Socioeconomic Status, Access to Triple Therapy, and Survival from HIV-disease Since 1996 Evan Wood, Julio S.G. Montaner, Keith Chan, Martin T. Schechter, Michael V. O’Shaughnessy, Robert S. Hogg. British Columbia Centre for Excellence in HIV/AIDS and the University of British Columbia, Vancouver, Canada Methods For the primary analysis we evaluated all 1408 individual who initiated double or triple therapy over the period August 1, 1996 to December 31, 1999, and who were followed until March 31, 2000. A sub-analysis of the 1031 participants who initiated triple therapy was also conducted. Cumulative mortality rates were estimated using Kaplan-Meier methods, and cox-proportional hazard regression was used to model the simultaneous effect of prognostic variables on survival. Conclusion In a universal healthcare system that provides antiretrovirals and AIDS care free of charge, we found that lower socio-economic status was strongly and independently associated with mortality in our cohort. When we investigated possible explanations for this association, we found that persons of lower socio-economic status were less likely to receive HAART. Our findings highlight the need for monitoring of therapeutic guidelines to insure equitable access, as treatment strategies are updated. Introduction Prior to the advent of Highly Active Antiretroviral Therapy (HAART), we identified a survival gradient by socioeconomic status among HIV-1-infected gay men (1, 2). This finding was particularly interesting due to the fact that that the data were derived in a universal healthcare setting, and could not be explained by differences in traditional prognostic markers such as age or CD4 cell count, or differential use of zidovudine or Pneumocystis carinii pneumonia (PCP) prophylaxis. Similarly, other studies conducted prior to the advent of HAART identified gender and racial gradients in survival from HIV disease, as well a disparities in survival between risk groups (3, 4), although in some studies the social disparities in survival could be attributed to inequitable access to zidovudine or PCP prophylaxis (5, 6). In a more recent study it was proposed that previously reported socioeconomic disparities in survival from HIV disease, that remained after adjustment for zidovudine use and PCP prophylaxis, were likely due to other healthcare-related factors, such as differences in the use of medical care (7). It is presently unknown if socioeconomic or healthcare-related disparities in HIV-related mortality have persisted among persons who are accessing HAART. Therefore, the present study was conducted to determine if social or healthcare-related gradients in HIV-1-related mortality have developed since the advent and widespread provision of HAART among participants in a province-wide treatment program that operates within a universal healthcare setting. Results Figure 1a), shows the Kaplan Meier plots of time to death in the 2 socio-economic strata for the entire cohort. As shown here, the product limit estimate (SE) of the cumulative mortality rate at 12 months for the high socio- economic group was 2.1% (0.4%). Conversely, the product limit estimate (SE) of the cumulative mortality rate at 12 months for the low socio-economic group was 5.7% (1.5%). Statistically significant differences in survival were noted between those the high and low socio-economic strata (log rank p <0.05). Figure 1b), shows the Kaplan Meier plots of time to death in the 2 socio-economic strata restricted to those that were initially prescribed a triple combination regimen. As shown here, the product limit estimate (SE) of the cumulative mortality rate at 12 months for the high socio-economic group was 2.1% (0.4%). Conversely, the product limit estimate (SE) of the cumulative mortality rate at 12 months for the low socio-economic group was 5.7% (1.5%). Statistically significant differences in survival were noted between those the high and low socio- economic strata amongst those initially prescribed triple therapy (log rank p <0.05). In a multivariate model that considered the entire cohort, we found that adherence (RR = 0.83; [95% CI: 0.78 – 0.89] per 10% increase), a lower CD4 cell count (RR = 1.53 [95% CI: 1.33 – 1.77] per 100 cell decrease), and lower socio-economic status (RR = 2.19 [95% CI: 1.43 – 3.35]), were independently predictive of shorter survival (Table 1). When a sub-analysis of the 1031 patients who initiated triple therapy was conducted, adherence (RR = 0.80; [95% CI: 0.74 – 0.87]) and a lower baseline CD4 cell count (RR = 1.74 [95% CI: 1.43 – 2.12]) were the only variables independently associated with shorter survival (Table 2). We then investigated if inequitable access to triple therapy by socio-economic status, could explain the discrepancy. Interestingly, when those initially treated with 2 or 3 drugs were re-analyzed, persons in the lower socio-economic strata were less likely to be prescribed triple therapy (OR = 0.62; [95% CI: 0.46 – 0.85]) even after adjustment for baseline plasma viral load, CD4 cell count, injection drug use, and physician experience (Table 3). Table 1: Univariate and multivariate analysis of the baseline factors associated with death among 1,408 antiretroviral naïve persons first prescribed double or triple combination antiretroviral therapy between August 1, 1996 and March 31, 2000. Risk Ratios (RR) Variable Crude Adjusted* [RR, (95% CI)] [RR, (95% CI)] p-value Gender (Male versus female) 0.67 (0.41 - 1.11) — — Age in Years (Continuous) 1.03 (1.00 - 1.05) Prior AIDS Diagnosis (Yes versus no) 1.97 (1.23 - 3.15) 1.23 (0.73 – 2.07) 0.433 Injection Drug Use (Yes versus no) 1.38 (0.91 - 2.08) 1.27 (0.83 – 1.94) 0.268 Adherence (per 10% increase) 0.86 (0.81 - 0.91) 0.83 (0.78 – 0.89) <0.001 Median Income (Low versus High) 2.58 (1.71 - 3.89) 2.19 (1.43 – 3.35) <0.001 Baseline CD4+ count (cells/mm3) per 100 cell decrease 1.50 (1.32 - 1.70) 1.53 (1.33 – 1.77) <0.001 Baseline HIV-1 RNA (copies/mL) per log10 increase 1.67 (1.20 - 2.34) 1.22 (0.88 – 1.69) 0.237 * Fixed model was adjusted for baseline HIV-1 RNA, history of injection drug use, and baseline AIDS diagnosis. Table 2: Univariate and multivariate analysis of the baseline factors associated with death among 1031 antiretroviral naïve persons first prescribed any triple combination antiretroviral therapy between August 1, 1996 and March 31, 2000. Risk Ratios (RR) Variable Crude Adjusted* [RR, (95% CI)] [RR, (95% CI)] p-value Gender (Male versus female) 0.83 (0.41 - 1.67) — — Age in Years (Continuous) 1.02 (0.99 - 1.05) — — Prior AIDS Diagnosis (Yes versus no) 2.06 (1.20 - 3.53) 1.12 (0.62 – 2.02) 0.708 Injection Drug Use (Yes versus no) 1.08 (0.62 - 1.86) 0.95 (0.54 – 1.66) 0.860 Adherence (per 10% increase) 0.85 (0.79 - 0.92) 0.80 (0.74 – 0.87) <0.001 Median Income (Low versus High) 1.81 (1.04 - 3.17) 1.54 (0.86 – 2.76) 0.148 Baseline CD4 count (cells/mm3) per 100 cell decrease 1.65 (1.39 - 1.96) 1.74 (1.43 – 2.12) <0.001 Baseline HIV-1 RNA (copies/mL) per log10 increase 1.87 (1.208 - 2.90) 1.25 (0.83 – 1.90) 0.284 * Fixed model was adjusted for baseline HIV-1 RNA, history of injection drug use, and baseline AIDS diagnosis. Table 3: Univariate analyses comparing socio-demographic and clinical characteristics of participants prescribed double versus triple combination antiretroviral therapy. Initial Regimen Characteristic Double Triple 377, (%) 1031, (%) p-value Baseline HIV-1 RNA (copies/ml) Median 48,000 120,000 <0.001 IQR 19,000 – 92,000 41,000 – 300,000 Baseline CD4+ count (cells X 109/L) Median 330 270 <0.001 IQR 220 – 440 130 - 420 Prior AIDS Diagnosis No 347 (92.4) 882 (85.5) <0.001 Yes 30 (8.0) 149 (14.5) Age Median 36 37 0.110 IQR 32 – 42 32 - 43 Gender Female 73 (19.4) 132 (12.8) 0.002 Male 304 (80.6) 899 (87.2) Injection Drug Use No 264 (70.0) 808 (78.4) <0.001 Yes 113 (30.0) 223 (21.6) Median Neighborhood Income High 292 (77.5) 874 (84.8) 0.001 Low 85 (22.5) 157 (15.2) Physician Experience Median 36 44 0.459 IQR 9 – 106 5 – 137 Table 4: Logistic regression analysis* of factors associated with being prescribed triple combination therapy as the initial regimen. Variable Adjusted Odds Ratio 95% CI p-value Baseline HIV-1 RNA (copies/mL) (per log10 increase) 2.13 (1.78 – 2.56) <0.001 Baseline CD4 cell count (per 100 cell decrease) 1.06 (1.01 – 1.12) 0.030 Injection Drug Use (Yes versus No) 0.69 (0.52 – 0.92) 0.011 Median Income (Low versus High) 0.62 (0.46 – 0.85) 0.003 * Variables that were statistically significant at the 0.05 cut-off in the univariate analysis were considered in the multivariate model. Model was adjusted for physician experience which was non-significant. References 1. Schechter MT, Hogg RS, Aylward B, Craib KJ, Le TN, Montaner JS. Higher socioeconomic status is associated with slower progression of HIV infection independent of access to health care. J Clin Epidemiol 1994;47(1):59-67. 2. Hogg RS, Strathdee SA, Craib KJ, O'Shaughnessy MV, Montaner JS, Schechter MT. Lower socioeconomic status and shorter survival following HIV infection [see comments]. Lancet 1994;344(8930):1120-4. 3. Rothenberg R, Woelfel M, Stoneburner R, Milberg J, Parker R, Truman B. Survival with the acquired immunodeficiency syndrome. Experience with 5833 cases in New York City. N Engl J Med 1987;317(21):1297-302. 4. Melnick SL, Sherer R, Louis TA, Hillman D, Rodriguez EM, Lackman C, et al. Survival and disease progression according to gender of patients with HIV infection. The Terry Beirn Community Programs for Clinical Research on AIDS. JAMA 1994;272(24):1915-21. 5. Easterbrook PJ, Keruly JC, Creagh-Kirk T, Richman DD, Chaisson RE, Moore RD. Racial and ethnic differences in outcome in zidovudine-treated patients with advanced HIV disease. Zidovudine Epidemiology Study Group. JAMA 1991;266(19):2713-8. 6. Moore RD, Hidalgo J, Sugland BW, Chaisson RE. Zidovudine and the natural history of the acquired immunodeficiency syndrome. N Engl J Med 1991;324(20):1412-6. 7. Chaisson RE, Keruly JC, Moore RD. Race, sex, drug use, and progression of human immunodeficiency virus disease. N Engl J Med 1995;333(12):751-6. Figure 1: Probability of Survival Stratified by Socio-economic Status