In all income-cohort groups, AIDS was the most common COD (Fig. 1a–c). In the TAHOD low-income group, the cumulative incidence for other/unknown causes was similar to AIDS (Fig. 1c); 19 of these 21 deaths were of unknown cause (Table 1). In AHOD, non-AIDS cancers had the second highest cumulative incidence, followed by cardiovascular disease-related and liver-related causes. The cumulative probability of dying from non-AIDS COD by 3 years follow-up was low in the TAHOD high-income and low-income groups.
Predictors of AIDS and non-AIDS mortality
CD4 cell count (baseline and time dependent) and HIV viral load were associated with both AIDS and non-AIDS mortality in the univariate analysis (Table 3). Age and HIV exposure were also associated with non-AIDS mortality, whereas prior AIDS, mono/dual therapy prior to cART and calendar year were associated with AIDS mortality; all were included in the multivariate analysis.
Significant predictors of non-AIDS mortality in model 1, which excluded CD4 cell count as a time-dependent covariate, were older age [hazard ratio 4.08 for >50 years compared to 15–29 years; 95% confidence interval (CI) 1.95–8.54], HIV exposure and lower baseline CD4 cell count (Table 4). A lower CD4 cell count was also associated with a higher risk of AIDS mortality, as were prior AIDS (hazard ratio 2.07; 95% CI 1.26–3.39) and higher HIV viral load at baseline. The risk of AIDS mortality decreased by almost 70% in 2005–2007 compared with 1999–2001.
In model 2 (incorporating time-dependent CD4 cell counts), older age remained a significant predictor of non-AIDS mortality (hazard ratio 4.29 for >50 years compared to 15–29 years; 95% CI 2.10–8.79). Lower CD4 cell counts were associated with both outcomes, although the magnitude of risk was much greater for AIDS (hazard ratio for ≤100 vs. >200 cells/μl, 34.97; 95% CI 18.01–67.90) than non-AIDS mortality (hazard ratio for ≤100 vs. >200 cells/μl, 8.59; 95% CI 5.66–13.03). A baseline HIV viral load of 10 001 copies/ml or more (vs. ≤400 copies/ml) was also associated with AIDS mortality (hazard ratio 4.21; 95% CI 2.07–8.55). Similar results were obtained in sensitivity analyses.
Association between income-cohort group and AIDS and non-AIDS mortality
There was no significant difference in the risk of AIDS or non-AIDS mortality between the income-cohort groups on the univariate analysis, except for a marginally lower risk of non-AIDS mortality in the TAHOD high-income group compared with AHOD (hazard ratio 0.56; 95% CI 0.32–0.99) (Fig. 2a). When unknown COD were classified as AIDS deaths, both TAHOD high-income and low-income groups had a lower risk of non-AIDS mortality than AHOD and the risk of AIDS mortality was higher in TAHOD low-income sites (hazard ratio 1.55; 95% CI 0.99–2.41) (Fig. 2b). Adjustment for significant covariates in model 1 and model 2 had a broadly similar effect across all sensitivity analyses; it reduced the risk of AIDS mortality in the TAHOD low-income group, but had little effect on the risk of non-AIDS mortality (Fig. 2). Recoding unknown COD as AIDS deaths resulted in little difference between AHOD and TAHOD in terms of AIDS mortality in the adjusted analyses (Fig. 2b). Exclusion of every second time-dependent CD4 cell count in AHOD also slightly increased the hazard ratio for the TAHOD low-income group in model 2 (Fig. 2g).
In patients who started cART in the Asia-Pacific region, immunodeficiency (as indicated by CD4 cell count) was associated with non-AIDS mortality, although to a lesser extent than AIDS mortality. Older age was also associated with an increased risk of non-AIDS mortality. Other risk factors traditionally associated with AIDS remained important predictors of AIDS mortality in the cART era. Although the risk of dying from AIDS decreased over the study period, this was largely due to differences in CD4 cell count over time. We found a lower risk of dying from non-AIDS causes in high-income Asian countries compared with Australia, but no difference in AIDS mortality between the two settings. Less conclusive was the relative risk of dying from AIDS and non-AIDS causes in low-income Asian countries compared with Australia because of the relatively high proportion of unknown COD at low-income sites.
Our finding that immunodeficiency is related to non-AIDS mortality in a diverse clinical population in the Asia-Pacific region is consistent with previous studies in high-income settings [9,13,30–34]. It also parallels previous studies of morbidity in patients with HIV infection in which immunodeficiency has been associated with non-AIDS cancers [35,36]. In this study, sample size limited us from further investigating the relationship between immunodeficiency and more specific non-AIDS COD in the Asia-Pacific region.
The association between older age and non-AIDS mortality in our study is also consistent with other studies of non-AIDS morbidity and mortality in high-income settings [18,21,30,34,36]. This finding reflects the ageing nature of HIV-affected populations in the cART era and possible drug-related toxicities. Despite this demographic transition and shift in the treated history of HIV disease, patients who present with risk factors traditionally associated with AIDS remain at higher risk of AIDS mortality in the cART era .
Consistent with previous reports of declining AIDS mortality in the cART era [9,14], we observed an almost 70% reduction in the risk of dying from AIDS between 1999–2001 and 2005–2007 in our study. This was largely explained by differences in CD4 cell count over time. As AHOD and TAHOD are relatively closed cohorts, this study is not ideal to investigate the association between calendar year and mortality.
Contrary to our hypothesis, we did not find any significant associations between viral hepatitis co-infection and non-AIDS mortality in our study. This may, in part, be due to limited statistical power. It may also be a consequence of under ascertainment of HBV and HCV co-infections in TAHOD. Missing values for hepatitis test results in TAHOD may reflect low testing rates despite the relatively high prevalence of HBV and HCV in Asia [37,38]. In contrast, patients without hepatitis test results recorded in AHOD were generally not tested because they had no known risk factors and were, therefore, presumed negative.
The overall follow-up rates in each of the income-cohort groups in our study were relatively high, although there were lower rates of follow-up at some sites. Similar to other HIV cohorts , lower rates of follow-up were observed at low-income sites, which may have led to under ascertainment of deaths in this setting. To assess the effect of follow-up rates, we performed a sensitivity analysis to exclude sites with follow-up rates less than 80%. This analysis yielded similar results for both AIDS and non-AIDS mortality.
The most important limitation of our study was the relatively large proportion of unknown COD at TAHOD low-income sites. To explore their effect on our results, we performed various sensitivity analyses. First, we assumed that patients with AIDS were more likely to be under close surveillance prior to death and classified unknown COD as non-AIDS deaths. In this scenario, there was no difference in AIDS mortality between the different income-cohort groups and TAHOD high-income sites had a lower risk of non-AIDS mortality than AHOD. Unexpectedly, adjustment for CD4 cell count (baseline or time-dependent), HIV viral load and prior AIDS led to a decreased risk of AIDS mortality in the TAHOD low-income group compared with AHOD. This was only partly accounted for by differences in the frequency of CD4 cell count measurements in AHOD and TAHOD. In a second scenario, we grouped unknown COD as AIDS deaths on the basis that the average last CD4 cell count prior to death in patients with other/unknown COD at TAHOD low-income sites was low and comparable to that in the AIDS death group. In this analysis, the TAHOD low-income group had an increased risk of AIDS mortality compared to AHOD, which decreased after adjustment for significant covariates in the predictor models. This was more in line with the expected direction of any cause-specific mortality differences between the income-cohort groups. Further, TAHOD low-income sites had a lower risk of non-AIDS mortality than AHOD, comparable with that at TAHOD high-income sites. The same pattern was observed for non-AIDS mortality when sites with more than 25% of deaths classified as unknown were excluded.
Other limitations of this study include enrolment of patients into AHOD and TAHOD after they started cART and inclusion of patients with mono/dual therapy experience prior to starting cART in this analysis. To address these limitations, we included duration of cART exposure prior to cohort enrolment and mono/dual therapy prior to cART as covariates in the competing risks model; neither variable was significantly associated with mortality from AIDS or non-AIDS causes in the final model. We also conducted a sensitivity analysis excluding patients with mono/dual therapy experience prior to cART, of which the vast majority were from AHOD. In this analysis, the risk of non-AIDS mortality was similar in all income-cohort groups.
The introduction of a new, standardized COD form in AHOD in 2002 may have led to differential misclassification bias for specific COD between the periods 1999–2002 and 2003–2007. To investigate whether the change in data collection affected our results, we conducted a sensitivity analysis with the baseline date set to 1 January 2003. We found similar results, suggesting the new COD form had little effect on the classification of COD into the broader categories of AIDS and non-AIDS causes used in our analysis.
This study has several strengths. To our knowledge, this is the first study to report mortality outcomes beyond 12 months of cART in low-income and high-income settings internationally. Further, we believe this is the first study to investigate mortality from AIDS vs. non-AIDS causes in low-income and high-income settings during the cART era. The use of competing risks methods in our analysis enabled simultaneous comparison of risk factors for AIDS and non-AIDS mortality and was less likely to overestimate mortality , both of which are advantages over standard survival methods. Finally, use of data from two observational cohort studies founded on the same methodology is a major strength of our study, reducing the likelihood that methodological differences can explain the findings.
In summary, improved immunological outcomes are likely to reduce mortality from both AIDS and non-AIDS causes in patients with HIV infection, although this needs to be evaluated in large clinical studies. The increased risk of non-AIDS mortality with age highlights the importance of managing risk factors for other chronic diseases in patients with HIV infection in the cART era. We found some indication of a lesser risk of non-AIDS mortality at sites in high-income, and possibly low-income, countries in Asia compared to Australia. The association between country-income level and AIDS mortality warrants further investigation and requires improved COD ascertainment in low-income settings. Finally, the results of our study can only be generalized to patients receiving cART in the Asia-Pacific region. Notably, those receiving cART represent only a small fraction of the overall number of individuals in need of treatment in low–middle-income countries in the Asia-Pacific region at this time .
K.F. and M.L. developed the analysis concept and K.F. drafted the analysis plan. K.F. coordinated the study, managed the data, conducted all statistical analyses and drafted the manuscript. All authors discussed the analysis plan, contributed to interpretation of the analysis results and commented on drafts of the manuscript. All authors approved the final manuscript draft for journal submission.
The authors would like to thank Dr Preeyaporn Srasuebkul for statistical advice on this paper. The authors also thank participating sites and steering committee members (listed below) and all patients who participated in this study.
The TREAT Asia HIV Observational Database and the Australian HIV Observational Database are part of the Asia Pacific HIV Observational Database and are initiatives of TREAT Asia, a program of amfAR, The Foundation for AIDS Research, with support from the National Institute of Allergy and Infectious Diseases (NIAID) of the U.S. National Institutes of Health (NIH), as part of the International Epidemiologic Databases to Evaluate AIDS (IeDEA) (grant no. U01AI069907), and the Dutch Ministry of Foreign Affairs, through a partnership with Stichting Aids Funds. The National Centre in HIV Epidemiology and Clinical Research is funded by the Australian Government Department of Health and Ageing, and is affiliated with the Faculty of Medicine, The University of New South Wales. The content of this publication is solely the responsibility of the authors and does not necessarily represent the official views of any of the institutions mentioned above.
M.G.L. has received research grants, consultancy and/or travel grants from Abbott; Boehringer Ingelheim; Bristol-Myers Squibb; Gilead; GlaxoSmithKline; Janssen-Cilag; Johnson & Johnson; Merck Sharp & Dohme; Pfizer; Roche and CSL Ltd. The other writing committee members have no conflicts of interest to declare.
The Australian HIV Observational Database.
D. Ellis, General Medical Practice, Coffs Harbour, NSW; J. Chuah*, D. Lester, W. Fankhauser, B. Dickson, Gold Coast Sexual Health Clinic, Miami, QLD; M. Bloch, T. Franic, S. Agrawal, Holdsworth House General Practice, Darlinghurst, NSW; R. Moore, P. Cortissos, S. Edwards, P. Locke, The Carlton Clinic, Carlton, VIC; D. Nolan, S. Mallal, C. Forsdyke, S. Bulgannawar, Department of Clinical Immunology, Royal Perth Hospital, Perth, WA; N.J. Roth*, J. Nicholson, Prahran Market Clinic, South Yarra, VIC; D. Allen, Holden Street Clinic, Gosford, NSW; D. Smith, C. Mincham, C. Gray Lismore Sexual Health & AIDS Services, Lismore, NSW; D. Baker*, R. Vale, East Sydney Doctors, Darlinghurst, NSW; D. Russell, J. Leamy, C. Remington, P. Brown Cairns Sexual Health Service, Cairns, QLD; C. O'Connor; D. Templeton, Royal Prince Alfred Hospital Sexual Health, Camperdown, NSW; D. Sowden, A. Walker*, Clinic 87, Sunshine Coast & Cooloola HIV Sexual Health Service, Nambour, QLD; D. Orth; D. Youds, Gladstone Road Medical Centre, Highgate Hill, QLD; E. Jackson, D. Hunter, K. McCallum, Blue Mountains Sexual Health and HIV Clinic, Katoomba, NSW; T. Read, J. Silvers, Melbourne Sexual Health Centre, Melbourne, VIC; A. Kulatunga, P. Knibbs, Communicable Disease Centre, Royal Darwin Hospital, Darwin, NT; A. Mijch, J. Hoy, K. Watson*, M. Bryant, The Alfred Hospital, Melbourne, VIC; M. Gotowski, S. Taylor, L. Stuart-Hill, Bligh Street Clinic, Tamworth, NSW; D. Cooper, A. Carr, M. Lacey, K. Hesse, G. Keogh, R. Norris, St Vincent's Hospital, Darlinghurst, NSW; R. Finlayson, I. Prone, Taylor Square Private Clinic, Darlinghurst, NSW; M.T. Liang, Nepean Sexual Health and HIV Clinic, Penrith, NSW; M. Kelly, P. Negus, P.L. Am,brose, H. Magon, AIDS Medical Unit, Brisbane, QLD; K. Brown, N. Skobalj, Illawarra Sexual Health Clinic, Warrawong, NSW; L. Wray, H. Lu, Sydney Sexual Health Centre, Sydney, NSW; W. Donohue, A. Lohmeyer, The Care and Prevention Programme, Adelaide University, Adelaide, SA; I. Woolley, M. Giles, Monash Medical Centre, Clayton, VIC; Dubbo Sexual Health Centre, Dubbo, NSW; P. Canavan*, National Association of People Living with HIV/AIDS; C. Lawrence*, National Aboriginal Community Controlled Health Organisation; I. Zablotska*, National Centre in HIV Social Research, University of NSW, Sydney; B. Mulhall*, Department of Public Health and Community Medicine, University of Sydney, Sydney, NSW; M. Law*, K. Petoumenos*, K. Falster*, S. Marashi Pour*, C. Bendall* National Centre in HIV Epidemiology and Clinical Research, University of NSW, Sydney; NSW. *Steering Committee member during 2007–2008.
The TREAT Asia HIV Observational Database.
C.V. Mean*, V. Saphonn* and K. Vohith, National Center for HIV/AIDS, Dermatology & STDs, Phnom Penh, Cambodia; F.J. Zhang*†, H.X. Zhao and N. Han, Beijing Ditan Hospital, Beijing, China; P.C.K. Li*‡ and M.P. Lee, Queen Elizabeth Hospital, Hong Kong, China; N. Kumarasamy* and S. Saghayam, Y.R.G. Centre for AIDS Research and Education, Chennai, India; S. Pujari* and K. Joshi, Institute of Infectious Diseases, Pune, India; T.P. Merati* and F. Yuliana, Faculty of Medicine Udayana University & Sanglah Hospital, Bali, Indonesia; S. Oka*‡ and M. Honda, International Medical Centre of Japan, Tokyo, Japan; J.Y. Choi* and S.H. Han, Division of Infectious Diseases, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea; C.K.C. Lee* and R. David, Hospital Sungai Buloh, Kuala Lumpur, Malaysia; A. Kamarulzaman* and A. Kajindran, University of Malaya, Kuala Lumpur, Malaysia; G. Tau*, Port Moresby General Hospital, Port Moresby, Papua New Guinea; R. Ditangco* and R. Capistrano, Research Institute for Tropical Medicine, Manila, Philippines; Y.M.A. Chen*, W.W. Wong and Y.W. Yang, Taipei Veterans General Hospital and AIDS Prevention and Research Centre, National Yang-Ming University, Taipei, Taiwan; P.L. Lim*, C.C. Lee and E. Foo, Tan Tock Seng Hospital, Singapore; P. Phanuphak*, and M. Khongphattanayothing, HIV-NAT/Thai Red Cross AIDS Research Centre, Bangkok, Thailand; S. Sungkanuparph* and B. Piyavong, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand; T. Sirisanthana* and W. Kotarathititum, Research Institute for Health Sciences, Chiang Mai, Thailand; J. Chuah*, Gold Coast Sexual Health Clinic, Miami, Queensland, Australia; K. Frost*, J. Smith* and B. Nakornsri, The Foundation for AIDS Research, New York, USA; D.A. Cooper*, M.G. Law*, K. Petoumenos, R. Oyomopito and J. Zhou*, National Centre in HIV Epidemiology and Clinical Research, The University of New South Wales, Sydney, Australia. * TAHOD Steering Committee member; † Current Steering Committee chair; ‡ co-chair.
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Keywords:© 2009 Lippincott Williams & Wilkins, Inc.
AIDS; antiretroviral therapy; causes of death; cohort studies; competing-risks models; highly active; HIV; survival analysis