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

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 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article 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cohort study ESTER TIMOTHY MWAVIKA, Peter Ponsian Kunambi, Samuel Joseph Masasi, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4744820/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Oct, 2024 Read the published version in Bulletin of the National Research Centre → Version 1 posted 4 You are reading this latest preprint version 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 4,718 clients for 15,100 person-years (PY) of observations. Of them, 1,402 experienced virologic failure, equivalent to 29.72% 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/mm 3 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/mm 3 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 the adult clients on second-line ART experience VF at a rate of 92.71 per 1000 person-years. This high virologic failure rate highlights the need for targeted interventions for HIV-infected clients on second-line ART to reduce the need for switching to the more costly and relatively more toxic third-line ART therapy and help to achieve the third UNAIDS goal of achieving viral suppression for 95% of those treated by 2030. Prevalence Rate Predictors Virologic failure Second-line ART Tanzania Figures Figure 1 Figure 2 Figure 3 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 ), and an estimated 1.5 million individuals residing in Tanzania (THIS 2022 ). 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, 15 million of them in SSA and 1.2 million in Tanzania (THIS 2022 ). With the increased availability of ART and 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 ). 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 ). Clients failing second-line ART regimens pose a specific problem, especially those 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 that was 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 clients failing 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. Study Participants We enrolled all adult clients aged 15 years and older, and 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 85–94% (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 was based on WHO stages (I, II, III, and IV), CD4 count (≥ 200 cells/mm 3 and < 200 cells/mm 3 ), 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 the 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 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 The study 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 (Table 1 ). Table 1 Socio-demographic characteristics of clients on second-line ART in Tanzania from January 2018 to December 2020 (n = 4718) Characteristics Frequency (n) Percentage (%) Sex Male 1901 40.29 Female 2817 59.71 Age group(years) 15–24 0 0 25–34 313 9.24 35–44 920 27.16 45–54 1233 36.40 ≥ 55 921 27.19 Marital status Married 2440 62.77 Single 1447 37.23 Facility ownership Private 346 7.35 Public 4360 92.65 Facility level Dispensary 110 2.34 Health center 564 11.99 Hospital 1006 21.38 Clinic 3025 64.29 Geographical zones Central Zone 254 5.40 Eastern 1719 36.53 Lake 420 8.92 Northern 1060 22.52 Southern Highlands 616 13.09 Southern 215 4.57 Southern West Highland 340 7.22 Western 82 1.74 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 < 1,000 cp/mL, with 2126 (53.01%) having a CD4 count of less than < 200 cells/mm 3 . 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/mm 3 . During the first-line ART 107 (2.30%) clients had a history of TB, compared to 44 (0.93%) during the second-line ART (Table 2 ). Table 2 Virological, immunological, and clinical characteristics of HIV clients during first-line and second-line ART Characteristic Frequency (n) Percentage (%) During First-line ART CD4 count (First test since Initiation of first-line ART) < 200 cells/mm 3 2126 53.01 ≥ 200 cells/mm 3 1885 46.99 Viral load count (First test since Initiation of first-line ART) < 1000 cp/mL 2050 61.10 ≥ 1000 cp/mL 1305 38.90 WHO stage at first-line ART initiation Stage I 506 10.87 Stage II 1235 26.52 Stage III 2160 46.39 Stage IV 755 16.22 Tuberculosis diagnosis during first-line ART No 4554 97.70 Yes 107 2.30 During second-line ART CD4 count (First CD4 After switching to second-line ART) * < 200 cells/mm 3 1130 40.07 ≥ 200 cells/mm 3 1690 59.93 WHO-stage at the switch to second-line ART Stage I 241 5.11 Stage II 713 15.12 Stage III 2396 50.81 Stage IV 1366 28.97 Tuberculosis diagnosis during second-line ART No 4674 99.07 Yes 44 0.93 ART regimens offered to HIV Positive Clients on Second-line ART (Insights from First-line Therapy) In this study, most clients, 4438 (94.07%), had been on antiretroviral therapy (ART) for 60 months or more, with 1854 (41.14%) clients initiated on AZT as part of their NRTI backbone, while 3317 (74.39%) were initiated on EFV/NVP (NNRTI). On switching to second-line ART regimens, 2274 (51.18%) clients took lopinavir, and 2339 (56.63%) used TDF as their NRTIs, and adherence was good (> 95%) during both first and second-line ART (Table 3 ) Table 3 Type of regimen given and the level of adherence during the first and second-line ART (n = 4718) Characteristic Frequency (n) Percentage (%) During First-line NRTI backbone at initiation Tenofovir (TDF) 787 17.46 Zidovudine (AZT) 1854 41.14 Abacavir (ABC) 13 0.29 Others (d4t, ddi) 1853 41.11 NNRTIs/INSTIs based regimen at initiation EFV/NVP 3317 74.39 DTG 637 14.29 Others 505 11.33 ART Adherence Good (> 95%) 4546 97.93 Poor (< 95%) 96 2.07 During second-line PI at switch Lopinavir/Ritonavir (LPV/r) 2274 51.18 Atazanavir/Ritonavir(ATV/r) 1848 41.59 Other 321 7.22 NRTI backbone at switch Tenofovir (TDF) 2339 56.63 Zidovudine (AZT) 347 8.40 Abacavir (ABC) 1444 34.96 ART Adherence Good (> 95%) 4494 95.29 Poor (< 95%) 222 4.71 Total duration of ART (Months) ≤ 12 months 3 0.06 13–35months 64 1.36 36–59 months 213 4.51 ≥ 60 months 4438 94.07 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 significant 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 4 ) . Table 4 Virological Failure Rates/1000 Person-Years in HIV-Positive Adult Clients on Second-Line ART (2018–2020) Variable Person-years Number Failed Failure rate/1000 person years(95% CI) Crude failure rate 15100 1402 92.85 (88.11, 97.84) Age group (years) 25–34 1001 101 100.86 (82.97, 122.58) 35–44 2555 304 118.99 (106.34, 133.14) 45–54 4086 282 69.02 (61.42, 77.56) ≥ 55 3428 180 52.52 (45.38, 60.78) Sex Male 6278 592 94.29 (87.00, 102.20) Female 8822 810 91.82 (85.71, 98.37) Marital status Married 7773 610 78.48 (72.49, 84.96) Single 4355 534 122.61 (112.64, 133.46) Facility level Dispensary 313 39 124.53 (90.99, 170.44) Health center 1402 190 135.53 (117.57, 156.24) Hospital 2596 329 126.73 (113.75, 141.19) Clinic 10751 841 78.22 (73.11, 83.69) Facility Ownership Private 1212 115 94.87 (79.02, 113.89) Public 13850 1284 92.71 (87.77, 97.92) 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 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 ≥ 1000cp/mL 235.99 (95% CI 216.70, 257.01) VF 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). 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, with the lowest rate reported among those on ART for > 60 months was 89.01(95% CI 84.49, 94.15) (Table 5 ). Table 5 Virological Failure rates according to Immunological, Virological, and Clinical Characteristics during First and Second-line Antiretroviral Therapy (n = 1402) Variable Person years Number Failed Failure rate/1000 person-years (95% CI) CD4 at first-line ART < 200 cells/mm 3 7626 599 78.55 (72.50, 85.10) ≥ 200 cells/mm 3 5598 577 103.08 (95.00, 111.84) HVL at first-line ART < 1000 cp/ml 7203 452 62.75 (57.23, 68.81) ≥ 1000 cp/ml 2237 528 235.99 (216.70, 257.01) WHO stages at first-line initiation Stage I 1471 136 92.45 (78.15, 109.37) Stage II 3928 350 89.09 (80.23, 98.93) Stage III 6789 694 102.23 (94.90, 110.13) Stage IV 2727 207 75.92 (66.25, 87.00) TB at first-line ART No 14609 1351 92.48 (87.67, 97.54) Yes 329 37 112.55 (81.54, 155.33) CD4 count at second-line < 200 cells/mm 3 4702 413 87.84 (79.76, 96.73) ≥ 200 cells/mm 3 6575 353 53.69 (48.37, 59.59) WHO stage at second-line ART Stage I 637 67 105.15 (82.76, 133.60) Stage II 2293 184 80.25 (69.46, 92.73) Stage III 7390 762 103.11 (96.04, 110.70) Stage IV 4767 388 81.39 (73.68, 89.90) Tb at second-line ART No 14956 1382 92.41 (87.66, 97.41) Yes 144 20 139.02 (89.69, 215.49) 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, an 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 two-fold 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 6 ). Table 6 Virological failure rates/1000 person-years by type of regimen during first and second-line ART (n = 1402) Variable Person years Number Failed Failure rate/1000 person-years (95% CI) NRTI backbone during first-line ART TDF 1647 223 135.39 (118.74, 154.38) AZT 5774 595 103.04 (94.09, 111.66) ABC 38 4 105.24 (39.50, 280.41) d4t, ddi 7203 487 67.60 (61.86, 73.88) NNRTIs/INSTIs at first line NNRTI 9785 984 100.56 (94.47, 107.05) DTG 2596 161 62.02 (53.14, 72.38) Other 2126 145 68.22 (57.97, 80.28) ART Adherence Good (> 95%) 14605 1,349 92.37 (87.57, 97.43) Poor (< 95%) 270 34 125.85 (89.93, 176.13) Protease Inhibitors during second-line ART Lopinavir/Ritonavir (LPV/r) 9124 668 73.21 (67.78, 78.98) Atazanavir/Ritonavir (ATV/r 3982 538 135.10 (124.16, 147.02) Other 1391 73 52.47 (41.72, 66.00) NRTI backbone during second-line ART Tenofovir (TDF) 6725 624 92.78 (85.78, 100.36) Zidovudine (AZT) 937 118 125.94 (105.15, 150.84) Abacavir (ABC) 5510 465 84.38 (77.05, 92.41) ART Adherence Good (> 95%) 14619 1,315 89.95 (85.22, 94.94) Poor (< 95%) 478 87 189.76 (147.32, 224.27) Duration of ART (Months) ≤ 12 months 1 2 1337.91 (334.61, 5349.56) 13–35months 72 24 331.93 (22.48, 495.22) 36–59 months 327 65 198.55 (155.70, 253.19) ≥ 60 months 14698 1,311 89.19 (84.49, 94.15) Predictors of virological failure among adult HIV clients on second-line ART in Tanzania from 2018 to 2020. 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/mm 3 CD4 count during second-line ART 1.89 (95% CI 1.46, 2.44). Paradoxically, individuals with a CD4 count of < 200 cells/mm 3 during first-line ART had a reduced risk of VF 0.77 (95% CI 0.60, 0.99) (Table 7 ). Table 7 Bivariate and multivariate analysis of predictors of virological failure among adult HIV clients on second-line ART in Tanzania from 2018 to 2020 Covariate Proportion failed (%) Bivariate analysis Multivariate analysis Crude hazard ratio (95% CI) p -value Adjusted hazard ratio (95% CI) p -value Age group (years) 25–34 7.20 1.95 (1.53, 2.49) < 0.001* 1.55 (0.88, 73) 0.132 35–44 21.68 2.35 (1.95, 2.82) 12.84 1 1 Sex Male 42.23 1 1 Female 57.77 0.98 (0.88, 1.09) 0.755 0.86 (0.66, 1.13) 0.295 Marital status Married 43.51 1 1 Single 38.09 1.57 (1.40, 1.77) 0.932 1.02 (0.76, 1.38) 0.295 Facility Ownership Private 8.20 1 1 Public 91.58 0.98 (0.81, 1.19) 0.863 1.31 (0.83, 2.09) 0.879 Facility Level Dispensary 2.78 1.64 (1.19, 2.27) 0.002 2.48 (1.12, 5.48) 0.025* Health center 13.55 1.83 (1.56, 2.14) < 0.001* 1.30 (0.79, 2.13) 0.299 Hospital 23.47 1.70 (1.49, 1.93) < 0.001* 1.22 (0.86, 1.70) 0.251 Clinic 59.99 1 1 Initial HVL after first-line Initiation of ART < 1000 76.35 1 1 ≥ 1000 6.00 4.29 (3.76, 4.89) < 0.001* 4.65 (3.57, 6.07) < 0.001* NRTI backbone during first-line ART Tenofovir (TDF) 15.91 2.25 (1.91, 2.65) < 0.001* 1.76 (1.06, 2.90) 0.028 Zidovudine (AZT) 42.44 1.5 (1.41, 1.79) < 0.001* 1.37 (0.97, 1.96) 0.078 Abacavir (ABC) 0.29 1.56 (0.58, 4.17) 0.377 6.8 (0.92, 50.66) 0.060 Others (d4t, ddi) 34.74 1 1 NNRTIs/INSTIs during first-line ART EFV/NVP 70.19 1.56 (1.31, 1.86) < 0.001* 1.43 (0.83, 2.48) 0.203 DTG 11.48 0.93 (0.74, 1.17) 0.543 1.45 (0.82, 2.55) 0.199 Other 10.34 1 1 PI during second line LPV/r 47.65 1.36 (1.06, 1.74) < 0.001* 4.20 (3.12, 7.10) < 0.001* ATV/r 38.37 2.96 (2.31, 3.79) < 0.001* 1.07 (0.94, 2.35) 0.213 Other 5.21 1 1 NRTI backbone during the second line ART Tenofovir (TDF) 44.51 1.14 (1.01, 1.30) 0.036 1.22 (0.91, 1.64) 0.186 Zidovudine (AZT) 8.42 1.56 (1.27, 1.92) < 0.001* 1.14 (0.67, 1.83) 0.670 Abacavir (ABC) 33.17 1 1 CD4 count during first-line ART ≥ 200 cells/mm 3 41.16 1 1 < 200 cells/mm 3 42.72 0.75 (0.67, 0.84) < 0.001* 0.77 (0.60, 0.99) 0.040* CD4 count during second-line ART ≥ 200 cells/mm 3 25.18 1 1 < 200 cells/mm 3 29.46 1.59 (1.38, 1.84) < 0.001* 1.89 (1.46, 2.44) < 0.001* WHO stage during the first line ART Stage 1 9.70 1 1 Stage 2 24.96 0.96 (0.79, 1.17) 0.711 1.44 (0.77, 2.69) 0.256 Stage 3 49.50 1.10 (0.91, 1.32) 0.312 1.47 (0.82, 2.63) 0.191 Stage 4 14.76 0.81 (0.65, 1.00) 0.052 1.26 (0.68, 2.36) 0.460 WHO stage during the second line ART Stage 1 4.78 1 1 Stage 2 13.12 0.75 (0.57, 0.99) 0.043 0.80 (0.34, 1.84) 0.601 Stage 3 54.35 0.97 (0.75, 1.23) 0.787 1.19 (0.56, 2.53) 0.648 Stage 4 27.67 0.76 (0.58, 0.98) 0.034 1.16 (0.55, 2.44) 0.698 TB during first-line ART No 96.36 1 1 Yes 2.64 1.23 (0.88, 1.70) 0.221 2.21 (1.05, 4.64) 0.037* TB during second-line ART No 98.57 1 1 Yes 1.43 1.50 (0.97, 2.34) 0.069 0.88 (0.21, 3.79) 0.869 Adherence to first-line ART Good (≥ 95%) 96.22 1 1 Poor (< 95%) 2.43 1.37 (0.98, 1.93) 0.068 0.93 (0.42, 2.06) 0.855 Adherence to second-line ART Good (≥ 95%) 93.79 1 1 Poor (< 95%) 6.21 2.13 (1.71, 2.65) < 0.001* 1.31 (0.79, 2.18) 0.293 Total duration on ART ≤ 12 months 0.14 41.39 (10.23, 167.36) < 0.001* 13–35months 1.71 4.6 (3.07, 6.94) < 0.001* 8.22 (2.21, 30.61) 0.002* 36–59 months 4.64 2.53 (1.97, 3.26) < 0.001* 1.59 (0.72, 3.50) 0.248 ≥ 60 months 93.51 1 1 * p -value ≤ 0.05 statistically significant 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/mm 3 during second-line ART. Interestingly, clients with CD4 counts < 200 cells/mm 3 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 iv) 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 coinfection(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 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 8-fold 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 7-fold 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/mm 3 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/mm 3 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, which require a register for regular recording and monitoring. 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 Control Programme (NACP) 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 National AIDS Control Program (NACP) 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. Abbreviations ABC Abacavir AIDS Acquired Immunodeficiency Syndrome ART Antiretroviral Therapy ATV/r Atazanavir/Ritonavir ZDV Azidothymidine CTC Care and Treatment Centre CI Confidence Interval DRMs Drug Resistance Mutations EAC Enhanced Adherence and Counselling HAART Highly Active Antiretroviral Therapy HIV Human Immunodeficiency Virus HIVDR HIV Drug Resistance HVL HIV Viral load IR Incidence Ratio LMICs Low- and Middle-Income Countries LPV Lopinavir NASHCoP National AIDS, STIs and Hepatitis Control Programe PCR Polymerase Chain Reaction PY Person Years PDR Pre-treatment Drug Resistance PI Protease Inhibitor PLHIV People Living with HIV/AIDS PMTCT Prevention of Mother To Child Transmission RTI Reverse Transcriptase Inhibitor RTV Ritonavir TB Tuberculosis TDF Tenofovir Disoproxil Fumarate UNAIDS United Nations Program on HIV and AIDS VF Virological Failure VL Viral Load WHO World Health Organization 3TC Lamivudine Declarations Ethical approval and consent to participate 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. Consent for publication Not applicable. 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. Competing interests The authors declare that they have no competing interests. Funding This study had no funds Authors' contributions 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. Acknowledgments 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. References Alemu KD, Moges NA, Asrade AA et al (2022) Time to Switch to Second-Line Anti-Retroviral Treatment and Its Predictors Among HIV Infected Adults with Virological Failure in Northwest Ethiopia: A Retrospective Follow-Up Study. HIV/AIDS - Research and Palliative Care 14:87–100. 10.2147/HIV.S348076 Alene M, Awoke T, Yenit MK, Tsegaye AT (2019) Incidence and predictors of second-line antiretroviral treatment failure among adults living with HIV in Amhara region: A multi-centered retrospective follow-up study. BMC Infect Dis doi. 10.1186/s12879-019-4243-5 Barabona G, Mahiti M, Masoud S et al (2019) Pre-Treatment and acquired HIV drug resistance in Dar es Salaam, Tanzania in the era of tenofovir and routine viral load monitoring. J Antimicrob Chemother 74:3016–3020. 10.1093/jac/dkz272 Bell LCK, Noursadeghi M (2017) Pathogenesis of HIV-1 and Mycobacterium tuberculosis co-infection. Nat Rev Microbiol 2017 16(2):80–90. 10.1038/nrmicro.2017.128 Bircher RE, Ntamatungiro AJ, Glass TR et al (2020) High failure rates of protease inhibitor-based antiretroviral treatment in rural Tanzania – A prospective cohort study. PLoS ONE 15:e0227600. 10.1371/journal.pone.0227600 Boettiger DC, Nguyen VK, Durier N et al (2015) Efficacy of second-line antiretroviral therapy among people living with HIV/AIDS in Asia: Results from the TREAT Asia HIV observational database. J Acquir Immune Defic Syndr 68:186–195. 10.1097/QAI.0000000000000411 Cain LE (2015) Boosted lopinavir-versus boosted atazanavir-containing regimens and immunologic, virologic, and clinical outcomes: A Prospective study of HIV-infected individuals in high-income countries. Clin Infect Dis 60:1262–1268. 10.1093/cid/ciu1167 Cesar C, Shepherd BE, Jenkins CA et al (2014) Use of third line antiretroviral therapy in Latin America. PLoS ONE 9:1–8. 10.1371/journal.pone.0106887 Chakravarty J, Sundar S, Chourasia A et al (2015) Outcome of patients on second line antiretroviral therapy under programmatic condition in India. BMC Infect Dis 15:1–11. 10.1186/s12879-015-1270-8 Chen S, Chen S, Han Y et al (2020) Very high baseline HIV viremia impairs efficacy of non-nucleoside reverse transcriptase inhibitor-based ART: a long-term observation in treatment-naïve patients. Infect Dis Poverty doi. 10.1186/S40249-020-00700-8 Collier D, Iwuji C, Derache A et al (2017) Virological Outcomes of Second-line Protease Inhibitor-Based Treatment for Human Immunodeficiency Virus Type 1 in a High-Prevalence Rural South African Setting: A Competing-Risks Prospective Cohort Analysis. Clin Infect diseases: official publication Infect Dis Soc Am 64:1006–1016. 10.1093/CID/CIX015 Crowell TA, Danboise B, Parikh A et al (2021) Pretreatment and Acquired Antiretroviral Drug Resistance Among Persons Living With HIV in Four African Countries. Clin Infect diseases: official publication Infect Dis Soc Am 73:e2311–e2322. 10.1093/cid/ciaa1161 Daftary A, Padayatchi N, O’Donnell M (2014) Preferential adherence to antiretroviral therapy over tuberculosis treatment: A qualitative study of drug-resistant TB/HIV co-infected patients in South Africa. Glob Public Health 9:1107–1116. 10.1080/17441692.2014.934266 Diress G, Dagne S, Alemnew B et al (2020) Viral Load Suppression after Enhanced Adherence Counseling and Its Predictors among High Viral Load HIV Seropositive People in North Wollo Zone Public Hospitals, Northeast Ethiopia, 2019: Retrospective Cohort Study. AIDS Res Treat. 10.1155/2020/8909232 Edessa D, Sisay M, Asefa F (2019) Second-line HIV treatment failure in subSaharan Africa: A systematic review and metaanalysis. PLoS ONE 14:1–19. 10.1371/journal.pone.0220159 Endebu T, Deksisa A, Moges T et al (2018) Incidence of Virological Failure and Associated Factors among Adult HIV-Positive Patients on First Line Antiretroviral Therapy Regimen, Central Ethiopia. International Journal of HIV/AIDS Prevention, Education and Behavioural Science 4:44–51. 10.11648/j.ijhpebs.20180402.13 Fokam J, Nangmo A, Wandum C et al (2020) Programme quality indicators of HIV drug resistance among adolescents in urban versus rural settings of the centre region of Cameroon. AIDS Res Therapy 17:1–10. 10.1186/s12981-020-00270-7 Gachogo RW, Mwai DN, Onyambu FG (2020) Cost analysis of implementing HIV drug resistance testing in Kenya: A case study of a service delivery site at a tertiary level hospital in Kenya. F1000Research. 10.12688/f1000research.23379.1 Getaneh T, Negesse A, Dessie G, Desta M (2022) The impact of tuberculosis co-infection on virological failure among adults living with HIV in Ethiopia: A systematic review and meta-analysis. J Clin Tuberculosis Other Mycobact Dis 27:100310. 10.1016/j.jctube.2022.100310 Gumede SB, Venter F, De Wit J et al (2022) Antiretroviral therapy uptake and predictors of virological failure in patients with HIV receiving first-line and second-line regimens in Johannesburg, South Africa: A retrospective cohort data analysis. BMJ Open 12:54019. 10.1136/bmjopen-2021-054019 Gunda DW, Kilonzo SB, Mtaki T et al (2019) Magnitude and correlates of virological failure among adult HIV patients receiving PI based second line ART regimens in north western Tanzania; A case control study. BMC Infect Dis 19:1–7. 10.1186/s12879-019-3852-3 Haftu AZ, Desta AA, Bezabih NM et al (2020) Incidence and factors associated with treatment failure among HIV infected adolescent and adult patients on second-line antiretroviral therapy in public hospitals of Northern Ethiopia: Multicenter retrospective study. PLoS ONE 15:1–15. 10.1371/journal.pone.0239191 Hawkins C, Ulenga N, Liu E et al (2016) HIV virological failure and drug resistance in a cohort of Tanzanian HIV-infected adults. J Antimicrob Chemother 71:1966–1974. 10.1093/jac/dkw051 Masaba R, Woelk G, Siamba S et al (2023) Antiretroviral treatment failure and associated factors among people living with HIV on therapy in Homa Bay, Kenya: A retrospective study. PLOS Global Public Health 3:e0001007. 10.1371/journal.pgph.0001007 Masresha SA, Kidie AA, Alen GD et al (2023) Virological failure and its predictors among human immunodeficiency virus infected individuals on second line antiretroviral treatment in North-East Ethiopia, 2021. Pharmacoepidemiology and Drug Safety. 10.1002/pds.5625 Mazuguni NS, Mazuguni F, Muro EP (2021) Detectable viral load among HIV – 1 positive pregnant women on ART (Option B +) in northern Tanzania: Baseline results from the HIVDR study. East Afr Sci 3:44–50. 10.24248/easci-d-20-00009 Mazzuti L, Melengu T, Falasca F et al (2020) Transmitted drug resistance mutations and trends of HIV-1 subtypes in treatment-naïve patients: A single-centre experience. J Global Antimicrob Resist 20:298–303. 10.1016/j.jgar.2019.08.024 Mchomvu RD, Hussein AK, Matee M (2022) Determinants of viral load non-suppression among HIV-positive children and adolescents attending care and treatment clinics in Tabora region, Tanzania. Bulletin of the National Research Centre. 10.1186/s42269-022-00961-3 Musana H, Ssensamba JT, Nakafeero M et al (2021) Predictors of failure on second-line antiretroviral therapy with protease inhibitor mutations in Uganda. AIDS Res Therapy 18:1–10. 10.1186/s12981-021-00338-y Naidoo K, Ramruthan J, Reddy M, Lancaster R (2022) A third-line antiretroviral therapy register to track patient clinical and virological outcomes. South Afr Med J 112:511–512. 10.7196/SAMJ.2022.v112i8.16695 Nastri BM, Pagliano P, Zannella C et al (2023) HIV and Drug-Resistant Subtypes. Microorganisms 11:221. 10.3390/MICROORGANISMS11010221/S1 Nsanzimana S, Semakula M, Ndahindwa V et al (2019) Retention in care and virological failure among adult HIV + patients on second-line ART in Rwanda: a national representative study. BMC Infect Dis 19:1–9. 10.1186/s12879-019-3934-2 Nwokolo N, Whitlock G, McOwan A (2017) Not just PrEP: other reasons for London’s HIV decline. Lancet HIV 4:e153. 10.1016/S2352-3018(17)30044-9 Olakunde BO, Adeyinka DA, Ozigbu CE et al (2019) Revisiting aid dependency for HIV programs in Sub-Saharan Africa. Public Health 170:57–60. 10.1016/J.PUHE.2019.02.016 Pingarilho M, Pimentel V, Diogo I et al (2020) Increasing prevalence of HIV-1 transmitted drug resistance in Portugal: Implications for first line treatment recommendations. Viruses 12:1238. 10.3390/v12111238 Ramadhani HO, Bartlett JA, Thielman NM et al (2016) The Effect of Switching to Second-Line Antiretroviral Therapy on the Risk of Opportunistic Infections Among Patients Infected With Human Immunodeficiency Virus in Northern Tanzania. Open Forum Infect Dis. 10.1093/OFID/OFW018 Rodger AJ, Cambiano V, Phillips AN et al (2019) Risk of HIV transmission through condomless sex in serodifferent gay couples with the HIV-positive partner taking suppressive antiretroviral therapy (PARTNER): final results of a multicentre, prospective, observational study. Lancet 393:2428–2438. 10.1016/S0140-6736(19)30418-0 Sam M, Masaba JPM, Alio D, Byakika-Tusiime J (2021) Treatment Failure and Associated Factors among Individuals on Second Line Antiretroviral Therapy in Eastern Uganda: A Retrospective Cohort Study. Infect Diseases: Res Treat 14:117863372110145. 10.1177/11786337211014518 Temereanca A, Ruta S (2023) Strategies to overcome HIV drug resistance-current and future perspectives. Front Microbiol 14:1–8. 10.3389/fmicb.2023.1133407 THIS (2022) The United Republic of Tanzania. TANZANIA HIV IMPACT SURVEY 2023:6–9 Tigabu BM, Agide FD, Mohraz M, Nikfar S (2020) Atazanavir / ritonavir versus lopinavir / ritonavir-based combined antiretroviral therapy (cART) for HIV-1 infection: A systematic review and meta-analysis. Afr Health Sci 20:91–101. 10.4314/ahs.v20i1.14 Trickey A, May MT, Vehreschild JJ et al (2017) Survival of HIV-positive patients starting antiretroviral therapy between 1996 and 2013: a collaborative analysis of cohort studies. Lancet HIV 4:e349–e356. 10.1016/S2352-3018(17)30066-8 Tsegaye AT, Wubshet M, Awoke T et al (2016) Predictors of treatment failure on second-line antiretroviral therapy among adults in northwest Ethiopia: A multicentre retrospective follow-up study. BMJ Open 6:1–8. 10.1136/bmjopen-2016-012537 WHO (2021) Consolidated guidelines on HIV prevention, testing, treatment, service delivery and monitoring: recommendations for a public health approach. World Health Organization, In: Geneva WHO (2022) World Cancer Day 2022 WHO Regional Office for Africa. In: WHO Africa. https://www.afro.who.int/regional-director/speeches-messages/world-aids-day-2022 . Accessed 2 May 2024 Zakaria HF, Raru TB, Hassen FA et al (2022) Incidence and Predictors of Virological Failure Among Adult HIV/AIDS Patients on Second-Line Anti-Retroviral Therapy, in Selected Public Hospital of Addis Ababa, Ethiopia: Retrospective Follow-Up Study. HIV/AIDS - Research and Palliative Care 14:319–329. doi: 10.2147/HIV.S367677 (2019) National Guidelines for the Management of HIV and AIDS.Ministry of Health Community Development, Gender, Eldery and Children. Development 7:2,274,923,575.00-29.08 Cite Share Download PDF Status: Published Journal Publication published 01 Oct, 2024 Read the published version in Bulletin of the National Research Centre → Version 1 posted Reviewers agreed at journal 16 Aug, 2024 Reviewers invited by journal 16 Aug, 2024 Editor assigned by journal 16 Aug, 2024 First submitted to journal 14 Aug, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4744820","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":341217209,"identity":"8e725792-85da-4880-89bd-2b25550f95e9","order_by":0,"name":"ESTER TIMOTHY MWAVIKA","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+klEQVRIiWNgGAWjYHACNijN2MzAUAGkmZkbCOhgRtZyBiTASLQWBmYGxjawXvxa+PnPH3vwcc+2xP4Zyc0GP+fVRvO3A7X8qNiGU4vkjGR2wxnPbifOuJHYnNi77XjujMOMDYw9Z27j1GJwg5lNmufA7dyGMwebD/BuO5bbANTCzNiGW4v9+cNs0n+AWuYDtRz8O+dY7nxCWgwYktmkGYBaNhxvbE7mbajJ3UBIi8SNZDPJngO36zcCtRjLHDuQuxGo5SA+v/D3H3wm8ePAbWO5w+yPJd/U1OXOO3/44IMfFbi1oIPDYPIA0eqBoI4UxaNgFIyCUTBCAADpLGL0kx3ULgAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0004-1469-5867","institution":"MUHAS: Muhimbili University of Health and Allied Sciences","correspondingAuthor":true,"prefix":"","firstName":"ESTER","middleName":"TIMOTHY","lastName":"MWAVIKA","suffix":""},{"id":341217210,"identity":"496a1eea-e5f1-44ef-ad8e-4d894fc0ba15","order_by":1,"name":"Peter Ponsian Kunambi","email":"","orcid":"","institution":"Muhimbili University of Health and Allied Sciences School of Public Health and Social Sciences","correspondingAuthor":false,"prefix":"","firstName":"Peter","middleName":"Ponsian","lastName":"Kunambi","suffix":""},{"id":341217211,"identity":"ab9f77bc-64cc-4988-ae48-5a106e92f20d","order_by":2,"name":"Samuel Joseph Masasi","email":"","orcid":"","institution":"University of Dar es Salaam","correspondingAuthor":false,"prefix":"","firstName":"Samuel","middleName":"Joseph","lastName":"Masasi","suffix":""},{"id":341217212,"identity":"756bd5ad-89f2-47c9-9867-bd8708831104","order_by":3,"name":"Nsiande Lema","email":"","orcid":"","institution":"Tanzania Field Epidemiology and Laboratory Training Program, P.O. Box 9083","correspondingAuthor":false,"prefix":"","firstName":"Nsiande","middleName":"","lastName":"Lema","suffix":""},{"id":341217213,"identity":"2419ca75-7b7f-4a71-a3b3-2440e954c821","order_by":4,"name":"Doreen Kamori","email":"","orcid":"","institution":"MUHAS: Muhimbili University of Health and Allied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Doreen","middleName":"","lastName":"Kamori","suffix":""},{"id":341217214,"identity":"4ecc50af-b63b-43a0-ab41-50dbdeb4174f","order_by":5,"name":"Mecky Matee","email":"","orcid":"","institution":"MUHAS: Muhimbili University of Health and Allied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mecky","middleName":"","lastName":"Matee","suffix":""}],"badges":[],"createdAt":"2024-07-15 18:34:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4744820/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4744820/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s42269-024-01248-5","type":"published","date":"2024-10-01T15:56:59+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":63811480,"identity":"192df7d1-e4dd-41e7-bff6-a2e0419a84eb","added_by":"auto","created_at":"2024-09-02 14:04:53","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":122671,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4744820/v1/f5237480d7123d5ee8a2bc29.jpg"},{"id":63810545,"identity":"c882cbbd-ebcb-49aa-b162-51bce4e0854c","added_by":"auto","created_at":"2024-09-02 13:56:53","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":83001,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4744820/v1/fe91729236b07e4bd25321a3.jpg"},{"id":63808550,"identity":"7aae62d1-1ebf-4c32-b03b-ba4688e53cce","added_by":"auto","created_at":"2024-09-02 13:48:53","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":112490,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4744820/v1/a946ec3eb64c91f675322e20.jpg"},{"id":66096715,"identity":"d3b6608c-d2b4-4693-9098-69dea06528b0","added_by":"auto","created_at":"2024-10-07 16:07:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2251015,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4744820/v1/45e6d357-6b3f-4ae6-867a-33a0dca97287.pdf"}],"financialInterests":"","formattedTitle":"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","fulltext":[{"header":"Background","content":"\u003cp\u003eWorldwide, as of 2022, nearly 39.0\u0026nbsp;million individuals were living with the Human Immunodeficiency Virus (HIV), with 25.6\u0026nbsp;million of them residing in Sub-Saharan Africa (SSA) (WHO \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and an estimated 1.5\u0026nbsp;million individuals residing in Tanzania (THIS \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFor people living with HIV (PLHIV), early initiation of Antiretroviral Therapy (ART) is crucial for improving viral suppression and increasing life expectancy (Nwokolo et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Trickey et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Rodger et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Currently, it is estimated that 29.8\u0026nbsp;million PLHIV are receiving ART, 15\u0026nbsp;million of them in SSA and 1.2\u0026nbsp;million in Tanzania (THIS \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWith the increased availability of ART and more individuals starting first-line ART, the risk of viral resistance and eventual treatment failure has escalated (Barabona et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Pingarilho et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Temereanca and Ruta \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), 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. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Alemu et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and this number is projected to increase significantly by 2030 (Rodger et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAs demonstrated in \u003cb\u003eFig.\u0026nbsp;1\u003c/b\u003e below, failure to second-line ART has been associated to; \u003cb\u003eDemographic factors\u003c/b\u003e like age(Gumede et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), sex(Gunda et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Zakaria et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and facility type/level(Nsanzimana et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Gumede et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e); \u003cb\u003eClinical factors\u003c/b\u003e like CD4 count (Gunda et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Gumede et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zakaria et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), WHO clinical stage(Nsanzimana et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and co-morbidities like TB(Zakaria et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) As well as ; \u003cb\u003eRegimen related factors\u003c/b\u003e that includes type of regimen used(Zakaria et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Masresha et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) Duration on ART(Gunda et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and adherence level(Zakaria et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eClients failing second-line ART regimens pose a specific problem, especially those in low-income countries since their access to third-line treatment regimens is very limited due to financial and logistic constraints (Olakunde et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). 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. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Musana et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMost of the studies in Tanzania have focused on virologic failure (VF) among PLHIV who are on first-line ART (Hawkins et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and have shown an increase in prevalence rates, from 14.9% in 2016 to 23% and 32.8% in 2021 (Mazuguni et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Mchomvu et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Information on VF among clients on second-line ART is limited and pertains to specific regions of the country. A study that was 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. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Bircher et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). 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 \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Unfortunately, nationwide estimates of clients failing 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.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and setting\u003c/h2\u003e \u003cp\u003eThis 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\u0026thinsp;+\u0026thinsp;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.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy Participants\u003c/h2\u003e \u003cp\u003eWe enrolled all adult clients aged 15 years and older, and 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.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSample size estimation\u003c/h2\u003e \u003cp\u003eThe 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. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) the estimated minimum sample size was \u003cb\u003e1147.\u003c/b\u003e As shown in \u003cb\u003eFig.\u0026nbsp;2\u003c/b\u003e below we enrolled a total of 4718 clients.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eDependent Variable\u003c/h2\u003e \u003cp\u003eIn this study, the dependent variable was virologic failure, which was defined as having two consecutive viral load results of \u0026ge;\u0026thinsp;1000 virus copies per mL of blood.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eIndependent Variables\u003c/h2\u003e \u003cp\u003eThe 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 \u003cb\u003egood\u003c/b\u003e if it was \u0026ge;\u0026thinsp;95% (\u0026lt;\u0026thinsp;2 doses of 30 doses or \u0026lt;\u0026thinsp;30 doss of 60 doses is missed) and \u003cb\u003epoor\u003c/b\u003e if it was between 85\u0026ndash;94% (3\u0026ndash;5 doses of 30 doses or 3\u0026ndash;9 doses of 60 doses is missed) (Legesse and Reta 2019) and the cumulative duration on ART was categorized as \u0026le;\u0026thinsp;12 months, 13\u0026ndash;35 months, 36\u0026ndash;59 months, and \u0026ge;\u0026thinsp;60 months.\u003c/p\u003e \u003cp\u003eFurther, categorization was based on WHO stages (I, II, III, and IV), CD4 count (\u0026ge;\u0026thinsp;200 cells/mm\u003csup\u003e3\u003c/sup\u003e and \u0026lt;\u0026thinsp;200 cells/mm\u003csup\u003e3\u003c/sup\u003e), and TB diagnosis.\u003c/p\u003e \u003cp\u003eObservations were censored at death, loss to follow-up, or when second-line ART was discontinued for reasons other than failure\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eFor 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 the 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 failure.\u003c/p\u003e \u003cp\u003eWe 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 \u003cem\u003ep\u003c/em\u003e-value of less than or equal to 0.2 were included in the multivariable model. Factors with a \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.05 were considered to be significantly associated with VF in clients receiving second-line ART.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eSocio-demographic characteristics of clients on second-line ART\u003c/h2\u003e \u003cp\u003eThe study reviewed the records of 4718 adult HIV-positive clients who were on second-line ART. The average age of the clients was 42.08 (\u0026plusmn;\u0026thinsp;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 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-demographic characteristics of clients on second-line ART in Tanzania from January 2018 to December 2020 (n\u0026thinsp;=\u0026thinsp;4718)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2817\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge group(years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e15\u0026ndash;24\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e313\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e920\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e921\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1447\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFacility ownership\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFacility level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDispensary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGeographical zones\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral Zone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEastern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1719\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e420\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorthern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouthern Highlands\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e616\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouthern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouthern West Highland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e340\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWestern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eVirological, immunological, and clinical characteristics of HIV clients during first-line and second-line ART\u003c/h2\u003e \u003cp\u003eDuring the first-line ART, 2160 (46.39%) clients were in WHO clinical stage III, and 2050 (61.10%) had viral load count of \u0026lt;\u0026thinsp;1,000 cp/mL, with 2126 (53.01%) having a CD4 count of less than \u0026lt;\u0026thinsp;200 cells/mm\u003csup\u003e3\u003c/sup\u003e. 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 \u0026ge;\u0026thinsp;200 cells/mm\u003csup\u003e3\u003c/sup\u003e. During the first-line ART 107 (2.30%) clients had a history of TB, compared to 44 (0.93%) during the second-line ART (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVirological, immunological, and clinical characteristics of HIV clients during first-line and second-line ART\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuring First-line ART\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4 count (First test since Initiation of first-line ART)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;200 cells/mm\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;200 cells/mm\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1885\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eViral load count (First test since Initiation of first-line ART)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1000 cp/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;1000 cp/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWHO stage at first-line ART initiation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e755\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTuberculosis diagnosis during first-line ART\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e97.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDuring second-line ART\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCD4 count (First CD4 After switching to second-line ART) *\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;200 cells/mm\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;200 cells/mm\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1690\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWHO-stage at the switch to second-line ART\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e713\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTuberculosis diagnosis during second-line ART\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4674\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e99.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eART regimens offered to HIV Positive Clients on Second-line ART (Insights from First-line Therapy)\u003c/h2\u003e \u003cp\u003eIn this study, most clients, 4438 (94.07%), had been on antiretroviral therapy (ART) for 60 months or more, with 1854 (41.14%) clients initiated on AZT as part of their NRTI backbone, while 3317 (74.39%) were initiated on EFV/NVP (NNRTI). On switching to second-line ART regimens, 2274 (51.18%) clients took lopinavir, and 2339 (56.63%) used TDF as their NRTIs, and adherence was good (\u0026gt;\u0026thinsp;95%) during both first and second-line ART (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eType of regimen given and the level of adherence during the first and second-line ART (n\u0026thinsp;=\u0026thinsp;4718)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuring First-line\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNRTI backbone at initiation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTenofovir (TDF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZidovudine (AZT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1854\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbacavir (ABC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers (d4t, ddi)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNNRTIs/INSTIs based regimen at initiation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEFV/NVP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e74.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e637\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e505\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eART Adherence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood (\u0026gt;\u0026thinsp;95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4546\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e97.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor (\u0026lt;\u0026thinsp;95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDuring second-line\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePI at switch\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLopinavir/Ritonavir (LPV/r)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAtazanavir/Ritonavir(ATV/r)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1848\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNRTI backbone at switch\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTenofovir (TDF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZidovudine (AZT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e347\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbacavir (ABC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1444\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eART Adherence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood (\u0026gt;\u0026thinsp;95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4494\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e95.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor (\u0026lt;\u0026thinsp;95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal duration of ART (Months)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;12 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u0026ndash;35months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e36\u0026ndash;59 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;60 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4438\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e94.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eThe rate of virological failure among HIV-positive adult clients on second-line ART\u003c/h2\u003e \u003cp\u003eThis 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\u0026ndash;97.84) per 1000 PY of observations.\u003c/p\u003e \u003cp\u003eThe rate of VF was high among clients aged 35\u0026ndash;44 years, 118.99(95% CI 106.34-133.14), and was lower among those aged\u0026thinsp;\u0026ge;\u0026thinsp;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).\u003c/p\u003e \u003cp\u003eThere was no significant 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\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVirological Failure Rates/1000 Person-Years in HIV-Positive Adult Clients on Second-Line ART (2018\u0026ndash;2020)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePerson-years\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber Failed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFailure rate/1000 person years(95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCrude failure rate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15100\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1402\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e92.85 (88.11, 97.84)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group (years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e100.86 (82.97, 122.58)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2555\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e118.99 (106.34, 133.14)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e69.02 (61.42, 77.56)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.52 (45.38, 60.78)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e592\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e94.29 (87.00, 102.20)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e810\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e91.82 (85.71, 98.37)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7773\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e610\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e78.48 (72.49, 84.96)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e534\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e122.61 (112.64, 133.46)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFacility level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDispensary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e313\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e124.53 (90.99, 170.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e135.53 (117.57, 156.24)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e126.73 (113.75, 141.19)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e841\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e78.22 (73.11, 83.69)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFacility Ownership\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e94.87 (79.02, 113.89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13850\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1284\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e92.71 (87.77, 97.92)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eRate of virological failure to second-line ART across regions of Tanzania\u003c/h2\u003e \u003cp\u003eAs shown in \u003cb\u003eFig.\u0026nbsp;3\u003c/b\u003e below, Ruvuma and Mtwara regions had the highest rates of VF, 140\u0026ndash;154 per 1000 person-years, followed by Pwani and Songwe regions (120 per 1000 person-years) while Kagera had the lowest rate (48\u0026ndash;59 per 1000 person-years).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eVirological Failure rates across Immunological, Virological, and Clinical Characteristics during First and Second-line Antiretroviral Therapy\u003c/h2\u003e \u003cp\u003eDuring first-line ART, a higher rate of VF was observed among clients with an initial viral load count of \u0026ge;\u0026thinsp;1000cp/mL 235.99 (95% CI 216.70, 257.01) VF than those with an initial viral load count\u0026thinsp;\u0026lt;\u0026thinsp;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).\u003c/p\u003e \u003cp\u003eDuring 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\u0026ndash;35 months had a higher VF rate of 331.93(95% CI 22.48, 495.22) than other groups, with the lowest rate reported among those on ART for \u0026gt;\u0026thinsp;60 months was 89.01(95% CI 84.49, 94.15) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVirological Failure rates according to Immunological, Virological, and Clinical Characteristics during First and Second-line Antiretroviral Therapy (n\u0026thinsp;=\u0026thinsp;1402)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePerson years\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber Failed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFailure rate/1000 person-years (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4 at first-line ART\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;200 cells/mm\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7626\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e599\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e78.55 (72.50, 85.10)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;200 cells/mm\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5598\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e577\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e103.08 (95.00, 111.84)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHVL at first-line ART\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1000 cp/ml\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e452\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e62.75 (57.23, 68.81)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;1000 cp/ml\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e235.99 (216.70, 257.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWHO stages at first-line initiation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e92.45 (78.15, 109.37)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3928\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e89.09 (80.23, 98.93)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6789\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e694\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e102.23 (94.90, 110.13)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2727\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e75.92 (66.25, 87.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTB at first-line ART\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14609\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1351\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e92.48 (87.67, 97.54)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e112.55 (81.54, 155.33)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCD4 count at second-line\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;200 cells/mm\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4702\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e87.84 (79.76, 96.73)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;200 cells/mm\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6575\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.69 (48.37, 59.59)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWHO stage at second-line ART\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e637\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e105.15 (82.76, 133.60)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e80.25 (69.46, 92.73)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e103.11 (96.04, 110.70)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4767\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e81.39 (73.68, 89.90)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTb at second-line ART\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1382\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e92.41 (87.66, 97.41)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e139.02 (89.69, 215.49)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eVirological failure rates classified by regimen use history in first and second-line Antiretroviral Therapy\u003c/h2\u003e \u003cp\u003eDuring the first line ART, clients who were on TDF, an 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 two-fold 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).\u003c/p\u003e \u003cp\u003eDuring 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\u0026ndash;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 \u0026gt;\u0026thinsp;60 months was 89.01(95% CI 84.49, 94.15) (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVirological failure rates/1000 person-years by type of regimen during first and second-line ART (n\u0026thinsp;=\u0026thinsp;1402)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePerson years\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber Failed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFailure rate/1000 person-years (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNRTI backbone during first-line ART\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTDF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1647\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e135.39 (118.74, 154.38)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAZT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5774\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e595\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e103.04 (94.09, 111.66)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eABC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e105.24 (39.50, 280.41)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ed4t, ddi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e487\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e67.60 (61.86, 73.88)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNNRTIs/INSTIs at first line\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNNRTI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9785\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e100.56 (94.47, 107.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e62.02 (53.14, 72.38)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e68.22 (57.97, 80.28)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eART Adherence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood (\u0026gt;\u0026thinsp;95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14605\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e92.37 (87.57, 97.43)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor (\u0026lt;\u0026thinsp;95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e125.85 (89.93, 176.13)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eProtease Inhibitors during second-line ART\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLopinavir/Ritonavir (LPV/r)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e668\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e73.21 (67.78, 78.98)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAtazanavir/Ritonavir (ATV/r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e538\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e135.10 (124.16, 147.02)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.47 (41.72, 66.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNRTI backbone during second-line ART\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTenofovir (TDF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6725\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e624\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e92.78 (85.78, 100.36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZidovudine (AZT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e937\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e125.94 (105.15, 150.84)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbacavir (ABC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5510\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e465\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e84.38 (77.05, 92.41)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eART Adherence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood (\u0026gt;\u0026thinsp;95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14619\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,315\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e89.95 (85.22, 94.94)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor (\u0026lt;\u0026thinsp;95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e478\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e189.76 (147.32, 224.27)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDuration of ART (Months)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;12 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1337.91 (334.61, 5349.56)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u0026ndash;35months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e331.93 (22.48, 495.22)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e36\u0026ndash;59 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e198.55 (155.70, 253.19)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;60 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14698\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e89.19 (84.49, 94.15)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003ePredictors of virological failure among adult HIV clients on second-line ART in Tanzania from 2018 to 2020.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eOn bivariate analysis, individuals aged 35\u0026ndash;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.\u003c/p\u003e \u003cp\u003eUpon adjusting for confounders, clients with increased risk of VF were those with; an initial viral load of \u0026ge;\u0026thinsp;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\u0026ndash;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\u0026thinsp;\u0026lt;\u0026thinsp;200 cells/mm\u003csup\u003e3\u003c/sup\u003e CD4 count during second-line ART 1.89 (95% CI 1.46, 2.44). Paradoxically, individuals with a CD4 count of \u0026lt;\u0026thinsp;200 cells/mm\u003csup\u003e3\u003c/sup\u003e during first-line ART had a reduced risk of VF 0.77 (95% CI 0.60, 0.99) (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBivariate and multivariate analysis of predictors of virological failure among adult HIV clients on second-line ART in Tanzania from 2018 to 2020\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCovariate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eProportion failed (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eBivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMultivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCrude hazard ratio (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdjusted hazard ratio (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eAge group (years)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.95 (1.53, 2.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.55 (0.88, 73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.35 (1.95, 2.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.50 (1.00, 2.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.33 (1.11, 1.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.92 (0.63, 1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.645\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e55\u0026gt;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.98 (0.88, 1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.755\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.86 (0.66, 1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.295\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.57 (1.40, 1.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.932\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.02 (0.76, 1.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.295\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFacility Ownership\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.98 (0.81, 1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.863\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.31 (0.83, 2.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.879\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFacility Level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDispensary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.64 (1.19, 2.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.48 (1.12, 5.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.025*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.83 (1.56, 2.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.30 (0.79, 2.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.299\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.70 (1.49, 1.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.22 (0.86, 1.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.251\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInitial HVL after first-line Initiation of ART\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.29 (3.76, 4.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.65 (3.57, 6.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNRTI backbone during first-line ART\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTenofovir (TDF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.25 (1.91, 2.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.76 (1.06, 2.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZidovudine (AZT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5 (1.41, 1.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.37 (0.97, 1.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbacavir (ABC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.56 (0.58, 4.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.8 (0.92, 50.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers (d4t, ddi)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNNRTIs/INSTIs during first-line ART\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEFV/NVP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.56 (1.31, 1.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.43 (0.83, 2.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.203\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.93 (0.74, 1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.45 (0.82, 2.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.199\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePI during second line\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLPV/r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.36 (1.06, 1.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.20 (3.12, 7.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eATV/r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.96 (2.31, 3.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.07 (0.94, 2.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.213\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNRTI backbone during the second line ART\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTenofovir (TDF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.14 (1.01, 1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.22 (0.91, 1.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.186\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZidovudine (AZT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.56 (1.27, 1.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.14 (0.67, 1.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.670\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbacavir (ABC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCD4 count during first-line ART\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;200 cells/mm\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;200 cells/mm\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.75 (0.67, 0.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.77 (0.60, 0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.040*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCD4 count during second-line ART\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;200 cells/mm\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;200 cells/mm\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.59 (1.38, 1.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.89 (1.46, 2.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWHO stage during the first line ART\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.96 (0.79, 1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.711\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.44 (0.77, 2.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.256\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.10 (0.91, 1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.47 (0.82, 2.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.191\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.81 (0.65, 1.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.26 (0.68, 2.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.460\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWHO stage during the second line ART\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.75 (0.57, 0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.80 (0.34, 1.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.601\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.97 (0.75, 1.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.19 (0.56, 2.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.648\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.76 (0.58, 0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.16 (0.55, 2.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.698\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTB during first-line ART\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.23 (0.88, 1.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.21 (1.05, 4.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.037*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTB during second-line ART\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.50 (0.97, 2.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.88 (0.21, 3.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.869\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdherence to first-line ART\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood (\u0026ge;\u0026thinsp;95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor (\u0026lt;\u0026thinsp;95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.37 (0.98, 1.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.93 (0.42, 2.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.855\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdherence to second-line ART\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood (\u0026ge;\u0026thinsp;95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor (\u0026lt;\u0026thinsp;95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.13 (1.71, 2.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.31 (0.79, 2.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.293\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal duration on ART\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;12 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.39 (10.23, 167.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u0026ndash;35months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.6 (3.07, 6.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.22 (2.21, 30.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.002*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e36\u0026ndash;59 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.53 (1.97, 3.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.59 (0.72, 3.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.248\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;60 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*\u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026le;\u0026thinsp;0.05 statistically significant\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe 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.\u003c/p\u003e \u003cp\u003eOverall 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 \u003cb\u003eFig.\u0026nbsp;3.\u003c/b\u003e\u003c/p\u003e \u003cp\u003eSeveral factors were found to be significantly associated with VF including, initial viral load count of \u0026ge;\u0026thinsp;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\u0026ndash;35 months, TB infection during first-line ART, and having CD4 counts\u0026thinsp;\u0026lt;\u0026thinsp;200 cells/mm\u003csup\u003e3\u003c/sup\u003e during second-line ART. Interestingly, clients with CD4 counts\u0026thinsp;\u0026lt;\u0026thinsp;200 cells/mm\u003csup\u003e3\u003c/sup\u003e during first-line ART were found to have a reduced risk of failure.\u003c/p\u003e \u003cp\u003eComparatively, 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. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), 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. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). 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. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe 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. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), 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. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Edessa et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). 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. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Haftu et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). 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 \u0026ge;\u0026thinsp;1000 copies/ml after \u0026ge;\u0026thinsp;six months on second-line ART (WHO \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), while another study described it as a viral load of \u0026gt;\u0026thinsp;1000 copies/mL on at least one occasion after \u0026ge;\u0026thinsp;6 months, finding a VF rate of 129 per 1000 PY (Collier et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). 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. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Other possible reasons include geographic differences i) in HIV subtypes (Nastri et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and HIV-drug resistance (HIVDR) levels and patterns (Mazzuti et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), ii) the quality of care and community/social support, and iv) levels of adherence to ART (Fokam et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). 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 \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRegarding 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. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). 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 \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). 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. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and has better oral bioavailability compared with other protease inhibitors (Tigabu et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe 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. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), and those of another study conducted in Ethiopia that showed a 2.46 times higher rate of VF among clients with HIV-TB coinfection(Getaneh et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). 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 \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Getaneh et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In addition, many clients with TB-HIV co-infection experience adverse side effects due to the high pill burden (Daftary et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn 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. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). 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. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Diress et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Nastri et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe discovered that clients with an initial viral load count of \u0026ge;\u0026thinsp;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 \u0026ge;\u0026thinsp;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. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The same findings were also reported in Asia, with a risk of 2.90 (95% CI 1.17\u0026ndash;7.18), and in India with an odds ratio of 3.4 (Boettiger et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Chakravarty et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). This collective evidence supports the theory that a high baseline viral load causes delayed or incomplete suppression and a higher risk of viral rebound (Chen et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study found a significantly greater risk of virological failure in clients who have been on ART for 13\u0026ndash;35 months, representing an 8-fold 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 7-fold increase in the risk of virological failure (HR 6.93, 95% CI 2.62, 18.33) among clients on ART for 12\u0026ndash;23 months compared to those on ART for more than 48 months (Endebu et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Another study conducted in northeast Ethiopia (Diress et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) observed a high risk of failure among those on ART for 36\u0026ndash;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.\u003c/p\u003e \u003cp\u003eWe observed a high likelihood of treatment failure among clients with a CD4 count of less than 200 cells/mm\u003csup\u003e3\u003c/sup\u003e 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. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Interestingly, clients with a CD4 count of less than 200 cells/mm\u003csup\u003e3\u003c/sup\u003e 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.\u003c/p\u003e \u003cp\u003eOur 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. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The estimated cost of HIV Drug Resistance (HIVDR) is approximately 272 USD per test (Gachogo et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), 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. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), 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, which require a register for regular recording and monitoring.\u003c/p\u003e \u003cp\u003eThe 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 Control Programme (NACP) 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.\u003c/p\u003e \u003cp\u003eHowever, 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 National AIDS Control Program (NACP) 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.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis 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.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"659\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003eABC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eAbacavir\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003eAIDS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eAcquired Immunodeficiency Syndrome\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003eART\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eAntiretroviral Therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003eATV/r \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eAtazanavir/Ritonavir\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003eZDV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eAzidothymidine\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003eCTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eCare and Treatment Centre\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003eCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eConfidence Interval\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003eDRMs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eDrug Resistance Mutations\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003eEAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eEnhanced Adherence and Counselling\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003eHAART\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eHighly Active Antiretroviral Therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003eHIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eHuman Immunodeficiency Virus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003eHIVDR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eHIV Drug Resistance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003eHVL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eHIV Viral load\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003eIR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eIncidence Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003eLMICs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eLow- and Middle-Income Countries\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003eLPV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eLopinavir\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003eNASHCoP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eNational AIDS, STIs and Hepatitis Control Programe\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003ePCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003ePolymerase Chain Reaction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003ePY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003ePerson Years\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003ePDR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003ePre-treatment Drug Resistance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003ePI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eProtease Inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003ePLHIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003ePeople Living with HIV/AIDS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003ePMTCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003ePrevention of Mother To Child Transmission\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003eRTI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eReverse Transcriptase Inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003eRTV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eRitonavir\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003eTB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eTuberculosis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003eTDF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eTenofovir Disoproxil Fumarate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003eUNAIDS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eUnited Nations Program on HIV and AIDS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003eVF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eVirological Failure\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003eVL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eViral Load\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003eWHO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eWorld Health Organization\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.41578148710167%\" valign=\"top\"\u003e\n \u003cp\u003e3TC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"85.58421851289833%\" valign=\"top\"\u003e\n \u003cp\u003eLamivudine\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe 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.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe data supporting this study\u0026apos;s findings are available from the Tanzania National AIDS Control Program, but access to them is restricted and not publicly available.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study had no funds\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; contributions\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eETM, 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\u0026apos;s integrity and the data analysis\u0026apos;s accuracy.\u003c/p\u003e\n\u003cp\u003eAcknowledgments\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe 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.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlemu KD, Moges NA, Asrade AA et al (2022) Time to Switch to Second-Line Anti-Retroviral Treatment and Its Predictors Among HIV Infected Adults with Virological Failure in Northwest Ethiopia: A Retrospective Follow-Up Study. HIV/AIDS - Research and Palliative Care 14:87\u0026ndash;100. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2147/HIV.S348076\u003c/span\u003e\u003cspan address=\"10.2147/HIV.S348076\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlene M, Awoke T, Yenit MK, Tsegaye AT (2019) Incidence and predictors of second-line antiretroviral treatment failure among adults living with HIV in Amhara region: A multi-centered retrospective follow-up study. BMC Infect Dis doi. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12879-019-4243-5\u003c/span\u003e\u003cspan address=\"10.1186/s12879-019-4243-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarabona G, Mahiti M, Masoud S et al (2019) Pre-Treatment and acquired HIV drug resistance in Dar es Salaam, Tanzania in the era of tenofovir and routine viral load monitoring. J Antimicrob Chemother 74:3016\u0026ndash;3020. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/jac/dkz272\u003c/span\u003e\u003cspan address=\"10.1093/jac/dkz272\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBell LCK, Noursadeghi M (2017) Pathogenesis of HIV-1 and Mycobacterium tuberculosis co-infection. Nat Rev Microbiol 2017 16(2):80\u0026ndash;90. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/nrmicro.2017.128\u003c/span\u003e\u003cspan address=\"10.1038/nrmicro.2017.128\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBircher RE, Ntamatungiro AJ, Glass TR et al (2020) High failure rates of protease inhibitor-based antiretroviral treatment in rural Tanzania \u0026ndash; A prospective cohort study. PLoS ONE 15:e0227600. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0227600\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0227600\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoettiger DC, Nguyen VK, Durier N et al (2015) Efficacy of second-line antiretroviral therapy among people living with HIV/AIDS in Asia: Results from the TREAT Asia HIV observational database. J Acquir Immune Defic Syndr 68:186\u0026ndash;195. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/QAI.0000000000000411\u003c/span\u003e\u003cspan address=\"10.1097/QAI.0000000000000411\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCain LE (2015) Boosted lopinavir-versus boosted atazanavir-containing regimens and immunologic, virologic, and clinical outcomes: A Prospective study of HIV-infected individuals in high-income countries. Clin Infect Dis 60:1262\u0026ndash;1268. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/cid/ciu1167\u003c/span\u003e\u003cspan address=\"10.1093/cid/ciu1167\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCesar C, Shepherd BE, Jenkins CA et al (2014) Use of third line antiretroviral therapy in Latin America. PLoS ONE 9:1\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0106887\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0106887\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChakravarty J, Sundar S, Chourasia A et al (2015) Outcome of patients on second line antiretroviral therapy under programmatic condition in India. BMC Infect Dis 15:1\u0026ndash;11. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12879-015-1270-8\u003c/span\u003e\u003cspan address=\"10.1186/s12879-015-1270-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen S, Chen S, Han Y et al (2020) Very high baseline HIV viremia impairs efficacy of non-nucleoside reverse transcriptase inhibitor-based ART: a long-term observation in treatment-na\u0026iuml;ve patients. Infect Dis Poverty doi. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/S40249-020-00700-8\u003c/span\u003e\u003cspan address=\"10.1186/S40249-020-00700-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCollier D, Iwuji C, Derache A et al (2017) Virological Outcomes of Second-line Protease Inhibitor-Based Treatment for Human Immunodeficiency Virus Type 1 in a High-Prevalence Rural South African Setting: A Competing-Risks Prospective Cohort Analysis. Clin Infect diseases: official publication Infect Dis Soc Am 64:1006\u0026ndash;1016. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/CID/CIX015\u003c/span\u003e\u003cspan address=\"10.1093/CID/CIX015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCrowell TA, Danboise B, Parikh A et al (2021) Pretreatment and Acquired Antiretroviral Drug Resistance Among Persons Living With HIV in Four African Countries. Clin Infect diseases: official publication Infect Dis Soc Am 73:e2311\u0026ndash;e2322. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/cid/ciaa1161\u003c/span\u003e\u003cspan address=\"10.1093/cid/ciaa1161\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDaftary A, Padayatchi N, O\u0026rsquo;Donnell M (2014) Preferential adherence to antiretroviral therapy over tuberculosis treatment: A qualitative study of drug-resistant TB/HIV co-infected patients in South Africa. Glob Public Health 9:1107\u0026ndash;1116. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/17441692.2014.934266\u003c/span\u003e\u003cspan address=\"10.1080/17441692.2014.934266\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDiress G, Dagne S, Alemnew B et al (2020) Viral Load Suppression after Enhanced Adherence Counseling and Its Predictors among High Viral Load HIV Seropositive People in North Wollo Zone Public Hospitals, Northeast Ethiopia, 2019: Retrospective Cohort Study. AIDS Res Treat. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1155/2020/8909232\u003c/span\u003e\u003cspan address=\"10.1155/2020/8909232\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEdessa D, Sisay M, Asefa F (2019) Second-line HIV treatment failure in subSaharan Africa: A systematic review and metaanalysis. PLoS ONE 14:1\u0026ndash;19. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0220159\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0220159\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEndebu T, Deksisa A, Moges T et al (2018) Incidence of Virological Failure and Associated Factors among Adult HIV-Positive Patients on First Line Antiretroviral Therapy Regimen, Central Ethiopia. International Journal of HIV/AIDS Prevention, Education and Behavioural Science 4:44\u0026ndash;51. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.11648/j.ijhpebs.20180402.13\u003c/span\u003e\u003cspan address=\"10.11648/j.ijhpebs.20180402.13\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFokam J, Nangmo A, Wandum C et al (2020) Programme quality indicators of HIV drug resistance among adolescents in urban versus rural settings of the centre region of Cameroon. AIDS Res Therapy 17:1\u0026ndash;10. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12981-020-00270-7\u003c/span\u003e\u003cspan address=\"10.1186/s12981-020-00270-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGachogo RW, Mwai DN, Onyambu FG (2020) Cost analysis of implementing HIV drug resistance testing in Kenya: A case study of a service delivery site at a tertiary level hospital in Kenya. F1000Research. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.12688/f1000research.23379.1\u003c/span\u003e\u003cspan address=\"10.12688/f1000research.23379.1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGetaneh T, Negesse A, Dessie G, Desta M (2022) The impact of tuberculosis co-infection on virological failure among adults living with HIV in Ethiopia: A systematic review and meta-analysis. J Clin Tuberculosis Other Mycobact Dis 27:100310. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jctube.2022.100310\u003c/span\u003e\u003cspan address=\"10.1016/j.jctube.2022.100310\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGumede SB, Venter F, De Wit J et al (2022) Antiretroviral therapy uptake and predictors of virological failure in patients with HIV receiving first-line and second-line regimens in Johannesburg, South Africa: A retrospective cohort data analysis. BMJ Open 12:54019. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmjopen-2021-054019\u003c/span\u003e\u003cspan address=\"10.1136/bmjopen-2021-054019\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGunda DW, Kilonzo SB, Mtaki T et al (2019) Magnitude and correlates of virological failure among adult HIV patients receiving PI based second line ART regimens in north western Tanzania; A case control study. BMC Infect Dis 19:1\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12879-019-3852-3\u003c/span\u003e\u003cspan address=\"10.1186/s12879-019-3852-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHaftu AZ, Desta AA, Bezabih NM et al (2020) Incidence and factors associated with treatment failure among HIV infected adolescent and adult patients on second-line antiretroviral therapy in public hospitals of Northern Ethiopia: Multicenter retrospective study. PLoS ONE 15:1\u0026ndash;15. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0239191\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0239191\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHawkins C, Ulenga N, Liu E et al (2016) HIV virological failure and drug resistance in a cohort of Tanzanian HIV-infected adults. J Antimicrob Chemother 71:1966\u0026ndash;1974. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/jac/dkw051\u003c/span\u003e\u003cspan address=\"10.1093/jac/dkw051\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMasaba R, Woelk G, Siamba S et al (2023) Antiretroviral treatment failure and associated factors among people living with HIV on therapy in Homa Bay, Kenya: A retrospective study. PLOS Global Public Health 3:e0001007. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pgph.0001007\u003c/span\u003e\u003cspan address=\"10.1371/journal.pgph.0001007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMasresha SA, Kidie AA, Alen GD et al (2023) Virological failure and its predictors among human immunodeficiency virus infected individuals on second line antiretroviral treatment in North-East Ethiopia, 2021. Pharmacoepidemiology and Drug Safety. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/pds.5625\u003c/span\u003e\u003cspan address=\"10.1002/pds.5625\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMazuguni NS, Mazuguni F, Muro EP (2021) Detectable viral load among HIV \u0026ndash;\u0026thinsp;1 positive pregnant women on ART (Option B +) in northern Tanzania: Baseline results from the HIVDR study. East Afr Sci 3:44\u0026ndash;50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.24248/easci-d-20-00009\u003c/span\u003e\u003cspan address=\"10.24248/easci-d-20-00009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMazzuti L, Melengu T, Falasca F et al (2020) Transmitted drug resistance mutations and trends of HIV-1 subtypes in treatment-na\u0026iuml;ve patients: A single-centre experience. J Global Antimicrob Resist 20:298\u0026ndash;303. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jgar.2019.08.024\u003c/span\u003e\u003cspan address=\"10.1016/j.jgar.2019.08.024\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMchomvu RD, Hussein AK, Matee M (2022) Determinants of viral load non-suppression among HIV-positive children and adolescents attending care and treatment clinics in Tabora region, Tanzania. Bulletin of the National Research Centre. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s42269-022-00961-3\u003c/span\u003e\u003cspan address=\"10.1186/s42269-022-00961-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMusana H, Ssensamba JT, Nakafeero M et al (2021) Predictors of failure on second-line antiretroviral therapy with protease inhibitor mutations in Uganda. AIDS Res Therapy 18:1\u0026ndash;10. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12981-021-00338-y\u003c/span\u003e\u003cspan address=\"10.1186/s12981-021-00338-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNaidoo K, Ramruthan J, Reddy M, Lancaster R (2022) A third-line antiretroviral therapy register to track patient clinical and virological outcomes. South Afr Med J 112:511\u0026ndash;512. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.7196/SAMJ.2022.v112i8.16695\u003c/span\u003e\u003cspan address=\"10.7196/SAMJ.2022.v112i8.16695\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNastri BM, Pagliano P, Zannella C et al (2023) HIV and Drug-Resistant Subtypes. Microorganisms 11:221. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/MICROORGANISMS11010221/S1\u003c/span\u003e\u003cspan address=\"10.3390/MICROORGANISMS11010221/S1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNsanzimana S, Semakula M, Ndahindwa V et al (2019) Retention in care and virological failure among adult HIV\u0026thinsp;+\u0026thinsp;patients on second-line ART in Rwanda: a national representative study. BMC Infect Dis 19:1\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12879-019-3934-2\u003c/span\u003e\u003cspan address=\"10.1186/s12879-019-3934-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNwokolo N, Whitlock G, McOwan A (2017) Not just PrEP: other reasons for London\u0026rsquo;s HIV decline. Lancet HIV 4:e153. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S2352-3018(17)30044-9\u003c/span\u003e\u003cspan address=\"10.1016/S2352-3018(17)30044-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOlakunde BO, Adeyinka DA, Ozigbu CE et al (2019) Revisiting aid dependency for HIV programs in Sub-Saharan Africa. Public Health 170:57\u0026ndash;60. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/J.PUHE.2019.02.016\u003c/span\u003e\u003cspan address=\"10.1016/J.PUHE.2019.02.016\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePingarilho M, Pimentel V, Diogo I et al (2020) Increasing prevalence of HIV-1 transmitted drug resistance in Portugal: Implications for first line treatment recommendations. Viruses 12:1238. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/v12111238\u003c/span\u003e\u003cspan address=\"10.3390/v12111238\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRamadhani HO, Bartlett JA, Thielman NM et al (2016) The Effect of Switching to Second-Line Antiretroviral Therapy on the Risk of Opportunistic Infections Among Patients Infected With Human Immunodeficiency Virus in Northern Tanzania. Open Forum Infect Dis. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/OFID/OFW018\u003c/span\u003e\u003cspan address=\"10.1093/OFID/OFW018\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRodger AJ, Cambiano V, Phillips AN et al (2019) Risk of HIV transmission through condomless sex in serodifferent gay couples with the HIV-positive partner taking suppressive antiretroviral therapy (PARTNER): final results of a multicentre, prospective, observational study. Lancet 393:2428\u0026ndash;2438. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0140-6736(19)30418-0\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(19)30418-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSam M, Masaba JPM, Alio D, Byakika-Tusiime J (2021) Treatment Failure and Associated Factors among Individuals on Second Line Antiretroviral Therapy in Eastern Uganda: A Retrospective Cohort Study. Infect Diseases: Res Treat 14:117863372110145. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/11786337211014518\u003c/span\u003e\u003cspan address=\"10.1177/11786337211014518\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTemereanca A, Ruta S (2023) Strategies to overcome HIV drug resistance-current and future perspectives. Front Microbiol 14:1\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fmicb.2023.1133407\u003c/span\u003e\u003cspan address=\"10.3389/fmicb.2023.1133407\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTHIS (2022) The United Republic of Tanzania. TANZANIA HIV IMPACT SURVEY 2023:6\u0026ndash;9\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTigabu BM, Agide FD, Mohraz M, Nikfar S (2020) Atazanavir / ritonavir versus lopinavir / ritonavir-based combined antiretroviral therapy (cART) for HIV-1 infection: A systematic review and meta-analysis. Afr Health Sci 20:91\u0026ndash;101. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4314/ahs.v20i1.14\u003c/span\u003e\u003cspan address=\"10.4314/ahs.v20i1.14\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTrickey A, May MT, Vehreschild JJ et al (2017) Survival of HIV-positive patients starting antiretroviral therapy between 1996 and 2013: a collaborative analysis of cohort studies. Lancet HIV 4:e349\u0026ndash;e356. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S2352-3018(17)30066-8\u003c/span\u003e\u003cspan address=\"10.1016/S2352-3018(17)30066-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTsegaye AT, Wubshet M, Awoke T et al (2016) Predictors of treatment failure on second-line antiretroviral therapy among adults in northwest Ethiopia: A multicentre retrospective follow-up study. BMJ Open 6:1\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmjopen-2016-012537\u003c/span\u003e\u003cspan address=\"10.1136/bmjopen-2016-012537\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWHO (2021) Consolidated guidelines on HIV prevention, testing, treatment, service delivery and monitoring: recommendations for a public health approach. World Health Organization, In: Geneva\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWHO (2022) World Cancer Day 2022 WHO Regional Office for Africa. In: WHO Africa. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.afro.who.int/regional-director/speeches-messages/world-aids-day-2022\u003c/span\u003e\u003cspan address=\"https://www.afro.who.int/regional-director/speeches-messages/world-aids-day-2022\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 2 May 2024\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZakaria HF, Raru TB, Hassen FA et al (2022) Incidence and Predictors of Virological Failure Among Adult HIV/AIDS Patients on Second-Line Anti-Retroviral Therapy, in Selected Public Hospital of Addis Ababa, Ethiopia: Retrospective Follow-Up Study. HIV/AIDS - Research and Palliative Care 14:319\u0026ndash;329. doi: 10.2147/HIV.S367677 (2019) National Guidelines for the Management of HIV and AIDS.Ministry of Health Community Development, Gender, Eldery and Children. Development 7:2,274,923,575.00-29.08\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bulletin-of-the-national-research-centre","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnrc","sideBox":"Learn more about [Bulletin of the National Research Centre](https://BNRC.springeropen.com)","snPcode":"42269","submissionUrl":"https://submission.springernature.com/new-submission/42269/3","title":"Bulletin of the National Research Centre","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Prevalence, Rate, Predictors, Virologic failure, Second-line ART, Tanzania","lastPublishedDoi":"10.21203/rs.3.rs-4744820/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4744820/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAntiretroviral 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.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWe followed 4,718 clients for 15,100 person-years (PY) of observations. Of them, 1,402 experienced virologic failure, equivalent to 29.72% 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 \u0026ge;\u0026thinsp;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\u0026thinsp;\u0026lt;\u0026thinsp;200 cells/mm\u003csup\u003e3\u003c/sup\u003e during second-line ART (HR 1.89 (95% CI 1.46, 2.44), and being on ART for 13\u0026ndash;35 months (HR 8.22 (95% CI 2.21, 30.61). Paradoxically, having a CD4 count\u0026thinsp;\u0026lt;\u0026thinsp;200 cells/mm\u003csup\u003e3\u003c/sup\u003e during first-line ART treatment was associated with a reduced risk of virologic failure (HR 0.77 95% CI 0.60, 0.99).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eIn Tanzania, approximately 30% of the adult clients on second-line ART experience VF at a rate of 92.71 per 1000 person-years. This high virologic failure rate highlights the need for targeted interventions for HIV-infected clients on second-line ART to reduce the need for switching to the more costly and relatively more toxic third-line ART therapy and help to achieve the third UNAIDS goal of achieving viral suppression for 95% of those treated by 2030.\u003c/p\u003e","manuscriptTitle":"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","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-02 13:48:49","doi":"10.21203/rs.3.rs-4744820/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2024-08-16T16:25:20+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-16T15:57:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-16T10:37:06+00:00","index":"","fulltext":""},{"type":"submitted","content":"Bulletin of the National Research Centre","date":"2024-08-15T02:10:25+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bulletin-of-the-national-research-centre","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnrc","sideBox":"Learn more about [Bulletin of the National Research Centre](https://BNRC.springeropen.com)","snPcode":"42269","submissionUrl":"https://submission.springernature.com/new-submission/42269/3","title":"Bulletin of the National Research Centre","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"33ab3cec-4be8-4982-b425-1a1a77525ea3","owner":[],"postedDate":"September 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-10-07T15:59:13+00:00","versionOfRecord":{"articleIdentity":"rs-4744820","link":"https://doi.org/10.1186/s42269-024-01248-5","journal":{"identity":"bulletin-of-the-national-research-centre","isVorOnly":false,"title":"Bulletin of the National Research Centre"},"publishedOn":"2024-10-01 15:56:59","publishedOnDateReadable":"October 1st, 2024"},"versionCreatedAt":"2024-09-02 13:48:49","video":"","vorDoi":"10.1186/s42269-024-01248-5","vorDoiUrl":"https://doi.org/10.1186/s42269-024-01248-5","workflowStages":[]},"version":"v1","identity":"rs-4744820","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4744820","identity":"rs-4744820","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}