洲女性感染艾滋病毒情况的艾滋病毒风险评估工具。
对三项针对非洲女性的生物医学艾滋病毒预防干预随机试验(VOICE、HPTN 035和FEM-PrEP)的数据进行分析。
我们采用开发临床预测规则的标准方法来生成一个风险评分工具,以预测1年内的艾滋病毒感染情况。通过内部和外部验证来评估该评分的性能。
多变量建模得出的最终风险评分包括年龄、已婚/与伴侣同居、伴侣提供经济或物质支持、伴侣有其他性伴侣、饮酒情况、可治愈性传播感染的检测结果以及单纯疱疹病毒2血清学状态。每个因素的分值范围为0至2分,最高总分为11分。得分≥5分与每100人年艾滋病毒发病率>5例相关,且在仅64%的女性中识别出了91%的艾滋病毒感染病例。该评分预测能力的曲线下面积(AUC)为0.71(95%置信区间[CI]:0.68至0.74),表明具有良好的预测能力。风险评分在内部交叉验证(AUC = 0.69;95% CI:0.66至0.73)以及在HPTN 035(AUC = 0.70;95% CI:0.65至0.75)和FEM-PrEP(AUC = 0.58;95% CI:从0.51至0.65)中的外部验证中表现总体相似。
一组在临床和研究环境中易于评估的离散特征可预测1年内的艾滋病毒感染情况。使用经过验证的风险评分可提高艾滋病毒预防研究的招募效率,并为扩大对高危女性的艾滋病毒预防策略提供依据。