TY - JOUR
T1 - HIV incidence determination in the united states
T2 - A multiassay approach
AU - Laeyendecker, Oliver
AU - Brookmeyer, Ron
AU - Cousins, Matthew M.
AU - Mullis, Caroline E.
AU - Konikoff, Jacob
AU - Donnell, Deborah
AU - Celum, Connie
AU - Buchbinder, Susan P.
AU - Seage, George R.
AU - Kirk, Gregory D.
AU - Mehta, Shruti H.
AU - Astemborski, Jacquie
AU - Jacobson, Lisa P.
AU - Margolick, Joseph B.
AU - Brown, Joelle
AU - Quinn, Thomas C.
AU - Eshleman, Susan H.
N1 - Funding Information:
Financial support. This work was supported by the HIV Prevention Trials Network, which is sponsored by the National Institute of Allergy and Infectious Diseases (NIAID), the National Institute of Child Health and Human Development, the National Institute on Drug Abuse (NIDA), the National Institute of Mental Health, and the Office of AIDS Research, NIH, DHHS (grants U01-AI46745, U01-AI48054, and UM1-AI068613); the NIAID(grant R01-AI095068 to S. H. E. and R. B.); and the Division of Intramural Research, NIAID. HIVNET 001 was funded by the HIVNET and sponsored by the NIAID (grants N01-AI35176, N01-AI-45200, and AI-45202). The ALIVE Study is funded by the NIDA (grants R01-DA-04334 and R01-DA12568). The MACS is funded by the NIAID, with additional supplemental funding from the National Cancer Institute and the National Heart, Lung, and Blood Institute (grants U01-AI35042, U01-AI35043, U01-AI35039, U01-AI35040, U01-AI35041, and UL1-RR025005). Potential conflicts of interest. All authors: No reported conflicts.
PY - 2013
Y1 - 2013
N2 - Background. Accurate testing algorithms are needed for estimating human immunodeficiency virus (HIV) incidence from cross-sectional surveys.Methods. We developed a multiassay algorithm (MAA) for HIV incidence that includes the BED capture enzyme immunoassay (BED-CEIA), an antibody avidity assay, HIV load, and CD4+ T-cell count. We analyzed 1782 samples from 709 individuals in the United States who had a known duration of HIV infection (range, 0 to >8 years). Logistic regression with cubic splines was used to compare the performance of the MAA to the BED-CEIA and to determine the window period of the MAA. We compared the annual incidence estimated with the MAA to the annual incidence based on HIV seroconversion in a longitudinal cohort.Results. The MAA had a window period of 141 days (95% confidence interval [CI], 94-150) and a very low false-recent misclassification rate (only 0.4% of 1474 samples from subjects infected for >1 year were misclassified as indicative of recent infection). In a cohort study, annual incidence based on HIV seroconversion was 1.04% (95% CI,. 70%-1.55%). The incidence estimate obtained using the MAA was essentially identical: 0.97% (95% CI,. 51%-1.71%).Conclusions. The MAA is as sensitive for detecting recent HIV infection as the BED-CEIA and has a very low rate of false-recent misclassification. It provides a powerful tool for cross-sectional HIV incidence determination.
AB - Background. Accurate testing algorithms are needed for estimating human immunodeficiency virus (HIV) incidence from cross-sectional surveys.Methods. We developed a multiassay algorithm (MAA) for HIV incidence that includes the BED capture enzyme immunoassay (BED-CEIA), an antibody avidity assay, HIV load, and CD4+ T-cell count. We analyzed 1782 samples from 709 individuals in the United States who had a known duration of HIV infection (range, 0 to >8 years). Logistic regression with cubic splines was used to compare the performance of the MAA to the BED-CEIA and to determine the window period of the MAA. We compared the annual incidence estimated with the MAA to the annual incidence based on HIV seroconversion in a longitudinal cohort.Results. The MAA had a window period of 141 days (95% confidence interval [CI], 94-150) and a very low false-recent misclassification rate (only 0.4% of 1474 samples from subjects infected for >1 year were misclassified as indicative of recent infection). In a cohort study, annual incidence based on HIV seroconversion was 1.04% (95% CI,. 70%-1.55%). The incidence estimate obtained using the MAA was essentially identical: 0.97% (95% CI,. 51%-1.71%).Conclusions. The MAA is as sensitive for detecting recent HIV infection as the BED-CEIA and has a very low rate of false-recent misclassification. It provides a powerful tool for cross-sectional HIV incidence determination.
KW - HIV
KW - United States
KW - epidemiology
KW - incidence testing
UR - http://www.scopus.com/inward/record.url?scp=84871786547&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84871786547&partnerID=8YFLogxK
U2 - 10.1093/infdis/jis659
DO - 10.1093/infdis/jis659
M3 - Article
C2 - 23129760
AN - SCOPUS:84871786547
SN - 0022-1899
VL - 207
SP - 232
EP - 239
JO - Journal of Infectious Diseases
JF - Journal of Infectious Diseases
IS - 2
ER -