Treatment of HIV-infected patients with highly active antiretroviral therapy (HAART) slows disease progression and reduces mortality directly attributable to HIV or AIDS.1-6 In addition, the incidence of therapy-related and other non-HIV-related causes of death remains stable over time, indicating that the adverse effects of HAART are not yet a major cause of death.4,5
It is well established that the CD4+ T-cell count and HIV RNA plasma concentration at the start of HAART are strong predictors of disease outcome.7-9 In a collaborative study, we showed that baseline CD4 counts and viral load are not significantly associated with prognosis once the initial response to HAART as reflected in the 6-month CD4 cell counts and RNA levels are taken into account.10
We used the latter observation as a starting point for our analysis of mortality in HIV-infected individuals treated with HAART who are prospectively followed in the ATHENA national observational cohort in The Netherlands. Previously, we reported 5-year survival probabilities for 3724 antiretroviral therapy-naive and pretreated patients initiating HAART.5 The current study was performed to estimate the probability of future death for previously antiretroviral therapy-naive patients who have been treated with HAART for at least 24 weeks and to compare these probabilities with those in the age- and gender-matched general Dutch population.11-13
The data used in this study were selected from the ATHENA national observational cohort. The design of this cohort has been described previously.5,14 Briefly, by December 31, 2003, 9181 HIV-infected patients living in The Netherlands and followed in any of the 24 designated HIV treatment centers had been included in the cohort. Inclusion started in May 1998. Demographic data were collected at the first visit. In addition, data were collected in retrospect when patients were known to be HIV-positive before 1998. During follow-up, clinical data were collected, including data on HIV-1-related events categorized according to the Centers for Disease Control and Prevention's definition,15 data on antiretroviral drug use and side effects, and data on T-cell subsets and RNA levels in peripheral blood.
The start date of HAART, T0, was determined from data on antiretroviral drug use. HAART was defined as a combination of at least 3 drugs from at least 2 classes (nucleoside and nonnucleoside reverse transcriptase [RT] inhibitors and protease inhibitors) or as a combination of 3 nucleoside RT inhibitors, including abacavir or tenofovir. Patients who were never treated with HAART or did not have their HAART regimen recorded before December 31, 2003 (n = 2113) and patients who were treated with antiretroviral drugs before starting HAART (n = 2212) were excluded from this study.
The end point in the study was the date of death. Patients who were still alive at the end of follow-up were censored at their last follow-up visit, whereas patients with less than 24 weeks of follow-up were excluded from the analysis.
Baseline (ie, at the start of HAART) CD4 cell count and viral load were determined by taking the value closest to the start of HAART. For viral loads, measurements were considered within 24 weeks before T0. For CD4 cell counts, the nearest measurement within 24 weeks before T0 or up to 1 week after T0 was selected. The CD4 cell count and viral load at 24 weeks after initiation of HAART, T1, were determined by taking the value closest to 24 weeks measured between 12 and 36 weeks after T0. The analysis was restricted to patients having a T1 CD4 cell count and RNA measurement.10
Disease status at baseline was defined as the most serious CDC event (category B or C) in the year before T0 and the first 4 weeks thereafter. Disease status at T1 was defined as the most serious CDC event from 4 weeks after T0 to 4 weeks after T1. In addition, information was collected on gender, age at T1, and the transmission route (homosexual contact, heterosexual contact, intravenous drug use [IDU], and other).
Groups of patients were compared using Wilcoxon Mann-Whitney and χ2 nonparametric tests. Mortality was calculated per 100 person-years of follow-up after T1. The Poisson distribution was used to calculate 95% confidence intervals (CIs) for rates.
The number of antiretroviral therapy-naive patients in the ATHENA national observational cohort who initiated HAART was 4856. Of 365 patients excluded because of less than 24 weeks of follow-up, 49 (13.4%) died before 24 weeks. These 365 patients were significantly more likely to be female, to have been diagnosed with a CDC category B or C event before starting HAART, and to have started HAART after 1998 compared with those with at least 24 weeks of follow-up. In the remaining 4491 patients, 24-week CD4 cell counts and RNA levels were missing in 648 (14%) and 452 (10%) patients, respectively, whereas in 287 (6%) patients, both these measurements were missing.
A multivariate hazards model was used to find the set of covariates that best predicted the time from 24 weeks after the start of HAART to death. For each patient, the hazard for death after t years of follow-up after T1 was modeled as the sum of the expected hazard, h0(t), and a function, ν(z,t), containing patient-specific covariates z. The expected hazard depended on the patient's age and gender at time t and was estimated from the annual mortality rates of the general population in the Netherlands averaged over the years 1995 to 2000.16 Because h0(t) and, possibly, ν(z,t) are time dependent, a discrete time-generalized linear model was used in which the follow-up time for each patient was split in 1-year intervals using a Poisson distribution for the observed number of deaths.17 The hazard hz(ti) of dying in time interval i with disease covariates z for the HIV-infected population is then given by the following equation:
where h0(ti) is the hazard of death in the general population. The probability of survival up to time ti, S(ti), in the HIV-infected population is given by the following equation:
where H(ti) is the cumulative hazard, defined as H(ti) = Σj≤iν(z,tj). The standardized mortality ratio (SMR) was defined as the 1-year mortality of HIV-infected patients relative to the general population and was given by the following equation:
where S and S0 are the survival probabilities up to 1 year for HIV-infected individuals and for the general population, respectively, and H denotes the cumulative hazard at 1 year. Hence, a patient with an SMR s has an s times higher probability of dying within 1 year than an uninfected individual of the same age and gender.
Univariate hazard models were used to identify covariates that were associated with progression to death. Covariates yielding an overall likelihood ratio with a P value less than 0.2 in the univariate model were considered for inclusion in the multivariate hazards model. Covariates were excluded from the multivariate model via backward elimination if this did not yield a significantly worse model (P < 0.01, likelihood ratio test). For baseline and 24-week CD4 cell counts and RNA levels, we only considered the one most significantly associated with time to death in the univariate models. Interactions between covariates and interactions with time of follow-up were also assessed. Wald 95% CIs were calculated for parameters. All statistical analyses were carried out using SAS, version 8.02 (SAS Institute, Cary, NC).
The total study population consisted of 3678 patients with a total follow-up time of 13,621 person-years since the start of HAART and 11,930 person-years from 24 weeks after the start of HAART. Characteristics of the patients are shown in Table 1. The composition of the initial HAART regimen changed over time. In 1996, all 273 patients initiating HAART started a protease inhibitor-containing regimen, whereas in 2003, this was the case for 96 (42%) of 227 patients. The number of patients initiating HAART with a nonnucleoside RT inhibitor increased from 1996 to 115 (51%) in 2003.
In total, 590 (16%) patients had a 24-week CD4 count greater than 600 × 106 cells/L. Of those, 144 (24%) already had a CD4 count greater than 600 × 106 cells/L at the start of HAART, 272 (45%) had CD4 counts between 350 and 600 × 106 cells/L, 108 (18%) had CD4 counts between 200 and 350 × 106 cells/L, and 18 (3%) had CD4 counts less than 200 × 106 cells/L at the start of HAART, whereas for 48 (8%) patients, CD4 counts at the initiation of HAART were unknown. Of the 775 patients with a CD4 count at the start of HAART exceeding 350 × 106 cells/L, 416 (54%) had a 24-week CD4 count greater than 600 × 106 cells/L.
Covariates considered for inclusion in the model are listed in Table 2. In the multivariate hazards model, only log-transformed CD4 cell count and viral load <100,000 or ≥100,000 copies/mL at 24 weeks10 and infection via IDU were significantly associated with survival. The final model therefore included 3 covariates associated with progression to death: the log-transformed CD4 cell count (hazard ratio [HR] = 0.50, 95% CI: 0.40 to 0.61 per unit increase) and the viral load (HR = 0.30, 95% CI: 0.15 to 0.60, viral load <100,000 vs. ≥100,000 copies/mL) at 24 weeks after the start of HAART and infection via IDU (HR = 0.16, 95% CI: 0.10 to 0.26, non-IDU vs. IDU). No statistically significant interactions between covariates and no interactions with time were observed.
During follow-up, 126 deaths (3.4%) were recorded, corresponding to an overall mortality of 1.06 (95% CI: 0.88 to 1.26) per 100 person-years. Figure 1 shows the mortality rates in 4 groups stratified by CD4 cell count at 24 weeks after initiation of HAART. Mortality decreased with increasing CD4 cell counts (P < 0.0001, test for trend). The mortality was 2.02 (95% CI: 1.53 to 2.62) per 100 person-years for patients with less than 200 × 106 CD4 cells/L at 24 weeks and 0.52 (95% CI: 0.26 to 0.93) if CD4 counts exceeded 600 × 106 cells/L. The median age at the start of HAART decreased from 38.3 (interquartile range [IQR]: 32.5 to 45.5) years in the lowest CD4 cell count stratum to 36.2 (IQR: 30.2 to 43.0) years in the highest stratum (P < 0.001), whereas gender did not significantly vary between the 4 strata (P = 0.07). Expected mortality for age- and gender-matched individuals from the general population ranged from 0.30 to 0.26 per 100 person-years. For patients with a 24-week viral load ≥100,000 copies/mL, mortality was 4.58 (95% CI: 2.28 to 8.19) per 100 person-years and 0.98 (95% CI: 0.81 to 1.18) for those with a viral load <100,000 copies/mL.
Figure 2a shows the probability of death within 1 year as a function of age for the general population in the Netherlands and, according to the model, for non-IDU HIV-positive patients with a CD4 count of 600 × 106 cells/L and a viral load less than 100,000 copies/mL at 24 weeks after the initiation of HAART. The expected SMR as a function of CD4 cell count at 24 weeks for men and women 35 years of age with a 24-week viral load less than 100,000 copies/mL is shown in Figure 2b. For HIV-infected men, the mortality rate was expected to be 20 (95% CI: 14 to 29) times higher than in the general population when CD4 counts at 24 weeks were 50 × 106 cells/L and 4.3 (3.3 to 5.8) times higher when CD4 counts were 600 × 106 cells/L, whereas for women, the expected mortality rates were 29 (95% CI: 20 to 42) and 5.9 (95% CI: 4.4 to 8.2) times higher, respectively.
Figures 2c and d show the expected SMR for HIV-infected men and women, respectively, as a function of age for various CD4 cell counts after 24 weeks of HAART. The expected mortality rates in men were 5.6 (95% CI: 4.1 to 7.6) times higher than in the general population at 25 years of age and 1.15 (95% CI: 1.11 to 1.22) times higher at 65 years of age; in women, the expected mortality rates were 11.0 (95% CI: 7.9 to 15.6) times higher at 25 years of age and 1.31 (95% CI: 1.21 to 1.45) at 65 years of age when CD4 counts were 600 × 106 cells/L at 24 weeks. For HIV-infected patients with 200 × 106 CD4 cells/L at 24 weeks, the mortality rates for men and women were expected to be 10.8 (95% CI: 8.5 to 13.9) and 22.7 (95% CI: 17.5 to 29.4) times higher for patients 25 years of age and 1.33 (95% CI: 1.25 to 1.44) and 1.66 (95% CI: 1.51 to 1.87) times higher for patients 65 years of age, respectively. When the analysis was restricted to patients older than 40 years of age at initiation of HAART, the expected mortality rates decreased by 2% to 16% but were not significantly different from those obtained when analyzing all 3678 patients.
In our study population, CD4 cell counts and HIV RNA plasma levels measured after 24 weeks of initial HAART treatment and infection via IDU were the only strong predictors for progression to death, with lower mortality observed in those with higher CD4 cell counts. This finding is consistent with recently published results from a large international cohort.10 In non-IDU patients with CD4 counts greater than 600 × 106 cells/L and viral loads less than 100,000 copies/mL, mortality was still higher than in the age- and gender-matched general population, and only a few of the study participants had 24-week CD4 counts greater than 600 × 106 cells/L. In addition, patients who progressed fast and died before 24 weeks of HAART were excluded from the study.
We emphasize that despite the large difference in SMRs between men and women of the same age, the absolute difference in mortality is small. In addition, the increasing risk of death associated with older age that is usually observed5,10 is, according to our model, fully accounted for by the expected increasing hazard in the non-HIV-infected population. Because most of the patients in our study were less than 45 years of age at 24 weeks after starting HAART, estimation of the SMR at older ages is largely based on extrapolation of results obtained at younger ages. The results did not change significantly when only considering patients older than 40 years of age, however.
One of the advantages of SMRs is that information on cause-specific mortality is not necessary. Even if clinical data are available at the time of death, it is often difficult to judge if death can be attributed directly to HIV or AIDS, to a side effect of therapy, or to a non-HIV-related cause of death.5 Nevertheless, careful registration of death cases remains of utmost importance to signal potential increases in the number of deaths related to antiretroviral therapy as well as to other causes.5,8
Our method might underestimate other differences between the HIV-infected population and the general population apart from being infected with HIV, even after correcting for gender and age.12 The male HIV-infected population consists mainly of homosexual men, who are likely to have a lifestyle different from the general male Dutch population. For example, in the general population in the Netherlands, approximately 40% of men and 33% of women between the ages of 18 and 65 years smoke tobacco,18 whereas in a subset of the patients in our analysis for whom this was recorded, half of the homosexual men and a third of the heterosexual men and women did so.19 Therefore, part of the increased mortality relative to the general population is attributable to other lifestyle-related factors rather than to HIV infection. In addition, it should be noted that the expected mortality rate for the general population is based on all causes of deaths and thus includes mortality in HIV-infected patients. For the general population between 25 and 50 years of age, however, the number of deaths in HIV-infected individuals is at most 2% of the total number of deaths.18
We did not take into account other potentially important factors such as coinfection with hepatitis C virus (HCV). HCV coinfection is associated with increased mortality, although this association disappears in some studies when adjusting for other covariates.20-22 Because HCV coinfection is mainly found in intravenous drug users, however, its effect is largely taken into account in the increased hazard for intravenous drug users in our analysis.20 Furthermore, the negative effect of HCV coinfection on CD4 cell response is partially accounted for by the 24-week CD4 cell count in our model. To keep our model from becoming too complex, we also did not include hemoglobin and transaminase levels, which have been shown to be associated with survival.21,23
The model outcomes presented are consistent with the recent findings of the antiretroviral therapy cohort collaboration in that CD4 cell count and RNA level at 24 weeks of HAART are the most important predictors of outcome.10 The probability of having a 24-week CD4 count greater than 600 × 106 cells/L increased with higher CD4 counts at the start of HAART.24 This argues in favor of early initiation of HAART when CD4 counts are still high.25 Independent of this, CD4 cell restoration is also related to age, with more complete restoration in younger patients.26,27
A proportion of the patients analyzed here initiated HAART regimens that are generally no longer administered. Over calendar time, the composition of the first HAART combination shifted toward regimens without protease inhibitors. These newer regimens may be less toxic and hence easier to adhere to. The current response to HAART is therefore likely to be sustained for a longer time, resulting in a better prognosis. Hence, the SMRs are likely to improve in the future.
Although mortality in HIV-infected patients responding well to HAART was still higher than in the general population, SMRs were comparable to those observed in patients with diabetes mellitus.12,28,29 A large British cohort study on insulin-treated diabetic patients found SMRs of 3.7 and 4.9 in men and women, respectively, aged between 30 and 39 years.29 Similar patterns were observed in the Swiss HIV Cohort Study, where it was shown that excess mortality among successfully treated HIV-infected patients is similar to that in patients with cancer who are successfully treated.11
In conclusion, mortality in non-IDU HIV-infected individuals who respond well to HAART, as reflected by high CD4 cell counts and low plasma viral loads after 24 weeks of HAART, is still higher than in the general population in the Netherlands. The higher mortality in the HIV-infected population compared with that in the general population decreases with older age and higher CD4 cell counts in women and men. The absolute increase in mortality in the HIV-infected population, however, is almost independent of age and gender.
1. Egger M, Hirschel B, Francioli P, et al. Impact of new antiretroviral combination therapies in HIV
infected patients in Switzerland: prospective multicentre study. BMJ
2. Palella FJ, Delaney KM, Moorman AC, et al. Declining morbidity and mortality among patients with advanced human immunodeficiency virus infection. N Engl J Med
3. Mocroft A, Vella S, Benfield TL, et al. Changing patterns of mortality across Europe in patients infected with HIV
4. Mocroft A, Ledergerber B, Katlama C, et al. Decline in the AIDS and death rates in the EuroSIDA study: an observational study. Lancet
5. van Sighem A, van de Wiel M, Ghani A, et al. Mortality and progression to AIDS after starting highly active antiretroviral therapy
6. Valdez H, Chowdhry TK, Asaad R, et al. Changing spectrum of mortality due to human immunodeficiency virus: analysis of 260 deaths during 1995-1999. Clin Infect Dis
7. Hogg RS, Yip B, Chan KJ, et al. Rates of disease progression by baseline CD4 cell count and viral load after initiating triple-drug therapy. JAMA
8. Egger M, May M, Chêne G, et al. Prognosis
-1-infected patients starting highly active antiretroviral therapy
: a collaborative analysis of prospective studies. Lancet
9. Sterling TR, Chaisson RE, Morre RD. HIV
-1 RNA, CD4 T-lymphocytes, and clinical response to highly active antiretroviral therapy
10. Antiretroviral Therapy Cohort Collaboration (ART). Prognostic importance of initial response in HIV
-1 infected patients starting potent antiretroviral therapy: analysis of prospective studies. Lancet
11. Jaggy C, Von Overbeck J, Ledergerber B, et al. Mortality in the Swiss HIV
Cohort Study (SHCS) and the Swiss general population. Lancet
12. Jensen-Fangel S, Pedersen L, Pedersen C, et al. Low mortality in HIV
-infected patients starting highly active antiretroviral therapy
: a comparison with the general population. AIDS
13. Keiser O, Taffé P, Zwahlen M, et al. All cause mortality in the Swiss HIV
cohort study from 1990 to 2001 in comparison with the Swiss population. AIDS
14. Gras L, van Sighem A, van Valkengoed I, et al, on behalf of the Netherlands collaborative HIV
treatment centres. Monitoring of Human Immunodeficiency Virus (HIV) Infection in the Netherlands
. Amsterdam: HIV
Monitoring Foundation; 2003.
15. Centers for Disease Control and Prevention. 1993 revised classification system for HIV
infection and expanded surveillance case definition for AIDS among adolescents and adults. MMWR Morb Mortal Wkly Rep
16. Actuarial Association. Woerden, 2002. Available at: http://www.ag-ai.nl
. Accessed August 2004.
17. Dickman PW, Sloggett A, Hills M, et al. Regression models for relative survival. Stat Med
18. Statistics Netherlands. Available at: http://www.cbs.nl
. Accessed August 2004.
19. Data Collection on Adverse Events of Anti-HIV
Drugs Study Group (DAD). Combination antiretroviral therapy and the risk of myocardial infarction. N Engl J Med
20. Greub G, Ledergerber B, Battegay M, et al. Clinical progression, survival, and immune recovery during antiretroviral therapy in patients with HIV
-1 and hepatitis C virus coinfection: the Swiss HIV
Cohort Study. Lancet
21. Rancinan C, Neau D, Savès M, et al. Is hepatitis C virus co-infection associated with survival in HIV
-infected patients treated by combination antiretroviral therapy? AIDS
22. Tedaldi EM, Baker RK, Moorman AC, et al. Influence of coinfection with hepatitis C virus on morbidity and mortality due to human immunodeficiency virus infection in the era of highly active antiretroviral therapy
. Clin Infect Dis
23. Lundgren JD, Mocroft A, Gatell JM, et al. A clinically prognostic scoring system for patient receiving highly active antiretroviral therapy
: results from the EuroSIDA Study. J Infect Dis
24. Kaufmann GR, Perrin L, Pantaleo G, et al. CD4 T-lymphocyte recovery in individuals with advanced HIV
-1 infection receiving potent antiretroviral therapy for 4 years. Arch Intern Med
25. Opravil M, Ledergerber B, Furrer H, et al. Clinical efficacy of early initiation of HAART in patients with asymptomatic HIV
infection and CD4 cell count >350 × 106
26. Viard JP, Mocroft A, Chiesi A, et al. Influence of age on CD4 cell recovery in human immunodeficiency virus-infected patients receiving highly active antiretroviral therapy
: evidence from the EuroSIDA Study. J Infect Dis
27. Yamashita TE, Phair JP, Muñoz A, et al. Immunologic and virologic response to highly active antiretroviral therapy
in the Multicenter AIDS Cohort Study. AIDS
28. Baan CA, Nusselder WJ, Barendregt JJ, et al. The burden of mortality of diabetes mellitus in The Netherlands. Epidemiology
29. Laing SP, Swerdlow AJ, Slater SD, et al. The British Diabetic Association Cohort Study, I: all-cause mortality in patients with insulin-treated diabetes mellitus. Diabet Med
The ATHENA national observational cohort has been made possible through the collaborative efforts of the following physicians: W. Bronsveld* and M. E. Hillebrand-Haverkort, Medical Center, Alkmaar; J. M. Prins,* J. C. Bos, J. K. M. Eeftinck Schattenkerk, S. E. Geerlings, M. H. Godfried, J. M. A. Lange, F. C. van Leth, S. H. Lowe, J. T. M. van der Meer, F. J. B. Nellen, K. Pogány, T. van der Poll, P. Reiss, Th.A. Ruys, S. Sankatsing, R. Steingrover, G. van Twillert, M. van der Valk, M. G. A. van Vonderen, S. M. E. Vrouenraets, M. van Vugt, and F. W. M. N. Wit, Academic Medical Center, Amsterdam; T. W. Kuijpers, D. Pajkrt, and H. J. Scherpbier, Emma Children's Hospital, Amsterdam; A. van Eeden,* Onze Lieve Vrouwe Gasthuis, Jan van Goyen, Amsterdam; J. H. ten Veen,* P. S. van Dam, and J. C. Roos, Onze Lieve Vrouwe Gasthuis, Prinsengracht, Amsterdam; K. Brinkman,* P. H. J. Frissen, and H. M. Weigel, Onze Lieve Vrouwe Gasthuis, Amsterdam; J. W. Mulder,* E. C. M. van Gorp, P. L. Meenhorst, and A. T. A. Mairuhu, Slotervaart Hospital, Amsterdam; J. Veenstra,* St. Lucas Andreas Hospital, Amsterdam; S. A. Danner,* M. A. van Agtmael, F. A. P. Claessen, R. M. Perenboom, A. Rijkeboer, and M. van Vonderen, Free University Medical Center, Amsterdam; C. Richter,* J. van der Berg, and R. van Leusen, Hospital Rijnstate, Arnheim; R. Vriesendorp* and F. J. F. Jeurissen, Westeinde Hospital, The Hague; R. H. Kauffmann* and E. L. W. Koger, Medical Centre Haaglanden, Leyenburg, The Hague; B. Bravenboer,* Catharina Hospital, Eindhoven; C.H.H. ten Napel* and G. J. Kootstra, Medisch Spectrum Twente, Enschede; H. G. Sprenger,* W. M. A. J. Miesen, R. Doedens, and E. H. Scholvinck, University Hospital, Groningen; R. W. ten Kate,* Kennemer Gasthuis, Haarlem; D. P. F. van Houte* and M. Polee, Medical Center, Leeuwarden, South; F. P. Kroon,* P. J. van den Broek, J. T. van Dissel, and E. F. Schippers, University Medical Center, Leiden; G. Schreij,* S. van de Geest, and A. Verbon, University Hospital, Maastricht; P. P. Koopmans,* M. Keuter, F. Post, and A. J. A. M. van der Ven, University Hospital, Nijmegen; M. E. van der Ende,* I. C. Gyssens, M. van der Feltz, J. G. den Hollander, S. de Marie, J. L. Nouwen, B. J. A. Rijnders, and T. E. M. S. de Vries, Erasmus University Medical Center, Rotterdam (EMCR); G. Driessen, R. de Groot, and N. Hartwig, Sophia Children's Hospital Rotterdam; J. R. Juttmann,* C. van de Heul, and M. E. E. van Kasteren, St. Elisabeth Hospital, Tilburg; I. M. Hoepelman,* M. J. M. Bonten, J. C. C. Borleffs, P. M. Ellerbroek, C. A. J. J. Jaspers, M. M. E. Schneider, I. Schouten, and C. A. M. Schurink, University Medical Center, Utrecht; S. P. M. Geelen and T. F. W. Wolfs, Wilhelmina Children's Hospital, Utrecht; W. L. Blok* and A. A. Tanis, Hospital Walcheren, Vlissingen; and P. H. P. Groeneveld,* Isala Clinics, Zwolle.
*Site coordinating physician.