Can a clinical prediction tool guide HIV-testing decisions? Experience at a national hospital in Guatemala

Matthew R. Anderson, B. Samayoa, L. F. O'Sullivan, J. Fletcher, E. Arathoon

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Pages (from-to)30-34
Number of pages5
JournalInternational Journal of STD and AIDS
Volume20
Issue number1
DOIs
StatePublished - Jan 2009

Fingerprint

Guatemala
HIV
Logistic Models
Demography
HIV Seropositivity
Decision Support Techniques
HIV Infections
Databases

Keywords

  • Adults
  • Guatemala
  • HIV infection
  • Risk factors

ASJC Scopus subject areas

  • Dermatology
  • Public Health, Environmental and Occupational Health
  • Pharmacology (medical)
  • Infectious Diseases

Cite this

Can a clinical prediction tool guide HIV-testing decisions? Experience at a national hospital in Guatemala. / Anderson, Matthew R.; Samayoa, B.; O'Sullivan, L. F.; Fletcher, J.; Arathoon, E.

In: International Journal of STD and AIDS, Vol. 20, No. 1, 01.2009, p. 30-34.

Research output: Contribution to journalArticle

@article{0d1d34dca63342f9b28b5aca04bf05d7,
title = "Can a clinical prediction tool guide HIV-testing decisions? Experience at a national hospital in Guatemala",
abstract = "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.",
keywords = "Adults, Guatemala, HIV infection, Risk factors",
author = "Anderson, {Matthew R.} and B. Samayoa and O'Sullivan, {L. F.} and J. Fletcher and E. Arathoon",
year = "2009",
month = "1",
doi = "10.1258/ijsa.2008.008223",
language = "English (US)",
volume = "20",
pages = "30--34",
journal = "International Journal of STD and AIDS",
issn = "0956-4624",
publisher = "SAGE Publications Ltd",
number = "1",

}

TY - JOUR

T1 - Can a clinical prediction tool guide HIV-testing decisions? Experience at a national hospital in Guatemala

AU - Anderson, Matthew R.

AU - Samayoa, B.

AU - O'Sullivan, L. F.

AU - Fletcher, J.

AU - Arathoon, E.

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

VL - 20

SP - 30

EP - 34

JO - International Journal of STD and AIDS

JF - International Journal of STD and AIDS

SN - 0956-4624

IS - 1

ER -