TY - JOUR
T1 - Can a clinical prediction tool guide HIV-testing decisions? Experience at a national hospital in Guatemala
AU - Anderson, Matt R.
AU - Samayoa, B.
AU - O'Sullivan, L. F.
AU - Fletcher, J.
AU - Arathoon, E.
N1 - Funding Information:
Dr Anderson's participation in this project was supported by a Fulbright Senior Scholars Fellowship. This work was supported in part by the Center for AIDS Research at the Albert Einstein College of Medicine and Montefiore Medical Center funded by the National Institutes of Health (NIH AR-51519). We gratefully acknowledge the help of the staff at the Clinica Familiar Luis Angel Garcia who conducted these surveys. We also thank Drs Peter Selwyn and Clyde Schechter for their review of a draft of this paper and helpful suggestions.
PY - 2009/1
Y1 - 2009/1
N2 - The USA and international recommendations no longer emphasize using risk factors to target groups for HIV-testing. Using a Guatemalan database of HIV tests, we developed a clinical prediction rule to guide decisions on HIV-testing. Prior to HIV-testing, data were collected on demographics, risk factors and prior testing. Based on a theoretical construct incorporating demographics, known HIV risk factors and symptoms, we developed a logistic regression model to predict HIV seropositivity. Between 2000 and 2005, 16,471 tests were performed, of which 19.8% were positive. The algorithm successfully predicted 1883 of 2489 HIV-positive tests (sensitivity 76%, likelihood ratio [LR]-positive 2.45) and 6282 of 9086 HIV-negative tests (specificity 69%, LR-negative 0.35). Although the model indices are robust, applying the model in a clinical setting would have little impact on improving selective testing practices. Our findings support current recommendations for universal HIV-testing, not selective testing based on risk factors. Before these recommendations can be adopted widely in Guatemala, treatment access needs to be assured and protections put in place for people diagnosed with HIV infection.
AB - The USA and international recommendations no longer emphasize using risk factors to target groups for HIV-testing. Using a Guatemalan database of HIV tests, we developed a clinical prediction rule to guide decisions on HIV-testing. Prior to HIV-testing, data were collected on demographics, risk factors and prior testing. Based on a theoretical construct incorporating demographics, known HIV risk factors and symptoms, we developed a logistic regression model to predict HIV seropositivity. Between 2000 and 2005, 16,471 tests were performed, of which 19.8% were positive. The algorithm successfully predicted 1883 of 2489 HIV-positive tests (sensitivity 76%, likelihood ratio [LR]-positive 2.45) and 6282 of 9086 HIV-negative tests (specificity 69%, LR-negative 0.35). Although the model indices are robust, applying the model in a clinical setting would have little impact on improving selective testing practices. Our findings support current recommendations for universal HIV-testing, not selective testing based on risk factors. Before these recommendations can be adopted widely in Guatemala, treatment access needs to be assured and protections put in place for people diagnosed with HIV infection.
KW - Adults
KW - Guatemala
KW - HIV infection
KW - Risk factors
UR - http://www.scopus.com/inward/record.url?scp=58249098762&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=58249098762&partnerID=8YFLogxK
U2 - 10.1258/ijsa.2008.008223
DO - 10.1258/ijsa.2008.008223
M3 - Article
C2 - 19103890
AN - SCOPUS:58249098762
SN - 0956-4624
VL - 20
SP - 30
EP - 34
JO - International Journal of STD and AIDS
JF - International Journal of STD and AIDS
IS - 1
ER -
