Using e-coins to ensure fair sharing of donor funds amongst HIV healthcare facilities

Donor funds are available for treatment of many diseases such as HIV. However, privacy constraints make it hard for donor organisations to verify that they have not sponsored the same patient twice | or sponsored a patient whose treatment was also sponsored by another donor. This paper presents a protocol based on digital cash that enables donor organisations to obtain a proof (in the form of an e-coin) from healthcare providers for patients such a provider claims to have treated. These coins are distributed to patients at the beginning of a funding cycle. The major challenge is to issue a unique coin to a patient | even if the coin is reissued. This is achieved without giving anyone access to a national database of identities; all databases contain effectively concealed information. Reissued coins will be identical to previous coins with a probability that can be decided beforehand.http://www.journals.co.za/ej/ejour_comp.htm

HIV-HBV coinfection in Southern Africa and the effect of Lamivudine- Versus tenofovir-containing cART on HBV outcomes

BACKGROUND:: This study assessed HIV-hepatitis B virus (HBV) coinfection in southern Africa in terms of prevalence, viral characteristics, occult HBV, and the effect of lamivudine- versus tenofovir-containing first-line combination antiretroviral treatment (cART) on HBV-related outcomes. METHODS:: A multicenter prospective cohort of HIV-infected adults in Zambia and South Africa who initiated cART. Outcomes by month 12 on cART were immunological recovery, hepatitis B surface antigen (HBsAg) loss, viral suppression, and drug resistance. We used descriptive statistics, logistic regression, and linear mixed models. RESULTS:: Of the 1087 participants, 92 were HBsAg seropositive, yielding a sample-weighted prevalence of 7.4% (95% confidence interval: 5.6 to 9.2), with 76% genotype HBV-A1. The estimated CD4 recovery on cART was similar between HIV monoinfection and HIV-HBV coinfection groups and between lamivudine- and tenofovir-treated participants. HBsAg loss was documented in 20% (4/20) of lamivudine-treated and 18% (3/17) of tenofovir-treated participants (P = 0.305). Viral suppression (HBV-DNA < 20 IU/mL) was achieved in 61.5% (16/26) of lamivudine-treated and 71.4% (15/21) of tenofovir-treated participants (P = 0.477). HBV pol sequencing demonstrated M204I (n = 3) and N236T (n = 1) resistance-associated mutations in 4 of 8 (50%) lamivudine-treated participants and none in tenofovir-treated participants. Occult HBV infection was present in 13.3% before cART, but by month 12, HBV-DNA was below the limit of detection (<15 IU/mL) in 90.5% (19/21) of lamivudine-treated and 100% (18/18) of tenofovir-treated participants (P = 0.179). CONCLUSIONS:: Tenofovir-containing first-line cART is preferred for HIV-HBV coinfection in Africa because of a superior resistance profile relative to lamivudine monotherapy. Extended follow-up will be needed to determine long-term complications of occult HBV coinfection. Improved access to HBsAg screening and tenofovir is needed

Unnecessary Antiretroviral Treatment Switches and Accumulation of HIV Resistance Mutations; Two Arguments for Viral Load Monitoring in Africa

Objectives: This study aimed to investigate the consequences of using clinicoimmunological criteria to detect antiretroviral treatment (ART) failure and guide regimen switches in HIV-infected adults in sub-Saharan Africa. Frequencies of unnecessary switches, patterns of HIV drug resistance, and risk factors for the accumulation of nucleoside reverse transcriptase inhibitor (NRTI)-associated mutations were evaluated. Methods: Cross-sectional analysis of adults switching ART regimens at 13 clinical sites in 6 African countries was performed. Two types of failure identification were compared: diagnosis of clinicoimmunological failure without viral load testing (CIF only) or CIF with local targeted viral load testing (targeted VL). After study enrollment, reference HIV RNA and genotype were determined retrospectively. Logistic regression assessed factors associated with multiple thymidine analogue mutations (TAMs) and NRTI cross-resistance (>= 2 TAMs or Q151M or K65R/K70E). Results: Of 250 patients with CIF switching to second-line ART, targeted VL was performed in 186. Unnecessary switch at reference HIV RNA = 2 TAMs (37.7%), K65R (7.1%), K70E (3.3%), or Q151M (3.3%). The presence of NRTI cross-resistance was associated with the duration of ART exposure and zidovudine use. Conclusions: Clinicoimmunological monitoring without viral load testing resulted in frequent unnecessary regimen switches. Prolonged treatment failure was indicated by extensive NRTI cross-resistance. Access to virological monitoring should be expanded to prevent inappropriate switches, enable early failure detection and preserve second-line treatment options in Afric

Patterns of HIV-1 Drug Resistance After First-Line Antiretroviral Therapy (ART) Failure in 6 Sub-Saharan African Countries: Implications for Second-Line ART Strategies

Background. Human immunodeficiency virus type 1 (HIV-1) drug resistance may limit the benefits of antiretroviral therapy (ART). This cohort study examined patterns of drug-resistance mutations (DRMs) in individuals with virological failure on first-line ART at 13 clinical sites in 6 African countries and predicted their impact on second-line drug susceptibility. Methods. A total of 2588 antiretroviral-naive individuals initiated ART consisting of different nucleoside reverse transcriptase inhibitor (NRTI) backbones (zidovudine, stavudine, tenofovir, or abacavir, plus lamivudine or emtricitabine) with either efavirenz or nevirapine. Population sequencing after 12 months of ART was retrospectively performed if HIV RNA was > 1000 copies/mL. The 2010 International Antiviral Society-USA list was used to score major DRMs. The Stanford algorithm was used to predict drug susceptibility. Results. HIV-1 sequences were generated for 142 participants who virologically failed ART, of whom 70% carried >= 1 DRM and 49% had dual-class resistance, with an average of 2.4 DRMs per sequence (range, 1-8). The most common DRMs were M184V (53.5%), K103N (28.9%), Y181C (15.5%), and G190A (14.1%). Thymidine analogue mutations were present in 8.5%. K65R was frequently selected by stavudine (15.0%) or tenofovir (27.7%). Among participants with >= 1 DRM, HIV-1 susceptibility was reduced in 93% for efavirenz/nevirapine, in 81% for lamivudine/emtricitabine, in 59% for etravirine/rilpivirine, in 27% for tenofovir, in 18% for stavudine, and in 10% for zidovudine. Conclusions. Early failure detection limited the accumulation of resistance. After stavudine failure in African populations, zidovudine rather than tenofovir may be preferred in second-line ART. Strategies to prevent HIV-1 resistance are a global priorit

Effect of pretreatment HIV-1 drug resistance on immunological, virological, and drug-resistance outcomes of first-line antiretroviral treatment in sub-Saharan Africa: a multicentre cohort study

Background The effect of pretreatment HIV-1 drug resistance on the response to first-line combination antiretroviral therapy (ART) in sub-Saharan Africa has not been assessed. We studied pretreatment drug resistance and virological, immunological, and drug-resistance treatment outcomes in a large prospective cohort. Methods HIV-1 infected patients in the PharmAccess African Studies to Evaluate Resistance Monitoring (PASER-M) cohort started non-nucleoside reverse transcriptase inhibitor-based ART at 13 clinical sites in six countries, from 2007 to 2009. We used the International Antiviral Society-USA drug resistance mutation list and the Stanford algorithm to classify participants into three pretreatment drug resistance categories: no pretreatment drug resistance, pretreatment drug resistance with fully active ART prescribed, or pretreatment drug resistance with reduced susceptibility to at least one prescribed drug. We assessed risk factors of virological failure (>= 400 copies per mL) and acquired drug resistance after 12 months of ART by use of multilevel logistic regression with multiple imputations for missing data. CD4 cell count increase was estimated with linear mixed models. Findings Pretreatment drug resistance results were available for 2579 (94%) of 2733 participants; 2404 (93%) had no pretreatment drug resistance, 123 (5%) had pretreatment drug resistance to at least one prescribed drug, and 52 (2%) had pretreatment drug resistance and received fully active ART Compared with participants without pretreatment drug resistance, the odds ratio (OR) for virological failure (OR 2.13,95% CI 1-44-3.14; p <0.0001) and acquired drug-resistance (2.30,1.55-3-40; p <0.0001) was increased in participants with pretreatment drug resistance to at least one prescribed drug, but not in those with pretreatment drug resistance and fully active ART CD4 count increased less in participants with pretreatment drug resistance than in those without (35 cells per mu L difference after 12 months; 95% CI 13-58; p=0.002). Interpretation At least three fully active antiretroviral drugs are needed to ensure an optimum response to first-line regimens and to prevent acquisition of drug resistance. Improved access to alternative combinations of antiretroviral drugs in sub-Saharan Africa is warranted. Funding The Netherlands Ministry of Foreign Affair

Accumulation of HIV-1 drug resistance after continued virological failure on first-line ART in adults and children in sub-Saharan Africa

Limited availability of viral load (VL) monitoring in HIV treatment programmes in sub-Saharan Africa can delay switching to second-line ART, leading to the accumulation of drug resistance mutations (DRMs). The objective of this study was to evaluate the accumulation of resistance to reverse transcriptase inhibitors after continued virological failure on first-line ART, among adults and children in sub-Saharan Africa. HIV-1-positive adults and children on an NNRTI-based first-line ART were included. Retrospective VL and, if VL ≥1000 copies/mL, pol genotypic testing was performed. Among participants with continued virological failure (≥2 VL ≥1000 copies/mL), drug resistance was evaluated. At first virological failure, DRM(s) were detected in 87% of participants: K103N (38.7%), G190A (21.8%), Y181C (20.2%), V106M (8.4%), K101E (8.4%), any E138 (7.6%) and V108I (7.6%) associated with NNRTIs, and M184V (69.7%), any thymidine analogue mutation (9.2%), K65R (5.9%) and K70R (5.0%) associated with NRTIs. New DRMs accumulated with an average rate of 1.45 (SD 2.07) DRM per year; 0.62 (SD 1.11) NNRTI DRMs and 0.84 (SD 1.38) NRTI DRMs per year, respectively. The predicted susceptibility declined significantly after continued virological failure for all reverse transcriptase inhibitors (all P  < 0.001). Acquired drug resistance patterns were similar in adults and children. Patterns of drug resistance after virological failure on first-line ART are similar in adults and children in sub-Saharan Africa. Improved VL monitoring to prevent accumulation of mutations, and new drug classes to construct fully active regimens, are require

Pretreatment HIV drug resistance increases regimen switches in sub-Saharan Africa

After the scale-up of antiretroviral therapy (ART) for human immunodeficiency virus (HIV) infection in Africa, increasing numbers of patients have pretreatment drug resistance. In a large multicountry cohort of patients starting standard first-line ART in six African countries, pol genotyping was retrospectively performed if viral load (VL) ≥1000 cps/mL. Pretreatment drug resistance was defined as a decreased susceptibility to ≥1 prescribed drug. We assessed the effect of pretreatment drug resistance on all-cause mortality, new AIDS events and switch to second-line ART due to presumed treatment failure, using Cox models. Among 2579 participants for whom a pretreatment genotype was available, 5.5% had pretreatment drug resistance. Pretreatment drug resistance was associated with an increased risk of regimen switch (adjusted hazard ratio [aHR] 3.80; 95% confidence interval [CI], 1.49-9.68; P = .005) but was not associated with mortality (aHR 0.75, 95% CI, .24-2.35; P = .617) or new AIDS events (aHR 1.06, 95% CI, .68-1.64; P = .807). During three years of follow up, 106 (4.1%) participants switched to second-line, of whom 18 (17.0%) switched with VL < 1000 cps/mL, 7 (6.6%) with VL ≥ 1000 cps/mL and no drug resistance mutations (DRMs), 46 (43.4%) with VL ≥ 1000 cps/mL and ≥1 DRMs; no HIV RNA data was available for 32 (30.2%) participants. Given rising pretreatment HIV drug resistance levels in sub-Saharan Africa, these findings underscore the need for expanded access to second-line ART. VL monitoring can improve the accuracy of failure detection and efficiency of switching practice

Protease Inhibitor Resistance in the First 3 Years of Second-Line Antiretroviral Therapy for HIV-1 in Sub-Saharan Africa

As antiretroviral therapy (ART) programs in sub-Saharan Africa mature, increasing numbers of persons with human immunodeficiency virus (HIV) infection will experience treatment failure, and require second- or third-line ART. Data on second-line failure and development of protease inhibitor (PI) resistance in sub-Saharan Africa are scarce. HIV-1-infected adults were included if they received >180 days of PI-based second-line ART. We assessed risk factors for having a detectable viral load (VL, ≥400 cps/mL) using Cox models. If VL was ≥1000 cps/mL, genotyping was performed. Of 227 included participants, 14.6%, 15.2% and 11.1% had VLs ≥400 cps/mL at 12, 24, and 36 months, respectively. Risk factors for a detectable VL were as follows: exposure to nonstandard nonnucleoside reverse-transcriptase inhibitor (NNRTI)-based (hazard ratio, 7.10; 95% confidence interval, 3.40-14.83; P < .001) or PI-based (7.59; 3.02-19.07; P = .001) first-line regimen compared with zidovudine/lamivudine/NNRTI, PI resistance at switch (6.69; 2.49-17.98; P < .001), and suboptimal adherence (3.05; 1.71-5.42; P = .025). Among participants with VLs ≥1000 cps/mL, 22 of 32 (69%) harbored drug resistance mutation(s), and 7 of 32 (22%) harbored PI resistance. Although VL suppression rates were high, PI resistance was detected in 22% of participants with VLs ≥1000 cps/mL. To ensure long-term ART success, intensified support for adherence, VL and drug resistance testing, and third-line drugs will be necessar

HIV-1 drug resistance in antiretroviral-naive individuals in sub-Saharan Africa after rollout of antiretroviral therapy: A multicentre observational study

Background: There are few data on the epidemiology of primary HIV-1 drug resistance after the roll-out of antiretroviral treatment (ART) in sub-Saharan Africa. We aimed to assess the prevalence of primary resistance in six African countries after ART roll-out and if wider use of ART in sub-Saharan Africa is associated with rising prevalence of drug resistance. Methods: We did a cross-sectional study in antiretroviral-naive adults infected with HIV-1 who had not started first-line ART, recruited between 2007 and 2009 from 11 regions in Kenya, Nigeria, South Africa, Uganda, Zambia, and Zimbabwe. We did population-based sequencing of the pol gene on plasma specimens with greater than 1000 copies per mL of HIV RNA. We identified drug-resistance mutations with the WHO list for transmitted resistance. The prevalence of sequences containing at least one drug-resistance mutation was calculated accounting for the sampling weights of the sites. We assessed the risk factors of resistance with multilevel logistic regression with random coefficients. Findings: 2436 (94.1%) of 2590 participants had a pretreatment genotypic resistance result. 1486 participants (57.4%) were women, 1575 (60.8%) had WHO clinical stage 3 or 4 disease, and the median CD4 count was 133 cells per μL (IQR 62-204). Overall sample-weighted drug-resistance prevalence was 5.6% (139 of 2436; 95% CI 4.6-6.7), ranging from 1.1% (two of 176; 0.0-2.7) in Pretoria, South Africa, to 12.3% (22 of 179; 7.5-17.1) in Kampala, Uganda. The pooled prevalence for all three Ugandan sites was 11.6% (66 of 570; 8.9-14.2), compared with 3.5% (73 of 1866; 2.5-4.5) for all other sites. Drug class-specific resistance prevalence was 2.5% (54 of 2436; 1.8-3.2) for nucleoside reverse-transcriptase inhibitors (NRTIs), 3.3% (83 of 2436; 2.5-4.2) for non-NRTIs (NNRTIs), 1.3% (31 of 2436; 0.8-1.8) for protease inhibitors, and 1.2% (25 of 2436; 0.7-1.7) for dual-class resistance to NRTIs and NNRTIs. The most common drug-resistance mutations were K103N (43 [1.8%] of 2436), thymidine analogue mutations (33 [1.6%] of 2436), M184V (25 [1.2%] of 2436), and Y181C/I (19 [0.7%] of 2436). The odds ratio for drug resistance associated with each additional year since the start of the ART roll-out in a region was 1.38 (95% CI 1.13-1.68; p=0.001). Interpretation: The higher prevalence of primary drug resistance in Uganda than in other African countries is probably related to the earlier start of ART roll-out in Uganda. Resistance surveillance and prevention should be prioritised in settings where ART programmes are scaled up. Funding: Ministry of Foreign Affairs of the Netherlands