Abstract
Background
Haematological malignancies have continued to be highly prevalent among people living with HIV (PLHIV). This study assessed the occurrence, risk factors for, and outcomes of haematological and non-haematological malignancies in PLHIV in Asia.
Methods
Incidence of malignancy after cohort enrolment was evaluated. Factors associated with development of haematological and non-haematological malignancy were analysed using competing risk regression and survival time using Kaplan-Meier.
Results
Of 7455 patients, 107 patients (1%) developed a malignancy: 34 (0.5%) haematological (0.08 per 100 person-years (/100PY)), and 73 (1%) non-haematological (0.17/100PY). Of the haematological malignancies, non-Hodgkin lymphoma was predominant (n=26, 76%): immunoblastic (n=6, 18%), Burkitt (n=5, 15%), diffuse large B-cell (n=5, 15%), and unspecified (n=10, 30%). Others include central nervous system lymphoma (n=7, 21%), and myelodysplastic syndrome (n=1, 3%). Non-haematological malignancies were mostly Kaposi’s sarcoma (n=12, 16%) and cervical cancer (n=10, 14%). Risk factors for haematological malignancy included age >50 vs. ≤30 years (sub-hazard ratio [SHR]=6.48, 95%CI 1.79–23.43), and being from a high-income vs. a lower-middle-income country (SHR=3.97, 95%CI 1.45–10.84). Risk was reduced with CD4 351–500 cells/µL (SHR=0.20, 95%CI 0.05–0.74), and CD4 >500 cells/µL (SHR=0.14, 95%CI 0.04–0.78), compared to CD4 ≤200 cells/µL. Similar risk factors were seen for non-haematological malignancy, with prior AIDS diagnosis showing a weak association. Patients diagnosed with a haematological malignancy had shorter survival time compared to non-haematological malignancy.
Conclusions
Non-haematological malignancies were common but NHL was more predominant in our cohort. PLHIV from high-income countries were more likely to be diagnosed, indicating a potential under-diagnosis of cancer in low-income settings.
Keywords: Cancer, HIV, Asia, lymphoma, resource-limited
Introduction
People living with HIV (PLHIV) have an increased risk of developing a haematological malignancy compared to the general population 1. Since the introduction of combination antiretroviral therapy (ART), there has been an increase in the proportion of deaths attributed to malignancies, and a change in the types of malignancies commonly seen. Diagnoses of Hodgkin lymphoma (HL), lung cancer, and non-melanoma skin cancers have risen. Cervical cancer and Burkitt lymphoma (BL) incidence has not changed 2, while the incidence of Kaposi’s sarcoma (KS), central nervous system (CNS) lymphoma, and diffuse large B-cell lymphoma (DLBCL) have fallen 3.
Haematological malignancies, particularly non-Hodgkin lymphoma (NHL), remain highly prevalent among PLHIV, and are considered to be associated with the most common cancer-related cause of death 2. In resource-rich settings, the most reported cancers were NHL, followed by lung cancer, KS, anal cancer, prostate cancer, liver cancer and HL 4. In sub-Saharan Africa, KS is the most common and is often associated with high mortality 5. Other highly prevalent cancers include cervical cancer, breast cancer, and NHL 6.
In Asia, there is limited data on malignancies among PLHIV, which may differ from other regions due to genetic and environmental factors, including differing incidence of infections with oncogenic viruses associated with malignancy. For example, breast cancer incidence in Taiwan, occurs at a lower median age compared to Western countries, with different molecular subtypes 7. In a linkage study conducted in India, no cases of KS were reported, which was in contrast to reported findings from the African region 8. The European COHERE cohort found a significant risk for AIDS-related NHL among male-to-male sex (MSM) and older age groups 9, however the risk in South African women was reportedly higher than those in Europe 10.
The aim of this study was to investigate the occurrence, risk factors and survival outcomes associated with haematological and non-haematological malignancies, in PLHIV in Asia enrolled in the TREAT Asia HIV Observational Database (TAHOD) of IeDEA Asia-Pacific.
Methods
Patients enrolled in TAHOD who had ever initiated ART with at least one day of follow-up after cohort entry were included in the analysis. The TAHOD cohort profile has been described elsewhere 11,12, but briefly TAHOD is an adult HIV observational database which enrols selected number of patients from each participating site based on their likelihood of remaining in follow-up. Due to the prospective nature of TAHOD data collection, we limited our analyses to first malignancy diagnosed either before or after ART initiation but post- cohort entry. Malignancies were reported descriptively, and categorised as either haematological or non-haematological. We calculated incidence rates (per 100 person-years (/100PY)) and assessed factors associated with haematological and non-haematological malignancy using Fine and Gray competing risk methods. Time fixed covariates included age at cohort entry, sex, HIV mode of exposure, hepatitis B/C co-infection, prior AIDS diagnosis and World Bank country income level. CD4, viral load (VL), ART duration and calendar year of follow-up were time-updated variables. With the exception of the ART duration variable, covariates in the univariate analysis with p<0.10 were fitted in the multivariate model using backward stepwise selection process. Covariates with p<0.05 in the multivariate model were considered significant. Survival time from malignancy diagnosis was plotted using Kaplan-Meier curves and compared using the log-rank test.
Ethics approvals were obtained from respective local ethics committees of all participating sites, the data management and biostatistical center (UNSW Sydney Ethics Committee), and the coordinating centre (TREAT Asia/amfAR). Data management and statistical analyses were performed using SAS software version 9.4 (SAS Institute Inc., Cary, NC, USA) and Stata software version 14.2 (Stata Corp., College Station, TX, USA).
Results
A total of 7455 patients were included from Cambodia, China and Hong Kong SAR, India, Indonesia, Japan, Malaysia, the Philippines, Singapore, South Korea, Taiwan, Thailand and Vietnam. There were 70% males, with 63% reporting heterosexual mode of HIV exposure. At cohort entry, the median age was 35 years (IQR: 30–42) and the median CD4 cell count was 248 cells/µL (IQR: 117–397). The median nadir CD4 count within one year prior to cohort entry was 206 cells/µL (IQR: 82–339). In the group with haematological malignancy, the median nadir CD4 count was lower at 142 cells/µL (IQR: 27–264). Those with non-haematological malignancy had a median nadir CD4 count of 133 cells/µL (IQR:78–266). World Bank high-income countries had the highest proportions of cancers (47% for haematological and 44% for non-haematological) and 60% of the patients with a malignancy were diagnosed from year 2010 onwards (Table 1). The median time on ART up to the date of malignancy diagnosis or analysis censoring date was 6.3 years (IQR:4.0–9.6).
Table 1:
Patient characteristics
| Total patients (%) N = 7455 (100) |
Number of patients with a haematological malignancy (%) N = 34 (0.5%) |
Number of patients with a non- haematological malignancy (%) N = 73 (1%) |
|
|---|---|---|---|
| Age at cohort entry (years) | Median = 35, IQR (30–42) | Median = 43, IQR (33–54) | Median = 42, IQR (34–53) |
| Sex | |||
| Male | 5206 (70) | 25 (74) | 53 (73) |
| Female | 2249 (30) | 9 (26) | 20 (27) |
| HIV mode of exposure | |||
| Heterosexual contact | 4727 (63) | 22 (65) | 49 (67) |
| MSM | 1596 (21) | 8 (24) | 17 (23) |
| Other/Unknown | 1132 (15) | 4 (12) | 7 (10) |
| Viral Load at cohort entry (copies/mL) | Median = 2790, IQR (49–91000) | Median = 19300, IQR (278.5–210000) | Median = 8130, IQR (49–840000) |
| CD4 count at cohort entry (cells/µL) | Median = 248, IQR (117–397) | Median = 218, IQR (53–264) | Median = 182.5, IQR (98–326) |
|
Nadir CD4 count prior to cohort entry
(cells/µL) |
Median = 206, IQR (82–339) | Median = 142, IQR (27–264) | Median = 133, IQR (78–266) |
| On ART at cohort entry | |||
| No | 1596 (21) | 12 (35) | 19 (26) |
| Yes | 5859 (79) | 22 (65) | 54 (74) |
| Hepatitis B co-infection | |||
| Negative | 5150 (69) | 26 (76) | 53 (73) |
| Positive | 590 (8) | 3 (9) | 10 (14) |
| Not tested | 1715 (23) | 5 (15) | 10 (14) |
| Hepatitis C co-infection | |||
| Negative | 4525 (61) | 23 (68) | 54 (74) |
| Positive | 819 (11) | 4 (12) | 6 (8) |
| Not tested | 2111 (28) | 7 (21) | 13 (18) |
| AIDS diagnosis prior to cohort entry | |||
| No | 4458 (60) | 17 (50) | 33 (45) |
| Yes | 2997 (40) | 17 (50) | 40 (55) |
| Country income | |||
| Lower middle | 3132 (42) | 7 (21) | 12 (16) |
| Upper middle | 2805 (38) | 11 (32) | 29 (40) |
| High | 1518 (20) | 16 (47) | 32 (44) |
| Year of cancer diagnosis | |||
| 2003–2005 | 10 (9) | 5 (15) | 5 (7) |
| 2006–2009 | 33 (31) | 11 (32) | 22 (30) |
| 2010–2015 | 64 (60) | 18 (53) | 46 (63) |
Between years 2001–2016, 107 patients (1%) had a malignancy diagnosis recorded: 34 (0.5%) haematological malignancies and 73 (1%) non-haematological malignancies. Of the haematological malignancies, NHL was the most common (26 patients, 76%): immunoblastic lymphoma (6 patients, 18%), BL (5 patients, 15%), DLBCL (5 patients, 15%), and unspecified NHL (n=10, 30%). Other haematological malignancies were CNS lymphoma (7 patients, 21%), and myelodysplastic syndrome (1 patient, 3%). The most common non-haematological malignancies were KS (12 patients, 16%), cervical (10 patients, 14%), liver (8 patients, 11%), colon (7 patients, 10%), lung (5 patients, 7%), and colon cancer (5 patients, 7%).
With a median cohort follow-up time of 5.5 years, the incidence rates for haematological and non-haematological malignancy were 0.08 and 0.17/100PY, respectively. The incidence rates for haematological malignancies by calendar year of follow-up were: 0.16/100PY for ≤2005, 0.10/100PY for 2006–2009 and 0.06/100PY for 2010–2016. For non-haematological malignancies, the rates were 0.16/100PY, 0.21/100PY, and 0.16/100PY for the three time periods. Factors associated with developing a malignancy after cohort entry were analysed and reported in Table 2. In the univariate competing risk analysis, factors associated with developing a haematological malignancy were older age (p<0.001), lower CD4 cell count categories (p=0.005), shorter ART duration (p=0.073) and World Bank high-income level (p=0.001). No significant trend in calendar year was observed (p-value =0.920). In multivariate analysis controlling for ART duration, age >50 years compared to ≤30 years at cohort entry (sub-hazard ratio (SHR)=6.48, 95%CI 1.79–23.43, p=0.004), and being from a World Bank high-income country (SHR=3.97, 95%CI 1.45–10.84, p=0.007), were associated with a haematological malignancy diagnosis. The hazard was reduced with higher CD4 count compared to CD4 ≤200 cells/µL (CD4 351–500 cells/µL: SHR=0.20, 95%CI 0.05–0.74, p=0.016; CD4 >500 cells/µL: SHR=0.14, 95%CI 0.04–0.78, p=0.022). ART duration was not associated with haematological malignancy diagnosis (p=0.286).
Table 2:
Factors associated with haematological and non-haematological malignancy diagnosis after cohort entry
| Haematological malignancy | Non-haematological malignancy | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Univariate | Multivariate | Univariate | Multivariate | |||||||||||
| Incidence rate (/100py) |
SHR | 95% CI | p-value | SHR | 95% CI | p-value | Incidence rate (/100py) |
SHR | 95% CI | p-value | SHR | 95% CI | p-value | |
| Total | 0.08 | 0.17 | ||||||||||||
| Calendar year | *0.920 | *0.437 | ||||||||||||
| ≤2005 | 0.16 | 1 | 0.16 | 1 | ||||||||||
| 2006–2009 | 0.10 | 1.23 | (0.41, 3.66) | 0.711 | 0.21 | 1.42 | (0.51, 3.99) | 0.502 | ||||||
| 2010–2016 | 0.06 | 1.12 | (0.39, 3.16) | 0.837 | 0.16 | 1.01 | (0.38, 2.66) | 0.992 | ||||||
| Age at cohort entry (years) | <0.001 | 0.011 | <0.001 | <0.001 | ||||||||||
| ≤30 | 0.04 | 1 | 1 | 0.06 | 1 | 1 | ||||||||
| 31–40 | 0.06 | 1.66 | (0.53, 5.21) | 0.386 | 1.80 | (0.55, 5.85) | 0.328 | 0.12 | 1.99 | (0.86, 4.61) | 0.109 | 1.79 | (0.77, 4.16) | 0.176 |
| 41–50 | 0.08 | 2.25 | (0.66, 7.70) | 0.195 | 2.00 | (0.55, 7.33) | 0.294 | 0.21 | 3.46 | (1.46, 8.21) | 0.005 | 2.67 | (1.11, 6.38) | 0.028 |
| >50 | 0.31 | 8.90 | (2.87, 27.61) | <0.001 | 6.48 | (1.79, 23.43) | 0.004 | 0.6 | 9.42 | (4.04, 21.96) | <0.001 | 6.60 | (2.88, 15.13) | <0.001 |
| Sex | ||||||||||||||
| Male | 0.08 | 1 | 0.18 | 1 | ||||||||||
| Female | 0.07 | 0.83 | (0.39, 1.79) | 0.641 | 0.15 | 0.88 | (0.53, 1.48) | 0.641 | ||||||
| HIV mode of exposure | 0.855 | 0.476 | ||||||||||||
| Heterosexual contact | 0.08 | 1 | 0.17 | 1 | ||||||||||
| MSM | 0.09 | 1.12 | (0.50, 2.52) | 0.779 | 0.19 | 1.15 | (0.66, 2.00) | 0.611 | ||||||
| Other/Unknown | 0.07 | 0.80 | (0.27, 2.31) | 0.676 | 0.12 | 0.67 | (0.30, 1.47) | 0.318 | ||||||
| Viral Load (copies/mL) | ||||||||||||||
| ≤1000 | 0.06 | 1 | 0.18 | 1 | ||||||||||
| >1000 | 0.17 | 1.23 | (0.51, 2.97) | 0.640 | 0.28 | 1.23 | (0.70, 2.14) | 0.474 | ||||||
| Not done | 0.08 | 0.07 | ||||||||||||
| CD4 (cells/µL) | 0.005 | 0.032 | 0.004 | 0.002 | ||||||||||
| ≤200 | 0.28 | 1 | 1 | 0.40 | 1 | 1 | ||||||||
| 201–350 | 0.12 | 0.67 | (0.31, 1.45) | 0.312 | 0.66 | (0.29, 1.53) | 0.333 | 0.13 | 0.42 | (0.21, 0.84) | 0.014 | 0.34 | (0.16, 0.72) | 0.005 |
| 351–500 | 0.03 | 0.18 | (0.05, 0.64) | 0.008 | 0.20 | (0.05, 0.74) | 0.016 | 0.09 | 0.29 | (0.14, 0.60) | 0.001 | 0.24 | (0.11, 0.51) | <0.001 |
| >500 | 0.02 | 0.16 | (0.04, 0.57) | 0.005 | 0.18 | (0.04, 0.78) | 0.022 | 0.17 | 0.52 | (0.30, 0.92) | 0.024 | 0.45 | (0.23, 0.88) | 0.019 |
| Not done | 0 | 0.17 | ||||||||||||
| ART duration | 0.073 | 0.286 | 0.024 | 0.206 | ||||||||||
| Not on ART | 0.05 | 0.17 | (0.02, 1.57) | 0.118 | 0.29 | (0.03, 2.60) | 0.266 | 0.11 | 0.32 | (0.07, 1.48) | 0.145 | 0.85 | (0.17, 4.24) | 0.846 |
| <3 months | 0.71 | 1 | 1 | 0.57 | 1 | 1 | ||||||||
| 3 months to <1 year | 0.24 | 0.51 | (0.16, 1.66) | 0.263 | 0.67 | (0.21, 2.11) | 0.496 | 0.14 | 0.24 | (0.08, 0.77) | 0.016 | 0.35 | (0.11, 1.18) | 0.090 |
| 1 year to <5 years | 0.09 | 0.40 | (0.14, 1.16) | 0.092 | 0.67 | (0.23, 2.01) | 0.477 | 0.13 | 0.39 | (0.19, 0.84) | 0.016 | 0.77 | (0.32, 1.81) | 0.544 |
| ≥5 years | 0.02 | 0.14 | (0.03, 0.59) | 0.007 | 0.26 | (0.06, 1.21) | 0.087 | 0.21 | 0.68 | (0.32, 1.43) | 0.307 | 1.19 | (0.50, 2.86) | 0.696 |
| Hepatitis B co-infection | ||||||||||||||
| Negative | 0.08 | 1 | 0.17 | 1 | ||||||||||
| Positive | 0.09 | 1.01 | (0.31, 3.34) | 0.983 | 0.29 | 1.67 | (0.85, 3.28) | 0.138 | ||||||
| Not tested | 0.05 | 0.11 | ||||||||||||
| Hepatitis C co-infection | ||||||||||||||
| Negative | 0.08 | 1 | 0.19 | 1 | ||||||||||
| Positive | 0.10 | 1.02 | (0.35, 2.96) | 0.971 | 0.15 | 0.70 | (0.30, 1.64) | 0.412 | ||||||
| Not tested | 0.06 | 0.11 | ||||||||||||
| AIDS Diagnosis prior to cohort entry | ||||||||||||||
| No | 0.07 | 1 | 0.13 | 1 | 1 | |||||||||
| Yes | 0.10 | 1.48 | (0.75, 2.90) | 0.254 | 0.23 | 1.75 | (1.10, 2.77) | 0.018 | 1.60 | (0.99, 2.59) | 0.054 | |||
| World Bank country income | 0.001 | 0.009 | <0.001 | <0.001 | ||||||||||
| Lower middle | 0.04 | 1 | 1 | 0.07 | 1 | 1 | ||||||||
| Upper middle | 0.06 | 1.65 | (0.64, 4.28) | 0.299 | 1.27 | (0.47, 3.41) | 0.634 | 0.17 | 2.25 | (1.14, 4.46) | 0.019 | 2.15 | (1.11, 4.15) | 0.023 |
| High | 0.16 | 4.49 | (1.87, 10.76) | 0.001 | 3.97 | (1.45, 10.84) | 0.007 | 0.33 | 4.84 | (2.47, 9.48) | <0.001 | 3.96 | (2.09, 7.50) | <0.001 |
ART-antiretroviral therapy
P-values in bold represent significant covariates in the final model.
Global p-values for calendar year are test for trend.
Other global p-values are test for heterogeneity excluding missing values.
Calendar year, CD4, VL, and ART duration are time-updated variables
Multivariate risk factors associated with non-haematological malignancy were older age 41–50 years (SHR=2.67, 95%CI 1.11–6.38, p=0.028) and age >50 years (SHR=6.60, 95%CI 2.88–15.13, p<0.001), compared to ≤30 years; and living in upper middle-income country (SHR=2.15, 95%CI 1.11–4.15, p=0.023) or high-income country (SHR=3.96, 95%CI 2.09–7.50, p<0.001), compared to lower-middle-income country. Having prior AIDS diagnosis (SHR=1.60, 95%CI 0.99–2.59, p=0.054) was borderline significant and was included in the multivariate model. Higher CD4 cell count showed a protective effect (CD4 201–350 cells/µL: SHR=0.34, 95%CI 0.16–0.72, p=0.005; CD4 351–500 cells/µL: SHR=0.24, 95%CI 0.11–0.51, p<0.001; and CD4 >500 cells/ µL: SHR=0.45, 95%CI 0.23–0.88, p=0.019), compared to CD4 ≤200 cells/µL. Similar to the haematological malignancy analysis, ART duration was not statistically significant (p=0.206), but was adjusted for in the final model.
Of the 107 patients with a malignancy, 77 (72%) had survival information available after the diagnosis and were included in the plot (Supplementary figure S1). There were 27 deaths (mortality rate 15/100PY). Among those with a haematological malignancy, there were 13/25 deaths (52%) with a mortality rate of 29/100PY, which was higher than 10/100PY mortality rate for the 14/52 deaths (27%) in the non-haematological malignancy group (p=0.009). PLHIV diagnosed with a haematological malignancy had poorer survival time compared to those with a non-haematological malignancy (p log-rank=0.008).
Discussion
There is a significant burden of malignancies in PLHIV across the Asian region. In our cohort, non-haematological malignancies were more common than haematological malignancies. However, NHL was the most predominant diagnosis overall. PLHIV of older age and from high-income countries were more likely to develop a haematological malignancy, while the risk was reduced in those with higher CD4 count. Similar risk factors were seen for non-haematological malignancy, with prior AIDS diagnosis showing a weak association. Survival time from malignancy diagnosis was longer in those with non-haematological malignancies.
The proportion of patients with haematological malignancies, mostly NHL, in our cohort was 0.5%, which was within the range of 0.3% to 2.5% reported in other cohorts 13,14. For non-haematological malignancies, liver and lung cancers are known to be two of the most common types of cancers in Asia, with lung cancer being the most common cause of cancer-related mortality and the second most common cancer in PLHIV4,7,15. In our study, liver cancer was the third most common non-haematological cancer after KS and cervical cancer.
Our study found that there was a reduced risk of developing malignancies with higher CD4 cell count, supporting the role of immunodeficiency as a risk factor for malignancies in PLHIV 16. Other factors such as time on ART and year of follow-up could also play an important role. Incidence rates for malignancy, particularly for KS and NHL, have been shown to decrease with increasing duration of ART use, after controlling for CD4 cell count, suggesting ART may have anti-cancer benefits 17. Our study found that although the hazards for malignancy diagnosis were reduced with longer ART duration, the effects were not statistically significant after adjusting for CD4 cell count and other significant confounders. Furthermore, due to effective ART, the incidence of malignancy diagnosis in PLHIV has decreased over time with future decline predicted for many malignancy types 18. Our study, however, did not show a decreasing trend for malignancy in both groups.
The relationship between age and malignancies is well established, however, we found people living in high-income countries were more likely to be diagnosed with either of the two types of malignancies. This may reflect the limited availability of diagnostic and treatment facilities in lower-income areas contributing to under-diagnosis of malignant disorders 19. Other confounders may include earlier ART initiation, availability of more potent ART, and less opportunistic infections causing competing mortality in high-income sites 20,21.
Previous literatures have reported an association between HIV viraemia and the development of malignancy 16,22. A Spanish cohort study has shown that low-level viraemia can also lead to increased risk of AIDS-defining events and/or mortality 23. VL was not a significant predictor in our analyses, however the weak effect of prior AIDS-illnesses on non haematological malignancy occurrence seen in our cohort is unlikely to be direct, more probably reflecting underlying interactions with either HIV viral replication, inflammation, or immune dysfunction.
Survival time after malignancy diagnosis was found to be shorter in those with a haematological malignancy. Poorer survival prognosis in those with haematological malignancies could be explained by the high proportion of aggressive forms of NHL in this group. NHL has been shown to be associated with lower survival rates compared to KS and cervical cancer, the two most common non-haematological malignancies in our cohort 24.
The limitations of our study included not being able to obtain histological or pathological reports from sites. These reports were not collected as part of TAHOD data transfers, and therefore we were not able re-assessing the accuracy of the malignancy classifications. We did not have detailed clinical parameters and treatment protocols associated with a new malignancy diagnosis, and were not able to analyse survival outcomes across different malignancy types in detail. Furthermore, because TAHOD does not collect data on HIV-negative patients, direct comparison with the HIV-negative population could not be attempted. Lastly, as TAHOD patients were enrolled based on the likelihood of remaining in care with small number of malignancies diagnosed, the generalisability of our findings may be limited.
Conclusions
Although there was a higher proportion of non-haematological malignancies in our cohort with KS and cervical cancer being the two most common, NHL was predominant overall. Malignancy occurrence was more likely in PLHIV from high-income countries indicating that there is a possible under-diagnosis in resource-limited settings. Further systematic data on incidence are needed, as are novel diagnostic tools applicable in low- and middle-income countries.
Supplementary Material
Acknowledgements
Source of Funding
The TREAT Asia HIV Observational Database is an initiative of TREAT Asia, a program of amfAR, The Foundation for AIDS Research, with support from the U.S. National Institutes of Health’s National Institute of Allergy and Infectious Diseases, the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the National Cancer Institute, the National Institute of Mental Health, and the National Institute on Drug Abuse, as part of the International Epidemiology Databases to Evaluate AIDS (IeDEA; U01AI069907). The Kirby Institute is funded by the Australian Government Department of Health and Ageing, and is affiliated with the Faculty of Medicine, UNSW Sydney. The content of this publication is solely the responsibility of the authors and does not necessarily represent the official views of any of the governments or institutions mentioned above.
Footnotes
Conflicts of interest
All authors stated that they have no conflicts of interest.
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 SAR
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
S Sangle*, V Mave and I Marbaniang, BJ Government Medical College and Sassoon General Hospital, 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 NB Rudi, 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 ML Mationg, 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 Z Ferdous, 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
S Khusuwan*, 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
CD Do*, AV Ngo and LT Nguyen, Bach Mai Hospital, Hanoi, Vietnam
AH Sohn*, JL Ross* and B Petersen, TREAT Asia, amfAR - The Foundation for AIDS Research, Bangkok, Thailand
DA Cooper, MG Law*, A Jiamsakul* and D Rupasinghe, The Kirby Institute, UNSW Sydney, NSW, Australia.
* TAHOD Steering Committee member; † Steering Committee Chair; ‡ co-Chair
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