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Prevalence, rate, and predictors of virologic failure among adult HIV-Infected clients on second-line antiretroviral therapy (ART) in Tanzania (2018–2020): a retrospective cohort study
Bulletin of the National Research Centre volume 48, Article number: 96 (2024)
Abstract
Background
Antiretroviral therapy (ART) has been proven to be highly effective in reducing the impact of human immunodeficiency virus (HIV) infection. However, as more people receive initial ART treatment, the risk of developing resistance and eventual treatment failure increases, leading to the need for second-line treatment regimens. Understanding the factors that contribute to virologic failure to second-line ART is crucial in preventing switching to the more expensive and toxic third-line regimens. This study provides information on the prevalence, rate, and predictors of virologic failure (VF) among clients on second-line ART in Tanzania.
Results
We followed 4718 clients for 15100 person-years (PY) of observations. Of them, 1402 (29.72%) experienced virologic failure at a rate of 92.85 per 1000 PY of observations (95% CI 88.11, 97.84). Factors that were associated with VF included: having a viral load count of ≥ 1000 copies/mL during first-line ART, with a hazard ratio (HR) 4.65 (95% CI 3.57, 6.07), using lopinavir (LPV/r) as a protease inhibitor during second-line ART (HR 4.20 (95% CI 3.12, 7.10), having a CD4 count < 200 cells/mm3 during second-line ART (HR 1.89 (95% CI 1.46, 2.44), and being on ART for 13–35 months (HR 8.22 (95% CI 2.21, 30.61). Paradoxically, having a CD4 count < 200 cells/mm3 during first-line ART treatment was associated with a reduced risk of virologic failure (HR 0.77 (95% CI 0.60, 0.99).
Conclusions
In Tanzania, approximately 30% of adult clients on second-line ART experience VF at a rate of 92.71 per 1000 person-years. This high virologic failure rate underscores the urgent need for targeted interventions, such as enhancing adherence support, optimizing drug regimens, and regular viral load monitoring. These interventions will reduce the need for switching to the more costly and toxic third-line ART therapy and are also crucial for achieving the UNAIDS goal of 95% viral suppression among treated individuals by 2030.
Background
Worldwide, As of 2022, nearly 39.0 million individuals were living with the Human Immunodeficiency Virus (HIV), with 25.6 million of them residing in Sub-Saharan Africa (SSA) (WHO 2022)
In Tanzania, approximately 1,548,000 adults are living with HIV, with an annual incidence rate of 0.18%, corresponding to around 60,000 new cases of HIV each year (THIS 2022). Regional HIV prevalence ranges from 0.5% in Zanzibar to 11.4% in Njombe (UNAIDS 2023).
For people living with HIV (PLHIV), early initiation of antiretroviral therapy (ART) is crucial for improving viral suppression and increasing life expectancy (Nwokolo et al. 2017; Trickey et al. 2017; Rodger et al. 2019). Currently, it is estimated that 29.8 million PLHIV are receiving ART in the world, 15 million of them in SSA and 1.2 million in Tanzania (THIS 2022).
With the increased availability of ART and as more individuals starting first-line ART, the risk of viral resistance and eventual treatment failure has escalated (Barabona et al. 2019; Pingarilho et al. 2020; Temereanca and Ruta 2023), necessitating the need to switch to second-line treatment regimens. Studies conducted in African countries have found the proportion of individuals switching to second-line treatment to range between 62.2 and 67.45% (Ramadhani et al. 2016; Alemu et al. 2022), and this number is projected to increase significantly by 2030 (Rodger et al. 2019).
Failure to second-line ART regimens pose a specific problem, especially in low-income countries since their access to third-line treatment regimens is very limited due to financial and logistic constraints (Olakunde et al. 2019). Third-line ART regimens are estimated to cost seven times as much as second-line ART regimens and require more resources for the provision of care and treatment (Cesar et al. 2014; Musana et al. 2021).
Most of the studies in Tanzania have focused on virologic failure (VF) among PLHIV who are on first-line ART (Hawkins et al. 2016) and have shown an increase in prevalence rates, from 14.9% in 2016 to 23% and 32.8% in 2021 (Mazuguni et al. 2021; Mchomvu et al. 2022). Information on VF among clients on second-line ART is limited and pertains to specific regions of the country. A study conducted in north-western Tanzania reported a prevalence of 12.18%, while another study in the Morogoro region found a prevalence of 13.1% (Gunda et al. 2019; Bircher et al. 2020). A more recent Tanzania Health Indicator Survey (THIS), which was conducted in 2022, revealed significant regional variations, ranging from 6.5% in Tanga to 34.2% in Tabora (THIS 2022). Unfortunately, nationwide estimates of failure to second-line ART regimens is missing. We conducted this study, to provide national estimates on the prevalence, rate, and factors associated with VF among adult HIV-positive clients on second-line ART in Tanzania. Unlike many previous studies, we also explored possible factors during first-line treatment that could predict failure in the second line. We hypothesized that with the increased use of second-line ART regimens, the likelihood of having clients experiencing VF will increase.
Methods
Study design and setting
This retrospective cohort study involved data analysis from the CTC2 database, an electronic system for HIV/AIDS Care and Treatment clinics. The analysis covered all 26 regions of mainland Tanzania and included 6206 health facilities that offer ART services, of them 2,103 were care and treatment centers (CTCs) and 4103 were Prevention of Mother to Child Transmission (PMTCT) facilities. The latter facilities do provide Option B + services, which refers to the provision of ART to all breastfeeding and pregnant women living with HIV, regardless of CD4 count or clinical stage. As of December 2018, approximately 3800 facilities had submitted data to the CTC2 database.
As demonstrated in Fig. 1 below, failure to second-line ART has been associated to; demographic factors like age (Gumede et al. 2022), sex (Gunda et al. 2019; Zakaria et al. 2022) and facility type/level (Nsanzimana et al. 2019; Gumede et al. 2022); clinical factors like CD4 count (Gunda et al. 2019; Gumede et al. 2022; Zakaria et al. 2022), WHO clinical stage (Nsanzimana et al. 2019) and co-morbidities like TB (Zakaria et al. 2022) As well as; regimen related factors that includes type of regimen used (Zakaria et al. 2022; Masresha et al. 2023) Duration on ART (Gunda et al. 2019) and adherence level (Zakaria et al. 2022).
Study participants
We enrolled all adult clients aged 15 years and older, who were receiving second-line ART between January 2018 and December 2020. We excluded clients on second-line ART for less than six months and those missing HIV viral load results.
Sample size estimation
The sample size estimation was calculated using the Open-Epi Version 3.1.01. Based on a study conducted in Tanzania that reported a VF of 12.18% (Gunda et al. 2019) the estimated minimum sample size was 1147. As shown in Fig. 2 below we enrolled a total of 4718 clients.
Dependent variable
In this study, the dependent variable was virologic failure, which was defined as having two consecutive viral load results of ≥ 1000 virus copies per mL of blood.
Independent variables
The independent variables were demographic characteristics (age, sex, marital status, facility details, and geographical location within the country), medical and clinical characteristics as follows: Regimens were categorized as Nucleoside Reverse Transcriptase Inhibitors (NRTI) backbone, Integrase Strand Transfer Inhibitors (INSTI), Non-Nucleoside Reverse Transcriptase Inhibitors (NNRTI) and Protease Inhibitors (PI) (2019). Adherence was considered to be good if it was ≥ 95% (< 2 doses of 30 doses or < 30 doss of 60 doses is missed) and poor if it was between 85 and 94% (3–5 doses of 30 doses or 3–9 doses of 60 doses is missed) (Legesse and Reta 2019) and the cumulative duration on ART was categorized as ≤ 12 months, 13–35 months, 36–59 months, and ≥ 60 months.
Further, categorization of clinical characteristics was based on WHO stages (I, II, III, and IV), CD4 count (≥ 200 cells/mm3 and < 200 cells/mm3), and TB diagnosis.
Observations were censored at death, loss to follow-up, or when second-line ART was discontinued for reasons other than failure.
Data analysis
For continuous and categorical variables we calculated frequencies, median, interquartile ranges (IQR), means, and standard deviations (SD). Person-time at risk was calculated as the time interval from when a patient switched to the second-line regimen to the end of follow-up. The rate of VF was calculated as number of clients with virologic failure per total person-time at risk for the follow-up period, while the prevalence of VF was calculated as the proportion of clients on second-line ART who experienced virologic failure.
We used the multivariable Cox proportional hazard models to assess independent causes of VF, including age, sex, marital status, facility level, facility ownership, regimen use history, TB co-infection, WHO stage, CD4 count, and adherence level. Bivariate analysis was used to assess the potential determinant factors of VF, and those with a p value of less than or equal to 0.2 were included in the multivariable model. Factors with a p ≤ 0.05 were considered to be significantly associated with VF in clients receiving second-line ART.
Results
Socio-demographic characteristics of clients on second-line ART
We reviewed the records of 4718 adult HIV-positive clients who were on second-line ART. The average age of the clients was 42.08 (± 15.47) years. Of them, 2817 (59.71%) were females, and 2440 (51.72%) were married. Most clients 4360 (92.65%) received care in public health facilities, and most of the 3025 (64.12%) were attending clinic-level health facilities. Geographically the Eastern zone contributed 1719 (36.53%) of the enrolled clients.
Virological, immunological, and clinical characteristics of HIV clients during first-line and second-line ART
During the first-line ART, 2160 (46.39%) clients were in WHO clinical stage III, and 2050 (61.10%) had viral load count of < 1000 cp/mL, with 2126 (53.01%) having a CD4 count of less than < 200 cells/mm3. When initiating second-line ART, half of the clients (2396 or 50.78%) were in WHO clinical stage III, and 1690 (59.93%) had a CD4 count of ≥ 200 cells/mm3. During the first-line ART 107 (2.30%) clients had a history of TB, compared to 44 (0.93%) during the second-line ART.
ART regimens offered to HIV-positive clients on second-line ART (insights from first-line therapy)
Most clients, 4438 (94.07%), had been on antiretroviral therapy for 60 months or more, with 1854 (41.14%) clients initiated on zidovudine (AZT) as part of their NRTI backbone, while 3317 (74.39%) were initiated on efavirenz (EFV)/nevirapine (NVP) as NNRTI. On switching to second-line ART regimens, 2274 (51.18%) clients were on lopinavir, while 2339 (56.63%) used tenofovir disoproxil fumarate (TDF) as their NRTIs, and adherence was good (> 95%) during both first- and second-line ART.
The rate of virological failure among HIV-positive adult clients on second-line ART
This study observed 4718 clients for a total of 15100 person-years (PY), of whom 1402 (29.72%) experienced virological failure during second-line ART. The overall rate of VF was 92.85 (95% CI 88.11–97.84) per 1000 PY of observations.
The rate of VF was high among clients aged 35–44 years, 118.99(95% CI 106.34–133.14), and was lower among those aged ≥ 55 years, 52.52 (95% CI 45.38, 60.78). Single clients had a higher failure rate of 122.61 (95% CI 112.64, 133.46) than those who were married 78.48 (95% CI 72.49, 84.96).
There was no significantly difference in VF between clients receiving care from private facilities 94.87 (95% CI 79.02, 113.89) and those receiving services in public facilities 92.71 (95% CI 87.77, 97.92). In comparison, clients receiving care in health centers had the highest VF at 135.53 (95% CI 117.57, 156.24) compared to those attending clinics at 78.22 (73.11, 83.69) (Table 1).
Rate of virological failure to second-line ART across regions of Tanzania
As shown in Fig. 3 below, Ruvuma and Mtwara regions had the highest rates of VF(140-154 per 1000 person-years), followed by Pwani and Songwe regions (120-139 per 1000 person-years) while Kagera had the lowest rate (48-59 per 1000 person-years).
Virological failure rates across immunological, virological, and clinical characteristics during first and second-line antiretroviral therapy
During first-line ART, a higher rate of VF was observed among clients with an initial viral load count of ≥ 1000 cp/mL 235.99 (95% CI 216.70, 257.01) than those with an initial viral load count < 1000/mL 62.75 (95% CI 57.23, 68.81). Clients with TB had a higher failure rate of 112.55 (95% CI 81.54, 155.33) than those without TB, 92.48 (95% CI 87.67, 97.54) (Table 2).
Virological failure rates classified by regimen use history in first and second-line antiretroviral therapy
During the first-line ART, clients who were on TDF, as NRTI had higher failure rates at 135.39 (95% CI 118.74, 154.38) compared to those on AZT 104.04 (95% CI 94.09, 111.66) and ABC 105 at 123.24 (39.50, 280.41). In addition, those who used NNRTI had a twofold higher failure rate at 100.56 (95% CI 94.47, 107.05) than those who used INSTI at 62.02 (95% CI 53.14, 72.38).
During the second line, the rate of VF was two times higher among those who used ATV/r 135.10 (95% CI 124.16, 147.02) than those on LPV/r 73.21 (95% CI 67.78, 78.98). Moreover, clients who were on ART for 13–35 months had a higher VF rate of 331.93(95% CI 22.48, 495.22) than other groups, and the lowest rate reported among those on ART for > 60 months was 89.01(95% CI 84.49, 94.15) (Table 3).
Predictors of virological failure among adult HIV clients on second-line ART
On bivariate analysis, individuals aged 35–44 years had a 2.35-fold increased risk (95% CI 1.95, 2.82) of virologic failure, while clients receiving care from health centers had a 1.83-fold increase (95% CI 1.56, 2.14). Regarding the type of ART regimen, clients who were on TDF (NRTI) had a 2.25 times increase (95% CI 1.19, 2.65), and those on NNRTI during first-line ART had a 1.56-fold increase (95% CI 1.31, 1.86). Clients with poor adherence during second-line ART had a 2.13 times higher risk of failing (95% CI 1.71, 2.65). However, these associations did not remain significant after adjusting for confounders in multivariate analysis.
Upon adjusting for confounders, clients with increased risk of VF were those with; an initial viral load of ≥ 1000 copies/mL during first-line ART 4.65 (95% CI 3.57, 6.07), using lopinavir during second-line ART 4.20 (95% CI 3.12, 7.10), being on ART for 13–35 months 8.22 (95% CI 2.21, 30.61), having TB during first-line ART 2.21 (95% CI 1.05, 4.64), receiving care at the dispensary 2.48 (95% CI 1.12, 5.48), and having < 200 cells/mm3 CD4 count during second-line ART 1.89 (95% CI 1.46, 2.44). Paradoxically, individuals with a CD4 count of < 200 cells/mm3 during first-line ART had a reduced risk of VF 0.77 (95% CI 0.60, 0.99) (Table 4).
Discussion
The study provides nationwide estimates of the prevalence, rate, and predictors of virological failure among clients on second-line antiretroviral therapy (ART) in Mainland Tanzania. In addition, the study also examined predictors of VF in the first-line ART that could have contributed to VF during the second-line ART.
Overall, the proportion of VF was found to be 29.72%, at a rate of 92.71 per 1000 person-years, with the highest rates being observed in Mtwara and Ruvuma regions, on the southern part of the country as elaborated in Fig. 3.
Several factors were found to be significantly associated with VF including, initial viral load count of ≥ 1000 copies/mL during first-line ART, using lopinavir as a protease inhibitor during second-line treatment, receiving care in dispensaries (which is the lowest level of caregiving facilities), being on ART for 13–35 months, TB infection during first-line ART, and having CD4 counts < 200 cells/mm3 during second-line ART. Interestingly, clients with CD4 counts < 200 cells/mm3 during first-line ART were found to have a reduced risk of failure.
Comparatively, the proportion of clients experiencing virological failure in this study (30%) over a two-year follow-up period is notably higher than previous findings due to variations in the follow-up periods. Earlier studies in Tanzania reported a virological failure proportion of 12.18% over six months (Gunda et al. 2019), while in Rwanda, virological failure was 12% for 26 months. Our findings are alarming when compared to those of studies conducted in Uganda showing a VF of 23% after five years of follow-up (Sam et al. 2021). The observed magnitude aligns with published data emanating from South Africa showing that 25% of clients receiving second-line ART experience treatment failure, citing poor adherence, delayed switching, and accumulation of PI-resistance mutations as the main determinants (Naidoo et al. 2022).
The rate of VF found in this study (92.71 per 1000 PY) is similar to a study conducted in Ethiopia that reported 98.6 per 1000 PY (Alene et al. 2019), but slightly higher rates of 129 per 1000 PY are reported in South Africa and 150 per 1000 person-years reported in the sub-Saharan Africa region (Collier et al. 2017; Edessa et al. 2019). On the other hand, significantly lower rates have been reported in Northern (61.7 per 1000 PY) and Northwest Ethiopia (72.3 per 1000 PY) (Tsegaye et al. 2016; Haftu et al. 2020). There are several possible explanations for variations seen between studies. We noted differences between studies in defining virological failure. In this study, VF was defined as two consecutive viral load results of ≥ 1000 copies/ml after ≥ six months on second-line ART (WHO 2021), while another study described it as a viral load of > 1000 copies/mL on at least one occasion after ≥ 6 months, finding a VF rate of 129 per 1000 PY (Collier et al. 2017). Another study included both clinical, immunological, mortality, and loss of follow-up factors in defining treatment failure, and ended up with a rate of 61.7 per 1000 PY (Tsegaye et al. 2016). Other possible reasons include geographic differences i) in HIV subtypes (Nastri et al. 2023) and HIV-drug resistance (HIVDR) levels and patterns (Mazzuti et al. 2020), ii) the quality of care and community/social support, and iii) levels of adherence to ART (Fokam et al. 2020). Within Tanzania, the highest rate of VF were observed in Mtwara and Ruvuma, regions that have the highest prevalence of HIV in the country and the highest use of antiretroviral drugs (THIS 2022).
Regarding the treatment regimen, we observed a higher failure rate among clients prescribed LPV/r than those on ATV/r. This finding is similar to the findings of a study conducted in Ethiopia, where ATV/r showed a 13% lower risk of failure than LPV/r (Tigabu et al. 2020). ATV/r has been shown to lower the risk of mortality and the incidence of AIDS-defining illness and to have a more significant 12-month increase in CD4 cell count and less risk of virologic failure at 12 months than LPV/r (Cain 2015). In addition, ATV/r is a well-tolerated drug with a lower pill burden compared to other Protease inhibitors, such as LPV (Sam et al. 2021), and has better oral bioavailability compared with other protease inhibitors (Tigabu et al. 2020).
We observed that clients with a history of TB while on the first-line ART had a significantly higher rate of VF, supporting the findings of a South African study, that reported an eleven times higher rate of VF in clients with TB (Collier et al. 2017), and those of another study conducted in Ethiopia that showed a 2.46 times higher rate of VF among clients with HIV-TB co-infection (Getaneh et al. 2022). This finding is expected since TB has been shown to enhance HIV viral replication and to be associated with poor treatment outcomes (Bell and Noursadeghi 2017; Getaneh et al. 2022). In addition, many clients with TB-HIV co-infection experience adverse side effects due to the high pill burden (Daftary et al. 2014).
In our study, we observed higher VF among clients receiving care at dispensary level 2.48 (1.12, 5.48) compared to those receiving care in health centers 1.30 (95% CI 0.79, 2.13) and hospitals 1.22 (95% CI 0.86, 1.70). This finding is consistent with those of a study conducted in Kenya that reported a high likelihood of failure 1.87 (95% CI 1.29, 2.72) among clients attending lower-level facilities (Masaba et al. 2023). Often, lower facilities are located in less privileged rural areas with relatively poor services such as counselling, community/social support, and quality of healthcare workers, which may impact treatment outcomes (Chakravarty et al. 2015; Diress et al. 2020; Nastri et al. 2023).
We discovered that clients with an initial viral load count of ≥ 1000 cp/mL during the first-line ART had a 4.30 (95% CI 3.43, 5.48) higher risk of failing. A study from Ethiopia reported similar findings, where clients with an initial viral load count of ≥ 5000 cp/mL had a lower probability of suppressing viral load, 0.44 (95% CI 0.28, 0.71) after enhanced adherence counselling (EAC) (Diress et al. 2020). The same findings were also reported in Asia, with a risk of 2.90 (95% CI 1.17–7.18), and in India with an odds ratio of 3.4 (Boettiger et al. 2015; Chakravarty et al. 2015). This collective evidence supports the theory that a high baseline viral load causes delayed or incomplete HIV suppression and a higher risk of viral rebound (Chen et al. 2020).
This study found a significantly greater risk of virological failure in clients who have been on ART for 13–35 months, representing an eightfold increase compared to those on ART for more than 60 months (HR 8.22, 95% CI 2.21, 30.61). There are significant variations concerning the duration of ART and VF. A study conducted in central Ethiopia reported a sevenfold increase in the risk of virological failure (HR 6.93, 95% CI 2.62, 18.33) among clients on ART for 12–23 months compared to those on ART for more than 48 months (Endebu et al. 2018). Another study conducted in northeast Ethiopia (Diress et al. 2020) observed a high risk of failure among those on ART for 36–59 months 0.35 (95% CI 0.130, 0.9491). The observed variations can be explained by differences in the distribution of clients among covariates.
We observed a high likelihood of treatment failure among clients with a CD4 count of less than 200 cells/mm3 during the second-line ART, with a relative risk of 1.77 (95% CI 1.41, 2.22). This supports previous findings that clients with low CD4 T-cell counts experience slower viral clearance and have higher levels of virological failure (Crowell et al. 2021). Interestingly, clients with a CD4 count of less than 200 cells/mm3 during the first-line of ART had a 30% reduction in the likelihood of treatment failure among the clients. These clients probably received intensive care and monitoring due to their medical history while on first-line ART which prompted healthcare workers to pay more attention to them during second-line ART.
Our findings have potential implications for the country. According to the study, 30% of clients receiving second-line ART in Tanzania require switching to the third-line ART regimens. With an estimated 24,000 clients currently on second-line ART (based on unpublished program data), 7,200 clients will need this change. The switch to third-line ART will require expensive phenotypic and genotypic HIVDR testing, expensive and rather toxic ARV drugs, and intensive clinical and laboratory monitoring (Gachogo et al. 2020). The estimated cost of HIV Drug Resistance (HIVDR) is approximately 272 USD per test (Gachogo et al. 2020), while the annual cost of third-line ART for the commonly used regimen such as ritonavir with darunavir, dolutegravir (DTG) and NRTI is close to 920 USD (Naidoo et al. 2022), bringing a total of 1192 USD for laboratory expenses and medication alone. For the estimated number of clients in Tanzania, this would cost the country 8.6 m USD which is equivalent to 0.94% of the entire budget allocated for health in the 2023/2024 budget per year. Additional costs would involve tracking the clients to ensure their clinical and virological outcomes, and regular monitoring and recording of severe adverse reactions.
The present study has several strengths. The study presents, for the first time, nationwide estimates of virological failure among clients on second-line ART, involving all facilities providing HIV care and treatment in Tanzania. Secondly, the data came from a diverse population of clients across various facilities at different levels of health service delivery. Such information is important to the National AIDS, STIs and Hepatitis Control Programme (NASHCoP) and other stakeholders involved in the provision of HIV services in Tanzania to investigate at community, district, regional, and national levels (i) the reasons for the magnitude of VF, (ii) assess the health service quality at different levels, (iii) find the reasons for inadequate individuals’ ART adherence level, and (iv) determine social and behavioral factors that hinder HIV viral load suppression.
However, we do acknowledge, as a limitation, that this is a retrospective study dependent on the completeness of the records. Hence, information bias might have occurred because of underreporting/missing data elements, including CD4 count and viral load, and under-reporting of clinical conditions. Furthermore, the information present in the NASHCoP database lacked information about HIV drug resistance, as this is not done routinely. This information might have furnished more information on VF among the clients.
Conclusions
This study offers valuable insights into the frequency and causes of VF among clients receiving second-line ART in Tanzania. It reveals that approximately 30% of clients on second-line ART experience VF, which hinders progress toward achieving the UNAIDS third 95% target. Addressing the factors associated with VF identified in this study could help reduce the need to switch to more expensive and toxic third-line ART regimens. Tanzania should establish national guidelines for managing clients on third-line ART that consider funding, sustainability, and equitable access for those needing third ART regimens. Furthermore, the type(s) of the third-line ART regimen should be based on the phenotypic and genotypic HIVDR test results.
Availability of data and materials
The data supporting this study's findings are available from the Tanzania National AIDS Control Program, but access to them is restricted and not publicly available.
Abbreviations
- ABC:
-
Abacavir
- AIDS:
-
Acquired Immunodeficiency Syndrome
- ART:
-
Antiretroviral Therapy
- ATV/r:
-
Atazanavir/Ritonavir
- AZT:
-
Zidovudine
- CI:
-
Confidence Interval
- CTC:
-
Care and Treatment Centre
- D4T:
-
Stavudine
- DDI:
-
Didanosine
- DRMs:
-
Drug Resistance Mutations
- DTG:
-
Dolutegravir
- EAC:
-
Enhanced Adherence and Counselling
- EFV:
-
Efavirenz
- HIV:
-
Human Immunodeficiency Virus
- HIVDR:
-
HIV Drug Resistance
- HVL:
-
HIV Viral Load
- HR:
-
Hazard Ratio
- INSTIs:
-
Integrase Strand Transfer Inhibitors
- IQR:
-
Inter Quartile Range
- LPV/r:
-
Lopinavir/ Ritonavir
- NASHCoP:
-
National AIDS, STIs and Hepatitis Control Programe
- NNRTI:
-
Non-Nucleoside Reverse Transcriptase Inhibitors
- NRTI:
-
Nucleoside Reverse Transcriptase Inhibitors
- NVP:
-
Nevirapine
- PIs:
-
Protease Inhibitors
- PLHIV:
-
People Living With HIV/AIDS
- PMTCT:
-
Prevention of Mother To Child Transmission
- PY:
-
Person Years
- SD:
-
Standard Deviation
- SSA:
-
Sub-Saharan Africa
- TB:
-
Tuberculosis
- TDF :
-
Tenofovir Disoproxil Fumarate
- UNAIDS:
-
United Nations Program on HIV and AIDS
- USD:
-
United States Dollar
- VF:
-
Virological Failure
- WHO:
-
World Health Organization
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Acknowledgements
We thank the Ministry of Health for permitting us to use data in conducting this study through the National AIDS Control Program (NACP). We also extend our sincere appreciation to the Tanzania Field Epidemiology and Laboratory Training Program (TFELTP) and the Departments of Epidemiology and Biostatistics and Microbiology and Immunology of the Muhimbili University of Health and Allied Sciences (MUHAS) for their invaluable support and guidance in this research work.
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ETM, NL, D.K, MIM—conceptualized and designed the study, ETM, MIM, PPK, SJM performed data cleaning and analysis, ETM, NL, D.K, MIM—drafted the manuscript. All authors have read and approved the submitted manuscript and take responsibility for the data's integrity and the data analysis's accuracy.
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The study received ethical approval from the Muhimbili University of Health and Allied Sciences (MUHAS) Institutional Review Board (IRB), with reference number MUHAS-REC-05-2023-1697. The researcher obtained permission to use patient data from the Permanent Secretary of the Ministry of Health. The dataset contains no patient-identifying information, such as names and phone numbers.
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Mwavika, E.T., Kunambi, P.P., Masasi, S.J. et al. Prevalence, rate, and predictors of virologic failure among adult HIV-Infected clients on second-line antiretroviral therapy (ART) in Tanzania (2018–2020): a retrospective cohort study. Bull Natl Res Cent 48, 96 (2024). https://doi.org/10.1186/s42269-024-01248-5
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DOI: https://doi.org/10.1186/s42269-024-01248-5