Mycobacterium avium complex (MAC) infection is a complication of advanced AIDS. Disseminated infection carries additional morbid effects and is an independent predictor of AIDS-related death.1,2 The incidence of MAC infection and associated mortality significantly decreased with the increasing availability of highly active antiretroviral therapy (ART).3,4 Nevertheless, chemoprophylaxis against MAC in patients with advanced immunodeficiency remains a recommendation of current guidelines.5
Macrolides have been shown to be effective in preventing disseminated MAC infection and have become the suggested prophylaxis for patients infected with HIV.2,6–8 Current guidelines recommend the use of clarithromycin 500 mg twice daily or azithromycin 1200 mg per week as first-line prophylaxis for HIV-infected persons with a CD4 cell count of <50 cells/mm3. Primary prophylaxis is withheld safely in HIV-infected persons whose CD4 cell counts have risen to >100 cells/mm3 for more than 3 months in response to ART.5 The choice of clarithromycin or azithromycin is based on perceptions of relative convenience, cost, tolerability, and effectiveness.2
Along with these recommendations, clinicians must weigh the potential benefits of macrolide prophylaxis against increased pill burden and cost, drug interactions and toxicity, and antimicrobial resistance.2,9,10 The objective of this study was to determine whether withholding macrolide prophylaxis when it is indicated has a significant impact on the occurrence of AIDS-defining conditions and/or HIV-associated mortality among patients starting ART in Asia.
The data used in this analysis came from the TREAT Asia HIV Observational Database (TAHOD), a multicenter, collaborative cohort study involving 20 study sites in the Asia-Pacific region. The cohort contributes to the International Epidemiology Databases to Evaluate AIDS (IeDEA) global consortium. Detailed methods have been published previously.11 Ethical approval was obtained from all participating sites' institutional review boards, the coordinating center, and the data management and biostatistical analysis center.
The data collected in TAHOD includes patient demographics, hepatitis B (HBV) status, hepatitis C (HCV) status, baseline CD4 cell count, HIV viral load (VL), prior AIDS diagnosis, initial ART regimen, and chemoprophylaxis use. Data transfers occur biannually. Patients from the September 2015 data transfer, aged 18 years and above at the time of ART initiation (defined as ≥3 antiretrovirals) and with CD4 cell count <50 cells/mm3, were included in the analysis. Baseline CD4 cell count and VL were defined as the closest CD4 or VL measurements within the defined window period of 6 months before ART initiation and 1 week after ART initiation.
Patients were considered to be on macrolide prophylaxis if they were using prophylactic azithromycin or clarithromycin at the time of ART initiation or started prophylactic azithromycin or clarithromycin within 3 months of ART initiation. Patients were considered hepatitis B coinfected if they had any record of a positive hepatitis B surface antigen test and hepatitis C coinfected if they had any record of a positive hepatitis C antibody test. Having a prior AIDS-defining condition at baseline was defined as having a Center for Disease Control and Prevention (CDC) category C illness at any time before ART initiation.12
The study outcomes were (1) the occurrence of an AIDS-defining condition or HIV-associated mortality (as a combined outcome) and (2) HIV-associated mortality. Deaths were classified as HIV-associated based on the revised 1993 CDC case definition.12 For the combined outcome analysis, the earliest event which took place was taken as the final outcome. Censored observations were considered as those individuals who did not experience or develop the outcomes of interest within 2 years of ART initiation. Loss to follow-up (LTFU) was defined as those patients not seen at the treatment sites ≥12 months from the last visit date without documentation of transfer. LTFU and death not associated with HIV/AIDS were considered as competing risks.
Competing risk regression analysis adjusted for the study site was used to evaluate predictors of the 2 outcomes of interest. Follow-up time was computed from ART start date until the occurrence of AIDS-defining conditions, death, LTFU, or censoring. Follow-up time in all time-to-event analyses was left censored. Macrolide use, age, sex, mode of HIV exposure, HBV/HCV status, and prior CDC category C illnesses were considered as fixed covariates, whereas CD4 cell count, HIV VL, ART regimen, cotrimoxazole use, and use of other chemoprophylaxis were considered as time-updated covariates.
Predictors to be included in the multivariate model were selected based on a significance level of ≤0.15 in the univariate analysis. Predictors were retained in the multivariate model if one or more categories exhibited a P value ≤0.05. Macrolide use was included in multivariate models regardless of significance. Patients with missing data were included in the analyses but hazard ratios for missing categories are not reported.
A sensitivity analysis was conducted to assess whether results were consistent in patients with a CD4 cell count <100 cells/mm3 at baseline. The same operational definitions and statistical analysis used in the primary analysis were followed in the sensitivity analysis. A second sensitivity analysis was performed to assess whether results were consistent if 50% of the LTFU patients were assumed to experience HIV-associated death. LTFU patients in the primary analysis were randomly selected and recoded with HIV death as their outcome. The same operational definitions and statistical analysis used in the primary analysis were followed.
Stata software version 14 (StataCorp. 2015; Stata Statistical Software: Release 14. College Station, TX: StataCorp LP) was used in all statistical analyses.
There were 1345 patients eligible for inclusion in this analysis. Baseline characteristics of patients at ART initiation are presented in Table 1. The majority of patients were male (78.1%) with a median age at ART initiation of 34.8 years [interquartile range (IQR) 29.9–41.1). Homosexual contact was the most common reported mode of HIV exposure (70.5%). Hepatitis B and C status was positive in 11.0% and 20.4% of patients tested, respectively. The median baseline CD4 cell count was 21 cells/mm3 (IQR 10–34), median VL was 120,000 copies/ml (IQR 50,578–372,000), and 50.0% of patients had known prior AIDS diagnosis. Of the eligible patients, 1186 (88.2%) were on nonnucleoside reverse transcriptase inhibitor—based therapy, 1027 patients (76.4%) received cotrimoxazole prophylaxis at baseline, 143 patients (10.6%) were on a macrolide prophylaxis regimen, and 587 patients (43.6%) received dapsone, pentamidine, pyrimethamine, sulfadiazine, clindamycin, fluconazole, itraconazole, ketoconazole, ganciclovir, acyclovir, isoniazid, rifampicin, pyrazinamide, or ethambutol as prophylaxis against tuberculosis, herpes, cytomegalovirus, Pneumocystis, and fungal infections. Between-group differences in the use of macrolide prophylaxis were noted. The study adjusted for these differences in the statistical model.
Table 2 shows that 49.8% of the eligible patients who had an initial CD4 cell count <50 cells/mm3 achieved CD4 recovery (ie, >200 cells/mm3) at 2 years of follow-up. Viral suppression was seen in 75.7% of the eligible patients with a VL test available after 2 years of follow-up.
For the combined outcome (occurrence of AIDS-defining condition or HIV-associated mortality), the total follow-up time was 1347 years. The combined outcome occurred in 99 patients (7.4%) at an incidence rate of 7.35 [95% confidence interval (CI): 6.04 to 8.95] per 100 patient-years. The incidence rate of the combined outcome among macrolide users was 15.02 (95% CI: 8.89 to 25.35) per 100 patient-years and 6.78 (95% CI: 5.48 to 8.93) per 100 patient-years among nonmacrolide users (Fig. 1A). The rate of LTFU among macrolide users was 62.2 (95% CI: 48.09 to 80.47) per 100 patient-years and 8.6 (95% CI: 7.13 to 10.40) per 100 patient-years among nonmacrolide users.
Risk factors associated with the combined outcome are presented in Table 3. In the final multivariate model, older age was associated with an increased risk of the combined outcome [hazard ratio (HR) = 1.39 for every 10-year increase, 95% CI: 1.10 to 1.77, P = 0.006], whereas higher CD4 cell count (HR = 0.94 for every 10 cells/mm3 increase, 95% CI: 0.90 to 0.98, P = 0.014) and use of cotrimoxazole prophylaxis (HR = 0.52 versus nonuse, 95% CI: 0.30 to 0.89, P = 0.017) were strongly associated with a lower risk of having the combined outcome. There was no significant association between macrolide use and the combined outcome (HR = 0.86 versus nonuse, 95% CI: 0.32 to 2.29, P = 0.764).
For HIV-associated mortality, the total follow-up time was 1467 years. HIV-associated mortality occurred in 46 patients (3.4%) at an incidence rate of 3.14 (95% CI: 2.35 to 4.19) per 100 patient-years. The incidence rate of HIV-associated mortality among macrolide users was 1.97 (95% CI: 0.49 to 7.87) per 100 patient-years and 3.22 (95% CI: 2.40 to 4.33) per 100 patient-years among nonmacrolide users (Fig. 1B). The rate of LTFU among macrolide users was 67.9 (95% CI: 53.64 to 85.99) per 100 patient-years and 9.0 (95% CI: 7.55 to 10.75) per 100 patient-years among nonmacrolide users. The rate of non–HIV-associated mortality among macrolide users was 5.20 (95% CI: 2.34 to 11.58) per 100 patient-years and 1.50 (95% CI: 1.07 to 2.09) per 100 patient-years among nonmacrolide users.
Table 4 summarizes the analyses of factors associated with HIV-associated mortality. In the final multivariate model, prior AIDS diagnosis was associated with HIV-associated mortality (HR = 4.23 versus no prior diagnosis, 95% CI: 1.49 to 11.98, P = 0.007), whereas higher CD4 cell counts (HR = 0.87 for every 10 cell/mm3 increase, 95% CI: 0.79 to 0.96, P = 0.006), cotrimoxazole use (HR = 0.37 versus nonuse, 95% CI: = 0.17 to 0.83, P = 0.015), and macrolide use (HR = 0.10 versus nonuse, 95% CI: 0.01 to 0.80, P = 0.031) were significantly associated with a lower rate of HIV-associated mortality.
Sensitivity analysis showed consistency of results among those patients with CD4 cell counts of <100 cells/mm3. Baseline characteristics of patients and the results of the univariate and multivariate analyses are shown in Tables 1–3, Supplemental Digital Content (http://links.lww.com/QAI/B258). The incidence rates of HIV-associated mortality among macrolide users and among nonmacrolide users are shown in Figure 1, Supplemental Digital Content (http://links.lww.com/QAI/B258).
The result of the sensitivity analysis on LTFU was similar to the primary analysis regarding the association of higher CD4 cell counts with decreased risks of having the combined outcome and HIV-associated mortality. Macrolide use and HCV status, on the contrary, were significantly associated with increased risks of the combined outcome and HIV-associated mortality. Results of the univariate and multivariate analyses are shown in Tables 4–5 (Supplemental Digital Content, http://links.lww.com/QAI/B258).
Routine use of prophylaxis against specific opportunistic infections among patients with HIV/AIDS has a significant impact on the incidence of opportunistic infection and overall patient mortality.13 Use of macrolide antibiotics, clarithromycin and azithromycin, have been respectively associated with an independent risk reduction of MAC disease and have become the mainstay prophylaxis for HIV-infected patients.2,7,14 Despite the recommended indications, the use of macrolide prophylaxis in TAHOD patients with a CD4 cell count <50 cells/mm3 remained low during the study period. Factors such as cost, increased pill burden, risk of untoward effects, and drug interactions may be applicable in our setting.9 Between-group disparities in the initiation of macrolide prophylaxis seen in the study may be due to differences in patients' care-seeking behavior, differences in access to care between the treatment sites, availability of the medicine, and the differences in the perception of the health care provider for the need of the prophylaxis.
With the availability of effective ART, the incidence of MAC infections has significantly decreased to 0.32–1.4 per 100 person-years from 2.9 to 8.8 per 100 person-years in the pre-ART period.3 Epidemiologic data from Asia on MAC infection among HIV-infected patients have been limited.15,16 Lack of diagnostic capacity, delayed diagnosis of MAC infection, shortened survival of AIDS patients, and the protective effect of a prior tuberculosis infection contribute to the reduced reported incidence of disseminated MAC infection in developing countries.1,6
Our study reports a higher incidence of the combined outcome (AIDS-defining condition or HIV-associated mortality) among macrolide users. This may be due to a tendency for clinicians to start chemoprophylaxis to patients assessed to have risks of developing AIDS-defining conditions or opportunistic infections. Patients included in the analysis had severe immunodeficiency, and the possibility of developing AIDS-defining conditions was high. Still, we found no significant association between the use of macrolide prophylaxis and having the combined outcome. The study, however, showed a significant decrease in the risk of HIV-associated mortality among patients who were started on macrolide prophylaxis.
Our sensitivity analysis revealed low risk of mortality among HIV-infected patients with CD4 cell count <100 cells/mm3 receiving macrolide prophylaxis. Although the risk of disseminated MAC infection and mortality is reduced in those with higher CD4 cell counts or CD4 recovery, literature suggests macrolide prophylaxis is still beneficial against other infections. Azithromycin was reported to provide additional protection against Pneumocystis jiroveci in addition to standard cotrimoxazole prophylaxis.17 The incidence of Pneumocystis pneumonia has also been lower among those azithromycin recipients who were not receiving cotrimoxazole or dapsone treatment regimen.7 Comparative clinical trials have demonstrated excellent activity of azithromycin against common respiratory tract pathogens and significant reduction in the incidence of presumed non-MAC respiratory infections.7,18 Clarithromycin prophylaxis has been reported to reduce the risk of bacterial respiratory tract and soft tissue infections, thereby reducing morbidity among HIV-infected patients.14,19 Our study indicates that further study is necessary to assess the relative advantage of increasing the CD4 threshold for starting macrolide prophylaxis to improve patient outcomes across different geographic settings.
Our study findings that age at ART initiation, CD4 cell count, and cotrimoxazole prophylaxis significantly lower the risk of the combined outcome and HIV-associated mortality also support current treatment recommendation, and further substantiates the recommendation to give cotrimoxazole prophylaxis with ART as part of the standard care for people with HIV infection and AIDS.20
Our study was limited by the potential for unascertained mortality among macrolide users who were LTFU. If 50% of those LTFU patients were assumed to have died, our sensitivity analysis showed increased risk of the combined outcome and HIV-associated mortality among those given macrolide prophylaxis. These patients had advanced clinical disease and low CD4 cell counts, which are indications for giving macrolide prophylaxis.5 Likewise, they are independent risk factors for LTFU. Patients who are lost to follow-up are at higher risk of dying from treatment failure and HIV complications.21,22 The interpretation of the study results is also limited by the incomplete reporting of confirmed MAC events. Furthermore, MAC diagnosis is not specifically collected in TAHOD because diagnostic workup for MAC infection may not be available in some of the participating sites.
Our study demonstrated the potential additive protective effect of macrolide prophylaxis against mortality among Asian HIV-infected adult patients with CD4 cell counts <100 cells/mm3, despite the availability of effective ART. Our study suggests the need to increase macrolide prophylaxis usage and coverage for those meeting prophylaxis criteria in our region.
APPENDIX 1. The TREAT Asia HIV Observational Database
PS Ly* and V Khol, National Center for HIV/AIDS, Dermatology & STDs, Phnom Penh, Cambodia; FJ Zhang* ‡, HX Zhao, and N Han, Beijing Ditan Hospital, Capital Medical University, Beijing, China; MP Lee*, PCK Li, W Lam, and YT Chan, Queen Elizabeth Hospital, Hong Kong, China; N Kumarasamy*, S Saghayam, and C Ezhilarasi, Chennai Antiviral Research and Treatment Clinical Research Site (CART CRS), YRGCARE Medical Centre, VHS, Chennai, India; S Pujari*, K Joshi, S Gaikwad, and A Chitalikar, Institute of Infectious Diseases, Pune, India; TP Merati*, DN Wirawan, and F Yuliana, Faculty of Medicine Udayana University & Sanglah Hospital, Bali, Indonesia; E Yunihastuti*, D Imran, and A Widhani, Faculty of Medicine Universitas Indonesia - Dr. Cipto Mangunkusumo General Hospital, Jakarta, Indonesia; J Tanuma*, S Oka, and T Nishijima, National Center for Global Health and Medicine, Tokyo, Japan; JY Choi*, Na S, and JM Kim, Division of Infectious Diseases, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea; BLH Sim*, YM Gani, and R David, Hospital Sungai Buloh, Sungai Buloh, Malaysia; A Kamarulzaman*, SF Syed Omar, S Ponnampalavanar, and I Azwa, University Malaya Medical Centre, Kuala Lumpur, Malaysia; R Ditangco*, MK Pasayan, and R Bantique, Research Institute for Tropical Medicine, Muntinlupa City, Philippines; WW Wong* †, WW Ku, and PC Wu, Taipei Veterans General Hospital, Taipei, Taiwan; OT Ng*, PL Lim, LS Lee, and PS Ohnmar, Tan Tock Seng Hospital, Singapore; A Avihingsanon*, S Gatechompol, P Phanuphak, and C Phadungphon, HIV-NAT/Thai Red Cross AIDS Research Centre, Bangkok, Thailand; S Kiertiburanakul*, A Phuphuakrat, L Chumla, and N Sanmeema, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand; R Chaiwarith*, T Sirisanthana, W Kotarathititum, and J Praparattanapan, Research Institute for Health Sciences, Chiang Mai, Thailand; P Kantipong* and P Kambua, Chiangrai Prachanukroh Hospital, Chiang Rai, Thailand; KV Nguyen*, HV Bui, DTH Nguyen, and DT Nguyen, National Hospital for Tropical Diseases, Hanoi, Vietnam; DD Cuong*, NV An, and NT Luan, Bach Mai Hospital, Hanoi, Vietnam; AH Sohn*, JL Ross,* and B Petersen, TREAT Asia, amfAR - The Foundation for AIDS Research, Bangkok, Thailand; MG Law*, A Jiamsakul,* and DC Boettiger, The Kirby Institute, UNSW Sydney, Sydney, Australia. *TAHOD Steering Committee member; †Steering Committee Chair; ‡co-Chair.
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