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Indices to Measure Risk of HIV Acquisition in Rakai, Uganda

INTRODUCTION: Targeting most-at-risk individuals with HIV preventive interventions is cost-effective. We developed gender-specific indices to measure risk of HIV among sexually active individuals in Rakai, Uganda. METHODS: We used multivariable Cox proportional hazards models to estimate time-to-HIV...

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Autores principales: Kagaayi, Joseph, Gray, Ronald H., Whalen, Christopher, Fu, Pingfu, Neuhauser, Duncan, McGrath, Janet W., Sewankambo, Nelson K., Serwadda, David, Kigozi, Godfrey, Nalugoda, Fred, Reynolds, Steven J., Wawer, Maria J., Singer, Mendel E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3976261/
https://www.ncbi.nlm.nih.gov/pubmed/24704778
http://dx.doi.org/10.1371/journal.pone.0092015
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author Kagaayi, Joseph
Gray, Ronald H.
Whalen, Christopher
Fu, Pingfu
Neuhauser, Duncan
McGrath, Janet W.
Sewankambo, Nelson K.
Serwadda, David
Kigozi, Godfrey
Nalugoda, Fred
Reynolds, Steven J.
Wawer, Maria J.
Singer, Mendel E.
author_facet Kagaayi, Joseph
Gray, Ronald H.
Whalen, Christopher
Fu, Pingfu
Neuhauser, Duncan
McGrath, Janet W.
Sewankambo, Nelson K.
Serwadda, David
Kigozi, Godfrey
Nalugoda, Fred
Reynolds, Steven J.
Wawer, Maria J.
Singer, Mendel E.
author_sort Kagaayi, Joseph
collection PubMed
description INTRODUCTION: Targeting most-at-risk individuals with HIV preventive interventions is cost-effective. We developed gender-specific indices to measure risk of HIV among sexually active individuals in Rakai, Uganda. METHODS: We used multivariable Cox proportional hazards models to estimate time-to-HIV infection associated with candidate predictors. Reduced models were determined using backward selection procedures with Akaike's information criterion (AIC) as the stopping rule. Model discrimination was determined using Harrell's concordance index (c index). Model calibration was determined graphically. Nomograms were used to present the final prediction models. RESULTS: We used samples of 7,497 women and 5,783 men. 342 new infections occurred among females (incidence 1.11/100 person years,) and 225 among the males (incidence 1.00/100 person years). The final model for men included age, education, circumcision status, number of sexual partners, genital ulcer disease symptoms, alcohol use before sex, partner in high risk employment, community type, being unaware of a partner's HIV status and community HIV prevalence. The Model's optimism-corrected c index was 69.1 percent (95% CI = 0.66, 0.73). The final women's model included age, marital status, education, number of sex partners, new sex partner, alcohol consumption by self or partner before sex, concurrent sexual partners, being employed in a high-risk occupation, having genital ulcer disease symptoms, community HIV prevalence, and perceiving oneself or partner to be exposed to HIV. The models optimism-corrected c index was 0.67 (95% CI = 0.64, 0.70). Both models were well calibrated. CONCLUSION: These indices were discriminative and well calibrated. This provides proof-of-concept that population-based HIV risk indices can be developed. Further research to validate these indices for other populations is needed.
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spelling pubmed-39762612014-04-08 Indices to Measure Risk of HIV Acquisition in Rakai, Uganda Kagaayi, Joseph Gray, Ronald H. Whalen, Christopher Fu, Pingfu Neuhauser, Duncan McGrath, Janet W. Sewankambo, Nelson K. Serwadda, David Kigozi, Godfrey Nalugoda, Fred Reynolds, Steven J. Wawer, Maria J. Singer, Mendel E. PLoS One Research Article INTRODUCTION: Targeting most-at-risk individuals with HIV preventive interventions is cost-effective. We developed gender-specific indices to measure risk of HIV among sexually active individuals in Rakai, Uganda. METHODS: We used multivariable Cox proportional hazards models to estimate time-to-HIV infection associated with candidate predictors. Reduced models were determined using backward selection procedures with Akaike's information criterion (AIC) as the stopping rule. Model discrimination was determined using Harrell's concordance index (c index). Model calibration was determined graphically. Nomograms were used to present the final prediction models. RESULTS: We used samples of 7,497 women and 5,783 men. 342 new infections occurred among females (incidence 1.11/100 person years,) and 225 among the males (incidence 1.00/100 person years). The final model for men included age, education, circumcision status, number of sexual partners, genital ulcer disease symptoms, alcohol use before sex, partner in high risk employment, community type, being unaware of a partner's HIV status and community HIV prevalence. The Model's optimism-corrected c index was 69.1 percent (95% CI = 0.66, 0.73). The final women's model included age, marital status, education, number of sex partners, new sex partner, alcohol consumption by self or partner before sex, concurrent sexual partners, being employed in a high-risk occupation, having genital ulcer disease symptoms, community HIV prevalence, and perceiving oneself or partner to be exposed to HIV. The models optimism-corrected c index was 0.67 (95% CI = 0.64, 0.70). Both models were well calibrated. CONCLUSION: These indices were discriminative and well calibrated. This provides proof-of-concept that population-based HIV risk indices can be developed. Further research to validate these indices for other populations is needed. Public Library of Science 2014-04-04 /pmc/articles/PMC3976261/ /pubmed/24704778 http://dx.doi.org/10.1371/journal.pone.0092015 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
spellingShingle Research Article
Kagaayi, Joseph
Gray, Ronald H.
Whalen, Christopher
Fu, Pingfu
Neuhauser, Duncan
McGrath, Janet W.
Sewankambo, Nelson K.
Serwadda, David
Kigozi, Godfrey
Nalugoda, Fred
Reynolds, Steven J.
Wawer, Maria J.
Singer, Mendel E.
Indices to Measure Risk of HIV Acquisition in Rakai, Uganda
title Indices to Measure Risk of HIV Acquisition in Rakai, Uganda
title_full Indices to Measure Risk of HIV Acquisition in Rakai, Uganda
title_fullStr Indices to Measure Risk of HIV Acquisition in Rakai, Uganda
title_full_unstemmed Indices to Measure Risk of HIV Acquisition in Rakai, Uganda
title_short Indices to Measure Risk of HIV Acquisition in Rakai, Uganda
title_sort indices to measure risk of hiv acquisition in rakai, uganda
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3976261/
https://www.ncbi.nlm.nih.gov/pubmed/24704778
http://dx.doi.org/10.1371/journal.pone.0092015
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