Early outcomes after implementation of <i>treat all</i> in Rwanda: an interrupted time series study

Ross, Jonathan; Sinayobye, Jean d’Amour; Yotebieng, Marcel; Hoover, Donald R.; Shi, Qiuhu; Ribakare, Muhayimpundu; Remera, Eric; Bachhuber, Marcus A.; Murenzi, Gad; Sugira, Vincent; Nash, Denis; Anastos, Kathryn; IeDEA, for Central Africa

doi:10.1002/jia2.25279

Cited by 22 publications

(30 citation statements)

References 32 publications

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“…Similar to other studies , younger age, being unmarried and clinical factors (BMI, haemoglobin, creatinine) increased the risk of adverse outcomes in both health zones and irrespective of disease progression. In contrast to another setting , the level of education did not show associations.…”

Section: Discussionsupporting

confidence: 86%

HIV programmatic outcomes following implementation of the ‘Treat‐All’ policy in a public sector setting in Eswatini: a prospective cohort study

et al. 2020

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Introduction The Treat‐All policy – antiretroviral therapy (ART) initiation irrespective of CD4 cell criteria – increases access to treatment. Many ART programmes, however, reported increasing attrition and viral failure during treatment expansion, questioning the programmatic feasibility of Treat‐All in resource‐limited settings. We aimed to describe and compare programmatic outcomes between Treat‐All and standard of care (SOC) in the public sectors of Eswatini. Methods This is a prospective cohort study of ≥16‐year‐old HIV‐positive patients initiated on first‐line ART under Treat‐All and SOC in 18 health facilities of the Shiselweni region, from October 2014 to March 2016. SOC followed the CD4 350 and 500 cells/mm3 treatment eligibility thresholds. Kaplan‐Meier estimates were used to describe crude programmatic outcomes. Multivariate flexible parametric survival models were built to assess associations of time from ART initiation with the composite unfavourable outcome of all‐cause attrition and viral failure. Results Of the 3170 patients, 1888 (59.6%) initiated ART under Treat‐All at a median CD4 cell count of 329 (IQR 168 to 488) cells/mm3 compared with 292 (IQR 161 to 430) (p < 0.001) under SOC. Although crude programme retention at 36 months tended to be lower under Treat‐All (71%) than SOC (75%) (p = 0.002), it was similar in covariate‐adjusted analysis (adjusted hazard ratio [aHR] 1.06, 95% CI 0.91 to 1.23). The hazard of viral suppression was higher for Treat‐All (aHR 1.12, 95% CI 1.01 to 1.23), while the hazard of viral failure was comparable (Treat‐All: aHR 0.89, 95% CI 0.53 to 1.49). Among patients with advanced HIV disease (n = 1080), those under Treat‐All (aHR 1.13, 95% CI 0.88 to 1.44) had a similar risk of an composite unfavourable outcome to SOC. Factors increasing the risk of the composite unfavourable outcome under both interventions were aged 16 to 24 years, being unmarried, anaemia, ART initiation on the same day as HIV care enrolment and CD4 ≤ 100 cells/mm3. Under Treat‐All only, the risk of the unfavourable outcome was higher for pregnant women, WHO III/IV clinical stage and elevated creatinine. Conclusions Compared to SOC, Treat‐All resulted in comparable retention, improved viral suppression and comparable composite outcomes of retention without viral failure.

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Section: Discussionsupporting

confidence: 86%

HIV programmatic outcomes following implementation of the ‘Treat‐All’ policy in a public sector setting in Eswatini: a prospective cohort study

et al. 2020

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“…However, this is unlikely as missing data mainly occurred at two clinics, which had similar CD4 count distributions to the other six clinics. Staff may have placed less emphasis on CD4 count testing as it was no longer required to guide ART eligibility; a phenomenon reported in other programmatic studies of Treat All [6]. Additionally, in a South African study, the main reasons for missing CD4 testing appeared to be independent of CD4 count (e.g.…”

Section: Discussionmentioning

confidence: 97%

“…Treat All has now been implemented in the majority of LMICs [2], but there is limited data regarding the impact on treatment outcomes in public sector ART programmes [6,7]. In these settings, there has been concern that asymptomatic PLHIV with high CD4 counts could be less motivated to remain in care and adhere to treatment [8].…”

Section: Introductionmentioning

confidence: 99%

HIV treatment outcomes among people with initiation CD4 counts >500 cells/µL after implementation of Treat All in South African public clinics: a retrospective cohort study

et al. 2020

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Introduction:The World Health Organisation recommends to Treat All people with HIV, irrespective of CD4 count. However, people with CD4 counts >500 cells/µL may be asymptomatic and therefore less motivated to adhere to antiretroviral therapy (ART). We aimed to assess whether people initiated with CD4 counts >500 cells/µL had worse treatment outcomes compared to those initiated at lower CD4 counts. Methods: We performed a retrospective cohort study among non-pregnant adults initiating ART at eight public clinics in South Africa between September 2016, when Treat All was implemented, and August 2017. We assessed whether initiation CD4 count >500 cells/µL was associated with the outcomes of attrition (death, lost to follow-up or treatment interruption >180 days), and viraemia >1000 copies/mL, by twelve months using Cox proportional hazards and Poisson regression models. Results and discussion: Among 4952 patients initiating ART, the median age was 32.4 years (interquartile range (IQR) 27.2 to 39.7), 58.9% were women and 30.3% had an initiation CD4 count >500 cells/µL. After twelve months, 3382 (68.3%) were retained in care, 303 (6.1%) had transferred to another clinic, 1010 (20.4%) were lost to follow-up, 232 (4.7%) had a treatment interruption >180 days and 25 (0.5%) were known to have died. Overall, 1267 experienced attrition at a median time of 91 days (IQR 23 to 213), with 302 of these (23.8%) experiencing attrition immediately after their ART initiation visit. Among those in care at twelve months with viral load results, 4.6% had viraemia. In multivariable analysis, the hazard of attrition was similar between patients newly eligible for ART with CD4 counts >500 cells/µL compared to those with CD4 ≤500 cells/µL (adjusted hazard ratio 1.03, 95% confidence interval (CI) 0.90 to 1.17). The risk of viraemia was lower among patients with CD4 counts >500 cells/µL compared to those with CD4 ≤500 cells/µL (adjusted risk ratio 0.58, 95% CI 0.37 to 0.92). Conclusions: After implementation of Treat All in South African public clinics, we found that patients newly eligible for ART with initiation CD4 counts >500 cells/µL had comparable or better outcomes compared to those with lower CD4 counts. These finding support ongoing implementation of Treat All in our setting.

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“…Compared to other implementation studies conducted to date comparing outcomes before and after "Treat All" [6][7][8][9][10][11][12][13], our study sample size was large. The pilot districts were distributed across all the regions of the country.…”

Section: Strength and Limitationsmentioning

confidence: 99%

“…Multiple studies have assessed the realworld effects of "Treat All" on ART initiation, linkage, virologic suppression, and retention. However, these studies have reported inconsistent results [6][7][8][9][10][11][12][13]. None of these previous studies has assessed if predictors for attrition changed since the transition to "Treat All".…”

Section: Introductionmentioning

confidence: 99%

Patient-mix, programmatic characteristics, retention and predictors of attrition among patients starting antiretroviral therapy (ART) before and after the implementation of HIV “Treat All” in Zimbabwe

et al. 2020

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Background Since the scale-up of the HIV "Treat All" recommendation, evidence on its real-world effect on predictors of attrition (either death or lost to follow-up) is lacking. We conducted a retrospective study using Zimbabwe ART program data to assess the association between "Treat All" and, patient-mix, programmatic characteristics, retention and predictors of attrition. Methods We used patient-level data from the electronic patient monitoring system (ePMS) from the nine districts, which piloted the "Treat All" recommendation. We compared patient-mix, programme characteristics, retention and predictors of attrition (lost to follow-up, death or stopping ART) in two cohorts; before (April/May 2016) and after (January/February 2017) "Treat All". Retention was estimated using survival analysis. Predictors of attrition were determined using a multivariable Cox regression model. Interactions were used to assess the change in predictors of attrition before and after "Treat All". Results We analysed 3787 patients, 1738 (45.9%) and 2049 (54.1%) started ART before and after "Treat All", respectively. The proportion of men was higher after "Treat All" (39.4.% vs 36.2%, p = 0.044). Same-day ART initiation was more frequent after "Treat All" (43.2% vs 16.4%; p<0.001) than before. Retention on ART was higher before "Treat All" (p<0.001).

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Early outcomes after implementation of treat all in Rwanda: an interrupted time series study

Cited by 22 publications

References 32 publications

HIV programmatic outcomes following implementation of the ‘Treat‐All’ policy in a public sector setting in Eswatini: a prospective cohort study

HIV programmatic outcomes following implementation of the ‘Treat‐All’ policy in a public sector setting in Eswatini: a prospective cohort study

HIV treatment outcomes among people with initiation CD4 counts >500 cells/µL after implementation of Treat All in South African public clinics: a retrospective cohort study

Patient-mix, programmatic characteristics, retention and predictors of attrition among patients starting antiretroviral therapy (ART) before and after the implementation of HIV “Treat All” in Zimbabwe

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