Impact of transition to Dolutegravir-based antiretroviral therapy on virological suppression among children living with HIV in Southern Nigeria: A before and after analysis of program data

Impact of transition to Dolutegravir-based antiretroviral therapy on virological suppression among children living with HIV in Southern Nigeria: A before and after analysis of program data | 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 Impact of transition to Dolutegravir-based antiretroviral therapy on virological suppression among children living with HIV in Southern Nigeria: A before and after analysis of program data Izuchukwu Ani, Ihoghosa Iyamu, Uduak Akpan, Esther Nwanja, Ogheneuzuazo Onwah, and 24 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5434482/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background In 2021, Nigeria introduced the 10mg paediatric dolutegravir (DTG) formulation for children living with HIV (CLHIV) aiming to improve virological outcomes, and immediately commenced transitioning children < 10 years old on first-line non-DTG-based regimen to DTG. We assessed the association between the transition to DTG-based ART and virological suppression among CLHIV. Methods We conducted a retrospective cohort study using routinely collected data from 121 PEPFAR-supported health facilities in Akwa Ibom and Cross River States. We included all ART-experienced CLHIV who were transitioned to DTG between July and December 2021, had a baseline viral load (VL) assessment before the transition and VL ≥ 6 months after transitioning. We defined VL as a three-level outcome (i.e., ≤ 50 copies/ml – undetectable, 51–999 copies/ml – low-level viremia and ≥ 1,000 copies/ml – unsuppressed). We assessed the association between the transition to DTG and VL using ordinal logistic regression with generalized estimating equations. We also conducted additional sensitivity analyses on a complete case dataset and assessed the impact of the transition on various definitions of virological suppression including undetectable (< 50 copies/ml) vs. detectable (≥ 50 copies/ml). Results Out of 1,951 CLHIV included in this analysis, 1,250 (64.1%) were between the ages of five and nine, 993 (50.9%) were male. Among these, 1,786 (91.5%) had undetectable VL levels, up from 1,611 (82.6%) at baseline, while 123 (6.3%) had low-level viraemia, down from 271 (13.9%) initially. The transition to DTG-based ART was associated with virological suppression (adjusted odds ratio [aOR]: 1.70, 95%CI: 1.20, 2.41) and undetectable VL (aOR: 2.56, 95%CI: 2.06, 3.19). Findings were consistent in sensitivity analyses. Conclusions CLHIV achieved favourable virological changes when transitioned to DTG-based ART, including undetectable viral load rates. Findings suggest DTG can improve overall program outcomes and reduce the risk for low-level viremia in CLHIV, emphasizing its role in achieving HIV epidemic control among CLHIV. HIV Integrase Inhibitors HIV in Children Low-level viraemia HIV outcomes Antiretroviral therapy Figures Figure 1 Introduction In 2018, the World Health Organization (WHO) recommended dolutegravir (DTG) as its preferred first and second-line antiretroviral therapy (ART) among all people living with HIV (PLHIV) including women and children. 1 , 2 Recommendations for DTG are based on data suggesting its superior efficacy in ensuring virological suppression, higher genetic barrier to resistance and more tolerable adverse effect profile. 3 – 5 Therefore HIV treatment programs including those funded by the US President’s Emergency Plan for AIDS Relief (PEPFAR) have supported the transition of treatment naïve and treatment-experienced clients to DTG-based ART. This transition has been considered an important strategy to reach the UNAIDS 95-95-95 targets. 6 By 2022, over 87% of PLHIV within PEPFAR’s global program had been transitioned to DTG-based ART, with early evidence of improved virological suppression. 7 – 9 . As of 2023, Nigeria had an estimated 2 million PLHIV, with 85% of these on ART and 82% achieving virologic suppression. 10 , 11 While this represents significant progress, with 90% of adults aged 15 years or older receiving ART, coverage among children aged 0–14 years lags behind country averages with only 29% of the estimated 45,000 children living with HIV (CHLIV) currently on ART. 10 In 2018, Nigeria commenced its transition to DTG-based ART, initially recommending transition for adults, adolescents, and children 6 years and older. 12 In 2021, following the introduction of a 10mg DTG formulation, PEPFAR-supported programs in Nigeria, in line with country guidelines, commenced transitioning of children who weighed less than 30kg to DTG-based therapy. 13 As of 2022, about 90% of all PLHIV on ART had been transitioned to DTG-based ART. 7 While there is ample program evidence of the impact of DTG-based therapy on virological suppression among adult PLHIV, evidence among children is limited, especially in Nigeria. 8 , 14 Where available, global evidence is limited to children weighing 14kg and over, in controlled settings. 15 Program evidence from Northern Nigeria suggests a non-significant effect of DTG-based ART on viral load suppression among CLHIV. 16 However, these findings are not necessarily generalizable to southern Nigeria given the heterogeneity within the program especially between Northern and Southern Nigeria. 17 Moreover, the cross-sectional design of the studies may have exposed its findings to confounding. 18 Further, there are emergent concerns about the potential for low-level viremia to result in virological failure, treatment resistance and increased viral transmissibility. 14 , 19 This is especially concerning given the acceleration of the undetectable equals untransmissible (U = U) campaign to destigmatize HIV. 20 While there is evidence that DTG-based ART reduces the prevalence and risk of low-level viremia, this evidence is mostly among adults. 14 , 21 Evidence among children especially in Nigeria is lacking and urgently needed to guide programs. To address these knowledge gaps regarding the HIV control programs for CLHIV, we reviewed routinely collected program data from a PEPFAR-funded comprehensive HIV epidemic control program in Akwa Ibom and Cross River states in southern Nigeria. We assessed the association between the transition to DTG-based ART and virological suppression among CLHIV. Here we assessed virological suppression at the WHO-defined level (i.e., < 1,000 viral copies/ml) and virologic suppression at undetectable levels (i.e., < 50 viral copies/ml). We hypothesized that virologic suppression rates among CLHIV would improve after the transition to DTG-based ART. Methods Study setting The Accelerating Control of the HIV Epidemic in Nigeria (ACE-5) Project supports the government of Nigeria in implementing comprehensive HIV services in Akwa-Ibom and Cross River states, Nigeria. 22 The project is implemented by Excellence Community Education Welfare Scheme (ECEWS) with funding from PEPFAR through the United States Agency for International Development (USAID). 22 Akwa-Ibom and Cross-River states are adjoining coastal states with HIV prevalence higher than the national average of 1.4%. Akwa-Ibom has the highest prevalence in the country at 4.8% while Cross-River has a prevalence of 1.6%. 11 ART services are provided free of charge through primary, secondary and tertiary health centres, with the highest level of care available at tertiary facilities where specialists and sub-specialists provide services, and the lowest level available at primary health facilities where nurses and community health workers provide services. 23 Differentiated service delivery (DSD) models are provided to clients on ART including children 5 years and older, in line with the National Guidelines for DSD. 24 Viral load testing for children is done six-monthly and during the study period, viral load assessments were conducted using Abbott®, and Hologic Panther®, each with a low detection limit (< 40 copies/ mL). 13 Study design and population This was a retrospective study of a cohort of ART-experienced CLHIV who were on first-line non-DTG-based ART regimen at the beginning of the study period (July 2021) in 121 health facilities in Akwa Ibom and Cross River States. These CLHIV were then transitioned to a DTG-based regimen for CLHIV between July and December 2021. Prior to the beginning of the transition, healthcare workers were trained on the formulation, dosing and adverse effects of DTG, caregivers were sensitized on the regimen during clinic encounters, and eligible CLHIV were line-listed. The actual transition to a DTG-based regimen was done during their routine clinic visits. We reviewed routinely collected program data for these CLHIV across the 121 health facilities supported by the ACE-5 project. First, we extracted client-level data from the Lafiya Management Information System-Plus (LAMIS-Plus) – an electronic medical record for ART services within PEPFAR-funded health facilities in Nigeria. This database includes demographic data like age and biological sex and clinical data including dates of ART commencement, ART regimen, WHO clinical stage, weight and viral load. Next, we extracted facility characteristics from program records, linking them with client-level data to explore facility-level characteristics associated with virological outcomes. Baseline (pre-transition) variables were abstracted as of December 2021, with endline (post-transition) variables abstracted for the period January to December 2022. Our reporting complies with the Reporting of studies Conducted using Observational Routinely collected health Data (RECORD) Statement. 25 Exposure, Outcome and confounding variables The main outcome variable was virological suppression defined in three ways. First as a three-level outcome (i.e., viral load ≤ 50 viral copies/ml – undetectable, 51–999 viral copies/ml – low-level viremia and ≥ 1,000 copies/ml – unsuppressed) [ref]. We defined a second outcome based on WHO guidelines for virological suppression (i.e., viral load < 1,000 viral copies/ml – suppressed and ≥ 1,000 copies/ml – unsuppressed). Third, we defined viral load as undetectable (< 50 viral copies/ml) or detectable (≥ 50 viral copies/ml). 1 Our main exposure was defined as the transition from traditional ART (e.g., nucleoside reverse transcriptase inhibitor (NRTI), non-nucleoside reverse transcriptase inhibitor (NNRTI) and protease inhibitor (PI)-based ART) to at least 6 months of DTG-based ART. Confounding variables included age (categorized as children aged < 5 years and between five and nine years old), biological sex (female or male), time on non-DTG ART (measured in months), weight at transition (in kg), baseline WHO clinical stage (categorized as stages 1, 2 and 3–4), urbanicity (i.e., how urban the region of residence is – categorized as urban or rural), facility care level (categorized as primary, secondary or tertiary), facility ownership (categorized as private-for-profit, private-not-for-profit and public). Analytic dataset and statistical analyses For our analytic dataset, we only included data for all ART-experienced CLHIV currently in care who were transitioned to DTG between July and December 2021, had a baseline viral load assessment before the transition and had reassessed their viral load at least 6 months post-transition to DTG and we still currently in care (Fig. 1 ). Only children with both a baseline and endline VL were included in the main analysis. We summarized the data using simple descriptive statistics (frequencies, proportions, means and medians). Given 0.2% and 16.9% missingness for baseline WHO clinical staging and weight at transition to DTG respectively, we conducted our main analysis using data multiply imputed in 20 datasets using multivariate imputation by chained equations (MICE) under the missing at random assumption. 26 This assumption was reasonable considering missingness in weight was higher among people at WHO stage 1 and covaried with age. Multiple imputation was conducted using the MICE package. 26 For each of the outcomes, bivariable analyses were conducted using ordinal and binomial logistic regression models with generalized estimating equations to account for clustering at the individual level. 27 While other studies assert clustering at the facility level, such models showed poor fit and were not included in the analyses. 16 For multivariable analyses, we held predictors known to be associated with virological suppression steady while adding additional variables and comparing Bayesian Information Criteria, selecting the final variables based on the majority rule. 28 , 29 The models were run on all imputed datasets with the final estimates pooled using Rubin’s rules. 30 We checked model fit using Hosmer-Lemeshow’s test and assessed collinearity, setting a threshold of variance < 10. 31 To assess the robustness of our findings, we conducted sensitivity analyses by rerunning our main ordinal logistic regression on a complete-case dataset, excluding any individuals with missing values. We purposefully included variables from the main analyses within the sensitivity analyses. All analyses were conducted at a significance level of 5%. All analyses were conducted using R version 4.4.1. 32 Results Sample characteristics Overall, we included data from 1,951 ART-experienced CLHIV transitioned to DTG between July and December 2021 and had both a baseline and endline viral load. Among these, 1,250 (64.1%) were aged between five and nine years, 993 (50.9%) were male, 1101 (56.4%) were in rural areas, 1,039 (63.9%) had a baseline WHO clinical stage 1 assessment, and 1,809 (92.7%) were receiving care in public health facilities (Table 1). Table 1: Characteristics of ART-experienced children living with HIV who were transitioned from non-DTG to DTG-based ART between July and December 2021 in Akwa Ibom and Cross River States, Nigeria Factors Analytic sample included in baseline and endline analysis N (%) 1951 (100%) * Age category (in years) <5 years 5-9 years 701 (35.9) 1250 (64.1) Biological Sex Female Male 958 (49.1) 993 (50.9) Time on ART in months (median (IQR)) 37.20 (27.92, 58.13) Weight (in kgs) at transition to DTG (mean (SD)) 17.40 (5.61) Baseline WHO clinical stage Stage 1 Stage 2 Stage 3 or 4 1039 (63.9) 344 (21.1) 244 (15.0) Urbanicity Rural Urban 1101 (56.4) 850 (43.6) Facility care level Primary Secondary Tertiary 972 (49.8) 900 (46.1) 79 (4.0) Facility ownership Private for-profit Private not-for-profit Public 96 (4.9) 46 (2.4) 1809 (92.7) DTG: Dolutegravir; IQR: Interquartile range; NRTI: nucleoside reverse transcriptase inhibitors; NNRT: Non-nucleoside reverse transcriptase inhibitors; PI: Protease inhibitors; SD: Standard deviation; WHO: World Health Organization. At baseline, 1,611 (82.6%) of the 1,951 CLHIV included in the study had undetectable viral load levels, while 271 (13.9%) had low-level viraemia. Among the 1,951 CLHIV at endline, those with undetectable viral load had increased to 91.5% (n=1,786) while those with low-level viremia had reduced to 6.3% (n=123) (Table 2). These patterns were similar across age and sex strata (Table 2). Table 2: Viral load outcomes among ART-experienced children living with HIV who were transitioned from non-DTG to DTG-based ART between July and December 2021 in Akwa Ibom and Cross River States, Nigeria Viral load Outcomes Baseline (on NRTIs, NNRTI, or PI-based ART) N (%) Endline (after 6 months on DTG-based ART) N (%) * Viral load (all CLHIV on ART) Unsuppressed (≥1000 copies/ml) Low-level viraemia (51-999 copies/ml) Undetectable (≤50 copies/ml) 69 (3.5) 271 (13.9) 1611 (82.6) 42 (2.2) 123 (6.3) 1786 (91.5) Viral load (CLHIV 0-4 years) Unsuppressed (≥1000 copies/ml) Low-level viraemia (51-999 copies/ml) Undetectable (≤50 copies/ml) 22 (3.1) 104 (14.8) 575 (82.0) 12 (1.7) 35 (5.0) 654 (93.3) Viral load (CLHIV – 5-9 years) Unsuppressed (≥1000 copies/ml) Low-level viraemia (51-999 copies/ml) Undetectable (≤50 copies/ml) 47 (3.8) 167 (13.4) 1036 (82.9) 30 (2.4) 88 (7.0) 1132 (90.6) Viral load (Female CLHIV) Unsuppressed (≥1000 copies/ml) Low-level viraemia (51-999 copies/ml) Undetectable (≤50 copies/ml) 32 (3.3) 129 (13.5) 797 (83.2) 23 (2.4) 57 (5.9) 878 (91.6) Viral load (Male CLHIV) Unsuppressed (≥1000 copies/ml) Low-level viraemia (51-999 copies/ml) Undetectable (≤50 copies/ml) 37 (3.7) 142 (14.3) 814 (82.0) 19 (1.9) 66 (6.6) 908 (91.4) DTG: Dolutegravir; IQR: Interquartile range; NRTI: nucleoside reverse transcriptase inhibitors; NNRT: Non-nucleoside reverse transcriptase inhibitors; PI: Protease inhibitors; SD: Standard deviation; WHO: World Health Organization; * Indicates subset of baseline cohort remaining at least 6 months after initiation of DTG-based ART. Impact of the transition to dolutegravir-based ART In bivariable ordinal logistic regression (Table 3), the transition to DTG-based ART was associated with improved virological suppression (odds ratio [OR]: 1.72, 95% confidence interval [CI]: 1.23,2.46) at least 6 months after the transition. This association stayed consistent when adjusted for age, sex, weight (in kgs) at the transition to DTG, facility ownership, facility level, and urbanicity (adjusted odds ratio [aOR]: 1.71, 95%CI: 1.21, 2.41). Table 3: Association between the transition to DTG-based ART and Viral load – Ordinal logistic regression Variables Crude Odds Ratio (95% Confidence Interval) a Adjusted Odds Ratio (95% Confidence Interval) b Intercepts Low-level viraemia | Undetectable Unsuppressed | Low-level-viraemia NA 3.94 (1.75, 8.83) * 20.49 (9.01, 46.58) * Regimen (time point) Baseline (on NRTIs, NNRTI, or PI-ART) Endline (on DTG-ART) Ref 1.72 (1.23, 2.46) * Ref 1.71 (1.21, 2.41) * Age category Under-five years Five-nine years Ref 0.80 (0.54, 1.18) Ref 0.78 (0.49, 1.23) Biological sex Female Male Ref 1.01 (0.71, 1.44) Ref 1.04 (0.73, 1.50) Time on ART in months 1.00 (0.99, 1.00) - Weight (in kgs) at the transition to DTG 1.02 (0.98, 1.05) 1.02 (0.99, 1.05) Baseline WHO clinical stage Stage 1 Stage 2 Stage 3 or 4 Ref 0.61 (0.40, 0.93) 0.65 (0.41, 1.04) - Urbanicity Rural Urban Ref 0.55 (0.38, 0.79) * Ref 0.67 (0.42, 1.06) Facility care level Primary Secondary Tertiary Ref 0.63 (0.43, 0.93) * 0.43 (0.22, 0.84) * Ref 0.76 (0. 48, 1.19) 0.52 (0.24, 1.12) Facility ownership Private for-profit Private not-for-profit Public Ref 0.89 (0.31, 2.54) 1.92 (1.06, 3.49) * Ref 0.99 (0.34, 2.83) 0.67 (0.42, 1.06) DTG: Dolutegravir; IQR: Interquartile range; NA: Not Applicable; NRTI: nucleoside reverse transcriptase inhibitors; NNRT: Non-nucleoside reverse transcriptase inhibitors; PI: Protease inhibitors; SD: Standard deviation; WHO: World Health Organization; * Significant at p<0.05; All Variance Inflating Factors (VIF) <5; a,b Models run on 20 multiply imputed datasets and pooled using Rubin’s rules. Based on the WHO categorization (i.e., viral load <1,000 copies/ml), the transition to DTG-based ART was associated with virological suppression (aOR: 1.62, 95%CI: 1.08, 2.43) (Table 4). Similar associations were observed when considering the effect of the transition to DTG-based therapy on undetectable viral load levels among CLHIV (aOR: 2.56, 95%CI: 2.06, 3.18). In the sensitivity analysis repeating the main ordinal logistic regression on a complete dataset, the transition to DTG-based ART was consistent and associated with virological suppression (aOR: 1.67, 95%CI: 1.15, 2.42). Table 4: Unadjusted and Adjusted associations between the transition to DTG-based ART and various definitions of virological suppression Variables Crude Odds Ratio (95% Confidence Interval) Adjusted Odds Ratio (95% Confidence Interval) a Model 1: Association between the transition to DTG-based ART and virological suppression based on WHO definition (VL<1000 copies/ml) Regimen (time point) # Baseline (on NRTIs, NNRTI, or PI-ART) Endline (on DTG-ART) Ref 1.62 (1.08, 2.41) * Ref 1.62 (1.08, 2.43) * Model 2: Association between the transition to DTG-based ART and virological undetectability (VL≤50 copies/ml) Regimen (time point) # Baseline (on NRTIs, NNRTI, or PI-ART) Endline (on DTG-ART) Ref 2.54 (2.04, 3.15) * Ref 2.56 (2.06, 3.18) * Model 3: Association between the transition to DTG-based ART and virological suppression in ordinal logistic regression $ Intercepts Low-level viraemia | Undetectable Unsuppressed | Low-level-viraemia NA 4.21 (1.67, 1.92) 20.67 (9.32, 45.85) Regimen (time point) Baseline (on NRTIs, NNRTI, or PI-ART) Endline (on DTG-ART) Ref 1.70 (1.18, 2.46) * Ref 1.67 (1.15, 2.42) * DTG: Dolutegravir; IQR: Interquartile range; NA: Not Applicable; NRTI: nucleoside reverse transcriptase inhibitors; NNRT: Non-nucleoside reverse transcriptase inhibitors; PI: Protease inhibitors; SD: Standard deviation; WHO: World Health Organization; * Significant at p<0.05; All Variance Inflating Factors (VIF) <5; # Models run on 20 multiply imputed datasets and pooled using Rubin’s rules; $ Models run on a complete case dataset, a All models adjusted for age, sex, weight (in kgs) at transition to DTG, facility ownership, facility level, urbanity and state. Discussion In this review of routinely collected data from a comprehensive ART program in 121 health facilities in Akwa-Ibom and Cross River states in Nigeria, we found that at least 6 months after the transition to DTG-based therapy, the proportion of ART-experienced CLHIV with undetectable VL increased from 82.5–91.5% and those with low-level viremia reduced from 13.6–6.3%. We also found the transition was associated with approximately 71% greater odds of virological suppression and 156% greater odds of undetectable viral load at least 6 months after the transition. These findings were consistent in both an imputed dataset and in a complete case analysis. Findings from this study add much-needed robust evidence about the impact of the transition to DTG-based ART especially among CLHIV in Southern Nigeria since recommendations took effect. 13 We have previously described the dearth of evidence of the impact of the transition to DTG-based ART in this population with most studies being among adolescents and adults aged 15 years or older, and in Northern Nigeria. 14 – 16 Our findings support those from other studies in adults and children which showed an association between DTG-based ART and improved undetectable viraemia. 14 , 21 , 33 , 34 However, these findings contrast those from a single-centre prospective study in Northern Nigeria where DTG-based ART had comparable impacts on viral suppression with non-DTG-based ART. 16 Given the longitudinal and paired nature of our analysis and its consistency with other similar studies, it is more plausible that DTG-based therapy significantly improves viral suppression in CLHIV. Moreover, we have previously demonstrated that DTG significantly reduces the risk of persistent low-level viraemia, and the current study findings are consistent with thisassertion. 21 , 33 Findings from our study have public health significance, especially in children given long-standing challenges with drug resistance, especially with nevirapine-based ART, adherence challenges with unpalatable formulations of lopinavir and other protease inhibitors and long-term side effects and toxicity concerns. 35 – 38 Given that DTG-based ART has significantly higher drug resistance barriers and simpler formulations, this transition can support program-level improvements in virological suppression among children who have historically lagged the general population both in terms of ART coverage and treatment outcomes. 9 , 38 Moreover, evidence from our study supports the need for consistent use of DTG-based ART as a way to address risk for low-level viraemia in CLHIV, while promoting the global U = U message to achieving the UNAIDS 95-95-95 targets. 9 , 21 , Such a message can help tackle significant stigma and discrimination that CLHIV face, which constitutes a barrier to ART. 20 , 39 , 40 However, careful virological monitoring is required to ensure sustained effects given the risk of transition to low-level viraemia even after achieving undetectable viral load levels, especially among CLHIV aged ≤ 14 years. 41 Future research will be needed to determine the long-term impacts of transitioning to DTG-based therapy among CLHIV, especially beyond 6–12 months which was the length of coverage for this study. As widespread DTG coverage is being achieved in Nigeria, it will also be important to understand how ART adherence and treatment interruptions influence outcomes, especially in the context of differentiated service delivery. More specific studies will also be required to understand the impact of facility-level characteristics on virologic suppression including the level of care at the facilities and ownership (i.e., public-for-profit vs. private). While our crude analyses suggest potential relationships between these factors and virological suppression, we have refrained from interpreting the adjusted odds due to the risk of Table 2 fallacy. 42 Strengths and limitations Findings from this study should be considered in terms of its strengths and limitations. First, our follow-up of a reasonably large cohort of CLHIV and assessments of repeated measures in a paired manner using regressions with generalized estimating equations reduces the risk for confounding (both measured and unmeasured). Findings from this study were robust and consistent both in the main and complete case analyses, reducing concerns about selective missingness in the data. Further, concerns about systematic losses to follow-up were assuaged by the significant similarities in characteristics between the cohort at baseline and endline. However, our use of routinely collected data limited the variables available to adjust our main effect. We have suggested the paired nature of the data limits this concern. Further, our assessment of the outcomes at least 6 months after initiation of DTG-based ART introduces heterogeneity. Exploring for example time to virological suppression may be more relevant and may be explored in future studies. Conclusion The transition to DTG-based ART was associated with significantly increased program-level virological suppression rates, including viral undetectable rates and lower rates of low-level viremia. Findings imply better treatment outcomes for CLHIV on DTG-based ART compared with other ART and highlight the benefits of transitioning programs to DTG-based therapy, especially among CLHIV, reducing emergent concerns about low-level viremia in this population. This can be a cornerstone in achieving the UNAIDS 95-95-95 target and reducing stigma in keeping with the U = U campaign. However, evidence is still needed to understand the impact of adherence levels on virological rates more generally, and especially in the context of widespread DTG-based ART. Declarations Ethical approvals We obtained permission for this secondary review of routinely collected program data from the Health Research Ethics Committee (HREC) in Akwa Ibom State on January 9, 2024 (HREC No. AKHREC/5/5/23/149) and Cross River State (CRSMOH/HRP/REC/2023/464). All data were anonymized before analyses. Ethics requirements for consent were waived considering ART and viral load testing are routine care. Consent for publication Statement Not applicable Data Availability Statement Derived data supporting the findings of this study are available from the corresponding author on request. Competing Interests Statement: I.I. has received funding from the Canadian Institutes for Health Research and Canadian HIV Trials Network. Funding statement: The authors received no specific funding for this research. The program reviewed is funded by the US President’s Emergency Plan for AIDS Relief (PEPFAR) through the U.S. Agency for International Development’s (USAID) Accelerating Control of the HIV Epidemic in Nigeria (ACE-5) Project implemented by Excellence Community Education Welfare Scheme (ECEWS). Contributorship statement: IA, UA, II, EN, OO and OT designed the study and developed the research protocol. UA, II, EN, OO and OT conducted the data analysis; IA, UA, II, EN, OO, BG, UJ, EE, MU, EI, CO, and OT interpreted the results and the writing of the manuscript, with the advice of MK, AI, BO, OA, DO, OI, PG, CO, UO, EJ, JP, OK-O, AA, AE. All authors contributed to data interpretation, writing of the manuscript, and approval of the final version. Acknowledgements Our appreciation goes to the frontline healthcare workers supporting HIV/AIDS services delivery across comprehensive HIV treatment health facilities; Federal Ministry of Health (FMOH) through the National HIV/AIDS and STIs Control Programme (NASCP); ECEWS for supporting the study; and the funding from U.S. President’s Emergency Plan for AIDS Relief (PEPFAR) through the United States Agency for International Development (USAID) to support the HIV/AIDS programming in Akwa Ibom and Cross River States. References World Health Organization. WHO recommends dolutegravir as preferred HIV treatment option in all populations. World Health Organization - News release. July 22, 2019. Accessed July 4, 2024. https://www.who.int/news/item/22-07-2019-who-recommends-dolutegravir-as-preferred-hiv-treatment-option-in-all-populations Allahna E, Nicole D, Neha S, et al. Virologic Impact of the Dolutegravir Transition: Prospective Results From the Multinational African Cohort Study. 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Prevalence and predictors of persistent low-level HIV viraemia: a retrospective cohort study among people receiving dolutegravir-based antiretroviral therapy in Southern Nigeria. Ther Adv Infect Dis . 2024;11:20499361241242240. doi:10.1177/20499361241242240 ECEWS. Project highlight: The Accelerating Control of the HIV Epidemic in Nigeria (ACE-5 Project) through targeted interventions in Nigeria’s Akwa Ibom and Cross River States. Excellence Community Education Welfare Scheme (ECEWS). 2024. Accessed August 4, 2024. https://ecews.org/project/ace-5-project/ Sanwo O, Iyamu I, Idemudia A, et al. Willingness to pay for antiretroviral therapy, viral load, and premium services; A contingent valuation survey of people living with HIV in southern Nigeria. Jahun I, ed. PLOS ONE . 2023;18(11):e0289507. doi:10.1371/journal.pone.0289507 Sanwo O, Persaud NE, Nwaokoro P, et al. Differentiated service delivery models among PLHIV in Akwa Ibom and Cross River States, Nigeria during the COVID‐19 pandemic: descriptive analysis of programmatic data. J Int AIDS Soc . 2021;24(S6):e25820. doi:10.1002/jia2.25820 National AIDS and STIs Control Programme. National Guidelines for HIV Prevention, Treatment and Care . Federal Ministry of Health; 2020. https://www.prepwatch.org/wp-content/uploads/2022/06/Nigeria-Guidelines-for-HIV-Prevention-Treatment-and-Care.pdf Benchimol EI, Smeeth L, Guttmann A, et al. The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) Statement. PLOS Med . 2015;12(10):e1001885. doi:10.1371/journal.pmed.1001885 van Buren S, Groothuis-Oudshoorn K. Multivariate Imputation by Chained Equations in R. J Stat Softw . 2011;45(3):1-67. Halekoh U, Højsgaard S, Yan J. The {R} Package geepack for Generalized Estimating Equationshe {R} Package geepack for Generalized Estimating Equations. J Stat Softw . 2006;15/2:1-11. Lumley T, Scott A. AIC and BIC for modeling with complex survey data. J Surv Stat Methodol . 2015;3(1):1-18. doi:10.1093/jssam/smu021 Raftery AE. Bayesian Model Selection in Social Research. Sociol Methodol . 1995;25:111. doi:10.2307/271063 Rubin D. Multiple Imputation for Nonresponse in Surveys . John Wiley and Sons Inc.; 1987. Accessed September 20, 2023. https://onlinelibrary.wiley.com/doi/book/10.1002/9780470316696 Archer KJ, Lemeshow S. Goodness-of-fit Test for a Logistic Regression Model Fitted using Survey Sample Data. Stata J . 2006;6(1):97-105. doi:10.1177/1536867X0600600106 R Core Team. R: A language and environment for statistical computing. Published online 2021. https://www.r-project.org/ Aoko A, Pals S, Ngugi T, et al. Retrospective longitudinal analysis of low-level viremia among HIV-1 infected adults on antiretroviral therapy in Kenya. eClinicalMedicine . 2023;63:102166. doi:10.1016/j.eclinm.2023.102166 Mutagonda RF, Mlyuka HJ, Maganda BA, Kamuhabwa AAR. Adherence, Effectiveness and Safety of Dolutegravir Based Antiretroviral Regimens among HIV Infected Children and Adolescents in Tanzania. J Int Assoc Provid AIDS Care JIAPAC . 2022;21:232595822211096. doi:10.1177/23259582221109613 Antunes F, Zindoga P, Gomes P, et al. Development of Nevirapine Resistance in Children Exposed to the Prevention of Mother-to-Child HIV-1 Transmission Programme in Maputo, Mozambique. Gantt S, ed. PLOS ONE . 2015;10(7):e0131994. doi:10.1371/journal.pone.0131994 Kanthula R, Rossouw TM, Feucht UD, et al. Persistence of HIV drug resistance among South African children given nevirapine to prevent mother-to-child-transmission. AIDS . 2017;31(8):1143-1148. doi:10.1097/QAD.0000000000001446 Nahirya-Ntege P, Cook A, Vhembo T, et al. Young HIV-Infected Children and Their Adult Caregivers Prefer Tablets to Syrup Antiretroviral Medications in Africa. Cameron DW, ed. PLoS ONE . 2012;7(5):e36186. doi:10.1371/journal.pone.0036186 Tukei VJ, Herrera N, Masitha M, et al. Optimizing antiretroviral therapy for children living with HIV: Experience from an observational cohort in Lesotho. Teeraananchai S, ed. PLOS ONE . 2023;18(7):e0288619. doi:10.1371/journal.pone.0288619 Iyamu I. The Findings of the National HIV / AIDS Indicator and Impact Survey ( NAIIS ) Presents an Opportunity for a Pivot in the HIV / AIDS Response in Nigeria. Glob Health Annu Rev . 2020;1(5):22-24. Iyamu I, Oladele EA, Eboreime E, Karim ME. Is Regular Access to Internet Services Associated with Comprehensive Correct HIV/AIDS Knowledge among People Aged 15–49 Years in Nigeria? Findings from the 2018 Demographic Health Survey. J Consum Health Internet . 2021;25(3):242-260. doi:10.1080/15398285.2021.1943634 Akpan UU, Nwanja EN, Badru T, et al. Predictors of Detectable Viremia, Outcomes, and Implications for Management of People Living With HIV Who Are Receiving Antiretroviral Therapy in Southern Nigeria. Open Forum Infect Dis . 2023;10(12):ofad562. doi:10.1093/ofid/ofad562 Westreich D, Greenland S. Commentary The Table 2 Fallacy : Presenting and Interpreting Confounder and Modifier Coefficients. Am J Epidemiol . 2013;177(4):292-298. doi:10.1093/aje/kws412 Additional Declarations No competing interests reported. Supplementary Files Appendices.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 17 Jan, 2025 Reviewers agreed at journal 17 Jan, 2025 Reviewers invited by journal 01 Jan, 2025 Editor invited by journal 18 Nov, 2024 Editor assigned by journal 14 Nov, 2024 Submission checks completed at journal 14 Nov, 2024 First submitted to journal 11 Nov, 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. 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children living with HIV who were transitioned to DTG-based ART between July and December 2021 - Review of Program Data\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5434482/v1/d087b5bb90bfb1e958930373.png"},{"id":71690287,"identity":"490a53d9-ef43-4021-be05-b3c884ae4eac","added_by":"auto","created_at":"2024-12-17 18:00:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":953804,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5434482/v1/33e12e67-e9fb-4fd0-8499-b51f25f1a917.pdf"},{"id":71688699,"identity":"4fdaa39e-8853-480c-b4b2-2da6855b63eb","added_by":"auto","created_at":"2024-12-17 17:44:32","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":35649,"visible":true,"origin":"","legend":"","description":"","filename":"Appendices.docx","url":"https://assets-eu.researchsquare.com/files/rs-5434482/v1/d0ea55f81a47881f83e01605.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of transition to Dolutegravir-based antiretroviral therapy on virological suppression among children living with HIV in Southern Nigeria: A before and after analysis of program data","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn 2018, the World Health Organization (WHO) recommended dolutegravir (DTG) as its preferred first and second-line antiretroviral therapy (ART) among all people living with HIV (PLHIV) including women and children.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Recommendations for DTG are based on data suggesting its superior efficacy in ensuring virological suppression, higher genetic barrier to resistance and more tolerable adverse effect profile.\u003csup\u003e\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Therefore HIV treatment programs including those funded by the US President\u0026rsquo;s Emergency Plan for AIDS Relief (PEPFAR) have supported the transition of treatment na\u0026iuml;ve and treatment-experienced clients to DTG-based ART. This transition has been considered an important strategy to reach the UNAIDS 95-95-95 targets.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e By 2022, over 87% of PLHIV within PEPFAR\u0026rsquo;s global program had been transitioned to DTG-based ART, with early evidence of improved virological suppression.\u003csup\u003e\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAs of 2023, Nigeria had an estimated 2\u0026nbsp;million PLHIV, with 85% of these on ART and 82% achieving virologic suppression.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e While this represents significant progress, with 90% of adults aged 15 years or older receiving ART, coverage among children aged 0\u0026ndash;14 years lags behind country averages with only 29% of the estimated 45,000 children living with HIV (CHLIV) currently on ART.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn 2018, Nigeria commenced its transition to DTG-based ART, initially recommending transition for adults, adolescents, and children 6 years and older.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e In 2021, following the introduction of a 10mg DTG formulation, PEPFAR-supported programs in Nigeria, in line with country guidelines, commenced transitioning of children who weighed less than 30kg to DTG-based therapy.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e As of 2022, about 90% of all PLHIV on ART had been transitioned to DTG-based ART.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e While there is ample program evidence of the impact of DTG-based therapy on virological suppression among adult PLHIV, evidence among children is limited, especially in Nigeria.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e Where available, global evidence is limited to children weighing 14kg and over, in controlled settings.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Program evidence from Northern Nigeria suggests a non-significant effect of DTG-based ART on viral load suppression among CLHIV.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e However, these findings are not necessarily generalizable to southern Nigeria given the heterogeneity within the program especially between Northern and Southern Nigeria.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e Moreover, the cross-sectional design of the studies may have exposed its findings to confounding.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFurther, there are emergent concerns about the potential for low-level viremia to result in virological failure, treatment resistance and increased viral transmissibility.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e This is especially concerning given the acceleration of the undetectable equals untransmissible (U\u0026thinsp;=\u0026thinsp;U) campaign to destigmatize HIV.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e While there is evidence that DTG-based ART reduces the prevalence and risk of low-level viremia, this evidence is mostly among adults.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e Evidence among children especially in Nigeria is lacking and urgently needed to guide programs. To address these knowledge gaps regarding the HIV control programs for CLHIV, we reviewed routinely collected program data from a PEPFAR-funded comprehensive HIV epidemic control program in Akwa Ibom and Cross River states in southern Nigeria. We assessed the association between the transition to DTG-based ART and virological suppression among CLHIV. Here we assessed virological suppression at the WHO-defined level (i.e., \u0026lt;\u0026thinsp;1,000 viral copies/ml) and virologic suppression at undetectable levels (i.e., \u0026lt;\u0026thinsp;50 viral copies/ml). We hypothesized that virologic suppression rates among CLHIV would improve after the transition to DTG-based ART.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eStudy setting\u003c/p\u003e \u003cp\u003eThe Accelerating Control of the HIV Epidemic in Nigeria (ACE-5) Project supports the government of Nigeria in implementing comprehensive HIV services in Akwa-Ibom and Cross River states, Nigeria.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e The project is implemented by Excellence Community Education Welfare Scheme (ECEWS) with funding from PEPFAR through the United States Agency for International Development (USAID). \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAkwa-Ibom and Cross-River states are adjoining coastal states with HIV prevalence higher than the national average of 1.4%. Akwa-Ibom has the highest prevalence in the country at 4.8% while Cross-River has a prevalence of 1.6%.\u003csup\u003e11\u003c/sup\u003e ART services are provided free of charge through primary, secondary and tertiary health centres, with the highest level of care available at tertiary facilities where specialists and sub-specialists provide services, and the lowest level available at primary health facilities where nurses and community health workers provide services.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eDifferentiated service delivery (DSD) models are provided to clients on ART including children 5 years and older, in line with the National Guidelines for DSD.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e Viral load testing for children is done six-monthly and during the study period, viral load assessments were conducted using Abbott\u0026reg;, and Hologic Panther\u0026reg;, each with a low detection limit (\u0026lt;\u0026thinsp;40 copies/ mL).\u003csup\u003e13\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eStudy design and population\u003c/p\u003e \u003cp\u003eThis was a retrospective study of a cohort of ART-experienced CLHIV who were on first-line non-DTG-based ART regimen at the beginning of the study period (July 2021) in 121 health facilities in Akwa Ibom and Cross River States. These CLHIV were then transitioned to a DTG-based regimen for CLHIV between July and December 2021. Prior to the beginning of the transition, healthcare workers were trained on the formulation, dosing and adverse effects of DTG, caregivers were sensitized on the regimen during clinic encounters, and eligible CLHIV were line-listed. The actual transition to a DTG-based regimen was done during their routine clinic visits.\u003c/p\u003e \u003cp\u003e We reviewed routinely collected program data for these CLHIV across the 121 health facilities supported by the ACE-5 project. First, we extracted client-level data from the Lafiya Management Information System-Plus (LAMIS-Plus) \u0026ndash; an electronic medical record for ART services within PEPFAR-funded health facilities in Nigeria. This database includes demographic data like age and biological sex and clinical data including dates of ART commencement, ART regimen, WHO clinical stage, weight and viral load. Next, we extracted facility characteristics from program records, linking them with client-level data to explore facility-level characteristics associated with virological outcomes. Baseline (pre-transition) variables were abstracted as of December 2021, with endline (post-transition) variables abstracted for the period January to December 2022. Our reporting complies with the Reporting of studies Conducted using Observational Routinely collected health Data (RECORD) Statement.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eExposure, Outcome and confounding variables\u003c/p\u003e \u003cp\u003eThe main outcome variable was virological suppression defined in three ways. First as a three-level outcome (i.e., viral load\u0026thinsp;\u0026le;\u0026thinsp;50 viral copies/ml \u0026ndash; undetectable, 51\u0026ndash;999 viral copies/ml \u0026ndash; low-level viremia and \u0026ge;\u0026thinsp;1,000 copies/ml \u0026ndash; unsuppressed) [ref]. We defined a second outcome based on WHO guidelines for virological suppression (i.e., viral load\u0026thinsp;\u0026lt;\u0026thinsp;1,000 viral copies/ml \u0026ndash; suppressed and \u0026ge;\u0026thinsp;1,000 copies/ml \u0026ndash; unsuppressed). Third, we defined viral load as undetectable (\u0026lt;\u0026thinsp;50 viral copies/ml) or detectable (\u0026ge;\u0026thinsp;50 viral copies/ml).\u003csup\u003e1\u003c/sup\u003e Our main exposure was defined as the transition from traditional ART (e.g., nucleoside reverse transcriptase inhibitor (NRTI), non-nucleoside reverse transcriptase inhibitor (NNRTI) and protease inhibitor (PI)-based ART) to at least 6 months of DTG-based ART. Confounding variables included age (categorized as children aged\u0026thinsp;\u0026lt;\u0026thinsp;5 years and between five and nine years old), biological sex (female or male), time on non-DTG ART (measured in months), weight at transition (in kg), baseline WHO clinical stage (categorized as stages 1, 2 and 3\u0026ndash;4), urbanicity (i.e., how urban the region of residence is \u0026ndash; categorized as urban or rural), facility care level (categorized as primary, secondary or tertiary), facility ownership (categorized as private-for-profit, private-not-for-profit and public).\u003c/p\u003e \u003cp\u003eAnalytic dataset and statistical analyses\u003c/p\u003e \u003cp\u003e For our analytic dataset, we only included data for all ART-experienced CLHIV currently in care who were transitioned to DTG between July and December 2021, had a baseline viral load assessment before the transition and had reassessed their viral load at least 6 months post-transition to DTG and we still currently in care (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Only children with both a baseline and endline VL were included in the main analysis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe summarized the data using simple descriptive statistics (frequencies, proportions, means and medians). Given 0.2% and 16.9% missingness for baseline WHO clinical staging and weight at transition to DTG respectively, we conducted our main analysis using data multiply imputed in 20 datasets using multivariate imputation by chained equations (MICE) under the missing at random assumption.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e This assumption was reasonable considering missingness in weight was higher among people at WHO stage 1 and covaried with age. Multiple imputation was conducted using the MICE package.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFor each of the outcomes, bivariable analyses were conducted using ordinal and binomial logistic regression models with generalized estimating equations to account for clustering at the individual level.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e While other studies assert clustering at the facility level, such models showed poor fit and were not included in the analyses.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e For multivariable analyses, we held predictors known to be associated with virological suppression steady while adding additional variables and comparing Bayesian Information Criteria, selecting the final variables based on the majority rule.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e The models were run on all imputed datasets with the final estimates pooled using Rubin\u0026rsquo;s rules.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e We checked model fit using Hosmer-Lemeshow\u0026rsquo;s test and assessed collinearity, setting a threshold of variance\u0026thinsp;\u0026lt;\u0026thinsp;10.\u003csup\u003e31\u003c/sup\u003e To assess the robustness of our findings, we conducted sensitivity analyses by rerunning our main ordinal logistic regression on a complete-case dataset, excluding any individuals with missing values. We purposefully included variables from the main analyses within the sensitivity analyses. All analyses were conducted at a significance level of 5%. All analyses were conducted using R version 4.4.1.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003eSample characteristics\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eOverall, we included data from 1,951 ART-experienced CLHIV transitioned to DTG between July and December 2021 and had both a baseline and endline viral load. Among these, 1,250 (64.1%) were aged between five and nine years, 993 (50.9%) were male, 1101 (56.4%) were in rural areas, 1,039 (63.9%) had a baseline WHO clinical stage 1 assessment, and 1,809 (92.7%) were receiving care in public health facilities (Table 1). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 1: Characteristics of ART-experienced children living with HIV who were transitioned from non-DTG to DTG-based ART between July and December 2021 in Akwa Ibom and Cross River States, Nigeria\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"595\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFactors\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnalytic sample included in baseline and endline analysis\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e1951 (100%)\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge category (in years)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026lt;5 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;years\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 5-9 \u0026nbsp; \u0026nbsp; \u0026nbsp;years\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e701 (35.9)\u003c/p\u003e\n \u003cp\u003e1250 (64.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBiological Sex\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Female\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Male\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e958 (49.1)\u003c/p\u003e\n \u003cp\u003e993 (50.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u003cstrong\u003eTime on ART in months\u003c/strong\u003e (median (IQR))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e37.20 (27.92, 58.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeight (in kgs) at transition to DTG (mean (SD))\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e17.40 (5.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBaseline WHO clinical stage\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Stage 1\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Stage 2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Stage 3 or 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1039 (63.9)\u003c/p\u003e\n \u003cp\u003e344 (21.1)\u003c/p\u003e\n \u003cp\u003e244 (15.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUrbanicity\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Rural\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Urban\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1101 (56.4)\u003c/p\u003e\n \u003cp\u003e850 (43.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFacility care level\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Primary\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Secondary\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Tertiary\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e972 (49.8)\u003c/p\u003e\n \u003cp\u003e900 (46.1)\u003c/p\u003e\n \u003cp\u003e79 (4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 378px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFacility ownership\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Private for-profit\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Private not-for-profit\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Public\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e96 (4.9)\u003c/p\u003e\n \u003cp\u003e46 (2.4)\u003c/p\u003e\n \u003cp\u003e1809 (92.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eDTG: Dolutegravir; IQR: Interquartile range; NRTI: nucleoside reverse transcriptase inhibitors; NNRT: Non-nucleoside reverse transcriptase inhibitors; PI: Protease inhibitors; SD: Standard deviation; WHO: World Health Organization.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAt baseline, 1,611 (82.6%) of the 1,951 CLHIV included in the study had undetectable viral load levels, while 271 (13.9%) had low-level viraemia. Among the 1,951 CLHIV at endline, those with undetectable viral load had increased to 91.5% (n=1,786) while those with low-level viremia had reduced to 6.3% (n=123) (Table 2). These patterns were similar across age and sex strata (Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2: Viral load outcomes among ART-experienced children living with HIV who were transitioned from non-DTG to DTG-based ART between July and December 2021 in Akwa Ibom and Cross River States, Nigeria \u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"690\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eViral load Outcomes\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBaseline (on NRTIs, NNRTI, or PI-based ART)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEndline (after 6 months on DTG-based ART)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN (%)\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eViral load (all CLHIV on ART)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Unsuppressed (\u0026ge;1000 copies/ml)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Low-level viraemia (51-999 copies/ml)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Undetectable (\u0026le;50 copies/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e69 (3.5)\u003c/p\u003e\n \u003cp\u003e271 (13.9)\u003c/p\u003e\n \u003cp\u003e1611 (82.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e42 (2.2)\u003c/p\u003e\n \u003cp\u003e123 (6.3)\u003c/p\u003e\n \u003cp\u003e1786 (91.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eViral load (CLHIV 0-4 years)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Unsuppressed (\u0026ge;1000 copies/ml)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Low-level viraemia (51-999 copies/ml)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Undetectable (\u0026le;50 copies/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e22 (3.1)\u003c/p\u003e\n \u003cp\u003e104 (14.8)\u003c/p\u003e\n \u003cp\u003e575 (82.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e12 (1.7)\u003c/p\u003e\n \u003cp\u003e35 (5.0)\u003c/p\u003e\n \u003cp\u003e654 (93.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eViral load (CLHIV \u0026ndash; 5-9 years)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Unsuppressed (\u0026ge;1000 copies/ml)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Low-level viraemia (51-999 copies/ml)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Undetectable (\u0026le;50 copies/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e47 (3.8)\u003c/p\u003e\n \u003cp\u003e167 (13.4)\u003c/p\u003e\n \u003cp\u003e1036 (82.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e30 (2.4)\u003c/p\u003e\n \u003cp\u003e88 (7.0)\u003c/p\u003e\n \u003cp\u003e1132 (90.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eViral load (Female CLHIV)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Unsuppressed (\u0026ge;1000 copies/ml)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Low-level viraemia (51-999 copies/ml)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Undetectable (\u0026le;50 copies/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e32 (3.3)\u003c/p\u003e\n \u003cp\u003e129 (13.5)\u003c/p\u003e\n \u003cp\u003e797 (83.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e23 (2.4)\u003c/p\u003e\n \u003cp\u003e57 (5.9)\u003c/p\u003e\n \u003cp\u003e878 (91.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eViral load (Male CLHIV)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Unsuppressed (\u0026ge;1000 copies/ml)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Low-level viraemia (51-999 copies/ml)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Undetectable (\u0026le;50 copies/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 207px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e37 (3.7)\u003c/p\u003e\n \u003cp\u003e142 (14.3)\u003c/p\u003e\n \u003cp\u003e814 (82.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e19 (1.9)\u003c/p\u003e\n \u003cp\u003e66 (6.6)\u003c/p\u003e\n \u003cp\u003e908 (91.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eDTG: Dolutegravir; IQR: Interquartile range; NRTI: nucleoside reverse transcriptase inhibitors; NNRT: Non-nucleoside reverse transcriptase inhibitors; PI: Protease inhibitors; SD: Standard deviation; WHO: World Health Organization; \u003csup\u003e*\u003c/sup\u003eIndicates subset of baseline cohort remaining at least 6 months after initiation of DTG-based ART.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eImpact of the transition to dolutegravir-based ART \u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eIn bivariable ordinal logistic regression (Table 3), the transition to DTG-based ART was associated with improved virological suppression (odds ratio [OR]: 1.72, 95% confidence interval [CI]: 1.23,2.46) at least 6 months after the transition. This association stayed consistent when adjusted for age, sex, weight (in kgs) at the transition to DTG, facility ownership, facility level, and urbanicity (adjusted odds ratio [aOR]: 1.71, 95%CI: 1.21, 2.41). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3: Association between the transition to DTG-based ART and Viral load \u0026ndash; Ordinal logistic regression\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"671\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 349px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCrude Odds Ratio\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(95% Confidence Interval)\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted Odds Ratio\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(95% Confidence Interval)\u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 349px;\"\u003e\n \u003cp\u003eIntercepts\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Low-level viraemia | Undetectable\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Unsuppressed | Low-level-viraemia\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.94 (1.75, 8.83)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e20.49 (9.01, 46.58)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 349px;\"\u003e\n \u003cp\u003eRegimen (time point)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Baseline (on NRTIs, NNRTI, or PI-ART)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Endline (on DTG-ART)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003cp\u003e1.72 (1.23, 2.46)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003cp\u003e1.71 (1.21, 2.41)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 349px;\"\u003e\n \u003cp\u003eAge category\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Under-five years\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Five-nine years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003cp\u003e0.80 (0.54, 1.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003cp\u003e0.78 (0.49, 1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 349px;\"\u003e\n \u003cp\u003eBiological sex\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Female\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Male\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003cp\u003e1.01 (0.71, 1.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003cp\u003e1.04 (0.73, 1.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 349px;\"\u003e\n \u003cp\u003eTime on ART in months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e1.00 (0.99, 1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 349px;\"\u003e\n \u003cp\u003eWeight (in kgs) at the transition to DTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e1.02 (0.98, 1.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e1.02 (0.99, 1.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 349px;\"\u003e\n \u003cp\u003eBaseline WHO clinical stage\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Stage 1\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Stage 2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Stage 3 or 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003cp\u003e0.61 (0.40, 0.93)\u003c/p\u003e\n \u003cp\u003e0.65 (0.41, 1.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 349px;\"\u003e\n \u003cp\u003eUrbanicity\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Rural\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Urban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003cp\u003e0.55 (0.38, 0.79)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003cp\u003e0.67 (0.42, 1.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 349px;\"\u003e\n \u003cp\u003eFacility care level\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Primary\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Secondary\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Tertiary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003cp\u003e0.63 (0.43, 0.93)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e0.43 (0.22, 0.84)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003cp\u003e0.76 (0. 48, 1.19)\u003c/p\u003e\n \u003cp\u003e0.52 (0.24, 1.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 349px;\"\u003e\n \u003cp\u003eFacility ownership\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Private for-profit\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Private not-for-profit\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Public\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003cp\u003e0.89 (0.31, 2.54)\u003c/p\u003e\n \u003cp\u003e1.92 (1.06, 3.49)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003cp\u003e0.99 (0.34, 2.83)\u003c/p\u003e\n \u003cp\u003e0.67 (0.42, 1.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eDTG: Dolutegravir; IQR: Interquartile range; NA: Not Applicable; NRTI: nucleoside reverse transcriptase inhibitors; NNRT: Non-nucleoside reverse transcriptase inhibitors; PI: Protease inhibitors; SD: Standard deviation; WHO: World Health Organization; \u003csup\u003e*\u003c/sup\u003eSignificant at p\u0026lt;0.05; All Variance Inflating Factors (VIF) \u0026lt;5; \u003csup\u003ea,b\u003c/sup\u003eModels run on 20 multiply imputed datasets and pooled using Rubin\u0026rsquo;s rules.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBased on the WHO categorization (i.e., viral load \u0026lt;1,000 copies/ml), the transition to DTG-based ART was associated with virological suppression (aOR: 1.62, 95%CI: 1.08, 2.43) (Table 4). Similar associations were observed when considering the effect of the transition to DTG-based therapy on undetectable viral load levels among CLHIV (aOR: 2.56, 95%CI: 2.06, 3.18).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the sensitivity analysis repeating the main ordinal logistic regression on a complete dataset, the transition to DTG-based ART was consistent and associated with virological suppression (aOR: 1.67, 95%CI: 1.15, 2.42).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4: Unadjusted and Adjusted associations between the transition to DTG-based ART and various definitions of virological suppression\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"671\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 349px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCrude Odds Ratio\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(95% Confidence Interval)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted Odds Ratio\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(95% Confidence Interval)\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 671px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 1: Association between the transition to DTG-based ART and virological suppression based on WHO definition (VL\u0026lt;1000 copies/ml)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 349px;\"\u003e\n \u003cp\u003eRegimen (time point)\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Baseline (on NRTIs, NNRTI, or PI-ART)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Endline (on DTG-ART)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003cp\u003e1.62 (1.08, 2.41)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003cp\u003e1.62 (1.08, 2.43)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 671px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 2: Association between the transition to DTG-based ART and virological undetectability (VL\u0026le;50 copies/ml)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 349px;\"\u003e\n \u003cp\u003eRegimen (time point)\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Baseline (on NRTIs, NNRTI, or PI-ART)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Endline (on DTG-ART)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003cp\u003e2.54 (2.04, 3.15)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003cp\u003e2.56 (2.06, 3.18)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 671px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 3: Association between the transition to DTG-based ART and virological suppression in ordinal logistic regression \u003csup\u003e$\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 349px;\"\u003e\n \u003cp\u003eIntercepts\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Low-level viraemia | Undetectable\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Unsuppressed | Low-level-viraemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4.21 (1.67, 1.92)\u003c/p\u003e\n \u003cp\u003e20.67 (9.32, 45.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 349px;\"\u003e\n \u003cp\u003eRegimen (time point)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Baseline (on NRTIs, NNRTI, or PI-ART)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Endline (on DTG-ART)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003cp\u003e1.70 (1.18, 2.46)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003cp\u003e1.67 (1.15, 2.42)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eDTG: Dolutegravir; IQR: Interquartile range; NA: Not Applicable; NRTI: nucleoside reverse transcriptase inhibitors; NNRT: Non-nucleoside reverse transcriptase inhibitors; PI: Protease inhibitors; SD: Standard deviation; WHO: World Health Organization; \u003csup\u003e*\u003c/sup\u003eSignificant at p\u0026lt;0.05; All Variance Inflating Factors (VIF) \u0026lt;5;\u003csup\u003e#\u003c/sup\u003eModels run on 20 multiply imputed datasets and pooled using Rubin\u0026rsquo;s rules; \u0026nbsp;\u003csup\u003e$\u003c/sup\u003eModels run on a complete case dataset, \u003csup\u003ea\u003c/sup\u003eAll models adjusted for age, sex, weight (in kgs) at transition to DTG, facility ownership, facility level, urbanity and state.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e In this review of routinely collected data from a comprehensive ART program in 121 health facilities in Akwa-Ibom and Cross River states in Nigeria, we found that at least 6 months after the transition to DTG-based therapy, the proportion of ART-experienced CLHIV with undetectable VL increased from 82.5\u0026ndash;91.5% and those with low-level viremia reduced from 13.6\u0026ndash;6.3%. We also found the transition was associated with approximately 71% greater odds of virological suppression and 156% greater odds of undetectable viral load at least 6 months after the transition. These findings were consistent in both an imputed dataset and in a complete case analysis.\u003c/p\u003e \u003cp\u003eFindings from this study add much-needed robust evidence about the impact of the transition to DTG-based ART especially among CLHIV in Southern Nigeria since recommendations took effect.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e We have previously described the dearth of evidence of the impact of the transition to DTG-based ART in this population with most studies being among adolescents and adults aged 15 years or older, and in Northern Nigeria.\u003csup\u003e\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Our findings support those from other studies in adults and children which showed an association between DTG-based ART and improved undetectable viraemia.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e However, these findings contrast those from a single-centre prospective study in Northern Nigeria where DTG-based ART had comparable impacts on viral suppression with non-DTG-based ART.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Given the longitudinal and paired nature of our analysis and its consistency with other similar studies, it is more plausible that DTG-based therapy significantly improves viral suppression in CLHIV. Moreover, we have previously demonstrated that DTG significantly reduces the risk of persistent low-level viraemia, and the current study findings are consistent with thisassertion.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFindings from our study have public health significance, especially in children given long-standing challenges with drug resistance, especially with nevirapine-based ART, adherence challenges with unpalatable formulations of lopinavir and other protease inhibitors and long-term side effects and toxicity concerns.\u003csup\u003e\u003cspan additionalcitationids=\"CR36 CR37\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e Given that DTG-based ART has significantly higher drug resistance barriers and simpler formulations, this transition can support program-level improvements in virological suppression among children who have historically lagged the general population both in terms of ART coverage and treatment outcomes.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e Moreover, evidence from our study supports the need for consistent use of DTG-based ART as a way to address risk for low-level viraemia in CLHIV, while promoting the global U\u0026thinsp;=\u0026thinsp;U message to achieving the UNAIDS 95-95-95 targets.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003c/sup\u003e Such a message can help tackle significant stigma and discrimination that CLHIV face, which constitutes a barrier to ART.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e However, careful virological monitoring is required to ensure sustained effects given the risk of transition to low-level viraemia even after achieving undetectable viral load levels, especially among CLHIV aged\u0026thinsp;\u0026le;\u0026thinsp;14 years.\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFuture research will be needed to determine the long-term impacts of transitioning to DTG-based therapy among CLHIV, especially beyond 6\u0026ndash;12 months which was the length of coverage for this study. As widespread DTG coverage is being achieved in Nigeria, it will also be important to understand how ART adherence and treatment interruptions influence outcomes, especially in the context of differentiated service delivery. More specific studies will also be required to understand the impact of facility-level characteristics on virologic suppression including the level of care at the facilities and ownership (i.e., public-for-profit vs. private). While our crude analyses suggest potential relationships between these factors and virological suppression, we have refrained from interpreting the adjusted odds due to the risk of Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e fallacy.\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eStrengths and limitations\u003c/p\u003e \u003cp\u003eFindings from this study should be considered in terms of its strengths and limitations. First, our follow-up of a reasonably large cohort of CLHIV and assessments of repeated measures in a paired manner using regressions with generalized estimating equations reduces the risk for confounding (both measured and unmeasured). Findings from this study were robust and consistent both in the main and complete case analyses, reducing concerns about selective missingness in the data. Further, concerns about systematic losses to follow-up were assuaged by the significant similarities in characteristics between the cohort at baseline and endline. However, our use of routinely collected data limited the variables available to adjust our main effect. We have suggested the paired nature of the data limits this concern. Further, our assessment of the outcomes at least 6 months after initiation of DTG-based ART introduces heterogeneity. Exploring for example time to virological suppression may be more relevant and may be explored in future studies.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe transition to DTG-based ART was associated with significantly increased program-level virological suppression rates, including viral undetectable rates and lower rates of low-level viremia. Findings imply better treatment outcomes for CLHIV on DTG-based ART compared with other ART and highlight the benefits of transitioning programs to DTG-based therapy, especially among CLHIV, reducing emergent concerns about low-level viremia in this population. This can be a cornerstone in achieving the UNAIDS 95-95-95 target and reducing stigma in keeping with the U\u0026thinsp;=\u0026thinsp;U campaign. However, evidence is still needed to understand the impact of adherence levels on virological rates more generally, and especially in the context of widespread DTG-based ART.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approvals \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe obtained permission for this secondary review of routinely collected program data from the Health Research Ethics Committee (HREC) in Akwa Ibom State on January 9, 2024 (HREC No. AKHREC/5/5/23/149) and Cross River State (CRSMOH/HRP/REC/2023/464). All data were anonymized before analyses. Ethics requirements for consent were waived considering ART and viral load testing are routine care.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication Statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDerived data supporting the findings of this study are available from the corresponding author on request.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests Statement:\u003c/strong\u003e I.I. has received funding from the Canadian Institutes for Health Research and Canadian HIV Trials Network.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding statement:\u003c/strong\u003e The authors received no specific funding for this research. The program reviewed is funded by the US President\u0026rsquo;s Emergency Plan for AIDS Relief (PEPFAR) through the U.S. Agency for International Development\u0026rsquo;s (USAID) Accelerating Control of the HIV Epidemic in Nigeria (ACE-5) Project implemented by Excellence Community Education Welfare Scheme (ECEWS).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributorship statement:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIA, UA, II, EN, OO and OT designed the study and developed the research protocol. UA, II, EN, OO and OT conducted the data analysis; IA, UA, II, EN, OO, BG, UJ, EE, MU, EI, CO, and OT interpreted the results and the writing of the manuscript, with the advice of MK, AI, BO, OA, DO, OI, PG, CO, UO, EJ, JP, OK-O, AA, AE. All authors contributed to data interpretation, writing of the manuscript, and approval of the final version. \u003cstrong\u003e\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur appreciation goes to the frontline healthcare workers supporting HIV/AIDS services delivery across comprehensive HIV treatment health facilities; Federal Ministry of Health (FMOH) through the National HIV/AIDS and STIs Control Programme (NASCP); ECEWS for supporting the study; \u0026nbsp;and the funding from U.S. President\u0026rsquo;s Emergency Plan for AIDS Relief (PEPFAR) through the United States Agency for International Development (USAID) to support the HIV/AIDS programming in Akwa Ibom and Cross River States.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eWorld Health Organization. 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The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) Statement. \u003cem\u003ePLOS Med\u003c/em\u003e. 2015;12(10):e1001885. doi:10.1371/journal.pmed.1001885\u003c/li\u003e\n \u003cli\u003evan Buren S, Groothuis-Oudshoorn K. Multivariate Imputation by Chained Equations in R. \u003cem\u003eJ Stat Softw\u003c/em\u003e. 2011;45(3):1-67.\u003c/li\u003e\n \u003cli\u003eHalekoh U, H\u0026oslash;jsgaard S, Yan J. The {R} Package geepack for Generalized Estimating Equationshe {R} Package geepack for Generalized Estimating Equations. \u003cem\u003eJ Stat Softw\u003c/em\u003e. 2006;15/2:1-11.\u003c/li\u003e\n \u003cli\u003eLumley T, Scott A. AIC and BIC for modeling with complex survey data. \u003cem\u003eJ Surv Stat Methodol\u003c/em\u003e. 2015;3(1):1-18. doi:10.1093/jssam/smu021\u003c/li\u003e\n \u003cli\u003eRaftery AE. 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Commentary The Table 2 Fallacy : Presenting and Interpreting Confounder and Modifier Coefficients. \u003cem\u003eAm J Epidemiol\u003c/em\u003e. 2013;177(4):292-298. doi:10.1093/aje/kws412\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"HIV Integrase Inhibitors, HIV in Children, Low-level viraemia, HIV outcomes, Antiretroviral therapy","lastPublishedDoi":"10.21203/rs.3.rs-5434482/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5434482/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eIn 2021, Nigeria introduced the 10mg paediatric dolutegravir (DTG) formulation for children living with HIV (CLHIV) aiming to improve virological outcomes, and immediately commenced transitioning children\u0026thinsp;\u0026lt;\u0026thinsp;10 years old on first-line non-DTG-based regimen to DTG. We assessed the association between the transition to DTG-based ART and virological suppression among CLHIV.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a retrospective cohort study using routinely collected data from 121 PEPFAR-supported health facilities in Akwa Ibom and Cross River States. We included all ART-experienced CLHIV who were transitioned to DTG between July and December 2021, had a baseline viral load (VL) assessment before the transition and VL\u0026thinsp;\u0026ge;\u0026thinsp;6 months after transitioning. We defined VL as a three-level outcome (i.e., \u0026le; 50 copies/ml \u0026ndash; undetectable, 51\u0026ndash;999 copies/ml \u0026ndash; low-level viremia and \u0026ge;\u0026thinsp;1,000 copies/ml \u0026ndash; unsuppressed). We assessed the association between the transition to DTG and VL using ordinal logistic regression with generalized estimating equations. We also conducted additional sensitivity analyses on a complete case dataset and assessed the impact of the transition on various definitions of virological suppression including undetectable (\u0026lt;\u0026thinsp;50 copies/ml) vs. detectable (\u0026ge;\u0026thinsp;50 copies/ml).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOut of 1,951 CLHIV included in this analysis, 1,250 (64.1%) were between the ages of five and nine, 993 (50.9%) were male. Among these, 1,786 (91.5%) had undetectable VL levels, up from 1,611 (82.6%) at baseline, while 123 (6.3%) had low-level viraemia, down from 271 (13.9%) initially. The transition to DTG-based ART was associated with virological suppression (adjusted odds ratio [aOR]: 1.70, 95%CI: 1.20, 2.41) and undetectable VL (aOR: 2.56, 95%CI: 2.06, 3.19). Findings were consistent in sensitivity analyses.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eCLHIV achieved favourable virological changes when transitioned to DTG-based ART, including undetectable viral load rates. Findings suggest DTG can improve overall program outcomes and reduce the risk for low-level viremia in CLHIV, emphasizing its role in achieving HIV epidemic control among CLHIV.\u003c/p\u003e","manuscriptTitle":"Impact of transition to Dolutegravir-based antiretroviral therapy on virological suppression among children living with HIV in Southern Nigeria: A before and after analysis of program data","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-17 17:44:28","doi":"10.21203/rs.3.rs-5434482/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"325003594389398650195010865159328105886","date":"2025-01-18T00:34:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"155201436146854083872892608378439936579","date":"2025-01-17T20:51:36+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-01-01T06:52:34+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-11-18T09:00:45+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-11-14T06:09:58+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-11-14T06:09:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pediatrics","date":"2024-11-11T20:21:15+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d46b91cb-af94-4378-a132-b6436a3defe0","owner":[],"postedDate":"December 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-12-17T17:44:28+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-17 17:44:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5434482","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5434482","identity":"rs-5434482","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}