Expanding the Finnish Diabetes Risk Score for Predicting Diabetes Incidence in People Living with HIV

AIDS Res Hum Retroviruses. 2021 May;37(5):373-379. doi: 10.1089/AID.2020.0247. Epub 2021 Apr 12.

Abstract

This study investigated whether the predictive ability of the Finnish Diabetes Risk Score (FINDRISC) can be improved among people with HIV by adding a marker of insulin resistance. In this longitudinal analysis of the Multicenter AIDS Cohort Study and the Women's Interagency HIV Study, HIV-positive and HIV-negative participants without prevalent diabetes were included. FINDRISC score and the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) were calculated at baseline. Cox proportional hazards models were used to examine associations between baseline risk scores and time to incident diabetes (first self-report of diabetes medication use). Model discrimination (Uno's c-statistic) and calibration (observed vs. cumulative probability of diabetes) were assessed for FINDRISC, HOMA-IR, and combined FINDRISC and HOMA-IR. Overall, 2,527 men (1,299 HIV-positive and 1,228 HIV-negative, median age = 44) and 2,446 women (1,841 HIV-positive and 605 HIV-negative, median age = 41) were included. Over 47,040 person-years of follow-up, diabetes incidence rates per 1,000 person-years were 9.5 in HIV-positive men, 7.1 in HIV-negative men, 14.5 in HIV-positive women, and 15.1 in HIV-negative women. FINDRISC discrimination (HIV-positive men c = 0.64 [0.55, 0.74], HIV-negative men c = 0.74 [0.68, 0.79], HIV-positive women c = 0.68 [0.64, 0.71], and HIV-negative women c = 0.73 [0.66, 0.79]) was significantly better than that of HOMA-IR. FINDRISC was better calibrated than HOMA-IR in each of the four groups. Adding HOMA-IR did not improve FINDRISC discrimination/calibration. Diabetes risk prediction with FINDRISC was suboptimal in men and women with HIV, and its performance was not improved with addition of HOMA-IR. The optimal method for identifying people living with HIV at-risk for diabetes is yet to be identified.

Keywords: HIV; dysglycemia; insulin resistance; risk prediction.

Publication types

  • Multicenter Study
  • Research Support, N.I.H., Extramural

MeSH terms

  • Cohort Studies
  • Diabetes Mellitus, Type 2*
  • Female
  • Finland / epidemiology
  • HIV Infections* / complications
  • HIV Infections* / epidemiology
  • Humans
  • Incidence
  • Insulin Resistance*
  • Male
  • Risk Factors