Integrative omics-analysis of lipid metabolism regulation by peroxisome proliferator-activated receptor a and b agonists in male Atlantic cod.

Lipid metabolism is essential in maintaining energy homeostasis in multicellular organisms. In vertebrates, the peroxisome proliferator-activated receptors (PPARs, NR1C) regulate the expression of many genes involved in these processes. Atlantic cod (Gadus morhua) is an important fish species in the North Atlantic ecosystem and in human nutrition, with a highly fatty liver. Here we study the involvement of Atlantic cod Ppar a and b subtypes in systemic regulation of lipid metabolism using two model agonists after in vivo exposure. WY-14,643, a specific PPARA ligand in mammals, activated cod Ppara1 and Ppara2 in vitro. In vivo, WY-14,643 caused a shift in lipid transport both at transcriptional and translational level in cod. However, WY-14,643 induced fewer genes in the fatty acid beta-oxidation pathway compared to that observed in rodents. Although GW501516 serves as a specific PPARB/D ligand in mammals, this compound activated cod Ppara1 and Ppara2 as well as Pparb in vitro. In vivo, it further induced transcription of Ppar target genes and caused changes in lipid composition of liver and plasma. The integrative approach provide a foundation for understanding how Ppars are engaged in regulating lipid metabolism in Atlantic cod physiology. We have shown that WY-14,643 and GW501516 activate Atlantic cod Ppara and Pparb, affect genes in lipid metabolism pathways, and induce changes in the lipid composition in plasma and liver microsomal membranes. Particularly, the combined transcriptomic, proteomics and lipidomics analyses revealed that effects of WY-14,643 on lipid metabolism are similar to what is known in mammalian studies, suggesting conservation of Ppara functions in mediating lipid metabolic processes in fish. The alterations in the lipid profiles observed after Ppar agonist exposure suggest that other chemicals with similar Ppar receptor affinities may cause disturbances in the lipid regulation of fish. Model organism: Atlantic cod (Gadus morhua). LSID: urn:lsid:zoobank.org:act:389BE401-2718-4CF2-BBAE-2E13A97A5E7B. COL Identifier: 6K72F.

Early response evaluation by single cell signaling profiling in acute myeloid leukemia.

Aberrant pro-survival signaling is a hallmark of cancer cells, but the response to chemotherapy is poorly understood. In this study, we investigate the initial signaling response to standard induction chemotherapy in a cohort of 32 acute myeloid leukemia (AML) patients, using 36-dimensional mass cytometry. Through supervised and unsupervised machine learning approaches, we find that reduction of extracellular-signal-regulated kinase (ERK) 1/2 and p38 mitogen-activated protein kinase (MAPK) phosphorylation in the myeloid cell compartment 24 h post-chemotherapy is a significant predictor of patient 5-year overall survival in this cohort. Validation by RNA sequencing shows induction of MAPK target gene expression in patients with high phospho-ERK1/2 24 h post-chemotherapy, while proteomics confirm an increase of the p38 prime target MAPK activated protein kinase 2 (MAPKAPK2). In this study, we demonstrate that mass cytometry can be a valuable tool for early response evaluation in AML and elucidate the potential of functional signaling analyses in precision oncology diagnostics.

GUBS: Graph-Based Unsupervised Brain Segmentation in MRI Images.

Brain segmentation in magnetic resonance imaging (MRI) images is the process of isolating the brain from non-brain tissues to simplify the further analysis, such as detecting pathology or calculating volumes. This paper proposes a Graph-based Unsupervised Brain Segmentation (GUBS) that processes 3D MRI images and segments them into brain, non-brain tissues, and backgrounds. GUBS first constructs an adjacency graph from a preprocessed MRI image, weights it by the difference between voxel intensities, and computes its minimum spanning tree (MST). It then uses domain knowledge about the different regions of MRIs to sample representative points from the brain, non-brain, and background regions of the MRI image. The adjacency graph nodes corresponding to sampled points in each region are identified and used as the terminal nodes for paths connecting the regions in the MST. GUBS then computes a subgraph of the MST by first removing the longest edge of the path connecting the terminal nodes in the brain and other regions, followed by removing the longest edge of the path connecting non-brain and background regions. This process results in three labeled, connected components, whose labels are used to segment the brain, non-brain tissues, and the background. GUBS was tested by segmenting 3D T1 weighted MRI images from three publicly available data sets. GUBS shows comparable results to the state-of-the-art methods in terms of performance. However, many competing methods rely on having labeled data available for training. Labeling is a time-intensive and costly process, and a big advantage of GUBS is that it does not require labels.

Wearing-off symptoms during standard and extended natalizumab dosing intervals: Experiences from the COVID-19 pandemic.

Natalizumab effectively prevents disease activity in relapsing-remitting multiple sclerosis, but many treated patients report subjective wearing-off symptoms at the end of the 4-week interval between infusions. Extended interval dosing (EID) is a promising strategy to mitigate the risk of natalizumab-associated progressive multifocal leukoencephalopathy, but it is unknown whether EID affects wearing-off symptoms. In this observational study, we evaluated if prevalence or intensity of wearing-off symptoms changed when natalizumab dosing intervals were extended from 4 to 6 weeks in 30 treated patients during the outbreak of COVID-19 in Norway. New or increased wearing-off symptoms during EID were reported by 50%. Symptom increase was more frequent among patients with pre-existing wearing-off symptoms during standard dosing compared to patients without such pre-existing symptoms [p = 0.0005]. Our observations support the need to study the effect of EID on wearing-off symptoms in randomized controlled trials.

Wearing-off at the end of natalizumab dosing intervals is associated with low receptor occupancy.

OBJECTIVE: We aimed to investigate whether wearing-off symptoms at the end of the natalizumab dosing interval were associated with clinical and demographic patient characteristics or natalizumab receptor occupancy (RO) on leukocytes. METHODS: In this cross-sectional study of 40 patients with relapsing-remitting MS (RRMS) receiving natalizumab at the Department of Neurology, Haukeland University Hospital, we recorded clinical and demographic data including age, body mass index (BMI), working status, smoking habits, disease characteristics, treatment duration, vitamin D levels, and wearing-off symptoms. We quantified neurofilament light chain in serum and measured natalizumab RO in leukocyte subtypes by high-parameter mass cytometry. Associations with wearing-off symptoms were analyzed. RESULTS: Eight (20.0%) patients who reported regular occurrence of wearing-off symptoms, 9 (22.5%) who sometimes had wearing-off symptoms, and 23 (57.5%) who did not have wearing-off symptoms were evaluated. Patients who regularly had wearing-off symptoms had lower natalizumab RO than patients who reported having such symptoms sometimes or never. The former group also had higher BMI and higher frequency of sick leave. High BMI was associated with low RO. No other demographic or disease characteristics were associated with the phenomenon. CONCLUSIONS: Low RO may explain the wearing-off phenomenon observed in some patients with RRMS treated with natalizumab, and high BMI may be the underlying cause.

Candidate Markers for Stratification and Classification in Rheumatoid Arthritis.

Rheumatoid arthritis (RA) is a chronic autoimmune, inflammatory disease, characterized by synovitis in small- and medium-sized joints and, if not treated early and efficiently, joint damage, and destruction. RA is a heterogeneous disease with a plethora of treatment options. The pro-inflammatory cytokine tumor necrosis factor (TNF) plays a central role in the pathogenesis of RA, and TNF inhibitors effectively repress inflammatory activity in RA. Currently, treatment decisions are primarily based on empirics and economic considerations. However, the considerable interpatient variability in response to treatment is a challenge. Markers for a more exact patient classification and stratification are lacking. The objective of this study was to identify markers in immune cell populations that distinguish RA patients from healthy donors with an emphasis on TNF signaling. We employed mass cytometry (CyTOF) with a panel of 13 phenotyping and 10 functional markers to explore signaling in unstimulated and TNF-stimulated peripheral blood mononuclear cells from 20 newly diagnosed, untreated RA patients and 20 healthy donors. The resulting high-dimensional data were analyzed in three independent analysis pipelines, characterized by differences in both data clean-up, identification of cell subsets/clustering and statistical approaches. All three analysis pipelines identified p-p38, IkBa, p-cJun, p-NFkB, and CD86 in cells of both the innate arm (myeloid dendritic cells and classical monocytes) and the adaptive arm (memory CD4+ T cells) of the immune system as markers for differentiation between RA patients and healthy donors. Inclusion of the markers p-Akt and CD120b resulted in the correct classification of 18 of 20 RA patients and 17 of 20 healthy donors in regression modeling based on a combined model of basal and TNF-induced signal. Expression patterns in a set of functional markers and specific immune cell subsets were distinct in RA patients compared to healthy individuals. These signatures may support studies of disease pathogenesis, provide candidate markers for response, and non-response to TNF inhibitor treatment, and aid the identification of future therapeutic targets.

Contaminant accumulation and biological responses in Atlantic cod (Gadus morhua) caged at a capped waste disposal site in Kollevåg, Western Norway.

The aim of this study was to assess whether fish in Kollevåg, a sheltered bay on the western coast of Norway, previously utilized as a waste disposal site, could be affected by environmental contaminants leaking from the waste. Farmed, juvenile Atlantic cod (Gadus morhua) were caged for six weeks at three different locations in Kollevåg bay and at one reference location. Sediments and cod samples (bile and liver) were analyzed for polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs), brominated flame retardants (BFRs), per-and polyfluoroalkyl substances (PFASs) and polycyclic aromatic hydrocarbon (PAH) metabolites, revealing a contamination gradient at the four stations. Furthermore, hepatosomatic index (HSI) and Fulton's condition factor (CF) were significantly lower in cod caged closest to the disposal site. Levels and activities of biomarker proteins, such as vitellogenin (Vtg), metallothionein (Mt), and biotransformation and oxidative stress enzymes, including cytochrome P450 1a and 3a (Cyp1a, Cyp3a), glutathione s-transferase (Gst) and catalase (Cat), were quantified in blood plasma and liver tissue. Hepatic Cat and Gst activities were significantly reduced in cod caged at the innermost stations in Kollevåg, indicating modulation of oxidative stress responses. However, these results contrasted with reduced hepatic lipid peroxidation. Significant increases in transcript levels were observed for genes involved in lipid metabolism (fasn and acly) in cod liver, while transcript levels of ovarian steroidogenic enzyme genes such as p450scc, cyp19, 3ß-hsd and 20ß-hsd showed significant station-dependent increases. Cyp1a and Vtg protein levels were however not significantly altered in cod caged in Kollevåg. Plasma levels of estradiol (E2) and testosterone (T) were determined by enzyme immunoassay (EIA) and showed elevated E2 levels, but only at the innermost station. We conclude that the bay of Kollevåg did not fullfill adequate environmental condition based on environmental quality standards (EQSs) for chemicals in coastal waters. Following a six weeks caging period, environmental contaminants accumulated in cod tissues and effects were observed on biomarker responses, especially those involved in reproductive processes in cod ovary.

Optimization of Receptor Occupancy Assays in Mass Cytometry: Standardization Across Channels with QSC Beads.

Receptor occupancy, the ratio between amount of drug bound and amount of total receptor on single cells, is a biomarker for treatment response to therapeutic monoclonal antibodies. Receptor occupancy is traditionally measured by flow cytometry. However, spectral overlap in flow cytometry limits the number of markers that can be measured simultaneously. This restricts receptor occupancy assays to the analysis of major cell types, although rare cell populations are of potential therapeutic relevance. We therefore developed a receptor occupancy assay suitable for mass cytometry. Measuring more markers than currently available in flow cytometry allows simultaneous receptor occupancy assessment and high-parameter immune phenotyping in whole blood, which should yield new insights into disease activity and therapeutic effects. However, varying sensitivity across the mass cytometer detection range may lead to misinterpretation of the receptor occupancy when drug and receptor are detected in different channels. In this report, we describe a method for optimization of mass cytometry receptor occupancy measurements by using antibody-binding quantum simply cellular (QSC) beads for standardization across channels with different sensitivities. We evaluated the method in a mass cytometry-based receptor occupancy assay for natalizumab, a therapeutic antibody used in multiple sclerosis treatment that binds to α4-integrin, which is expressed on leukocyte cell surfaces. Peripheral blood leukocytes from a treated patient were stained with a panel containing metal-conjugated antibodies for detection of natalizumab and α4-integrin. QSC beads with known antibody binding capacity were stained with the same metal-conjugated antibodies and were used to standardize the signal intensity in the leukocyte sample before calculating receptor occupancy. We found that QSC bead standardization across channels corrected for sensitivity differences for detection of drug and receptor and generated more accurate results than observed without standardization. © 2019 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.

Effects of defined mixtures of POPs and endocrine disruptors on the steroid metabolome of the human H295R adrenocortical cell line.

The presence of environmental pollutants in our ecosystem may impose harmful health effects to wildlife and humans. Several of these toxic chemicals have a potential to interfere with the endocrine system. The adrenal cortex has been identified as the main target organ affected by endocrine disrupting chemicals. The aim of this work was to assess exposure effects of defined and environmentally relevant mixtures of chlorinated, brominated and perfluorinated chemicals on steroidogenesis, using the H295R adrenocortical cell line model in combination with a newly developed liquid chromatography tandem mass spectrometry (LC-MS/MS) method. By using this approach, we could simultaneously analyze 19 of the steroids in the steroid biosynthesis pathway, revealing a deeper insight into possible disruption of steroidogenesis. Our results showed a noticeable down-regulation in steroid production when cells were exposed to the highest concentration of a mixture of brominated and fluorinated compounds (10,000-times human blood values). In contrast, up-regulation was observed with estrone under the same experimental condition, as well as with some other steroids when cells were exposed to a perfluorinated mixture (1000-times human blood values), and the mixture of chlorinated and fluorinated compounds. Interestingly, the low concentration of the perfluorinated mixture alone produced a significant, albeit small, down-regulation of pregnenolone, and the total mixture a similar effect on 17-hydroxypregnenolone. Other mixtures resulted in only slight deviations from the control. Indication of synergistic effects were noted when we used a statistical model to improve data interpretation. A potential for adverse outcomes of human exposures is indicated, pointing to the need for further investigation into these mixtures.

The Effect of Monitoring Viral Load and Tracing Patients Lost to Follow-up on the Course of the HIV Epidemic in Malawi: A Mathematical Model.

BACKGROUND: Antiretroviral therapy (ART) reduces HIV transmission, but treated patients may again become infectious. We used a mathematical model to determine whether ART as prevention is more effective if viral load (VL) is routinely monitored and patients lost to follow-up (LTFU) traced. METHODS: We simulated ART cohorts to parameterize a deterministic transmission model calibrated to Malawi. We investigated the following strategies for improving treatment and retention: monitoring VL every 12 or 24 months, tracing patients LTFU, or a generic strategy leading to uninterrupted treatment. We tested 3 scenarios, where ART scale-up continues at current (Universal ART), reduced (Failed scale-up), or accelerated speed (Test&Treat). RESULTS: In the Universal ART scenario, between 2017 and 2020 (2050), monitoring VL every 24 months prevented 0.5% (0.9%), monitoring every 12 months prevented 0.8% (1.4%), tracing prevented 0.3% (0.5%), and uninterrupted treatment prevented 5.5% (9.9%) of HIV infections. Failed scale-up resulted in 25% more infections than the Universal ART scenarios, whereas Test&Treat resulted in 7%-8% less. CONCLUSIONS: Test&Treat reduces transmission of HIV, despite individual cases of treatment failure and ART interruption. Whereas viral load monitoring and tracing have only a minor impact on transmission, interventions that aim to minimize treatment interruptions can further increase the preventive effect of ART.

Evaluating model reduction under parameter uncertainty.

BACKGROUND: The dynamics of biochemical networks can be modelled by systems of ordinary differential equations. However, these networks are typically large and contain many parameters. Therefore model reduction procedures, such as lumping, sensitivity analysis and time-scale separation, are used to simplify models. Although there are many different model reduction procedures, the evaluation of reduced models is difficult and depends on the parameter values of the full model. There is a lack of a criteria for evaluating reduced models when the model parameters are uncertain. RESULTS: We developed a method to compare reduced models and select the model that results in similar dynamics and uncertainty as the original model. We simulated different parameter sets from the assumed parameter distributions. Then, we compared all reduced models for all parameter sets using cluster analysis. The clusters revealed which of the reduced models that were similar to the original model in dynamics and variability. This allowed us to select the smallest reduced model that best approximated the full model. Through examples we showed that when parameter uncertainty was large, the model should be reduced further and when parameter uncertainty was small, models should not be reduced much. CONCLUSIONS: A method to compare different models under parameter uncertainty is developed. It can be applied to any model reduction method. We also showed that the amount of parameter uncertainty influences the choice of reduced models.

RNA-Seq analysis of transcriptome responses in Atlantic cod (Gadus morhua) precision-cut liver slices exposed to benzo[a]pyrene and 17α-ethynylestradiol.

Polycyclic aromatic hydrocarbons such as benzo[a]pyrene (BaP) that activate the aryl hydrocarbon receptor (Ahr) pathway, and endocrine disruptors acting through the estrogen receptor pathway are among environmental pollutants of major concern. In this work, we exposed Atlantic cod (Gadus morhua) precision-cut liver slices (PCLS) to BaP (10 nM and 1000 nM), ethynylestradiol (EE2) (10 nM and 1000 nM), and equimolar mixtures of BaP and EE2 (10 nM and 1000 nM) for 48 h, and performed RNA-Seq based transcriptome mapping followed by systematic bioinformatics analyses. Our gene expression analysis showed that several genes were differentially expressed in response to BaP and EE2 treatments in PCLS. Strong up-regulation of genes coding for the cytochrome P450 1a (Cyp1a) enzyme and the Ahr repressor (Ahrrb) was observed in BaP treated PCLS. EE2 treatment of liver slices strongly up-regulated genes coding for precursors of vitellogenin (Vtg) and eggshell zona pellucida (Zp) proteins. As expected, pathway enrichment and network analysis showed that the Ahr and estrogen receptor pathways are among the top affected by BaP and EE2 treatments, respectively. Interestingly, two genes coding for fibroblast growth factor 3 (Fgf3) and fibroblast growth factor 4 (Fgf4) were up-regulated by EE2 in this study. To our knowledge, the fgf3 and fgf4 genes have not previously been described in relation to estrogen signaling in fish liver, and these results suggest the modulation of the FGF signaling pathway by estrogens in fish. The signature expression profiles of top differentially expressed genes in response to the single compound (BaP or EE2) treatment were generally maintained in the expression responses to the equimolar binary mixtures. However, in the mixture-treated groups, BaP appeared to have anti-estrogenic effects as observed by lower number of differentially expressed putative EE2 responsive genes. Our in-depth quantitative analysis of changes in liver transcriptome in response to BaP and EE2, using PCLS tissue culture provides further mechanistic insights into effects of the compounds. Moreover, the analyses demonstrate the usefulness of PCLS in cod for omics experiments.

Impact of screening and antiretroviral therapy on anal cancer incidence in HIV-positive MSM.

BACKGROUND: The incidence of anal cancer is high in HIV-positive MSM. We modeled the impact of screening strategies and combination antiretroviral therapy (cART) coverage on anal cancer incidence in Switzerland. METHODS: Individual-based, dynamic simulation model parameterized with Swiss HIV Cohort Study and literature data. We assumed all men to be human papillomavirus infected. CD4 cell count trajectories were the main predictors of anal cancer. From 2016 we modeled cART coverage either as below 100% (corresponding to 2010-2015) or as 100%, and the following four screening strategies: no screening, yearly anal cytology (Papanicolaou smears), yearly anoscopy and targeted anoscopy 5 years after CD4 count dropped below 200 cells/µl. RESULTS: Median nadir CD4 cell count of 6411 MSM increased from 229 cells/µl during 1980-1989 to 394 cells/µl during 2010-2015; cART coverage increased from 0 to 83.4%. Modeled anal cancer incidence peaked at 81.7/100 000 in 2009, plateaued 2010-2015 and will decrease to 58.7 by 2030 with stable cART coverage, and to 52.0 with 100% cART coverage. With yearly cytology, incidence declined to 38.2/100 000 by 2030, with yearly anoscopy to 32.8 and with CD4 cell count guided anoscopy to 51.3. The numbers needed to screen over 15 years to prevent one anal cancer case were 384 for yearly cytology, 313 for yearly anoscopy and 242 for CD4 cell count-dependent screening. CONCLUSION: Yearly screening of HIV-positive MSM may reduce anal cancer incidence substantially, with a number needed to screen that is comparable with other screening interventions to prevent cancer.

Tuberculosis in Cape Town: An age-structured transmission model.

BACKGROUND: Tuberculosis (TB) is the leading cause of death in South Africa. The burden of disease varies by age, with peaks in TB notification rates in the HIV-negative population at ages 0-5, 20-24, and 45-49 years. There is little variation between age groups in the rates in the HIV-positive population. The drivers of this age pattern remain unknown. METHODS: We developed an age-structured simulation model of Mycobacterium tuberculosis (Mtb) transmission in Cape Town, South Africa. We considered five states of TB progression: susceptible, infected (latent TB), active TB, treated TB, and treatment default. Latently infected individuals could be re-infected; a previous Mtb infection slowed progression to active disease. We further considered three states of HIV progression: HIV negative, HIV positive, on antiretroviral therapy. To parameterize the model, we analysed treatment outcomes from the Cape Town electronic TB register, social mixing patterns from a Cape Town community and used literature estimates for other parameters. To investigate the main drivers behind the age patterns, we conducted sensitivity analyses on all parameters related to the age structure. RESULTS: The model replicated the age patterns in HIV-negative TB notification rates of Cape Town in 2009. Simulated TB notification rate in HIV-negative patients was 1000/100,000 person-years (pyrs) in children aged <5 years and decreased to 51/100,000 in children 5-15 years. The peak in early adulthood occurred at 25-29 years (463/100,000 pyrs). After a subsequent decline, simulated TB notification rates gradually increased from the age of 30 years. Sensitivity analyses showed that the dip after the early adult peak was due to the protective effect of latent TB and that retreatment TB was mainly responsible for the rise in TB notification rates from the age of 30 years. CONCLUSION: The protective effect of a first latent infection on subsequent infections and the faster progression in previously treated patients are the key determinants of the age-structure of TB notification rates in Cape Town.

The need for second-line antiretroviral therapy in adults in sub-Saharan Africa up to 2030: a mathematical modelling study.

BACKGROUND: The number of patients in need of second-line antiretroviral drugs is increasing in sub-Saharan Africa. We aimed to project the need of second-line antiretroviral therapy in adults in sub-Saharan Africa up to 2030. METHODS: We developed a simulation model for HIV and applied it to each sub-Saharan African country. We used the WHO country intelligence database to estimate the number of adult patients receiving antiretroviral therapy from 2005 to 2014. We fitted the number of adult patients receiving antiretroviral therapy to observed estimates, and predicted first-line and second-line needs between 2015 and 2030. We present results for sub-Saharan Africa, and eight selected countries. We present 18 scenarios, combining the availability of viral load monitoring, speed of antiretroviral scale-up, and rates of retention and switching to second-line. HIV transmission was not included. FINDINGS: Depending on the scenario, 8·7-25·6 million people are expected to receive antiretroviral therapy in 2020, of whom 0·5-3·0 million will be receiving second-line antiretroviral therapy. The proportion of patients on treatment receiving second-line therapy was highest (15·6%) in the scenario with perfect retention and immediate switching, no further scale-up, and universal routine viral load monitoring. In 2030, the estimated range of patients receiving antiretroviral therapy will remain constant, but the number of patients receiving second-line antiretroviral therapy will increase to 0·8-4·6 million (6·6-19·6%). The need for second-line antiretroviral therapy was two to three times higher if routine viral load monitoring was implemented throughout the region, compared with a scenario of no further viral load monitoring scale-up. For each monitoring strategy, the future proportion of patients receiving second-line antiretroviral therapy differed only minimally between countries. INTERPRETATION: Donors and countries in sub-Saharan Africa should prepare for a substantial increase in the need for second-line drugs during the next few years as access to viral load monitoring improves. An urgent need exists to decrease the costs of second-line drugs. FUNDING: World Health Organization, Swiss National Science Foundation, National Institutes of Health.

Growth in Virologically Suppressed HIV-Positive Children on Antiretroviral Therapy: Individual and Population-level References.

BACKGROUND: Combination antiretroviral therapy (ART) suppresses viral replication in HIV-infected children. The growth of virologically suppressed children on ART has not been well documented. We aimed to develop dynamic reference curves for weight-for-age Z scores (WAZ) and height-for-age Z scores (HAZ). METHODS: Children aged <11 years at ART initiation with continuously undetectable viral loads (<400 copies/mL) treated at 7 South African ART programs with routine viral load monitoring were included. We used multilevel models to define trajectories of WAZ and HAZ up to 3 years and developed a web application to monitor trajectories in individual children. RESULTS: A total of 4876 children were followed for 7407 person-years. Analyses were stratified by baseline Z scores and age, which were the most important predictors of growth response. The youngest children showed the most pronounced increase in weight and height initially but catch-up growth stagnated after 1-2 years. Three years after starting ART, WAZ ranged from -2.2 [95% prediction interval (PrI), -5.6 to 0.8] in children with baseline age >5 years and Z score less than -3 to 0.0 (95% PrI, -2.7 to 2.4) in children with baseline age <2 years and WAZ greater than -1. For HAZ, the corresponding range was -2.3 (95% PrI, -4.9 to 0.3) in children with baseline age >5 years and Z score less than -3 to 0.3 (95% PrI, -3.1 to 3.4) in children with baseline age 2-5 years and HAZ greater than -1. CONCLUSIONS: We have developed an online tool to calculate reference trajectories in fully suppressed children. The web application could help to define "optimal" growth response and identify children with treatment failure.

gems: An R Package for Simulating from Disease Progression Models.

Mathematical models of disease progression predict disease outcomes and are useful epidemiological tools for planners and evaluators of health interventions. The 𝖱 package gems is a tool that simulates disease progression in patients and predicts the effect of different interventions on patient outcome. Disease progression is represented by a series of events (e.g., diagnosis, treatment and death), displayed in a directed acyclic graph. The vertices correspond to disease states and the directed edges represent events. The package gems allows simulations based on a generalized multistate model that can be described by a directed acyclic graph with continuous transition-specific hazard functions. The user can specify an arbitrary hazard function and its parameters. The model includes parameter uncertainty, does not need to be a Markov model, and may take the history of previous events into account. Applications are not limited to the medical field and extend to other areas where multistate simulation is of interest. We provide a technical explanation of the multistate models used by gems, explain the functions of gems and their arguments, and show a sample application.

The cost-effectiveness of monitoring strategies for antiretroviral therapy of HIV infected patients in resource-limited settings: software tool.

BACKGROUND: The cost-effectiveness of routine viral load (VL) monitoring of HIV-infected patients on antiretroviral therapy (ART) depends on various factors that differ between settings and across time. Low-cost point-of-care (POC) tests for VL are in development and may make routine VL monitoring affordable in resource-limited settings. We developed a software tool to study the cost-effectiveness of switching to second-line ART with different monitoring strategies, and focused on POC-VL monitoring. METHODS: We used a mathematical model to simulate cohorts of patients from start of ART until death. We modeled 13 strategies (no 2nd-line, clinical, CD4 (with or without targeted VL), POC-VL, and laboratory-based VL monitoring, with different frequencies). We included a scenario with identical failure rates across strategies, and one in which routine VL monitoring reduces the risk of failure. We compared lifetime costs and averted disability-adjusted life-years (DALYs). We calculated incremental cost-effectiveness ratios (ICER). We developed an Excel tool to update the results of the model for varying unit costs and cohort characteristics, and conducted several sensitivity analyses varying the input costs. RESULTS: Introducing 2nd-line ART had an ICER of US$1651-1766/DALY averted. Compared with clinical monitoring, the ICER of CD4 monitoring was US$1896-US$5488/DALY averted and VL monitoring US$951-US$5813/DALY averted. We found no difference between POC- and laboratory-based VL monitoring, except for the highest measurement frequency (every 6 months), where laboratory-based testing was more effective. Targeted VL monitoring was on the cost-effectiveness frontier only if the difference between 1st- and 2nd-line costs remained large, and if we assumed that routine VL monitoring does not prevent failure. CONCLUSION: Compared with the less expensive strategies, the cost-effectiveness of routine VL monitoring essentially depends on the cost of 2nd-line ART. Our Excel tool is useful for determining optimal monitoring strategies for specific settings, with specific sex-and age-distributions and unit costs.

Viral load versus CD4⁺ monitoring and 5-year outcomes of antiretroviral therapy in HIV-positive children in Southern Africa: a cohort-based modelling study.

OBJECTIVES: Many paediatric antiretroviral therapy (ART) programmes in Southern Africa rely on CD4⁺ to monitor ART. We assessed the benefit of replacing CD4⁺ by viral load monitoring. DESIGN: A mathematical modelling study. METHODS: A simulation model of HIV progression over 5 years in children on ART, parameterized by data from seven South African cohorts. We simulated treatment programmes with 6-monthly CD4⁺ or 6- or 12-monthly viral load monitoring. We compared mortality, second-line ART use, immunological failure and time spent on failing ART. In further analyses, we varied the rate of virological failure, and assumed that the rate is higher with CD4⁺ than with viral load monitoring. RESULTS: About 7% of children were predicted to die within 5 years, independent of the monitoring strategy. Compared with CD4⁺ monitoring, 12-monthly viral load monitoring reduced the 5-year risk of immunological failure from 1.6 to 1.0% and the mean time spent on failing ART from 6.6 to 3.6 months; 1% of children with CD4⁺ compared with 12% with viral load monitoring switched to second-line ART. Differences became larger when assuming higher rates of virological failure. When assuming higher virological failure rates with CD4⁺ than with viral load monitoring, up to 4.2% of children with CD4⁺ compared with 1.5% with viral load monitoring experienced immunological failure; the mean time spent on failing ART was 27.3 months with CD4⁺ monitoring and 6.0 months with viral load monitoring. Conclusion: Viral load monitoring did not affect 5-year mortality, but reduced time on failing ART, improved immunological response and increased switching to second-line ART.