Diagnostic accuracy of a point-of-care urine tenofovir assay, and associations with HIV viraemia and drug resistance among people receiving dolutegravir and efavirenz-based antiretroviral therapy

INTRODUCTION

Novel point-of-care assays which measure urine tenofovir (TFV) concentrations may have a role in improving adherence monitoring for people living with HIV (PLHIV) receiving antiretroviral therapy (ART). However, further studies of their diagnostic accuracy, and whether results are associated with viraemia and drug resistance, are needed to guide their use, particularly in the context of the global dolutegravir rollout.

METHODS

We conducted a cross-sectional evaluation among PLHIV receiving first-line ART containing tenofovir disoproxil fumarate at enrolment into a randomized trial in two South African public sector clinics. We calculated the diagnostic accuracy of the Abbott point-of-care immunoassay to detect urine TFV compared to liquid chromatography-tandem mass spectrometry (LC-MS/MS). We evaluated the association between point-of-care urine TFV results and self-reported adherence, viraemia ≥1000 copies/ml and HIV drug resistance, among people receiving either efavirenz or dolutegravir-based ART.

RESULTS

Between August 2020 and March 2022, we enrolled 124 participants. The median age was 39 (IQR 34-45) years, 55% were women, 74 (59.7%) were receiving efavirenz and 50 (40.3%) dolutegravir. The sensitivity and specificity of the immunoassay to detect urine TFV ≥1500 ng/ml compared to LC-MS/MS were 96.1% (95% CI 90.0-98.8) and 95.2% (75.3-100.0), respectively. Urine TFV results were associated with short (p<0.001) and medium-term (p = 0.036) self-reported adherence. Overall, 44/124 (35.5%) had viraemia, which was associated with undetectable TFV in those receiving efavirenz (OR 6.01, 1.27-39.0, p = 0.014) and dolutegravir (OR 25.7, 4.20-294.8, p<0.001). However, in those with viraemia while receiving efavirenz, 8/27 (29.6%) had undetectable urine TFV, compared to 11/17 (64.7%) of those receiving dolutegravir. Drug resistance was detected in 23/27 (85.2%) of those receiving efavirenz and only 1/16 (6.3%) of those receiving dolutegravir. There was no association between urine TFV results and drug resistance.

CONCLUSIONS

Among PLHIV receiving ART, a rapid urine TFV immunoassay can be used to accurately monitor urine TFV levels compared to the gold standard of LC-MS/MS. Undetectable point-of-care urine TFV results were associated with viraemia, particularly among people receiving dolutegravir.

TRIAL REGISTRATION

Pan-African Clinical Trials Registry: PACTR202001785886049.

Nonparametric estimation of Spearman's rank correlation with bivariate survival data

We study rank-based approaches to estimate the correlation between two right-censored variables. With end-of-study censoring, it is often impossible to nonparametrically identify the complete bivariate survival distribution, and therefore it is impossible to nonparametrically compute Spearman's rank correlation. As a solution, we propose two measures that can be nonparametrically estimated. The first measure is Spearman's correlation in a restricted region. The second measure is Spearman's correlation for an altered but estimable joint distribution. We describe population parameters for these measures and illustrate how they are similar to and different from the overall Spearman's correlation. We propose consistent estimators of these measures and study their performance through simulations. We illustrate our methods with a study assessing the correlation between the time to viral failure and the time to regimen change among persons living with HIV in Latin America who start antiretroviral therapy.

Tenofovir diphosphate levels in dried blood spots are associated with virologic failure and resistance to first-line therapy in South Africa: a case-control cohort study

INTRODUCTION

Tenofovir diphosphate (TFV-DP) in dried blood spots (DBS), a measure of cumulative antiretroviral therapy (ART) adherence, is associated with viral suppression and predicts future viremia in persons with HIV (PWH). However, its utility to identify those at risk for virologic failure (VF) and drug resistance is unknown. To address this, we aimed to establish the association between this adherence biomarker and VF with drug resistance in a cohort of PWH initiating first-line ART in KwaZulu-Natal, South Africa.

METHODS

PWH initiating TFV disoproxil fumarate (TDF)-based ART within a parent prospective cohort were evaluated. Using a nested design, DBS for TFV-DP were collected from cases who developed VF (HIV-1 RNA ≥1000 copies/ml) after ≥5 months on ART versus controls, matched 1:2 by site, age, gender, race and ART duration. Cases were categorized as having VF with or without resistance using genotyping. One-way analysis of variance (ANOVA) was used to compare TFV-DP for controls, cases with VF and resistance, and cases with VF without resistance. Data are presented as mean (standard deviation, SD) or geometric mean [95% confidence interval, 95% CI].

RESULTS AND DISCUSSION

One thousand participants were enrolled in the parent study between 2014 and 2016, of which 288 (29%) had DBS available. Of these, 94 (33%) were cases and 194 (67%) were controls; 59% were women. Mean age of our population was 33 (SD 8) years. Genotyping was available in 50 (53%) of the 94 cases. Geometric mean TFV-DP in DBS from controls was 708 [95% CI; 647-773] fmol/punch, which was higher compared to participants having VF with resistance (n = 36), 386 [95% CI; 241-617] fmol/punch and VF without resistance (n = 14), 61 [95% CI; 22-164] fmol/punch; p<0.001. Genotype could not be obtained in 44 (47%) cases.

CONCLUSIONS

TFV-DP in DBS showed a stepwise association with VF and drug resistance in South African PWH. Participants having VF with resistance had mid-range concentrations of TFV-DP, which were higher than those for PWH without resistance. Future research on the clinical utility of TFV-DP concentrations in DBS to predict and prevent the development of VF and drug resistance is needed.

Eight-day Inpatient Directly Observed Therapy for Antiretroviral Therapy (ART) Failure: A Tool For Preventing Unnecessary ART Changes and Optimizing Adherence Support

Eight-day inpatient directly observed therapy confirmed nonadherence as the major cause of virologic failure for 9 (45%) of 20 highly treatment-experienced persons with human immunodeficiency virus, extensive antiretroviral drug resistance, and high self-reported adherence rates, preventing unnecessary regimen changes.

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

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.

Comparison of machine learning methods for predicting viral failure: a case study using electronic health record data

Background

Human immunodeficiency virus (HIV) viral failure occurs when antiretroviral therapy fails to suppress and sustain a person's viral load count below 1,000 copies of viral ribonucleic acid per milliliter. For those newly diagnosed with HIV and living in a setting where healthcare resources are limited, such as a low- and middle-income country, the World Health Organization recommends viral load monitoring six months after initiation of antiretroviral treatment and yearly thereafter. Deviations from this schedule are made in cases where viral failure occurs or at the discretion of the clinician. Failure to detect viral failure in a timely fashion can lead to delayed administration of essential interventions. Clinical prediction models based on information available in the patient medical record are increasingly being developed and deployed for decision support in clinical medicine and public health. This raises the possibility that prediction models can be used to detect potential for viral failure in advance of viral measurements, particularly when those measurements occur infrequently.

Objective

Our goal is to use electronic health record data from a large HIV care program in Kenya to characterize and compare the predictive accuracy of several statistical machine learning methods for predicting viral failure at the first and second measurements following initiation of antiretroviral therapy. Predictive accuracy is measured in terms of sensitivity, specificity and area under the receiver-operator characteristic curve.

Methods

We trained and cross-validated 10 statistical machine learning models and algorithms on data from over 10,000 patients in the Academic Model Providing Access to Healthcare care program in western Kenya. These included parametric, non-parametric, ensemble, and Bayesian methods. The input variables included 50 items from the clinical record, hand picked in consultation with clinician experts. Predictive accuracy measures were calculated using 10-fold cross validation.

Results

Viral load failure rate is about 20% in this patient cohort at both the first and second measurements. Ensemble techniques generally outperformed other methods. For predicting viral failure at the first follow up measure, specificity was over 90% for these methods, but sensitivity was typically in the 50-60% range. Predictive accuracy was greater for the second follow up measure, with sensitivities over 80%. Super Learner, gradient boosting and Bayesian additive regression trees consistently outperformed other methods. For a viral failure rate of 20%, the positive predictive value for the top-performing methods is between 75 and 85%, while the negative predictive value is over 95%.

Conclusion

Evidence from this study suggests that machine learning techniques have potential to identify patients at risk for viral failure prior to their scheduled measurements. Ultimately, prognostic virologic assessment can help guide the administration of earlier targeted intervention such as enhanced drug resistance monitoring, rigorous adherence counseling, or appropriate next-line therapy switching. External validation studies should be used to confirm the results found here.

Associations between baseline characteristics, CD4 cell count response and virological failure on first-line efavirenz + tenofovir + emtricitabine for HIV

OBJECTIVES

The aim of this study was to investigate associations between baseline characteristics and CD4 cell count response on first-line antiretroviral therapy and risk of virological failure (VF) with or without drug resistance.

METHODS

We conducted an analysis of UK Collaborative HIV Cohort data linked to the UK HIV Drug Resistance Database. Inclusion criteria were viral sequence showing no resistance prior to initiation of first-line efavirenz + tenofovir disoproxil fumarate + emtricitabine and virological suppression within 6 months. Outcomes of VF (≥200 copies/mL) with or without drug resistance were assessed using a competing risks approach fitted jointly with a model for CD4 cell count recovery. Hazard ratios for each VF outcome were estimated for baseline CD4 cell count and viral load and characteristics of CD4 cell count response using latent variables on a standard normal scale.

RESULTS

A total of 3640 people were included with 338 VF events; corresponding viral sequences were available in 134 with ≥1 resistance mutation in 36. VF with resistance was associated with lower baseline CD4 (0.30, 0.09-0.62), lower CD4 recovery (0.04, 0.00-0.17) and higher CD4 variability (4.40, 1.22-12.68). A different pattern of associations was observed for VF without resistance, but the strength of these results was less consistent across sensitivity analyses. Cumulative incidence of VF with resistance was estimated to be <2% at 3 years for baseline CD4 ≥350 cells/μL.

CONCLUSION

Lower baseline CD4 cell count and suboptimal CD4 recovery are associated with VF with drug resistance. People with low CD4 cell count before ART or with suboptimal CD4 recovery on treatment should be a priority for regimens with high genetic barrier to resistance.

Identifying Risk of Viral Failure in Treated HIV-Infected Patients Using Different Measures of Adherence: The Antiretroviral Therapy Cohort Collaboration

Adherence to antiretroviral therapy (ART) is critical for successful treatment of Human Immunodeficiency Virus (HIV), but comparisons across settings are difficult because adherence is measured in different ways. We examined utility of different adherence measures for identification of patients at risk of viral failure (VF). Eight cohorts in the ART Cohort Collaboration contributed data from pharmacy refills or self-report questionnaires collected between 1996 and 2013 (N = 11689). For pharmacy data (N = 7156), we examined associations of percentage adherence during the 1st year of ART with VF (>500 copies/mL) at 1 year. For self-report data (N = 4533), we examined 28-day adherence with VF based on closest viral load measure within 6 months after questionnaire date. Since adherence differed markedly by measurement type, we defined different cut-off points for pharmacy (lower <45%, medium 45–99%, higher 100%) and self-report (lower ≤95%, medium 96–99%, higher 100%) data. Adjusted odds ratios (ORs) for VF in lower and medium, compared to higher adherence groups, were 23.04 (95% CI: 18.44–28.78) and 3.84 (3.36–4.39) for pharmacy data. For self-report data, they were 3.19 (2.31–4.40) and 1.08 (0.80–1.46). Both types of measure were strongly associated with VF. Although adherence measurements over longer time-frames are preferable for prediction, they are less useful for intervention.

Long-term effectiveness of initiating non-nucleoside reverse transcriptase inhibitor- versus ritonavir-boosted protease inhibitor-based antiretroviral therapy: implications for first-line therapy choice in resource-limited settings

Introduction

In many resource-limited settings, combination antiretroviral therapy (cART) failure is diagnosed clinically or immunologically. As such, there is a high likelihood that patients may stay on a virologically failing regimen for a substantial period of time. Here, we compared the long-term impact of initiating non-nucleoside reverse transcriptase inhibitor (NNRTI)- versus boosted protease inhibitor (bPI)-based cART in British Columbia (BC), Canada.

Methods

We followed prospectively 3925 ART-naïve patients who started NNRTIs (N=1963, 50%) or bPIs (N=1962; 50%) from 1 January 2000 until 30 June 2013 in BC. At six months, we assessed whether patients virologically failed therapy (a plasma viral load (pVL) >50 copies/mL), and we stratified them based on the pVL at the time of failure ≤500 versus >500 copies/mL. We then followed these patients for another six months and calculated their probability of achieving subsequent viral suppression (pVL <50 copies/mL twice consecutively) and of developing drug resistance. These probabilities were adjusted for fixed and time-varying factors, including cART adherence.

Results

At six months, virologic failure rates were 9.5 and 14.3 cases per 100 person-months for NNRTI and bPI initiators, respectively. NNRTI initiators who failed with a pVL ≤500 copies/mL had a 16% higher probability of achieving subsequent suppression at 12 months than bPI initiators (0.81 (25th–75th percentile 0.75–0.83) vs. 0.72 (0.61–0.75)). However, if failing NNRTI initiators had a pVL >500 copies/mL, they had a 20% lower probability of suppressing at 12 months than pVL-matched bPI initiators (0.37 (0.29–0.45) vs. 0.46 (0.38–0.54)). In terms of evolving HIV drug resistance, those who failed on NNRTI performed worse than bPI in all scenarios, especially if they failed with a viral load >500 copies/mL.

Conclusions

Our results show that patients who virologically failed at six months on NNRTI and continued on the same regimen had a lower probability of subsequently achieving viral suppression and a higher chance of evolving HIV drug resistance. These results suggest that improving access to regular virologic monitoring is critically important, especially if NNRTI-based cART is to remain a preferred choice for first-line therapy in resource-limited settings.

Drug resistance mutations after the first 12 months on antiretroviral therapy and determinants of virological failure in Rwanda

OBJECTIVE

To evaluate HIV drug resistance (HIVDR) and determinants of virological failure in a large cohort of patients receiving first-line tenofovir-based antiretroviral therapy (ART) regimens.

METHODS

A nationwide retrospective cohort from 42 health facilities was assessed for virological failure and development of HIVDR mutations. Data were collected at ART initiation and at 12 months of ART on patients with available HIV-1 viral load (VL) and ART adherence measurements. HIV resistance genotyping was performed on patients with VL ≥1000 copies/ml. Multiple logistic regression was used to determine factors associated with treatment failure.

RESULTS

Of 828 patients, 66% were women, and the median age was 37 years. Of the 597 patients from whom blood samples were collected, 86.9% were virologically suppressed, while 11.9% were not. Virological failure was strongly associated with age <25 years (adjusted odds ratio [aOR]: 6.4; 95% confidence interval [CI]: 3.2-12.9), low adherence (aOR: 2.87; 95% CI: 1.5-5.0) and baseline CD4 counts <200 cells/μl (aOR 3.4; 95% CI: 1.9-6.2). Overall, 9.1% of all patients on ART had drug resistance mutations after 1 year of ART; 27% of the patients who failed treatment had no evidence of HIVDR mutations. HIVDR mutations were not observed in patients on the recommended second-line ART regimen in Rwanda.

CONCLUSIONS

The last step of the UNAIDS 90-90-90 target appears within grasp, with some viral failures still due to non-adherence. Nonetheless, youth and late initiators are at higher risk of virological failure. Youth-focused programmes could help prevent further drug HIVDR development.

Viremia and drug resistance among HIV-1 patients on antiretroviral treatment: a cross-sectional study in Soweto, South Africa

BACKGROUND

We assessed risk factors for viremia and drug resistance among long-term recipients of antiretroviral therapy (ART) in South Africa.

METHODS

In 2008, we conducted a cross-sectional study among patients receiving ART for 12 months or more. Genotypic resistance testing was performed on individuals with a viral load higher than 400 RNA copies/ml. Multiple logistic regression analysis was used to assess associations.

RESULTS

Of 998 participants, 75% were women with a median age of 41 years. Most (64%) had been on treatment for more than 3 years. The prevalence of viremia was 14% (n = 139): 12% (102/883) on first-line [i.e. nonnucleoside reverse-transcriptase inhibitor (NNRTI)-based regimen] and 33% (37/115) on second-line (i.e. protease inhibitor (PI)-based regimen) ART. Of viremic patients, 78% had drug resistance mutations. For NRTIs, NNRTIs and PIs, the prevalence of mutations was 64, 81 and 2%, respectively, among first-line failures and 29, 54 and 6%, respectively, among second-line failures. M184V/I, K103N and V106A/M were the most common mutations. Significant risk factors associated with viremia on first-line regimen included concurrent tuberculosis treatment [odds ratio (OR) 6.4, 95% confidence interval (CI) 2.2-18.8, P < 0.01] and a recent history of poor adherence (OR 2.7, 1.3-5.6, P = 0.01). Among second-line failures, attending a public clinic (OR 4.6, 95% CI 1.8-11.3, P < 0.01) and not having a refrigerator at home (OR 6.7, 95% CI 1.2-37.5, P = 0.03) were risk factors for virological failure.

CONCLUSION

Risk factors for viral failure were line regimen dependent. Second-line ART recipients had a higher rate of viremia, albeit with infrequent PI drug resistance mutations. Measures to maintain effective virologic suppression should include increased adherence counseling, attention to concomitant tuberculosis treatment and heat-stable formulations of second-line ART regimens.