Background: 

Clinicians and health departments would ideally undertake targeted efforts to promote HIV pre-exposure prophylaxis (PrEP) and frequent HIV testing using data-based criteria to identify populations at elevated risk for HIV. We developed an HIV risk prediction score for men who have sex with men (MSM) to identify individuals at substantial risk for HIV acquisition.

Methods: 

We created a retrospective cohort of MSM who tested HIV-negative at the sexually transmitted disease clinic in Seattle, WA, from 2001 to 2015, and identified seroconversions using HIV surveillance data. We split the cohort randomly 2:1 into derivation and validation data sets, and used Cox proportional hazards to estimate the hazard of acquiring HIV associated with behavioral and clinical predictors, and the Akaike information criterion to determine which variables to retain in our model.

Results: 

Among 16,448 MSM, 640 seroconverted over a 14.3-year follow-up period. The best prediction model included 13 variables and had an area under the receiver operating characteristic curve of 0.73 (95% confidence interval: 0.71 to 0.76), 76% sensitivity, and 63% specificity at a score cutoff ≥11. A simplified model restricted to 2011–2015 included 4 predictors [methamphetamine use, condomless receptive anal intercourse (CRAI), ≥10 partners, and current diagnosis or self-reported gonorrhea/syphilis in the past year]. This model, the Seattle PrEP Score, had an area under the receiver operating characteristic curve of 0.69 (95% confidence interval: 0.64 to 0.73), 62% sensitivity, and 70% specificity. One-year incidence was 0.5% for a score of 0, 0.7% for a score of 1, and 2.1% for scores ≥2.

Conclusions: 

The Seattle PrEP Score was predictive of HIV acquisition and could help clinicians and public health agencies identify MSM who could benefit from PrEP and frequent HIV testing.

中文翻译：

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同性恋者，双性恋者和其他与男性发生性关系以告知性病门诊患者开始PREP的男性中HIV风险预测分数的推导和验证

背景： 

临床医生和卫生部门将理想地进行有针对性的努力，以促进艾滋病毒暴露前预防（PrEP）并使用基于数据的标准进行频繁的艾滋病毒检测，以鉴定出艾滋病毒风险较高的人群。我们为与男性发生性关系的男性（MSM）建立了HIV 风险预测分数，以识别有大量HIV感染风险的个体。

方法： 

我们创建了一个回顾性MSM队列，从2001年至2015年在华盛顿州西雅图市的性传播疾病诊所对HIV阴性进行了检测，并使用HIV监测数据确定了血清转化。我们将队列以2：1的比例随机分为派生和验证数据集，并使用Cox比例风险评估与行为和临床预测因素相关的HIV感染的风险，并使用Akaike信息标准来确定在模型中保留哪些变量。

结果： 

在16.448个MSM中，在14.3年的随访期内进行了640次血清转换。最佳预测模型包括13个变量，并且在接收器工作特性曲线下的面积为0.73（95％的置信区间：0.71至0.76），76％的灵敏度和63％的专一性，且分值≥11。限于2011-2015年的简化模型包括4个预测因子[使用甲基苯丙胺，无避孕套的接受肛门性交（CRAI），≥10个伴侣，以及过去一年的当前诊断或自我报告的淋病/梅毒]。该模型，即西雅图PrEP得分，在接收器工作特性曲线下的面积为0.69（95％置信区间：0.64至0.73），62％的敏感性和70％的特异性。一年的发病率 得分为0时为0.5％，得分为1时为0.7％，而得分≥2的得分为2.1％。

结论： 

Seattle PrEP得分可预测感染艾滋病毒的情况，可帮助临床医生和公共卫生机构确定可从PrEP和频繁的HIV检测中受益的MSM。