Predicting diabetes risk among HIV-positive and HIV-negative women

• Type of Material: Article
• Authors: Karla Galaviz Arredondo, Emory University; Michael F. Schneider, Johns Hopkins Bloomberg School of Public Health; Phyllis C. Tien, University of California San Francisco; Christina Mehta, Emory University; Ighovwerha Ofotokun, Emory University; Jonathan Colasanti, Emory University; Vincent Marconi, Emory University; Kartika Palar, University of California San Francisco; Gina Wingood, Emory University; Adaora A. Adimora, University of North Carolina Chapel Hill; Maria Alcaide, University of Miami; Mardge H. Cohen, Stroger Hospital; Deborah Gustafson, Suny Downstate Medical Center; Roksana Karim, University of Southern California; Deborah Konkle-Parker, University of Mississippi; Daniel Merenstein, Georgetown University; Anjali Sharma, Albert Einstein College of Medicine; Mohammed Ali, Emory University
• Language: English
• Date: 2018-11-28
• Publisher: LIPPINCOTT WILLIAMS & WILKINS
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2018 Wolters Kluwer Health, Inc. All rights reserved.
• Final Published Version (URL): http://dx.doi.org/10.1097/QAD.0000000000002017
• Title of Journal or Parent Work: AIDS
• Volume: 32
• Issue: 18
• Start Page: 2767
• End Page: 2775
• Grant/Funding Information: WIHS data collection is also supported by UL1-TR000004 (UCSF CTSA), UL1-TR000454 (Atlanta CTSA), and P30-AI-050410 (UNC CFAR).; The study was funded by the National Institute of Allergy and Infectious Diseases through the WIHS (U01AI103408-04). M.K.A. and KIG were partially supported by the Georgia Center for Diabetes Translation Research (P30DK111024).
• Keywords: DISEASES; Science & Technology; ASSOCIATION; PREVALENCE; Infectious Diseases; screening; Virology; women's healthcare; MELLITUS; Life Sciences & Biomedicine; INFECTION; epidemiology; VALIDATION; HIV; Immunology; risk analysis; SCORE
• Research Categories: Biology, Virology; Health Sciences, Public Health; Health Sciences, Epidemiology

Abstract

Objective:To assess the performance of an adapted American Diabetes Association (ADA) risk score and the concise Finnish Diabetes Risk Score (FINRISC) for predicting type 2 diabetes development in women with and at risk of HIV infection.Design:Longitudinal analysis of the Women's Interagency HIV Study.Methods:The women's Interagency HIV Study is an ongoing prospective cohort study of women with and at risk for HIV infection. Women without prevalent diabetes and 3-year data on fasting blood glucose, hemoglobin A1c, self-reported diabetes medication use, and self-reported diabetes were included. ADA and FINRISC scores were computed at baseline and their ability to predict diabetes development within 3 years was assessed [sensitivity, specificity and area under the receiver operating characteristics (AUROC) curve].Results:A total of 1111 HIV-positive (median age 41, 60% African American) and 454 HIV-negative women (median age 38, 63% African-American) were included. ADA sensitivity did not differ between HIV-positive (77%) and HIV-negative women (81%), while specificity was better in HIV-negative women (42 vs. 49%, P = 0.006). Overall ADA discrimination was suboptimal in both HIV-positive [AUROC = 0.64 (95% CI: 0.58, 0.70)] and HIV-negative women [AUROC = 0.67 (95% CI: 0.57, 0.77)]. FINRISC sensitivity and specificity did not differ between HIV-positive (72 and 49%, respectively) and HIV-negative women (86 and 52%, respectively). Overall FINRISC discrimination was suboptimal in HIV-positive [AUROC = 0.68 (95% CI: 0.62, 0.75)] and HIV-negative women [AUROC = 0.78 (95% CI: 0.66, 0.90)].Conclusion:Model performance was suboptimal in women with and at risk of HIV, while greater misclassification was generally observed among HIV-positive women. HIV-specific risk factors known to contribute to diabetes risk should be explored in these models.