HIV Disease Progression Among Antiretroviral Therapy Patients in Zimbabwe: A Multistate Markov Model

HIV-1 Disease Progression and Drug Resistance Mutations among Children on First-Line Antiretroviral Therapy in Ethiopia

Background: High rates of disease progression and HIV drug resistance (HIVDR) among adults taking highly active antiretroviral treatment (HAART) in Sub-Saharan Africa were previously documented. However, children were generally not considered despite their greater risk. Hence, this study was aimed to evaluate HIV-1 disease progression and drug resistance mutation among children on first-line antiretroviral therapy in Ethiopia. Method: A longitudinal study was conducted among 551 HIV-positive children (<15 years old) recruited between 2017 and 2019 at 40 antiretroviral treatment delivery sites in Ethiopia. Disease progression was retrospectively measured over a 12-year (2007-2019) follow-up as the progress towards immunosuppression. Two consecutive viral load (VL) tests were conducted in 6-month intervals to assess virologic failure (VF). For children with VF, HIV-1 genotyping and sequencing was performed for the pol gene region using in-house assay validated at the Chinese Center for Disease Control and Prevention, and the Stanford HIVDB v9.0 algorithm was used for identification of drug resistance mutations. The Kaplan-Meier analysis and Cox proportional hazards regression model were used to estimate the rate and predictors of disease progression, respectively. Results: The disease progression rate was 6.3 per 100 person-years-observation (95% CI = 4.21-8.53). Overall immunosuppression (CD4 count < 200 cells/mm3) during the 12-year follow-up was 11.3% (95% CI = 7.5-15.1). Immunosuppression was significantly increased as of the mean duration of 10.5 (95% CI = 10.1-10.8) years (38.2%) to 67.8% at 12 years (p < 0.001). Overall, 14.5% had resistance to at least one drug, and 6.2% had multi-drug resistance. A resistance of 67.8% was observed among children with VF. Resistance to non-nucleotide reverse transcriptase inhibitors (NNRTI) and nucleotide reverse transcriptase inhibitors (NRTI) drugs were 11.4% and 10.1%, respectively. Mutations responsible for NRTI resistance were M184V (30.1%), K65R (12.1%), and D67N (5.6%). Moreover, NNRTI-associated mutations were K103N (14.8%), Y181C (11.8%), and G190A (7.7%). Children who had a history of opportunistic infection [AHR (95% CI) = 3.4 (1.8-6.2)], vitamin D < 20 ng/mL [AHR (95% CI) = 4.5 (2.1-9.9)], drug resistance [AHR (95% CI) = 2.2 (1.4-3.6)], and VF [AHR (95% CI) = 2.82 (1.21, 3.53)] had a higher hazard of disease progression; whereas, being orphan [AOR (95% CI) = 1.8 (1.2-3.1)], history of drug substitution [(AOR (95% CI) = 4.8 (2.1-6.5), hemoglobin < 12 mg/dL [AOR (95% CI) = 1.2 (1.1-2.1)] had higher odds of developing drug resistance. Conclusions: Immunosuppression was increasing over time and drug resistance was also substantially high. Enhancing routine monitoring of viral load and HIVDR and providing a vitamin-D supplement during clinical management could help improve the immunologic outcome. Limiting HAART substitution is also crucial for children taking HAART in Ethiopia.

Examining annual transitions in healthcare spending among U.S. medicare beneficiaries using multistate Markov models: Analysis of medicare current beneficiary survey data, 2003-2019

Many studies have examined factors associated with individuals of high or low healthcare spending in a given year. However, few have studied how healthcare spending changes over multiple years and which factors are associated with the changes. In this study, we examined the dynamic patterns of healthcare spending over a three-year period, among a nationally representative cohort of Medicare beneficiaries in the U.S. and identified factors associated with these patterns. We extracted data for 30,729 participants from the national Medicare Current Beneficiary Survey (MCBS), for the period 2003-2019. Using multistate Markov (MSM) models, we estimated the probabilities of year-to-year transitions in healthcare spending categorized as three states (low (L), medium (M) and high (H)), or to the terminal state, death. The participants, 13,554 (44.1%), 13,715 (44.6%) and 3,460 (11.3%) were in the low, medium and high spending states at baseline, respectively. The majority of participants remained in the same spending category from one year to the next (L-to-L: 76.8%; M-to-M: 71.7%; H-to-H: 56.6 %). Transitions from the low to high spending state were significantly associated with older age (75-84, ≥85 years), residing in a long-term care facility, greater assistance with activities of daily living, enrollment in fee-for-service Medicare, not receiving a flu shot, and presence of specific medical conditions, including cancer, dementia, and heart disease. Using data from a large population-based longitudinal survey, we have demonstrated that MSM modelling is a flexible framework and useful tool for examining changes in healthcare spending over time.

Loss to Follow-Up Risk among HIV Patients on ART in Zimbabwe, 2009-2016: Hierarchical Bayesian Spatio-Temporal Modeling

Loss to follow-up (LTFU) is a risk factor for poor outcomes in HIV patients. The spatio-temporal risk of LTFU is useful to identify hotspots and guide policy. Secondary data on adult HIV patients attending a clinic in provinces of Zimbabwe between 2009 and 2016 were used to estimate the LTFU risk in each of the 10 provinces. A hierarchical Bayesian spatio-temporal Poisson regression model was fitted using the Integrated Nested Laplace Approximation (INLA) package with LTFU as counts adjusting for age, gender, WHO clinical stage, tuberculosis coinfection and duration on ART. The structured random effects were modelled using the conditional autoregression technique and the temporal random effects were modelled using first-order random walk Gaussian priors. The overall rate of LTFU was 22.7% (95%CI: 22.6/22.8) with Harare (50.28%) and Bulawayo (31.11%) having the highest rates. A one-year increase in the average number of years on ART reduced the risk of LTFU by 35% (relative risk (RR) = 0.651; 95%CI: 0.592-0.712). In general, the provinces with the highest exceedance LTFU risk were Matabeleland South and Matabeleland North. LTFU is one of the drawbacks of HIV prevention. Interventions targeting high-risk regions in the southern and northern regions of Zimbabwe are a priority. Community-based interventions and programmes which mitigate LTFU risk remain essential in the global HIV prevention campaign.

Markov modelling of viral load adjusting for CD4 orthogonal variable and multivariate conditional autoregressive mapping of the HIV immunological outcomes among ART patients in Zimbabwe

BACKGROUND

This study aimed to jointly model HIV disease progression patterns based on viral load (VL) among adult ART patients adjusting for the time-varying "incremental transients states" variable, and the CD4 cell counts orthogonal variable in a single 5-stage time-homogenous multistate Markov model. We further jointly mapped the relative risks of HIV disease progression outcomes (detectable VL (VL ≥ 50copies/uL) and immune deterioration (CD4 < 350cells/uL) at the last observed visit) conditional not to have died or become loss to follow-up (LTFU).

METHODS

Secondary data analysis of individual-level patients on ART was performed. Adjusted transition intensities, hazard ratios (HR) and regression coefficients were estimated from the joint multistate model of VL and CD4 cell counts. The mortality and LTFU transition rates defined the extent of patients' retention in care. Joint mapping of HIV disease progression outcomes after ART initiation was done using the Bayesian intrinsic Multivariate Conditional Autoregressive prior model.

RESULTS

The viral rebound from the undetectable state was 1.78times more likely compared to viral suppression among patients with VL ranging from 50-1000copies/uL. Patients with CD4 cell counts lower than expected had a higher risk of viral increase above 1000copies/uL and death if their VL was above 1000copies/uL (state 2 to 3 (λ₂₃): HR = 1.83 and (λ₃₄): HR = 1.42 respectively). Regarding the time-varying effects of CD4 cell counts on the VL transition rates, as the VL increased, (λ₁₂ and λ₂₃) the transition rates increased with a decrease in the CD4 cell counts over time. Regardless of the individual's VL, the transition rates to become LTFU decreased with a decrease in CD4 cell counts. We observed a strong shared geographical pattern of 66% spatial correlation between the relative risks of detectable VL and immune deterioration after ART initiation, mainly in Matabeleland North.

CONCLUSION

With high rates of viral rebound, interventions which encourage ART adherence and continual educational support on the barriers to ART uptake are crucial to achieve and sustain viral suppression to undetectable levels. Area-specific interventions which focus on early ART screening through self-testing, behavioural change campaigns and social support strategies should be strengthened in heavily burdened regions to sustain the undetectable VL. Sustaining undetectable VL lowers HIV transmission in the general population and this is a step towards achieving zero HIV incidences by 2030.

A review of multistate modelling approaches in monitoring disease progression: Bayesian estimation using the Kolmogorov-Chapman forward equations

There are numerous fields of science in which multistate models are used, including biomedical research and health economics. In biomedical studies, these stochastic continuous-time models are used to describe the time-to-event life history of an individual through a flexible framework for longitudinal data. The multistate framework can describe more than one possible time-to-event outcome for a single individual. The standard estimation quantities in multistate models are transition probabilities and transition rates which can be mapped through the Kolmogorov-Chapman forward equations from the Bayesian estimation perspective. Most multistate models assume the Markov property and time homogeneity; however, if these assumptions are violated, an extension to non-Markovian and time-varying transition rates is possible. This manuscript extends reviews in various types of multistate models, assumptions, methods of estimation and data features compatible with fitting multistate models. We highlight the contrast between the frequentist (maximum likelihood estimation) and the Bayesian estimation approaches in the multistate modeling framework and point out where the latter is advantageous. A partially observed and aggregated dataset from the Zimbabwe national ART program was used to illustrate the use of Kolmogorov-Chapman forward equations. The transition rates from a three-stage reversible multistate model based on viral load measurements in WinBUGS were reported.

Translation and cross-cultural adaptation of WHOQOL-HIV Bref among people living with HIV/AIDS in Pakistan

BACKGROUND

Reliable Health-Related Quality of Life (HRQoL) assessment will be useful in identifying health issues and in identifying health care actions. Due to the lack of a psychometrically valid tool in Urdu, we aim to translate and examine the psychometric and cross-cultural adaptation of WHOQOL HIV Bref among people living with HIV/AIDS (PLWHA) in Pakistan.

METHODS

The standard forward-backwards translation technique was used to convert English version of the WHOQOL HIV Bref into Urdu. After cognitive debriefing, final Urdu version of instrument was developed. Based on the principle of at least 5 subjects for each item, a sample of 182 patients was used using a universal random sampling technique from the Pakistan Institute of Medical Sciences, Islamabad. The Cronbach's alpha and intra-class correlation coefficients (ICC) were estimated to assess internal validity and reliability of the translated version. Exploratory factor analysis was carried out to determine the factor structure and independent associations between the instrument domains and CD-4T-cell count were assessed using multivariable linear regression RESULTS: High Cronbach alpha 0.93 was found for all WHOQOL HIV Bref facets. The test-retest reliability demonstrated a statistically significant ICC ranged from 0.88 to 0.98 (p < 0.001). In known group validity, lower CD-4 lymphocytes count was significantly related to poor scores for all six domains (p < 0.001). Similarly, symptomatic subjects had significantly lower scores compared to asymptomatic subjects on the physical, psychological, social relationship and independence domains (p < 0.05). Statistically significant positive correlation of all six domains of instrument with CD4 cells count (p < 0.001), exhibiting patients with higher CD-4 cells will have higher mean scores of all domains. Factor analysis revealed 5 domains, including physical health, psychological health, social relationship, environmental, and spiritual health. Multivariable linear regression analysis reported; only physical, psychological health and environment health domains were found significantly associated with higher CD-4 lymphocytes count (Beta = 0.121, p < 0.001, Beta = 0.103, p = 0.002, and Beta = 0.032, p = 0.032).

CONCLUSION

Findings suggested that the Urdu version of WHOQOL HIV Bref is a psychometrically valid and culturally well-adapted HRQoL measurement tool for PLWHA in Pakistan.

Competing risk of mortality on loss to follow-up outcome among patients with HIV on ART: a retrospective cohort study from the Zimbabwe national ART programme

OBJECTIVE

To determine the loss to follow-up (LTFU) rates at different healthcare levels after antiretroviral therapy (ART) services decentralisation among ART patients who initiated ART between 2004 and 2017 using the competing risk model in addition to the Kaplan-Meier and Cox regressions analysis.

DESIGN

A retrospective cohort study.

SETTING

The study was done in Zimbabwe using a nationwide routinely collected HIV patient-level data from various health levels of care facilities compiled through the electronic patient management system (ePMS).

PARTICIPANTS

We analysed 390 771 participants aged 15 years and above from 538 health facilities.

OUTCOMES

The primary endpoint was LTFU defined as a failure of a patient to report for drug refill for at least 90 days from last appointment date or if the patient missed the next scheduled visit date and never showed up again. Mortality was considered a secondary outcome if a patient was reported to have died.

RESULTS

The total exposure time contributed was 1 544 468 person-years. LTFU rate was 5.75 (95% CI 5.71 to 5.78) per 100 person-years. Adjustment for the competing event independently increased LTFU rate ratio in provincial and referral (adjusted sub-HRs (AsHR) 1.22; 95% CI 1.18 to 1.26) and district and mission (AsHR 1.47; 95% CI 1.45 to 1.50) hospitals (reference: primary healthcare); in urban sites (AsHR 1.61; 95% CI 1.59 to 1.63) (reference: rural); and among adolescence and young adults (15-24 years) group (AsHR 1.19; 95% CI 1.16 to 1.21) (reference: 35-44 years). We also detected overwhelming association between LTFU and tuberculosis-infected patients (AsHR 1.53; 95% CI 1.45 to 1.62) (reference: no tuberculosis).

CONCLUSIONS

We have observed considerable findings that 'leakages' (LTFU) within the ART treatment cascade persist even after the decentralisation of health services. Risk factors for LTFU reflect those found in sub-Saharan African studies. Interventions that retain patients in care by minimising any 'leakages' along the treatment cascade are essential in attaining the 90-90-90 UNAIDS fast-track targets.