BMC Infectious Diseases (Feb 2010)

Regional differences in rates of HIV-1 viral load monitoring in Canada: Insights and implications for antiretroviral care in high income countries

  • Cooper Curtis,
  • Klein Marina B,
  • Bayoumi Ahmed M,
  • Su DeSheng,
  • Loutfy Mona R,
  • Raboud Janet M,
  • Machouf Nima,
  • Rourke Sean,
  • Walmsley Sharon,
  • Rachlis Anita,
  • Harrigan P Richard,
  • Smieja Marek,
  • Tsoukas Christos,
  • Montaner Julio SG,
  • Hogg Robert S

DOI
https://doi.org/10.1186/1471-2334-10-40
Journal volume & issue
Vol. 10, no. 1
p. 40

Abstract

Read online

Abstract Background Viral load (VL) monitoring is an essential component of the care of HIV positive individuals. Rates of VL monitoring have been shown to vary by HIV risk factor and clinical characteristics. The objective of this study was to determine whether there are differences among regions in Canada in the rates of VL testing of HIV-positive individuals on combination antiretroviral therapy (cART), where the testing is available without financial barriers under the coverage of provincial health insurance programs. Methods The Canadian Observational Cohort (CANOC) is a collaboration of nine Canadian cohorts of HIV-positive individuals who initiated cART after January 1, 2000. The study included participants with at least one year of follow-up. Generalized Estimating Equation (GEE) regression models were used to determine the effect of geographic region on (1) the occurrence of an interval of 9 months or more between two consecutive recorded VL tests and (2) the number of days between VL tests, after adjusting for demographic and clinical covariates. Overall and regional annual rates of VL testing were also reported. Results 3,648 individuals were included in the analysis with a median follow-up of 42.9 months and a median of 15 VL tests. In multivariable GEE logistic regression models, gaps in VL testing >9 months were more likely in Quebec (Odds Ratio (OR) = 1.72, p Conclusions Significant variation in rates of VL testing and the probability of a significant gap in testing were related to geographic region, HIV risk factor, age, year of cART initiation, type of cART regimen, being in the first year of cART, AIDS-defining illness and whether or not the previous VL was below the limit of detection.