INTRODUCTION: Treatment options and therapeutic guidelines have evolved substantially since highly active antiretroviral treatment (HAART) became the standard of HIV care in 1996. We conducted the present population-based analysis to characterize the determinants of direct costs of HAART over time in British Columbia, Canada. METHODS: We considered individuals ever receiving HAART in British Columbia from 1996 to 2011. Linear mixed-effects regression models were constructed to determine the effects of demographic indicators, clinical stage, and treatment characteristics on quarterly costs of HAART (in 2010$CDN) among individuals initiating in different temporal periods. The least-square mean values were estimated by CD4 category and over time for each temporal cohort. RESULTS: Longitudinal data on HAART recipients (N = 9601, 17.6% female, mean age at initiation = 40.5) were analyzed. Multiple regression analyses identified demographics, treatment adherence, and pharmacological class to be independently associated with quarterly HAART costs. Higher CD4 cell counts were associated with modestly lower costs among pre-HAART initiators [least-square means (95% confidence interval), CD4 > 500: 4674 (4632-4716); CD4: 350-499: 4765 (4721-4809) CD4: 200-349: 4826 (4780-4871); CD4 <200: 4809 (4759-4859)]; however these differences were not significant among post-2003 HAART initiators. Population-level mean costs increased through 2006 and stabilized post-2003 HAART initiators incurred quarterly costs up to 23% lower than pre-2000 HAART initiators in 2010. CONCLUSIONS: Our results highlight the magnitude of the temporal changes in HAART costs, and disparities between recent and pre-HAART initiators. This methodology can improve the precision of economic modeling efforts by using detailed cost functions for annual, population-level medication costs according to the distribution of clients by clinical stage and era of treatment initiation.
INTRODUCTION: Treatment options and therapeutic guidelines have evolved substantially since highly active antiretroviral treatment (HAART) became the standard of HIV care in 1996. We conducted the present population-based analysis to characterize the determinants of direct costs of HAART over time in British Columbia, Canada. METHODS: We considered individuals ever receiving HAART in British Columbia from 1996 to 2011. Linear mixed-effects regression models were constructed to determine the effects of demographic indicators, clinical stage, and treatment characteristics on quarterly costs of HAART (in 2010$CDN) among individuals initiating in different temporal periods. The least-square mean values were estimated by CD4 category and over time for each temporal cohort. RESULTS: Longitudinal data on HAART recipients (N = 9601, 17.6% female, mean age at initiation = 40.5) were analyzed. Multiple regression analyses identified demographics, treatment adherence, and pharmacological class to be independently associated with quarterly HAART costs. Higher CD4 cell counts were associated with modestly lower costs among pre-HAART initiators [least-square means (95% confidence interval), CD4 > 500: 4674 (4632-4716); CD4: 350-499: 4765 (4721-4809) CD4: 200-349: 4826 (4780-4871); CD4 <200: 4809 (4759-4859)]; however these differences were not significant among post-2003 HAART initiators. Population-level mean costs increased through 2006 and stabilized post-2003 HAART initiators incurred quarterly costs up to 23% lower than pre-2000 HAART initiators in 2010. CONCLUSIONS: Our results highlight the magnitude of the temporal changes in HAART costs, and disparities between recent and pre-HAART initiators. This methodology can improve the precision of economic modeling efforts by using detailed cost functions for annual, population-level medication costs according to the distribution of clients by clinical stage and era of treatment initiation.
Authors: C C Carpenter; M A Fischl; S M Hammer; M S Hirsch; D M Jacobsen; D A Katzenstein; J S Montaner; D D Richman; M S Sáag; R T Schooley; M A Thompson; S Vella; P G Yeni; P A Volberding Journal: JAMA Date: 1996-07-10 Impact factor: 56.272
Authors: C C Carpenter; D A Cooper; M A Fischl; J M Gatell; B G Gazzard; S M Hammer; M S Hirsch; D M Jacobsen; D A Katzenstein; J S Montaner; D D Richman; M S Saag; M Schechter; R T Schooley; M A Thompson; S Vella; P G Yeni; P A Volberding Journal: JAMA Date: 2000-01-19 Impact factor: 56.272
Authors: S A Bozzette; G Joyce; D F McCaffrey; A A Leibowitz; S C Morton; S H Berry; A Rastegar; D Timberlake; M F Shapiro; D P Goldman Journal: N Engl J Med Date: 2001-03-15 Impact factor: 91.245
Authors: Patrick G Yeni; Scott M Hammer; Martin S Hirsch; Michael S Saag; Mauro Schechter; Charles C J Carpenter; Margaret A Fischl; Jose M Gatell; Brian G Gazzard; Donna M Jacobsen; David A Katzenstein; Julio S G Montaner; Douglas D Richman; Robert T Schooley; Melanie A Thompson; Stefano Vella; Paul A Volberding Journal: JAMA Date: 2004-07-14 Impact factor: 56.272
Authors: Patrick G Yeni; Scott M Hammer; Charles C J Carpenter; David A Cooper; Margaret A Fischl; Jose M Gatell; Brian G Gazzard; Martin S Hirsch; Donna M Jacobsen; David A Katzenstein; Julio S G Montaner; Douglas D Richman; Michael S Saag; Mauro Schechter; Robert T Schooley; Melanie A Thompson; Stefano Vella; Paul A Volberding Journal: JAMA Date: 2002-07-10 Impact factor: 56.272
Authors: W A O'Brien; P M Hartigan; D Martin; J Esinhart; A Hill; S Benoit; M Rubin; M S Simberkoff; J D Hamilton Journal: N Engl J Med Date: 1996-02-15 Impact factor: 91.245
Authors: Bohdan Nosyk; Jeong E Min; Emanuel Krebs; Xiao Zang; Miranda Compton; Reka Gustafson; Rolando Barrios; Julio S G Montaner Journal: Clin Infect Dis Date: 2018-02-10 Impact factor: 9.079
Authors: Benjamin Enns; Jeong Eun Min; Dimitra Panagiotoglou; Julio S G Montaner; Bohdan Nosyk Journal: BMC Health Serv Res Date: 2019-09-03 Impact factor: 2.655