Correcting mortality for loss to follow-up: a nomogram applied to antiretroviral treatment programmes in sub-Saharan Africa

Background The World Health Organization estimates that in sub-Saharan Africa about 4 million HIV-infected patients had started antiretroviral therapy (ART) by the end of 2008. Loss of patients to follow-up and care is an important problem for treatment programmes in this region. As mortality is high in these patients compared to patients remaining in care, ART programmes with high rates of loss to follow-up may substantially underestimate mortality of all patients starting ART. Methods and Findings We developed a nomogram to correct mortality estimates for loss to follow-up, based on the fact that mortality of all patients starting ART in a treatment programme is a weighted average of mortality among patients lost to follow-up and patients remaining in care. The nomogram gives a correction factor based on the percentage of patients lost to follow-up at a given point in time, and the estimated ratio of mortality between patients lost and not lost to follow-up. The mortality observed among patients retained in care is then multiplied by the correction factor to obtain an estimate of programme-level mortality that takes all deaths into account. A web calculator directly calculates the corrected, programme-level mortality with 95% confidence intervals (CIs). We applied the method to 11 ART programmes in sub-Saharan Africa. Patients retained in care had a mortality at 1 year of 1.4% to 12.0%; loss to follow-up ranged from 2.8% to 28.7%; and the correction factor from 1.2 to 8.0. The absolute difference between uncorrected and corrected mortality at 1 year ranged from 1.6% to 9.8%, and was above 5% in four programmes. The largest difference in mortality was in a programme with 28.7% of patients lost to follow-up at 1 year. Conclusions The amount of bias in mortality estimates can be large in ART programmes with substantial loss to follow-up. Programmes should routinely report mortality among patients retained in care and the proportion of patients lost. A simple nomogram can then be used to estimate mortality among all patients who started ART, for a range of plausible mortality rates among patients lost to follow-up.

Polycyclic aromatic compounds (PAHs and oxygenated PAHs) and trace metals in fish species from Ghana (West Africa): Bioaccumulation and health risk assessment

We report the concentrations of 28 PAHs, 15 oxygenated PAHs (OPAHs) and 11 trace metals/metalloids (As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Se, and Zn) in muscle and gut + gill tissues of demersal fishes (Drapane africana, Cynoglossus senegalensis and Pomadasys peroteti) from three locations along the coast of the Gulf of Guinea (Ghana). The concentrations of ∑ 28PAHs in muscle tissues averaged 192 ng g− 1 dw (range: 71–481 ng g− 1 dw) and were not statistically different between locations. The concentrations of ∑ 28 PAHs were higher in guts + gills than in muscles. The PAH composition pattern was dominated by low molecular weight compounds (naphthalene, alkyl-naphthalenes and phenanthrene). All fish tissues had benzo[a]pyrene concentrations lower than the EU limit for food safety. Excess cancer risk from consumption of some fish was higher than the guideline value of 1 × 10− 6. The concentrations of ∑ 15 OPAHs in fish muscles averaged 422 ng g− 1 dw (range: 28–1715 ng g− 1dw). The ∑ 15 OPAHs/∑ 16 US-EPA PAHs concentration ratio was > 1 in 68% of the fish muscles and 100% of guts + gills. The log-transformed concentrations of PAHs and OPAHs in muscles, guts + gills were significantly (p < 0.05) correlated with their octanol–water partitioning coefficients, strongly suggesting that equilibrium partitioning from water/sediment into fish tissue was the main mechanism of bioaccumulation. The trace metal concentrations in the fish tissues were in the medium range when compared to fish from other parts of the world. The concentrations of some trace metals (Cd, Cu, Fe, Mn, Zn) were higher in guts + gills than in muscle tissues. The target hazard quotients for metals were < 1 and did not indicate a danger to the local population. We conclude that the health risk arising from the consumption of the studied fish (due to their PAHs and trace metals content) is minimal.

Estimating the Reproduction Number of Ebola Virus (EBOV) During the 2014 Outbreak in West Africa

The 2014 Ebola virus (EBOV) outbreak in West Africa is the largest outbreak of the genus Ebolavirus to date. To better understand the spread of infection in the affected countries, it is crucial to know the number of secondary cases generated by an infected index case in the absence and presence of control measures, i.e., the basic and effective reproduction number. In this study, I describe the EBOV epidemic using an SEIR (susceptible-exposed-infectious-recovered) model and fit the model to the most recent reported data of infected cases and deaths in Guinea, Sierra Leone and Liberia. The maximum likelihood estimates of the basic reproduction number are 1.51 (95% confidence interval [CI]: 1.50-1.52) for Guinea, 2.53 (95% CI: 2.41-2.67) for Sierra Leone and 1.59 (95% CI: 1.57-1.60) for Liberia. The model indicates that in Guinea and Sierra Leone the effective reproduction number might have dropped to around unity by the end of May and July 2014, respectively. In Liberia, however, the model estimates no decline in the effective reproduction number by end-August 2014. This suggests that control efforts in Liberia need to be improved substantially in order to stop the current outbreak.

CD41 T cell recovery during suppression of HIV replication: an international comparison of the immunological efficacy of antiretroviral therapy in North America, Asia and Africa.

BACKGROUND Even among HIV-infected patients who fully suppress plasma HIV RNA replication on antiretroviral therapy, genetic (e.g. CCL3L1 copy number), viral (e.g. tropism) and environmental (e.g. chronic exposure to microbial antigens) factors influence CD4 recovery. These factors differ markedly around the world and therefore the expected CD4 recovery during HIV RNA suppression may differ globally. METHODS We evaluated HIV-infected adults from North America, West Africa, East Africa, Southern Africa and Asia starting non-nucleoside reverse transcriptase inhibitorbased regimens containing efavirenz or nevirapine, who achieved at least one HIV RNA level <500/ml in the first year of therapy and observed CD4 changes during HIV RNA suppression. We used a piecewise linear regression to estimate the influence of region of residence on CD4 recovery, adjusting for socio-demographic and clinical characteristics. We observed 28 217 patients from 105 cohorts over 37 825 person-years. RESULTS After adjustment, patients from East Africa showed diminished CD4 recovery as compared with other regions. Three years after antiretroviral therapy initiation, the mean CD4 count for a prototypical patient with a pre-therapy CD4 count of 150/ml was 529/ml [95% confidence interval (CI): 517–541] in North America, 494/ml (95% CI: 429–559) in West Africa, 515/ml (95% CI: 508–522) in Southern Africa, 503/ml (95% CI: 478–528) in Asia and 437/ml (95% CI: 425–449) in East Africa. CONCLUSIONS CD4 recovery during HIV RNA suppression is diminished in East Africa as compared with other regions of the world, and observed differences are large enough to potentially influence clinical outcomes. Epidemiological analyses on a global scale can identify macroscopic effects unobservable at the clinical, national or individual regional level.

HIV infection, viral hepatitis and liver fibrosis among prison inmates in West Africa.

BACKGROUND Prisoners represent a vulnerable population for blood-borne and sexually transmitted infections which can potentially lead to liver fibrosis and ultimately cirrhosis. However, little is known about the prevalence of liver fibrosis and associated risk factors among inmates in sub-Saharan Africa. METHODS Screening of liver fibrosis was undertaken in a randomly selected sample of male inmates incarcerated in Lome, Togo and in Dakar, Senegal using transient elastography. A liver stiffness measurement ≥9.5 KPa was retained to define the presence of a severe liver fibrosis. All included inmates were also screened for HIV, Hepatitis B Virus (HBV) and Hepatitis C Virus (HCV) infection. Substances abuse including alcohol, tobacco and cannabis use were assessed during face-to-face interviews. Odds Ratio (OR) estimates were computed with their 95 % Confidence Interval (CI) to identify factors associated with severe liver fibrosis. RESULTS Overall, 680 inmates were included with a median age of 30 years [interquartile range: 24-35]. The prevalence of severe fibrosis was 3.1 % (4.9 % in Lome and 1.2 % in Dakar). Infections with HIV, HBV and HCV were identified in 2.6 %, 12.5 % and 0.5 % of inmates, respectively. Factors associated with a severe liver fibrosis were HIV infection (OR = 7.6; CI 1.8-32.1), HBV infection (OR = 4.8; CI 1.8-12.8), HCV infection (OR = 52.6; CI 4.1-673.8), use of traditional medicines (OR = 3.7; CI 1.4-10.1) and being incarcerated in Lome (OR = 3.3; CI 1.1-9.8) compared to Dakar. CONCLUSIONS HIV infection and viral hepatitis infections were identified as important and independent determinants of severe liver fibrosis. While access to active antiviral therapies against HIV and viral hepatitis expands in Africa, adapted strategies for the monitoring of liver disease need to be explored, especially in vulnerable populations such as inmates.

Adjusting mortality for loss to follow-up: analysis of five ART programmes in sub-Saharan Africa

Evaluation of antiretroviral treatment (ART) programmes in sub-Saharan Africa is difficult because many patients are lost to follow-up. Outcomes in these patients are generally unknown but studies tracing patients have shown mortality to be high. We adjusted programme-level mortality in the first year of antiretroviral treatment (ART) for excess mortality in patients lost to follow-up.

Early mortality and loss to follow-up in HIV-infected children starting antiretroviral therapy in Southern Africa

Many HIV-infected children in Southern Africa have been started on antiretroviral therapy (ART), but loss to follow up (LTFU) can be substantial. We analyzed mortality in children retained in care and in all children starting ART, taking LTFU into account.

Mortality after failure of antiretroviral therapy in sub-Saharan Africa

Objective  To assess the outcome of patients who experienced treatment failure with antiretrovirals in sub-Saharan Africa. Methods  Analysis of 11 antiretroviral therapy (ART) programmes in sub-Saharan Africa. World Health Organization (WHO) criteria were used to define treatment failure. All ART-naive patients aged ≥16 who started with a non-nucleoside reverse transcriptase inhibitor (NNRTI)-based regimen and had at least 6 months of follow-up were eligible. For each patient who switched to a second-line regimen, 10 matched patients who remained on a non-failing first-line regimen were selected. Time was measured from the time of switching, from the corresponding time in matched patients, or from the time of treatment failure in patients who remained on a failing regimen. Mortality was analysed using Kaplan–Meier curves and random-effects Cox models. Results  Of 16 591 adult patients starting ART, 382 patients (2.3%) switched to a second-line regimen. Another 323 patients (1.9%) did not switch despite developing immunological or virological failure. Cumulative mortality at 1 year was 4.2% (95% CI 2.2–7.8%) in patients who switched to a second-line regimen and 11.7% (7.3%–18.5%) in patients who remained on a failing first-line regimen, compared to 2.2% (1.6–3.0%) in patients on a non-failing first-line regimen (P < 0.0001). Differences in mortality were not explained by nadir CD4 cell count, age or differential loss to follow up. Conclusions  Many patients who meet criteria for treatment failure do not switch to a second-line regimen and die. There is an urgent need to clarify the reasons why in sub-Saharan Africa many patients remain on failing first-line ART.

Temporal changes in programme outcomes among adult patients initiating antiretroviral therapy across South Africa, 2002-2007

Little is known about the temporal impact of the rapid scale-up of large antiretroviral therapy (ART) services on programme outcomes. We describe patient outcomes [mortality, loss-to-follow-up (LTFU) and retention] over time in a network of South African ART cohorts.

Prognosis of patients with HIV-1 infection starting antiretroviral therapy in sub-Saharan Africa: a collaborative analysis of scale-up programmes

Background Prognostic models have been developed for patients infected with HIV-1 who start combination antiretroviral therapy (ART) in high-income countries, but not for patients in sub-Saharan Africa. We developed two prognostic models to estimate the probability of death in patients starting ART in sub-Saharan Africa. Methods We analysed data for adult patients who started ART in four scale-up programmes in Côte d'Ivoire, South Africa, and Malawi from 2004 to 2007. Patients lost to follow-up in the first year were excluded. We used Weibull survival models to construct two prognostic models: one with CD4 cell count, clinical stage, bodyweight, age, and sex (CD4 count model); and one that replaced CD4 cell count with total lymphocyte count and severity of anaemia (total lymphocyte and haemoglobin model), because CD4 cell count is not routinely measured in many African ART programmes. Death from all causes in the first year of ART was the primary outcome. Findings 912 (8·2%) of 11 153 patients died in the first year of ART. 822 patients were lost to follow-up and not included in the main analysis; 10 331 patients were analysed. Mortality was strongly associated with high baseline CD4 cell count (≥200 cells per μL vs <25; adjusted hazard ratio 0·21, 95% CI 0·17–0·27), WHO clinical stage (stages III–IV vs I–II; 3·45, 2·43–4·90), bodyweight (≥60 kg vs <45 kg; 0·23, 0·18–0·30), and anaemia status (none vs severe: 0·27, 0·20–0·36). Other independent risk factors for mortality were low total lymphocyte count, advanced age, and male sex. Probability of death at 1 year ranged from 0·9% (95% CI 0·6–1·4) to 52·5% (43·8–61·7) with the CD4 model, and from 0·9% (0·5–1·4) to 59·6% (48·2–71·4) with the total lymphocyte and haemoglobin model. Both models accurately predict early mortality in patients starting ART in sub-Saharan Africa compared with observed data. Interpretation Prognostic models should be used to counsel patients, plan health services, and predict outcomes for patients with HIV-1 infection in sub-Saharan Africa.

Rates and Predictors of Failure of First-line Antiretroviral Therapy and Switch to Second-line ART in South Africa

To measure rates and predictors of virologic failure and switch to second-line antiretroviral therapy (ART) in South Africa.

Viral load monitoring of antiretroviral therapy, cohort viral load and HIV transmission in Southern Africa: A mathematical modelling analysis

In low-income settings, treatment failure is often identified using CD4 cell count monitoring. Consequently, patients remain on a failing regimen, resulting in a higher risk of transmission. We investigated the benefit of routine viral load monitoring for reducing HIV transmission.

Accuracy of immunological criteria for identifying virological failure in children on antiretroviral therapy - The IeDEA Southern Africa Collaboration

Objectives  To determine the diagnostic accuracy of World Health Organization (WHO) 2010 and 2006 as well as United States Department of Health and Human Services (DHHS) 2008 definitions of immunological failure for identifying virological failure (VF) in children on antiretroviral therapy (ART). Methods  Analysis of data from children (<16 years at ART initiation) at South African ART sites at which CD4 count/per cent and HIV-RNA monitoring are performed 6-monthly. Incomplete virological suppression (IVS) was defined as failure to achieve ≥1 HIV-RNA ≤400 copies/ml between 6 and 15 months on ART and viral rebound (VR) as confirmed HIV-RNA ≥5000 copies/ml in a child on ART for ≥18 months who had achieved suppression during the first year on treatment. Results  Among 3115 children [median (interquartile range) age 48 (20-84) months at ART initiation] on treatment for ≥1 year, sensitivity of immunological criteria for IVS was 10%, 6% and 26% for WHO 2006, WHO 2010 and DHHS 2008 criteria, respectively. The corresponding positive predictive values (PPV) were 31%, 20% and 20%. Diagnostic accuracy for VR was determined in 2513 children with ≥18 months of follow-up and virological suppression during the first year on ART with sensitivity of 5% (WHO 2006/2010) and 27% (DHHS 2008). PPV results were 42% (WHO 2010), 43% (WHO 2006) and 20% (DHHS 2008). Conclusion  Current immunological criteria are unable to correctly identify children failing ART virologically. Improved access to viral load testing is needed to reliably identify VF in children.