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RISK- AND SYMPTOM-BASED SCREENING IMPROVES IDENTIFICATION OF ACUTE HIV INFECTION
Maartje Dijkstra1, Godelieve J. de Bree2, Ineke Stolte1, Udi Davidovich1, Eduard Sanders3, Maria Prins1, Maarten F. Schim van der Loeff1
1Pub Hlth Service Amsterdam, Netherlands,2Academic Med Cntr, Amsterdam, Netherlands,3Kenya Med Rsr Inst, Kilifi, Kenya
Identifying patients with acute HIV infection (AHI) is important; (1) patients with AHI benefit from immediate start of antiretroviral therapy (ART), (2) early treatment of AHI could have a significant impact on the ongoing HIV epidemic, (3) patients who start ART during AHI may offer insight into the potential for post treatment HIV control. The recent development of point-of-care HIV RNA tests has made prompt diagnosis of AHI possible at time of care seeking. However, these tests are expensive and guidelines on whom to test for AHI are lacking.
A case definition for possible AHI based on literature and expert opinion – including 14 symptoms associated with AHI – was evaluated using data from the Amsterdam Cohort Studies (ACS), the Netherlands. We optimized the risk score by constructing 2 multivariable logistic regression models: one including only symptoms and one combining symptoms with known risk factors for HIV seroconversion, using generalized estimating equations. Points were assigned to each of the symptoms and risk factors equal to the beta coefficients. Several risk scores were generated and the optimal risk score was validated using data of the Multicenter AIDS Cohort Study (MACS), USA.
Using data from 1,562 MSM with 17,271 seronegative and 175 seroconversion visits in the ACS, the area under the curve (AUC) for the case definition was 0.70. Sensitivity was 45.7% (95%CI 38.2-53.4) and specificity 89.5% (95%CI 89.1-90.0). The optimal risk score included 4 symptoms (oral thrush, fever, lymphadenopathy, weight loss) and 3 risk factors (self-reported gonorrhea, receptive condomless anal intercourse, more than 5 sexual partners, all in the preceding 6 months) and yielded an AUC of 0.82. Sensitivity was 76.3% (95%CI 68.2-83.2) and specificity 76.3% (95%CI 75.6-77.0). Validation in the MACS resulted in an AUC of 0.78, sensitivity of 56.0% (95%CI 48.5-63.4) and specificity of 88.5% (95%CI 0.74-0.82). Using this risk score as a screening tool, 11.7% (MACS) to 24.2% of men (ACS) would be indicated for AHI testing.
A risk score for AHI including risk factors and symptoms performed better than a risk score including only symptoms. The optimal risk score had good performance in the ACS and performed comparable (but lower sensitivity) in the validation study. Screening for AHI with our optimal risk score would increase the efficiency of HIV RNA testing and potentially enhance early diagnosis and immediate treatment.