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      Life Expectancies of South African Adults Starting Antiretroviral Treatment: Collaborative Analysis of Cohort Studies

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          Abstract

          Leigh Johnson and colleagues estimate the life expectancies of HIV positive South African adults who are taking antiretroviral therapy by using information from 6 programmes between 2001 and 2010.

          Abstract

          Background

          Few estimates exist of the life expectancy of HIV-positive adults receiving antiretroviral treatment (ART) in low- and middle-income countries. We aimed to estimate the life expectancy of patients starting ART in South Africa and compare it with that of HIV-negative adults.

          Methods and Findings

          Data were collected from six South African ART cohorts. Analysis was restricted to 37,740 HIV-positive adults starting ART for the first time. Estimates of mortality were obtained by linking patient records to the national population register. Relative survival models were used to estimate the excess mortality attributable to HIV by age, for different baseline CD4 categories and different durations. Non-HIV mortality was estimated using a South African demographic model. The average life expectancy of men starting ART varied between 27.6 y (95% CI: 25.2–30.2) at age 20 y and 10.1 y (95% CI: 9.3–10.8) at age 60 y, while estimates for women at the same ages were substantially higher, at 36.8 y (95% CI: 34.0–39.7) and 14.4 y (95% CI: 13.3–15.3), respectively. The life expectancy of a 20-y-old woman was 43.1 y (95% CI: 40.1–46.0) if her baseline CD4 count was ≥200 cells/µl, compared to 29.5 y (95% CI: 26.2–33.0) if her baseline CD4 count was <50 cells/µl. Life expectancies of patients with baseline CD4 counts ≥200 cells/µl were between 70% and 86% of those in HIV-negative adults of the same age and sex, and life expectancies were increased by 15%–20% in patients who had survived 2 y after starting ART. However, the analysis was limited by a lack of mortality data at longer durations.

          Conclusions

          South African HIV-positive adults can have a near-normal life expectancy, provided that they start ART before their CD4 count drops below 200 cells/µl. These findings demonstrate that the near-normal life expectancies of HIV-positive individuals receiving ART in high-income countries can apply to low- and middle-income countries as well.

          Please see later in the article for the Editors' Summary

          Editors' Summary

          Background

          According to the latest figures, more than 34 million people worldwide currently live with HIV/AIDS. In 2011, an estimated 2.5 million people were newly infected with HIV, and in the same year 1.7 million people died from AIDS. Since the beginning of the epidemic in the 1980s, more than 60 million people have contracted HIV and nearly 30 million have died of HIV-related causes. Despite the stark statistics, the life expectancy for people infected with the AIDS virus has dramatically improved over the past decade since the introduction of an effective combination of antiretroviral drugs. In high-income countries, people who are HIV-positive can expect a near-normal life expectancy if they take these drugs (as antiretroviral treatment—ART) throughout their life.

          Why Was This Study Done?

          Recent studies investigating the life expectancy of people living with HIV have mostly focused on the situation in high-income settings. The situation in low- and middle-income countries is vastly different. People who are diagnosed with HIV are often late in starting treatment, treatments regimes are sometimes interrupted, and a large proportion of patients are lost to follow-up. It is important to gain a realistic estimate of life expectancy in low- and middle-income countries so patients can be given the best information. So in this study the researchers used a model to estimate the life expectancy of patients starting ART in South Africa, using data from several ART programs.

          What Did the Researchers Do and Find?

          The researchers used data collected from six programs in South Africa based in Western Cape, Gauteng, and KwaZulu-Natal between 2001 and 2010. The researchers calculated the observation time from the time of ART initiation to the date of death or to the end of the study. Then the researchers used a relative survival approach to model the excess mortality attributable to HIV, relative to non-HIV mortality rates in South Africa, over different periods from ART initiation.

          Using these methods, the researchers found that over the time period, 37,740 adults started ART and 2,066 deaths were recorded in patient record systems. Of the 16,250 patients who were lost to follow-up, the researchers identified 2,947 further deaths in the population register. When they inputted these figures into their model, the researchers estimated that the mortality rate was 83.2 per 1,000 person-years of observation (PYO), and was higher in males (99.8 per 1,000 PYO) than in females (72.6 per 1,000 PYO). The researchers also found that the most significant factor determining the life expectancy of treated patients was their age at ART initiation: the average life expectancy of men starting ART varied between 27.6 years at age 20 and 10.1 years at age 60, while corresponding estimates in women were 36.8 and 14.4, respectively. Life expectancies were also significantly influenced by baseline CD4 counts; life expectancies in patients with baseline CD4 counts ≥200 cells/µl were between 70% and 86% of those of HIV-negative adults of the same age and sex, while patients starting ART with CD4 counts of <50 cells/µl had life expectancies that were between 48% and 61% of those of HIV-negative adults. Importantly, the researchers found that life expectancies were also 15%–20% higher in patients who survived their first 24 months after starting ART than in patients of the same age who had just started therapy.

          What Do These Findings Mean?

          These findings suggest that in South Africa, patients starting ART have life expectancies around 80% of normal life expectancy, provided that they start treatment before their CD4 count drops below 200 cells/µl. Although these results are encouraging, this study highlights that health services must overcome major challenges, such as dealing with late diagnosis, low uptake of CD4 testing, loss from pre-ART care, and delayed ART initiation, if near-normal life expectancies are to be achieved for the majority of HIV-positive South Africans. With the anticipated increase in the fraction of patients starting ART at higher CD4 counts in the future, long-term survival can be expected to increase even further. It is therefore critical that appropriate funding systems and innovative ways to reduce costs are put in place, to ensure the long-term sustainability of ART delivery in low- and middle-income countries.

          Additional Information

          Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001418.

          Related collections

          Most cited references27

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          Mortality of Patients Lost to Follow-Up in Antiretroviral Treatment Programmes in Resource-Limited Settings: Systematic Review and Meta-Analysis

          Background The retention of patients in antiretroviral therapy (ART) programmes is an important issue in resource-limited settings. Loss to follow up can be substantial, but it is unclear what the outcomes are in patients who are lost to programmes. Methods and Findings We searched the PubMed, EMBASE, Latin American and Caribbean Health Sciences Literature (LILACS), Indian Medlars Centre (IndMed) and African Index Medicus (AIM) databases and the abstracts of three conferences for studies that traced patients lost to follow up to ascertain their vital status. Main outcomes were the proportion of patients traced, the proportion found to be alive and the proportion that had died. Where available, we also examined the reasons why some patients could not be traced, why patients found to be alive did not return to the clinic, and the causes of death. We combined mortality data from several studies using random-effects meta-analysis. Seventeen studies were eligible. All were from sub-Saharan Africa, except one study from India, and none were conducted in children. A total of 6420 patients (range 44 to 1343 patients) were included. Patients were traced using telephone calls, home visits and through social networks. Overall the vital status of 4021 patients could be ascertained (63%, range across studies: 45% to 86%); 1602 patients had died. The combined mortality was 40% (95% confidence interval 33%–48%), with substantial heterogeneity between studies (P<0.0001). Mortality in African programmes ranged from 12% to 87% of patients lost to follow-up. Mortality was inversely associated with the rate of loss to follow up in the programme: it declined from around 60% to 20% as the percentage of patients lost to the programme increased from 5% to 50%. Among patients not found, telephone numbers and addresses were frequently incorrect or missing. Common reasons for not returning to the clinic were transfer to another programme, financial problems and improving or deteriorating health. Causes of death were available for 47 deaths: 29 (62%) died of an AIDS defining illness. Conclusions In ART programmes in resource-limited settings a substantial minority of adults lost to follow up cannot be traced, and among those traced 20% to 60% had died. Our findings have implications both for patient care and the monitoring and evaluation of programmes.
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            A scandal of invisibility: making everyone count by counting everyone.

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              Prognosis of HIV-1-infected patients starting highly active antiretroviral therapy: a collaborative analysis of prospective studies.

              Insufficient data are available from single cohort studies to allow estimation of the prognosis of HIV-1 infected, treatment-naive patients who start highly active antiretroviral therapy (HAART). The ART Cohort Collaboration, which includes 13 cohort studies from Europe and North America, was established to fill this knowledge gap. We analysed data on 12,574 adult patients starting HAART with a combination of at least three drugs. Data were analysed by intention-to-continue-treatment, ignoring treatment changes and interruptions. We considered progression to a combined endpoint of a new AIDS-defining disease or death, and to death alone. The prognostic model that generalised best was a Weibull model, stratified by baseline CD4 cell count and transmission group. FINDINGS During 24,310 person-years of follow up, 1094 patients developed AIDS or died and 344 patients died. Baseline CD4 cell count was strongly associated with the probability of progression to AIDS or death: compared with patients starting HAART with less than 50 CD4 cells/microL, adjusted hazard ratios were 0.74 (95% CI 0.62-0.89) for 50-99 cells/microL, 0.52 (0.44-0.63) for 100-199 cells/microL, 0.24 (0.20-0.30) for 200-349 cells/microL, and 0.18 (0.14-0.22) for 350 or more CD4 cells/microL. Baseline HIV-1 viral load was associated with a higher probability of progression only if 100,000 copies/microL or above. Other independent predictors of poorer outcome were advanced age, infection through injection-drug use, and a previous diagnosis of AIDS. The probability of progression to AIDS or death at 3 years ranged from 3.4% (2.8-4.1) in patients in the lowest-risk stratum for each prognostic variable, to 50% (43-58) in patients in the highest-risk strata. The CD4 cell count at initiation was the dominant prognostic factor in patients starting HAART. Our findings have important implications for clinical management and should be taken into account in future treatment guidelines.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS Med
                PLoS Med
                PLoS
                plosmed
                PLoS Medicine
                Public Library of Science (San Francisco, USA )
                1549-1277
                1549-1676
                April 2013
                April 2013
                9 April 2013
                : 10
                : 4
                : e1001418
                Affiliations
                [1 ]Centre for Infectious Disease Epidemiology and Research, University of Cape Town, Cape Town, South Africa
                [2 ]Africa Centre for Health and Population Studies, University of KwaZulu-Natal, Mtubatuba, South Africa
                [3 ]Centre for Actuarial Research, University of Cape Town, Cape Town, South Africa
                [4 ]Aurum Institute, Johannesburg, South Africa
                [5 ]Division of Infectious Diseases, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
                [6 ]Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
                [7 ]Center for Global Health and Development, Boston University, Boston, Massachusetts, United States of America
                [8 ]Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
                [9 ]Desmond Tutu HIV Centre, University of Cape Town, Cape Town, South Africa
                [10 ]Division of Infectious Diseases, Department of Medicine, University of Stellenbosch, Cape Town, South Africa
                [11 ]Tygerberg Academic Hospital, Cape Town, South Africa
                [12 ]McCord Hospital, Durban, South Africa
                [13 ]Médecins Sans Frontières, Cape Town, South Africa
                Johns Hopkins University, United States of America
                Author notes

                The authors have declared that no competing interests exist.

                Conceived and designed the experiments: LFJ RED JM OK MPF MS ME AB. Performed the experiments: LJ MS AB MC. Analyzed the data: LJ MS AB MC. Wrote the first draft of the manuscript: LJ. Contributed to the writing of the manuscript: LFJ JM RED MS CJH OK MPF RW HP JG DBG MC ME AB. ICMJE criteria for authorship read and met: LFJ JM RED MS CJH OK MPF RW HP JG DBG MC ME AB. Agree with manuscript results and conclusions: LFJ JM RED MS CJH OK MPF RW HP JG DBG MC ME AB. Enrolled patients: CH JM HP MF JG DBG RW.

                ¶ Membership of The International Epidemiologic Databases to Evaluate AIDS Southern Africa (IeDEA-SA) Collaboration is provided in the Acknowledgments.

                Article
                PMEDICINE-D-12-02435
                10.1371/journal.pmed.1001418
                3621664
                23585736
                c614be25-a500-4bee-8deb-7f2350f1e85c
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 16 August 2012
                : 28 February 2013
                Page count
                Pages: 11
                Funding
                Support for this study was provided by the US National Institute of Allergy and Infectious Diseases (NIAID) through the International epidemiological Databases to Evaluate AIDS, Southern Africa (IeDEA-SA), grant no. 5U01AI069924-05. MPF was supported by the National Institute of Allergy and Infectious Diseases [K01AI083097]. JM received partial financial support from the German government through the Centre for International Migration and Development (CIM). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine
                Infectious Diseases
                Sexually Transmitted Diseases
                AIDS
                Viral Diseases
                HIV

                Medicine
                Medicine

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