To the Editors:
The Centers for Disease Control and Prevention recommends routine human immunodeficiency virus (HIV) screening in health care settings.1 To evaluate HIV case finding, which is the process of identifying HIV-infected persons who have not been diagnosed, programs use 2 outcome measures–median CD4 count at diagnosis and proportion of late diagnoses.2–4 It is expected that an improvement in case finding would result in an increasing median CD4 count at diagnosis and a decreasing proportion of late diagnoses. However, despite continuing efforts, the 2 measures remain stable. A recent review article reported a minimal rise of 1.5 cells/mm3/year in the CD4 count at entry into care and a negligible change in the proportion of late diagnoses in 11 high-income countries from 1992 to 2011.5
When 2 commonly used indicators remain stable over a long period in so many countries despite continuing efforts to expand HIV testing, we should reexamine how well the indicators measure case finding. Here, we use hypothetical data to show the limitations of these 2 indicators. (Detailed methods are presented in the eAppendix, https://links.lww.com/EDE/A844).
As shown in the Table, the HIV case detection rate, stratified by duration of infection, is identical across the 3 communities. However, Community A, with an emerging epidemic, has the highest median CD4 count at diagnosis (418 cells/mm3), lowest proportion of late diagnoses (33.0%) and lowest crude case detection rate (15.8%); Community C, with a declining epidemic, has the lowest median CD4 count at diagnosis (331 cells/mm3), highest proportion of late diagnoses (39.7%) and highest crude case detection rate (16.6%). All 3 communities have an identical adjusted case detection rate (16.2%) and an identical case detection rate among new infections (25.0%).
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TABLE: Median CD4 Count at Diagnosis, Proportion of Late Diagnoses, and HIV Diagnosis Rates in 3 Hypothetical Communities
Using hypothetical data, we demonstrate the limitations of median CD4 count at diagnosis and proportion of late diagnoses. Despite an identical case detection rate stratified by duration of infection, an emerging epidemic would see a higher median CD4 count at diagnosis and a lower proportion of late diagnoses, and a declining epidemic would see a lower median CD4 count at diagnosis and a higher proportion of late diagnoses. Real-world data also show the same phenomenon, eg, Eastern European countries with emerging epidemics had a lower proportion of late diagnoses than Western European countries.6
Median CD4 count at diagnosis and proportion of late diagnoses are measuring the distribution of duration of infection among persons who are newly diagnosed, not case finding. Since a change in case finding usually happens across the board, the change would have little effect on the 2 measures. An improvement in case finding would increase not only the case detection rate among early infections but also late infections, leaving the distribution of duration of infection among the newly diagnosed unchanged.7
We propose 2 new measures for HIV case finding: adjusted case detection rate and case detection rate among new infections. These 2 case detection rates directly measure HIV case finding and are not affected by HIV incidence or distribution of duration of infection. The 2 new indicators cannot be directly measured, but must be estimated based on the distribution of duration of infection among the undiagnosed and newly diagnosed, which is not available using existing methods. With recent advances in estimating HIV incidence, we may soon be able to produce these 2 estimates, or at least the case detection rate among new infections–the less difficult of the 2 to estimate. An estimated population of undiagnosed HIV-infected individuals by duration of infection in the United States can be used as the standard population for jurisdictions to estimate their adjusted HIV case detection rates. Meanwhile, jurisdictions should be cautious in their reporting of median CD4 count at diagnosis and proportion of late diagnosis, as stable trends may be misinterpreted as failure.8
ACKNOWLEDGMENTS
This analysis was supported in part by a Cooperative Agreement with the Centers for Disease Control and Prevention, PS08-80202, #UC62/CCU223595. We thank Kent Sepkowitz, Blayne Cutler, Jay Varma, James Hadler, and an anonymous reviewer for their review and valuable comments.
Qiang Xia
Lucia V. Torian
Colin W. Shepard
The New York City
Department of Health and Mental Hygiene
Bureau of HIV Prevention and Control
HIV Epidemiology and
Field Services Program
Long Island City, NY
[email protected]
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http://news.bbc.co.uk/go/pr/fr/-/2/hi/health/4541029.stm. Accessed August 18 2014
