Timing matters: Examining the lag in Dolutegravir rollout among people living with HIV with Tuberculosis and advanced HIV disease in Rural South Africa (2019- 2023)

Timing matters: Examining the lag in Dolutegravir rollout among people living with HIV with Tuberculosis and advanced HIV disease in Rural South Africa (2019- 2023) | 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 Timing matters: Examining the lag in Dolutegravir rollout among people living with HIV with Tuberculosis and advanced HIV disease in Rural South Africa (2019- 2023) Reuben Christopher Moyo, Larisse Bolton, Elphas Luchemo Okango, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7102523/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Oct, 2025 Read the published version in AIDS Research and Therapy → Version 1 posted 7 You are reading this latest preprint version Abstract Background: While Dolutegravir (DTG)-based antiretroviral therapy (ART) has become the preferred regimen for people living with HIV (PLHIV), the pace and equity of its adoption—especially among subgroups with tuberculosis (TB) and advanced HIV disease—remain understudied in high-burden settings like rural KwaZulu-Natal (KZN), South Africa. Methods: We conducted a longitudinal cohort study using routine HIV program data from 69,916 PLHIV aged ≥ 15 years, followed across 19 HIV clinics in rural KZN between October 1, 2019, and December 31, 2023. Kaplan-Meier analysis estimated time to DTG transition. Cox proportional hazards models assessed the effect of TB and advanced HIV disease (CD4 count < 200 cells/mm³) on DTG transition. Mixed-effects logistic regression models estimated the odds of TB and advanced HIV disease by ART regimen. Results: Of the cohort, 49,365 (69.2%) were female, with a median age of 40 years (IQR: 32–49). By study end, 70.9% (n = 49,598) had transitioned to DTG. PLHIV with TB had a 22% lower hazard of transitioning to DTG compared to those without TB [adjusted hazard ratio (AHR) = 0.78; 95% CI: 0.76–0.82], while those with CD4 < 200 cells/mm³ had a 43% lower hazard [AHR = 0.57; 95% CI: 0.54–1.59]. DTG use was associated with significantly lower odds of advanced HIV disease (OR = 0.42; 95% CI: 0.40–0.43) and TB (OR = 0.73; 95% CI: 0.68–0.77). Conclusion: PLHIV with TB or advanced HIV disease were less likely to transition to DTG regimens. Strengthening adherence to clinical guidelines and improving integration of HIV and TB care are critical to ensure equitable access to DTG-based ART in rural settings Tuberculosis Advanced HIV disease Dolutegravir South Africa Figures Figure 1 BACKGROUND Tuberculosis is a highly infectious disease caused by Mycobacterium Tuberculosis that primarily affects the lungs. It is one of the leading causes of death among people living with HIV 1 . In 2023, approximately 10.8 million people were diagnosed with TB globally, resulting in 1.25 million deaths, including 161,000 PLHIV 1 .South Africa has one of the world’s highest tuberculosis (TB) burdens, with an estimated incidence rate of 468 per 100,000 person-years, of which a substantial proportion occurs among PLHIV ² ³. The first South African national TB survey conducted in 2018 reported the prevalence of TB as 852 (95% CI: 679–1026) cases per 100,000 persons 2 . The survey further reported a prevalence of TB among PLHIV of 1,734 (95% CI: 1219–2234) cases per 100,000 population. TB is also common among PLHIV with advanced HIV disease 3 , is a late stage of HIV infection characterised by severe immune system damage 4 . Early initiation of antiretroviral therapy (ART) and prompt TB treatment in PLHIV has been shown to offer improved clinical outcomes 5 . Another strategy of reducing the risk of developing active TB disease in PLHIV in high TB burden areas is through the use of Isoniazid preventive therapy 6 . This strategy, recommended by the World Health Organization (WHO), has been shown to reduce the risk of developing active TB by almost 60% 7 . Efavirenz (EFV), a class of non-nucleoside reverse transcriptase inhibitor (NNRTI), has been the main component of ART in South Africa since 2004 8 . Management of PLHIV using EFV as the main component of ART was, however, faced with NNRTI drug resistant HIV strains 9 , 10 . Consequently, the WHO recommended DTG, an integrase strand transfer inhibitor (INSTI) class of ART 11 , as an alternative to EFV in 2018 due to its high genetic barrier to resistance 9 , 10 , tolerance 12 , efficacy 13 , and cost-effectiveness 14 . South Africa started transitioning to DTG in September 2019 9 . Evidence on the overall transition to dolutegravir (DTG), and how this transition differs by tuberculosis (TB) disease status, which is a leading cause of death among people living with HIV (PLHIV)¹⁵ and advanced HIV disease, is sparse. Knowing which categories of PLHIV who have not transitioned to DTG, including those coinfected with TB, would be useful in addressing patient or clinical related reasons for not transitioning to DTG. Gaining insight into these barriers can inform targeted interventions to promote a more widespread adoption of DTG-based regimens. This study reports the transition to DTG using data from a high HIV burden in rural KwaZulu-Natal, South Africa. METHODS Study design and setting. This study followed a retrospective cohort study design comprised of routinely collected deidentified data obtained from 19 HIV clinics in Umkhanyakude, rural KZN, South Africa. This HIV incidence in the study setting is high, approximately 2.5 per 100 person-years for females and 1.5 per 100 person years for males 16 . The study site is nested within a health and demographic surveillance system (HDSS) that has been operated by the Africa Health Research Institute (AHRI) since 2000. Data Sources The study used clinical program data from the three interlinked electronic registers(TIER.NET), an HIV data capturing and management system introduced in South African clinics in 2010 17 . PLHIV initiated on ART before the introduction of TIER.NET had their data transferred into TIER.NET from previous ART databases and patient master cards. Study population and inclusion criteria The study population comprised a cohort of 69,916 PLHIV aged 15 years and older who were still in care at the start of the follow-up period on 1st October 2019. Children living with HIV aged 14 years and younger were not included because there was no paediatric formulation of DTG during the early transition. The start of the follow-up was chosen as 1 October 2019 since South Africa initiated the transition to DTG in September 2019. Measures The following variables were considered within our analyses; 1) Regimen type: This variable described whether an individual was on a DTG containing regimen or a non-DTG containing regimen. The non-DTG group included individuals on Efavirenz (EFV)-based regimens or those receiving protease inhibitors (PIs). 2) Viral load suppression (VLS): This time-varying variable indicates whether an individual is virally suppressed or not at different follow-up points. We selected the cut-off point for viral suppression as ≤400 copies per millilitre of blood, while those with > 400 copies per millilitre of blood were considered virally unsuppressed 18 , 19 . 30 Advanced HIV disease is defined as people living with CD4 count less than 200 cell/mm 3 . 3) Tuberculosis (TB) disease status: captured whether an individual had a documented diagnosis of tuberculosis at any point during follow-up 4) CD4 count, measured in cells/mm³, serves as an indicator of immune function and disease progression in people living with HIV. For analysis, CD4 counts were categorised into four groups: 0–199, 200–499, 500–999, and ≥ 1,000 cells/mm³. CD4 count was treated as a time-varying variable in the dataset.5) Sex of participants: This variable described the biological differentiation of sex into males and females as assigned at birth. 6) Participant age groups: Age groups were generated from the participants' age variable, generated by subtracting the date of data generation (31st December 2023) and participant date of birth. The participant age was categorised into the following categories; 15 to 24, 25 to 34, 35 to 44, 45 to 54 and above 55 years. Age was a time-varying variable. Statistical analysis Descriptive statistics were used to characterise participants by TB status, which were stratified by age groups and sex. The Pearson chi-square test of independence was used to assess whether the association between PLHIV characteristics and DTG regimen status was statistically significant 20 . Since PLHIV transitioned to or initiated DTG at different time points, we applied Kaplan Meir methods to describe the transition by TB status, age groups, sex, and CD4 count 21 . We evaluated the effect of tuberculosis (TB) on the hazard of transitioning to dolutegravir (DTG) using a multivariable mixed-effects Cox proportional hazards model, accounting for clustering by clinic. The Cox proportional hazard models are distribution free survival models that assume that the survival/failure curves for two or more strata of the predictor variables are proportional over time 22 and have been widely used in public health research to fit models for time-to-event data. Since the CD4 count and viral load data had missing values, we applied regression-based multiple imputation to impute the missing observations for these covariates. Multiple imputation is the recommended approach for missing information in longitudinal survival data 23 , 24 . The covariates included in our adjusted Cox proportional hazard model were DTG status?, sex, age groups, VLS and CD4 count. This study also modelled the risk of TB and advanced HIV disease among PLHIV in rural KwaZulu-Natal. To model the risk of advanced HIV disease and TB, we employed a mixed effects logistic regression model because observations were dependent, that is PLHIV were screened for TB symptoms and for advanced HIV disease at each visit. Statistical significance in this study was considered at p < 0.05. RESULTS Of the 69,916 people living with HIV (PLHIV) included in the cohort, 49,365 (69.15%) were female, and the median age was 40 years (IQR: 33–49). Clinical symptoms consistent with tuberculosis (TB) disease were identified in 1,407 (2.0%) individuals, while 29% (n = 20,275) presented with advanced HIV disease during the study period. By December 31, 2023, approximately 70% (n = 48,598) of PLHIV had transitioned to dolutegravir (DTG)-based antiretroviral therapy (ART), while 30% (n = 21,318) remained on non-DTG regimens. Among PLHIV with TB, only 770 (54.7%) transitioned to DTG, in contrast to 70.3% (n = 48,002) of those without active TB. While overall DTG uptake showed minimal gender disparity, more females transitioned to DTG than males beginning in 2021. Younger individuals, particularly those aged 15–24 years, had lower transition rates compared to older age groups. Transition rates were also persistently lower across time among PLHIV with active TB symptoms and those with low CD4 counts. Findings from the mixed effects logistic regression model (Table 3 ) indicated that female PLHIV had 39% lower odds of TB disease compared to males [OR = 0.61, 95% CI: 0.58–0.56]. Use of DTG-based regimens was associated with a 27% reduction in the odds of TB [OR = 0.73, 95% CI: 0.68–0.77] compared to non-DTG regimens. Age was an important factor, with lower odds of TB observed among PLHIV aged 25 years and above relative to those aged 15–24 years. CD4 count also significantly influenced TB risk: PLHIV with CD4 counts between 200–350 cells/mm³ had 39% lower odds of TB [OR = 0.61, 95% CI: 0.54–0.69], while those with CD4 ≥ 500 cells/mm³ had 43% lower odds [OR = 0.57, 95% CI: 0.52–0.64] compared to individuals with CD4 < 200 cells/mm³. Table 1 Distribution of regimen type by age groups, sex, and TB disease status (N = 69,916) Characteristic Regimen type, n (%) DTG Containing Non-DTG containing p-value Overall 48,598 (70) 21,318 (30) N/A Age Groups (years) < 0.001 15 to 24 3,297 (71.7) 1,299 (28.3) 25 to 34 12,098 (72.6) 4,560 (27.3) 35 to 44 16,247 (68.7) 7,420 (31.3) 45 to 54 9,946 (68.2) 4,648 (31.8) 55 and Above 7,184 (69.9) 3,217 (30.9) Sex 0.007 Male 14,720 (69.1) 6,598 (30.9) Female 34,052 (70.1) 14,546 (29.9) TB disease status < 0.001 With active TB 770 (54.7) 637 (45.3) Without active TB 48,002 (70.3) 20,593 (29.7) Table 2 Cox proportional hazard models of the hazard to transition to DTG among PLHIV in rural KZN, South Africa. Adjusted hazard ratio (95% Confidence interval) p-value On TB treatment No 1 Yes 0.79 (0.76–0.82) < 0.001 Sex Male 1 Female 1.05 (0.92–1,19 0.468 Age at transitioning (years) 15–24 1 25–34 1.30 (1,23–1.25) < 0.001 35–44 1.29 (1.26–1.31) < 0.001 45–54 1.31 (1.29–1.33) < 0.001 55 and above 1.38 (1.36–1.41) < 0.001 VLS No Yes 1.33 (1.31–1.34) < 0.001 CD4 Count Category (insert unit) < 200 0.57 (0.54–1.59) < 0.001 200 to 350 0.70 (0.68–0.72) < 0.001 351 to 499 1 — 500 and above 0.94 (0.92–0.96) < 0.001 Table 3 Odds ratios for the risk of developing Tuberculosis among people living with HIV Odds ratio (95% Confidence interval) p-value Gender Male 1 Female 0.61 (0.58–0.56) < 0.001 On DTG No 1 Yes 0.73 (0.68–0.77) < 0.001 Age groups 15–24 1 25–34 0.86 (0.75 – 0.97) 0.020 35–44 0.85 (0.73–0.96) 0.010 45–54 0.79 (0.70–0.88) 0.002 55 and above 0.84 (0.74–0.95) 0.005 Virally suppressed No 1 Yes 0.97 (0.91–1.04) 0.479 CD4 Count Category (insert unit) < 200 200 to 350 0.61 (0.0.54–0.69) < 0.001 351 to 499 0.58 (0.53–0.64) < 0.001 500 and above 0.57 (0.52–0.64) < 0.001 Analysis of factors associated with advanced HIV disease (Table 4 ) showed that females had a 40% lower risk than males [OR = 0.60, 95% CI: 0.35–0.53]. Use of DTG was again protective, with 58% lower odds of advanced HIV disease among those on DTG [OR = 0.52, 95% CI: 0.40–0.43] compared to those on non-DTG regimens. The risk of advanced HIV disease increased significantly with age; individuals aged 50 years and above had over twice the odds of advanced disease compared to those aged 15–24 years [OR = 2.31, 95% CI: 2.15–2.47]. Additionally, PLHIV with symptomatic TB and those who were not virally suppressed exhibited higher proportions of advanced HIV disease. Table 4 Odds ratios for the risk of advanced HIV disease among people living with HIV Odds ratio (95% Confidence interval) p-value Gender Male 1 Female 0.60 (0.35–0.53) < 0.001 On DTG No 1 Yes 0.42 (0.40–0.43) < 0.001 Age groups 15–24 1 25–34 1.37 (1.28 – 01.48) < 0.001 35–44 2.17 (2.03–2.33) < 0.001 45–54 2.50 (2.34–2.68) < 0.001 55 and above 2.31 (2.15–2.47) < 0.001 Virally suppressed Yes 1 No 1.72 (1.67–1.78) < 0.001 TB status Asymptomatic 1 Symptomatic 1.69 (1.55–1.83) < 0.001 With respect to treatment transitions, the hazard of transitioning to DTG was 22% lower among PLHIV with TB compared to those without TB [AHR = 0.78, 95% CI: 0.76–0.82]. Age was positively associated with DTG transition: compared to PLHIV aged 15–24 years, those aged 25–34 and ≥ 55 years had 30% [AHR = 1.30, 95% CI: 1.23–1.38] and 38% [AHR = 1.38, 95% CI: 1.36–1.41] higher hazards of transitioning, respectively. Viral suppression was also a strong predictor, with suppressed individuals having a 33% higher hazard of DTG transition [AHR = 1.33, 95% CI: 1.31–1.36]. In contrast, low CD4 count significantly reduced the likelihood of transition: PLHIV with CD4 < 200 cells/mm³ had a 43% lower hazard [AHR = 0.57, 95% CI: 0.54–0.58] compared to those with CD4 counts between 351–499 cells/mm³. DISCUSSION This study described the transition of people living with HIV (PLHIV) to dolutegravir (DTG) and evaluated the effect of HIV–tuberculosis (TB) coinfection on the risk of transitioning to DTG in rural KwaZulu-Natal, South Africa, between 2019 and 2023. Our findings indicate an incomplete transition, with a quarter of the population cohort still left untreated. Furthermore, our findings indicate that the transition to DTG lagged in PLHIV coinfected with TB and those with advanced HIV disease (CD4 count < 200 cell/mm 3 ). We data further demonstrates that the risk of TB was high among PLHIV with advanced HIV disease and those on non-DTG regimens. The transition to DTG among PLHIV by 31 December 2023 was below the 90% target the South African National Department of Health envisioned to achieve by then 25 . The overall transition to DTG in South Africa lags compared to other sub-Saharan countries. In Malawi, the national transition target was achieved by 2021.²⁶ In Zimbabwe, approximately 80% of people living with HIV (PLHIV) had transitioned to DTG by 2021,²⁷ while in Zambia, 98% had transitioned by 2023.²⁸ Despite our study setting bearing/reflecting the worst burden of HIV in South Africa, many factors may have contributed to the incomplete transition apart from clinical and demographic factors identified in this study. These include HIV–TB coinfection, a higher prevalence of advanced HIV disease, and a larger proportion of younger PLHIV. Some of these factors could be related to limited training among service providers on DTG interactions with other drugs during the early stages of the transition 26 , limited laboratory facilities for monitoring treatment progress and determining eligibility 27 , ³⁰ and concerns—among both providers and clients—about the potential adverse effects of DTG during the first trimester of pregnancy in women of childbearing age living with HIV.¹⁰ The lagged transition to DTG among PLHIV with active TB has been attributed to concerns of drug-drug interactions with rifampicin used to treat TB as a main component 28 . Research indicates that Rifampicin interacts with DTG, thereby decreasing its efficacy 29 , 30 . Evidence from controlled trials on the effect of a double DTG dose among PLHIV coinfected with TB who require Rifampicin demonstrated favourable clinical outcomes as a result of immune recovery? 30 . If service providers could follow the current South African National Department of Health's HIV and TB treatment guidelines (40), they could bridge the gap observed in lagged transitions in PLHIV to the level of their counterparts without TB (39). For PLHIV with advanced HIV disease (low CD4 counts), the slow transition may be attributed to concerns about possible adverse effects associated with DTG and adherence challenges, although these concerns are not well-supported by evidence 31 , 32 . A strong relationship between lagged transition to DTG and the high risk of TB disease and advanced HIV disease mean that correcting the lagged transition could improve clinical outcomes, particularly those related to advanced HIV disease which has been shown to predict TB in PLHIV in this study as well as a related study 3 . This study utilised data from a setting with the world’s highest HIV burden and high rates of tuberculosis (TB) infection to assess progress in the transition to dolutegravir (DTG).. It is also one of the few studies to examine how demographic and clinical factors contribute to disparities in the scale-up of DTG. Based on the findings, targeted interventions are needed to accelerate the delayed transition to dolutegravir (DTG) among people living with HIV (PLHIV) who are coinfected with tuberculosis (TB) or have advanced HIV disease, to improve clinical outcomes in rural KwaZulu-Natal.One of the limitations of this study is the potential for provider bias in how individuals were transitioned to dolutegravir (DTG), particularly if clinical guidelines were not consistently followed or if DTG was not readily available during the transition period. In addition, misclassification within the clinical data may have introduced bias in the estimates and led to incorrect assumptions about the effect of HIV–TB coinfection on the likelihood of transitioning to dolutegravir (DTG)For example, PLHIV on EFV could have been misclassified as being on DTG and vice versa or asymptomatic individuals could have been misclassified as TB positive. Interventions to correct the lagged transition among PLHIV coinfected with TB and PLHIV with advanced HIV disease are required to improve clinical outcomes in rural KZN. Conclusion The transition to dolutegravir (DTG) was delayed among people living with HIV (PLHIV) who were co-infected with tuberculosis (TB) and those with advanced HIV disease. Targeted efforts are needed to ensure equitable DTG rollout, particularly for PLHIV with TB, to match the pace of transition seen in those without TB in rural KwaZulu-Natal. Declarations Human Ethics We used anonymised secondary data that is provided routinely collected in HIV clinics and captured in TIER.NET. Ethical clearances for the study were granted by the Stellenbosch University health research ethics with reference number S24/11/300 (PhD) and the University of KwaZulu-Natal’s Biomedical Research Ethics Committee (BE290/16 ). Consent to Participate Since we used HIV program Data, participants' consent to participate was not applicable. Conflicts of Interest The authors declare no conflict of interest. Source of Funding This work is supported by the National Institute of Mental Health (NIMH) (Award # R01MH131480) and the German Research Foundation (BA2067/14-1). The AHRI’s Demographic Surveillance Information System and Population Intervention Program is funded by the Wellcome Trust (227167/A/23/Z) and the South Africa Population Research Infrastructure Network (funded by the South African Department of Science and Technology and hosted by the South African Medical Research Council). Author Contributions Conceptualization of the topic: Reuben Moyo, Elphas Okango, Peter Nyasulu, Larisse Bolton, and Frank Tanser Background and Methods: Reuben Moyo, Elphas Okango, Nthoesele Letoao , Margot Otto, Peter Nyasulu, Frank Tanser Data analysis and interpretation: Reuben Moyo, Elphas Okango, Larisse Bolton, Peter Nyasulu, Frank Tanser Reviewing of final draft: Reuben Moyo, Elphas Okango, Nthoesele Letoao, Larisse Bolton, Margot Otto, Peter S Nyasulu, Frank Tanser Availability of Data Data for this study is freely available and maybe requested from the Africa Health Research Institute (AHRI) by contacting the data management officer. 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Cite Share Download PDF Status: Published Journal Publication published 24 Oct, 2025 Read the published version in AIDS Research and Therapy → Version 1 posted Editorial decision: Revision requested 04 Aug, 2025 Reviews received at journal 03 Aug, 2025 Reviewers agreed at journal 18 Jul, 2025 Reviewers invited by journal 16 Jul, 2025 Editor assigned by journal 11 Jul, 2025 Submission checks completed at journal 11 Jul, 2025 First submitted to journal 11 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7102523","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":487635592,"identity":"e9ced3a2-b2a9-466b-bb03-a2d9cc798e2a","order_by":0,"name":"Reuben Christopher Moyo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIie3RoWvDQBTH8XcEruZtsS9spP/ClcLVjPRfuSMQFT1VESi0Jiw2/TsK1VcCmQnUxjVuNmpMdQtzFetlruI++n35iQfgOHfIn2yPXY8c/dFJkDfxrHx+DINsbCJaJZ/wJZwLM3rGKBWUqdT7UyM7WEUw3Vpilh2N6JtEH9p0IaCOgeXqduKxTOldXg8JSgJuwANLwj0Q1cPlW++LZkguBrjf3U6Qw2yNyOcCUklsYwDJskKIMSuRh9Qmr6TfYiSyrCzPH+9fv68sqgP1n1E4LSwr14Zj/M+94ziO84cfHE0/TzkEcpEAAAAASUVORK5CYII=","orcid":"","institution":"Stellenbosch University","correspondingAuthor":true,"prefix":"","firstName":"Reuben","middleName":"Christopher","lastName":"Moyo","suffix":""},{"id":487635593,"identity":"c0325ee3-d5c0-42d9-9709-96320d2a8ecd","order_by":1,"name":"Larisse Bolton","email":"","orcid":"","institution":"Stellenbosch University","correspondingAuthor":false,"prefix":"","firstName":"Larisse","middleName":"","lastName":"Bolton","suffix":""},{"id":487635595,"identity":"44abe121-6861-401a-894d-2f1ea533507a","order_by":2,"name":"Elphas Luchemo Okango","email":"","orcid":"","institution":"University of KwaZulu-Natal","correspondingAuthor":false,"prefix":"","firstName":"Elphas","middleName":"Luchemo","lastName":"Okango","suffix":""},{"id":487635597,"identity":"7ec352e8-60e3-462f-85f4-7375af31f4ab","order_by":3,"name":"Margot Otto","email":"","orcid":"","institution":"Stellenbosch University","correspondingAuthor":false,"prefix":"","firstName":"Margot","middleName":"","lastName":"Otto","suffix":""},{"id":487635599,"identity":"ed712ac5-ea53-4a23-b6ce-d8cad97ed2f4","order_by":4,"name":"Nthoesele Letoao","email":"","orcid":"","institution":"Stellenbosch University","correspondingAuthor":false,"prefix":"","firstName":"Nthoesele","middleName":"","lastName":"Letoao","suffix":""},{"id":487635602,"identity":"6f3efc76-6edd-4b4c-b2b6-70077ad8888c","order_by":5,"name":"Peter S. Nyasulu","email":"","orcid":"","institution":"Stellenbosch University","correspondingAuthor":false,"prefix":"","firstName":"Peter","middleName":"S.","lastName":"Nyasulu","suffix":""},{"id":487635605,"identity":"de3cbae8-fd4a-4b95-a6d3-ebcdb411434a","order_by":6,"name":"Frank Tanser","email":"","orcid":"","institution":"Stellenbosch University","correspondingAuthor":false,"prefix":"","firstName":"Frank","middleName":"","lastName":"Tanser","suffix":""}],"badges":[],"createdAt":"2025-07-11 14:23:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7102523/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7102523/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12981-025-00810-z","type":"published","date":"2025-10-24T16:17:12+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":87186980,"identity":"bd47fc9c-3933-40fa-a5eb-8ae9e45bb41f","added_by":"auto","created_at":"2025-07-21 10:37:53","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":131289,"visible":true,"origin":"","legend":"\u003cp\u003e1a – 1d: Proportion of PLHIV transitioning to DTG over time\u003c/p\u003e\n\u003cp\u003eThe figures above indicate the proportion of PLHIV transition to DTG by Sex (1a), age groups (1b), TB status (1c) and CD4 count (1d).\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7102523/v1/d6201440a797d25b2366a417.jpeg"},{"id":94490225,"identity":"e8ba4fd7-1c80-4149-b273-46fb62f2048a","added_by":"auto","created_at":"2025-10-27 17:08:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":952266,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7102523/v1/f6d46291-4fbb-4fae-aef8-2c71c755614f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Timing matters: Examining the lag in Dolutegravir rollout among people living with HIV with Tuberculosis and advanced HIV disease in Rural South Africa (2019- 2023)","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eTuberculosis is a highly infectious disease caused by Mycobacterium Tuberculosis that primarily affects the lungs. It is one of the leading causes of death among people living with HIV\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. In 2023, approximately 10.8\u0026nbsp;million people were diagnosed with TB globally, resulting in 1.25\u0026nbsp;million deaths, including 161,000 PLHIV\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e.South Africa has one of the world\u0026rsquo;s highest tuberculosis (TB) burdens, with an estimated incidence rate of 468 per 100,000 person-years, of which a substantial proportion occurs among PLHIV \u0026sup2; \u0026sup3;. The first South African national TB survey conducted in 2018 reported the prevalence of TB as 852 (95% CI: 679\u0026ndash;1026) cases per 100,000 persons \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. The survey further reported a prevalence of TB among PLHIV of 1,734 (95% CI: 1219\u0026ndash;2234) cases per 100,000 population. TB is also common among PLHIV with advanced HIV disease\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, is a late stage of HIV infection characterised by severe immune system damage\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Early initiation of antiretroviral therapy (ART) and prompt TB treatment in PLHIV has been shown to offer improved clinical outcomes \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Another strategy of reducing the risk of developing active TB disease in PLHIV in high TB burden areas is through the use of Isoniazid preventive therapy \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. This strategy, recommended by the World Health Organization (WHO), has been shown to reduce the risk of developing active TB by almost 60% \u003csup\u003e7\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eEfavirenz (EFV), a class of non-nucleoside reverse transcriptase inhibitor (NNRTI), has been the main component of ART in South Africa since 2004 \u003csup\u003e8\u003c/sup\u003e. Management of PLHIV using EFV as the main component of ART was, however, faced with NNRTI drug resistant HIV strains \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Consequently, the WHO recommended DTG, an integrase strand transfer inhibitor (INSTI) class of ART\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, as an alternative to EFV in 2018 due to its high genetic barrier to resistance \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, tolerance \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, efficacy \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, and cost-effectiveness \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. South Africa started transitioning to DTG in September 2019 \u003csup\u003e9\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eEvidence on the overall transition to dolutegravir (DTG), and how this transition differs by tuberculosis (TB) disease status, which is a leading cause of death among people living with HIV (PLHIV)\u0026sup1;⁵ and advanced HIV disease, is sparse. Knowing which categories of PLHIV who have not transitioned to DTG, including those coinfected with TB, would be useful in addressing patient or clinical related reasons for not transitioning to DTG. Gaining insight into these barriers can inform targeted interventions to promote a more widespread adoption of DTG-based regimens. This study reports the transition to DTG using data from a high HIV burden in rural KwaZulu-Natal, South Africa.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e\u003cb\u003eStudy design and setting.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study followed a retrospective cohort study design comprised of routinely collected deidentified data obtained from 19 HIV clinics in Umkhanyakude, rural KZN, South Africa. This HIV incidence in the study setting is high, approximately 2.5 per 100 person-years for females and 1.5 per 100 person years for males\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. The study site is nested within a health and demographic surveillance system (HDSS) that has been operated by the Africa Health Research Institute (AHRI) since 2000.\u003c/p\u003e\u003cp\u003e\u003cb\u003eData Sources\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe study used clinical program data from the three interlinked electronic registers(TIER.NET), an HIV data capturing and management system introduced in South African clinics in 2010\u003csup\u003e17\u003c/sup\u003e. PLHIV initiated on ART before the introduction of TIER.NET had their data transferred into TIER.NET from previous ART databases and patient master cards.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStudy population and inclusion criteria\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe study population comprised a cohort of 69,916 PLHIV aged 15 years and older who were still in care at the start of the follow-up period on 1st October 2019. Children living with HIV aged 14 years and younger were not included because there was no paediatric formulation of DTG during the early transition. The start of the follow-up was chosen as 1 October 2019 since South Africa initiated the transition to DTG in September 2019.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMeasures\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe following variables were considered within our analyses; 1) Regimen type: This variable described whether an individual was on a DTG containing regimen or a non-DTG containing regimen. The non-DTG group included individuals on Efavirenz (EFV)-based regimens or those receiving protease inhibitors (PIs). 2) Viral load suppression (VLS): This time-varying variable indicates whether an individual is virally suppressed or not at different follow-up points. We selected the cut-off point for viral suppression as \u0026le;400 copies per millilitre of blood, while those with \u0026gt;\u0026thinsp;400 copies per millilitre of blood were considered virally unsuppressed \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. 30 Advanced HIV disease is defined as people living with CD4 count less than 200 cell/mm\u003csup\u003e3\u003c/sup\u003e. 3) Tuberculosis (TB) disease status: captured whether an individual had a documented diagnosis of tuberculosis at any point during follow-up 4) CD4 count, measured in cells/mm\u0026sup3;, serves as an indicator of immune function and disease progression in people living with HIV. For analysis, CD4 counts were categorised into four groups: 0\u0026ndash;199, 200\u0026ndash;499, 500\u0026ndash;999, and \u0026ge;\u0026thinsp;1,000 cells/mm\u0026sup3;. CD4 count was treated as a time-varying variable in the dataset.5) Sex of participants: This variable described the biological differentiation of sex into males and females as assigned at birth. 6) Participant age groups: Age groups were generated from the participants' age variable, generated by subtracting the date of data generation (31st December 2023) and participant date of birth. The participant age was categorised into the following categories; 15 to 24, 25 to 34, 35 to 44, 45 to 54 and above 55 years. Age was a time-varying variable.\u003c/p\u003e\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eDescriptive statistics were used to characterise participants by TB status, which were stratified by age groups and sex. The Pearson chi-square test of independence was used to assess whether the association between PLHIV characteristics and DTG regimen status was statistically significant \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Since PLHIV transitioned to or initiated DTG at different time points, we applied Kaplan Meir methods to describe the transition by TB status, age groups, sex, and CD4 count \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. We evaluated the effect of tuberculosis (TB) on the hazard of transitioning to dolutegravir (DTG) using a multivariable mixed-effects Cox proportional hazards model, accounting for clustering by clinic. The Cox proportional hazard models are distribution free survival models that assume that the survival/failure curves for two or more strata of the predictor variables are proportional over time\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e and have been widely used in public health research to fit models for time-to-event data. Since the CD4 count and viral load data had missing values, we applied regression-based multiple imputation to impute the missing observations for these covariates. Multiple imputation is the recommended approach for missing information in longitudinal survival data \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. The covariates included in our adjusted Cox proportional hazard model were DTG status?, sex, age groups, VLS and CD4 count. This study also modelled the risk of TB and advanced HIV disease among PLHIV in rural KwaZulu-Natal. To model the risk of advanced HIV disease and TB, we employed a mixed effects logistic regression model because observations were dependent, that is PLHIV were screened for TB symptoms and for advanced HIV disease at each visit. Statistical significance in this study was considered at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eOf the 69,916 people living with HIV (PLHIV) included in the cohort, 49,365 (69.15%) were female, and the median age was 40 years (IQR: 33\u0026ndash;49). Clinical symptoms consistent with tuberculosis (TB) disease were identified in 1,407 (2.0%) individuals, while 29% (n\u0026thinsp;=\u0026thinsp;20,275) presented with advanced HIV disease during the study period. By December 31, 2023, approximately 70% (n\u0026thinsp;=\u0026thinsp;48,598) of PLHIV had transitioned to dolutegravir (DTG)-based antiretroviral therapy (ART), while 30% (n\u0026thinsp;=\u0026thinsp;21,318) remained on non-DTG regimens. Among PLHIV with TB, only 770 (54.7%) transitioned to DTG, in contrast to 70.3% (n\u0026thinsp;=\u0026thinsp;48,002) of those without active TB. While overall DTG uptake showed minimal gender disparity, more females transitioned to DTG than males beginning in 2021. Younger individuals, particularly those aged 15\u0026ndash;24 years, had lower transition rates compared to older age groups. Transition rates were also persistently lower across time among PLHIV with active TB symptoms and those with low CD4 counts.\u003c/p\u003e\u003cp\u003eFindings from the mixed effects logistic regression model (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) indicated that female PLHIV had 39% lower odds of TB disease compared to males [OR\u0026thinsp;=\u0026thinsp;0.61, 95% CI: 0.58\u0026ndash;0.56]. Use of DTG-based regimens was associated with a 27% reduction in the odds of TB [OR\u0026thinsp;=\u0026thinsp;0.73, 95% CI: 0.68\u0026ndash;0.77] compared to non-DTG regimens. Age was an important factor, with lower odds of TB observed among PLHIV aged 25 years and above relative to those aged 15\u0026ndash;24 years. CD4 count also significantly influenced TB risk: PLHIV with CD4 counts between 200\u0026ndash;350 cells/mm\u0026sup3; had 39% lower odds of TB [OR\u0026thinsp;=\u0026thinsp;0.61, 95% CI: 0.54\u0026ndash;0.69], while those with CD4\u0026thinsp;\u0026ge;\u0026thinsp;500 cells/mm\u0026sup3; had 43% lower odds [OR\u0026thinsp;=\u0026thinsp;0.57, 95% CI: 0.52\u0026ndash;0.64] compared to individuals with CD4\u0026thinsp;\u0026lt;\u0026thinsp;200 cells/mm\u0026sup3;.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDistribution of regimen type by age groups, sex, and TB disease status (N\u0026thinsp;=\u0026thinsp;69,916)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eRegimen type, \u003cem\u003en (%)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eDTG Containing\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eNon-DTG containing\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOverall\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e48,598 (70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21,318 (30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge Groups (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15 to 24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3,297 (71.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,299 (28.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25 to 34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12,098 (72.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4,560 (27.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e35 to 44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16,247 (68.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7,420 (31.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e45 to 54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9,946 (68.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4,648 (31.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e55 and Above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7,184 (69.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3,217 (30.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14,720 (69.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6,598 (30.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e34,052 (70.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14,546 (29.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTB disease status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWith active TB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e770 (54.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e637 (45.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWithout active TB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e48,002 (70.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20,593 (29.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCox proportional hazard models of the hazard to transition to DTG among PLHIV in rural KZN, South Africa.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAdjusted hazard ratio (95% Confidence interval)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOn TB treatment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.79 (0.76\u0026ndash;0.82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.05 (0.92\u0026ndash;1,19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.468\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge at transitioning (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u0026ndash;24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25\u0026ndash;34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.30 (1,23\u0026ndash;1.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e35\u0026ndash;44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.29 (1.26\u0026ndash;1.31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e45\u0026ndash;54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.31 (1.29\u0026ndash;1.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e55 and above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.38 (1.36\u0026ndash;1.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVLS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.33 (1.31\u0026ndash;1.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCD4 Count Category (insert unit)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;200\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.57 (0.54\u0026ndash;1.59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e200 to 350\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.70 (0.68\u0026ndash;0.72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e351 to 499\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e500 and above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.94 (0.92\u0026ndash;0.96)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eOdds ratios for the risk of developing Tuberculosis among people living with HIV\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOdds ratio (95% Confidence interval)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.61 (0.58\u0026ndash;0.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOn DTG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.73 (0.68\u0026ndash;0.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge groups\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u0026ndash;24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25\u0026ndash;34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.86 (0.75 \u0026ndash; 0.97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.020\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e35\u0026ndash;44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.85 (0.73\u0026ndash;0.96)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e45\u0026ndash;54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.79 (0.70\u0026ndash;0.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e55 and above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.84 (0.74\u0026ndash;0.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVirally suppressed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.97 (0.91\u0026ndash;1.04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.479\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCD4 Count Category (insert unit)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;200\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e200 to 350\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.61 (0.0.54\u0026ndash;0.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e351 to 499\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.58 (0.53\u0026ndash;0.64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e500 and above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.57 (0.52\u0026ndash;0.64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAnalysis of factors associated with advanced HIV disease (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) showed that females had a 40% lower risk than males [OR\u0026thinsp;=\u0026thinsp;0.60, 95% CI: 0.35\u0026ndash;0.53]. Use of DTG was again protective, with 58% lower odds of advanced HIV disease among those on DTG [OR\u0026thinsp;=\u0026thinsp;0.52, 95% CI: 0.40\u0026ndash;0.43] compared to those on non-DTG regimens. The risk of advanced HIV disease increased significantly with age; individuals aged 50 years and above had over twice the odds of advanced disease compared to those aged 15\u0026ndash;24 years [OR\u0026thinsp;=\u0026thinsp;2.31, 95% CI: 2.15\u0026ndash;2.47]. Additionally, PLHIV with symptomatic TB and those who were not virally suppressed exhibited higher proportions of advanced HIV disease.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eOdds ratios for the risk of advanced HIV disease among people living with HIV\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOdds ratio (95% Confidence interval)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.60 (0.35\u0026ndash;0.53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOn DTG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.42 (0.40\u0026ndash;0.43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge groups\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u0026ndash;24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25\u0026ndash;34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.37 (1.28 \u0026ndash; 01.48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e35\u0026ndash;44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.17 (2.03\u0026ndash;2.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e45\u0026ndash;54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.50 (2.34\u0026ndash;2.68)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e55 and above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.31 (2.15\u0026ndash;2.47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVirally suppressed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.72 (1.67\u0026ndash;1.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTB status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAsymptomatic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSymptomatic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.69 (1.55\u0026ndash;1.83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWith respect to treatment transitions, the hazard of transitioning to DTG was 22% lower among PLHIV with TB compared to those without TB [AHR\u0026thinsp;=\u0026thinsp;0.78, 95% CI: 0.76\u0026ndash;0.82]. Age was positively associated with DTG transition: compared to PLHIV aged 15\u0026ndash;24 years, those aged 25\u0026ndash;34 and \u0026ge;\u0026thinsp;55 years had 30% [AHR\u0026thinsp;=\u0026thinsp;1.30, 95% CI: 1.23\u0026ndash;1.38] and 38% [AHR\u0026thinsp;=\u0026thinsp;1.38, 95% CI: 1.36\u0026ndash;1.41] higher hazards of transitioning, respectively. Viral suppression was also a strong predictor, with suppressed individuals having a 33% higher hazard of DTG transition [AHR\u0026thinsp;=\u0026thinsp;1.33, 95% CI: 1.31\u0026ndash;1.36]. In contrast, low CD4 count significantly reduced the likelihood of transition: PLHIV with CD4\u0026thinsp;\u0026lt;\u0026thinsp;200 cells/mm\u0026sup3; had a 43% lower hazard [AHR\u0026thinsp;=\u0026thinsp;0.57, 95% CI: 0.54\u0026ndash;0.58] compared to those with CD4 counts between 351\u0026ndash;499 cells/mm\u0026sup3;.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study described the transition of people living with HIV (PLHIV) to dolutegravir (DTG) and evaluated the effect of HIV\u0026ndash;tuberculosis (TB) coinfection on the risk of transitioning to DTG in rural KwaZulu-Natal, South Africa, between 2019 and 2023. Our findings indicate an incomplete transition, with a quarter of the population cohort still left untreated. Furthermore, our findings indicate that the transition to DTG lagged in PLHIV coinfected with TB and those with advanced HIV disease (CD4 count\u0026thinsp;\u0026lt;\u0026thinsp;200 cell/mm\u003csup\u003e3\u003c/sup\u003e). We data further demonstrates that the risk of TB was high among PLHIV with advanced HIV disease and those on non-DTG regimens.\u003c/p\u003e\u003cp\u003eThe transition to DTG among PLHIV by 31 December 2023 was below the 90% target the South African National Department of Health envisioned to achieve by then\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. The overall transition to DTG in South Africa lags compared to other sub-Saharan countries. In Malawi, the national transition target was achieved by 2021.\u0026sup2;⁶ In Zimbabwe, approximately 80% of people living with HIV (PLHIV) had transitioned to DTG by 2021,\u0026sup2;⁷ while in Zambia, 98% had transitioned by 2023.\u0026sup2;⁸ Despite our study setting bearing/reflecting the worst burden of HIV in South Africa, many factors may have contributed to the incomplete transition apart from clinical and demographic factors identified in this study. These include HIV\u0026ndash;TB coinfection, a higher prevalence of advanced HIV disease, and a larger proportion of younger PLHIV. Some of these factors could be related to limited training among service providers on DTG interactions with other drugs during the early stages of the transition \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, limited laboratory facilities for monitoring treatment progress and determining eligibility \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e, \u0026sup3;⁰ and concerns\u0026mdash;among both providers and clients\u0026mdash;about the potential adverse effects of DTG during the first trimester of pregnancy in women of childbearing age living with HIV.\u0026sup1;⁰\u003c/p\u003e\u003cp\u003eThe lagged transition to DTG among PLHIV with active TB has been attributed to concerns of drug-drug interactions with rifampicin used to treat TB as a main component \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Research indicates that Rifampicin interacts with DTG, thereby decreasing its efficacy \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Evidence from controlled trials on the effect of a double DTG dose among PLHIV coinfected with TB who require Rifampicin demonstrated favourable clinical outcomes as a result of immune recovery? \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. If service providers could follow the current South African National Department of Health's HIV and TB treatment guidelines (40), they could bridge the gap observed in lagged transitions in PLHIV to the level of their counterparts without TB (39). For PLHIV with advanced HIV disease (low CD4 counts), the slow transition may be attributed to concerns about possible adverse effects associated with DTG and adherence challenges, although these concerns are not well-supported by evidence\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. A strong relationship between lagged transition to DTG and the high risk of TB disease and advanced HIV disease mean that correcting the lagged transition could improve clinical outcomes, particularly those related to advanced HIV disease which has been shown to predict TB in PLHIV in this study as well as a related study\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThis study utilised data from a setting with the world\u0026rsquo;s highest HIV burden and high rates of tuberculosis (TB) infection to assess progress in the transition to dolutegravir (DTG).. It is also one of the few studies to examine how demographic and clinical factors contribute to disparities in the scale-up of DTG. Based on the findings, targeted interventions are needed to accelerate the delayed transition to dolutegravir (DTG) among people living with HIV (PLHIV) who are coinfected with tuberculosis (TB) or have advanced HIV disease, to improve clinical outcomes in rural KwaZulu-Natal.One of the limitations of this study is the potential for provider bias in how individuals were transitioned to dolutegravir (DTG), particularly if clinical guidelines were not consistently followed or if DTG was not readily available during the transition period. In addition, misclassification within the clinical data may have introduced bias in the estimates and led to incorrect assumptions about the effect of HIV\u0026ndash;TB coinfection on the likelihood of transitioning to dolutegravir (DTG)For example, PLHIV on EFV could have been misclassified as being on DTG and vice versa or asymptomatic individuals could have been misclassified as TB positive. Interventions to correct the lagged transition among PLHIV coinfected with TB and PLHIV with advanced HIV disease are required to improve clinical outcomes in rural KZN.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe transition to dolutegravir (DTG) was delayed among people living with HIV (PLHIV) who were co-infected with tuberculosis (TB) and those with advanced HIV disease. Targeted efforts are needed to ensure equitable DTG rollout, particularly for PLHIV with TB, to match the pace of transition seen in those without TB in rural KwaZulu-Natal.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eHuman Ethics \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe used anonymised secondary data that is provided routinely collected in HIV clinics and captured in TIER.NET. Ethical clearances for the study were granted by the \u003cstrong\u003eStellenbosch University health research ethics\u003c/strong\u003e with reference number\u0026nbsp;\u003cstrong\u003eS24/11/300 (PhD)\u003c/strong\u003e and the \u003cstrong\u003eUniversity of KwaZulu-Natal’s Biomedical Research Ethics Committee\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(BE290/16\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSince we used HIV program Data, participants' consent to participate was \u003cstrong\u003enot applicable.\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSource of Funding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work is supported by the National Institute of Mental Health (NIMH) (Award # R01MH131480) and the German Research Foundation (BA2067/14-1). The AHRI’s Demographic Surveillance Information System and Population Intervention Program is funded by the Wellcome Trust (227167/A/23/Z) and the South Africa Population Research Infrastructure Network (funded by the South African Department of Science and Technology and hosted by the South African Medical Research Council).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConceptualization of the topic:\u003c/strong\u003e Reuben Moyo, Elphas Okango, Peter Nyasulu, Larisse Bolton, and Frank Tanser\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBackground and Methods:\u003c/strong\u003e Reuben Moyo, Elphas Okango, Nthoesele Letoao , Margot Otto, Peter Nyasulu, Frank Tanser\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData analysis and interpretation:\u003c/strong\u003e Reuben Moyo, Elphas Okango, Larisse Bolton, Peter Nyasulu, Frank Tanser\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReviewing of final draft:\u003c/strong\u003e Reuben Moyo, Elphas Okango, Nthoesele Letoao, Larisse Bolton, Margot Otto, Peter S Nyasulu, Frank Tanser\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData for this study is freely available and maybe requested from the Africa Health Research Institute (AHRI) by contacting the data management officer.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eTuberculosis [Internet]. 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Demographic and Clinical Characteristics Predicting Missed Clinic Visits among Patients Living with HIV on Antiretroviral Treatment in Kinshasa and Haut-Katanga Provinces of the Democratic Republic of Congo. Healthcare (Switzerland). Volume 12. Multidisciplinary Digital Publishing Institute (MDPI); 2024. 13.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFimbo A, Mwalwisi YH, Mwamwitwa K et al. Incidence and determinants of adverse events in individuals with HIV commencing Dolutegravir-based antiretroviral therapy in mainland Tanzania. Sci Rep Nat Res; 2024;14(1).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"aids-research-and-therapy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"arty","sideBox":"Learn more about [AIDS Research and Therapy](http://aidsrestherapy.biomedcentral.com/)","snPcode":"12981","submissionUrl":"https://submission.nature.com/new-submission/12981/3","title":"AIDS Research and Therapy","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Tuberculosis, Advanced HIV disease, Dolutegravir, South Africa","lastPublishedDoi":"10.21203/rs.3.rs-7102523/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7102523/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e\u003cp\u003eWhile Dolutegravir (DTG)-based antiretroviral therapy (ART) has become the preferred regimen for people living with HIV (PLHIV), the pace and equity of its adoption\u0026mdash;especially among subgroups with tuberculosis (TB) and advanced HIV disease\u0026mdash;remain understudied in high-burden settings like rural KwaZulu-Natal (KZN), South Africa.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e\u003cp\u003e We conducted a longitudinal cohort study using routine HIV program data from 69,916 PLHIV aged\u0026thinsp;\u0026ge;\u0026thinsp;15 years, followed across 19 HIV clinics in rural KZN between October 1, 2019, and December 31, 2023. Kaplan-Meier analysis estimated time to DTG transition. Cox proportional hazards models assessed the effect of TB and advanced HIV disease (CD4 count\u0026thinsp;\u0026lt;\u0026thinsp;200 cells/mm\u0026sup3;) on DTG transition. Mixed-effects logistic regression models estimated the odds of TB and advanced HIV disease by ART regimen.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e\u003cp\u003eOf the cohort, 49,365 (69.2%) were female, with a median age of 40 years (IQR: 32\u0026ndash;49). By study end, 70.9% (n\u0026thinsp;=\u0026thinsp;49,598) had transitioned to DTG. PLHIV with TB had a 22% lower hazard of transitioning to DTG compared to those without TB [adjusted hazard ratio (AHR)\u0026thinsp;=\u0026thinsp;0.78; 95% CI: 0.76\u0026ndash;0.82], while those with CD4\u0026thinsp;\u0026lt;\u0026thinsp;200 cells/mm\u0026sup3; had a 43% lower hazard [AHR\u0026thinsp;=\u0026thinsp;0.57; 95% CI: 0.54\u0026ndash;1.59]. DTG use was associated with significantly lower odds of advanced HIV disease (OR\u0026thinsp;=\u0026thinsp;0.42; 95% CI: 0.40\u0026ndash;0.43) and TB (OR\u0026thinsp;=\u0026thinsp;0.73; 95% CI: 0.68\u0026ndash;0.77).\u003c/p\u003e\u003ch2\u003eConclusion:\u003c/h2\u003e\u003cp\u003ePLHIV with TB or advanced HIV disease were less likely to transition to DTG regimens. Strengthening adherence to clinical guidelines and improving integration of HIV and TB care are critical to ensure equitable access to DTG-based ART in rural settings\u003c/p\u003e","manuscriptTitle":"Timing matters: Examining the lag in Dolutegravir rollout among people living with HIV with Tuberculosis and advanced HIV disease in Rural South Africa (2019- 2023)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-21 10:29:48","doi":"10.21203/rs.3.rs-7102523/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-04T22:52:42+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-03T13:00:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"244349906538446645376653521367268782960","date":"2025-07-18T21:18:47+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-16T19:39:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-11T19:30:20+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-11T15:43:08+00:00","index":"","fulltext":""},{"type":"submitted","content":"AIDS Research and Therapy","date":"2025-07-11T14:11:17+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"aids-research-and-therapy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"arty","sideBox":"Learn more about [AIDS Research and Therapy](http://aidsrestherapy.biomedcentral.com/)","snPcode":"12981","submissionUrl":"https://submission.nature.com/new-submission/12981/3","title":"AIDS Research and Therapy","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b13efefe-1d90-426a-877a-02b12013ff76","owner":[],"postedDate":"July 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-27T16:32:55+00:00","versionOfRecord":{"articleIdentity":"rs-7102523","link":"https://doi.org/10.1186/s12981-025-00810-z","journal":{"identity":"aids-research-and-therapy","isVorOnly":false,"title":"AIDS Research and Therapy"},"publishedOn":"2025-10-24 16:17:12","publishedOnDateReadable":"October 24th, 2025"},"versionCreatedAt":"2025-07-21 10:29:48","video":"","vorDoi":"10.1186/s12981-025-00810-z","vorDoiUrl":"https://doi.org/10.1186/s12981-025-00810-z","workflowStages":[]},"version":"v1","identity":"rs-7102523","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7102523","identity":"rs-7102523","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}