Monitoring Costs Research Articles

Development of Wearable Device and their Application in Medical IoT

Health is one of the most important aspects of life. Still, people still could not get proper health services. It's caused by limitation to the used technology in hospitals and limitations to get to the hospital. Internet-of-Things (IoT) as one of the utmost trending motifs presently, formerly giving so many results in many ways, for example, in healthcare. Wearable devices are currently at the heart of just about every discussion related to the Internet of Things. The requirement for self-health monitoring and preventive medicine is increasing due to the projected dramatic increase in the number of elderly people until 2020.Developed technologies are truly able to reduce the overall costs for prevention and monitoring. This is possible by constantly monitoring health indicators in various areas and in particular, wearable devices are considered to carry this task out. These wearable devices and mobile apps now have been integrated with telemedicine and telehealth efficiently, to structure the medical Internet of Things. This paper reviews wearable health care devices both in scientific papers and commercial efforts. Key Words: Delivering of health care, Information Storage and Retrieval, Internet, Mobile Application, Smartphones, Telemedicine

Development of pyramid neural networks for prediction of significant wave height for renewable energy farms

Significant wave height (Hs) is a critical parameter in the design, operation, and maintenance of nearshore and offshore wind and wave farms. In this study, the original pyramid neural network (PNN) was introduced and applied to predict Hs for North Sea renewable energy farms. The performance of PNN was compared with state-of-the-art algorithms. The results show that the machine learning (ML) models trained by the network datasets can accurately predict Hs at any point of nearshore or offshore energy farms, significantly reducing wave monitoring costs. The PNN models predict Hs with high accuracy. The results predicted by PNN, with SRMSE of 0.256 and R2 of 0.873, are more accurate than the corresponding results obtained by the deep neural network (DNN) model, which show that PNNs with their far simpler structures and lower number of parameters are attractive alternatives for complex and time-consuming DNN models. The ensemble of regular models, with SRMSE of 0.247, is ranked as the most accurate method. The results also show that the applied state-of-the-art algorithms including MLR, SNN, DNN, ANFIS, and SVR models predict non-physical negative values of Hs. The PNNs developed in this study predict Hs with positive values. Moreover, the analysis shows that the scatter of the results obtained by the derived nonlinear models is less pronounced than the scatter of corresponding results obtained by other methods. The results also show that to evaluate the performance of nonlinear ML methods for large datasets, the analysis of standard statistical indices is not sufficient. For large datasets standard statistical indices provide inadequate or insufficient information and additional calculations, and statistical analysis are required.

A multiplex direct PCR method for the rapid and accurate discrimination of three species of spider mites (Acari: Tetranychidae) in fruit orchards in Beijing.

Spider mites (Acari: Tetranychidae) are polyphagous pests of economic importance in agriculture, among which the two-spotted spider mite Tetranychus urticae Koch has spread widely worldwide as an invasive species, posing a serious threat to fruit tree production in China, including Beijing. The hawthorn spider mite, Amphitetranychus viennensis Zacher, is also a worldwide pest of fruit trees and woody ornamental plants. The cassava mite, Tetranychus truncatus Ehara, is mainly found in Asian countries, including China, Korea and Japan, and mainly affects fruit trees and agricultural crops. These three species of spider mites are widespread and serious fruit tree pests in Beijing. Rapid and accurate identification of spider mites is essential for effective pest and plant quarantine in Beijing orchard fields. The identification of spider mite species is difficult due to their limited morphological characteristics. Although the identification of insect and mite species based on PCR and real-time polymerase chain reaction TaqMan is becoming increasingly common, DNA extraction is difficult, expensive and time-consuming due to the minute size of spider mites. Therefore, the objective of this study was to establish a direct multiplex PCR method for the simultaneous identification of three common species of spider mites in orchards, A. viennensis, T. truncatus and T. urticae, to provide technical support for the differentiation of spider mite species and phytosanitary measures in orchards in Beijing. Based on the mitochondrial cytochrome c oxidase subunit I (COI) of the two-spotted spider mite and the cassava mite and the 18S gene sequence of the hawthorn spider mite as the amplification target, three pairs of specific primers were designed, and the primer concentrations were optimized to establish a direct multiplex PCR system for the rapid and accurate discrimination of the three spider mites without the need for DNA extraction and purification. The method showed a high sensitivity of 0.047ng for T. truncatus and T. urticae DNA and 0.0002ng for A. viennensis. This method eliminates the DNA extraction and sequencing procedures of spider mite samples, offers a possibility for rapid monitoring of multiple spider mites in an integrated microarray laboratory system, reducing the time and cost of leaf mite identification and quarantine monitoring in the field.

The economic burden of systemic lupus erythematosus in Taiwan

Background Our cost-of-illness (COI) model adopted both payer and societal perspectives over a time horizon of 5 years to measure the economic burden of systemic lupus erythematosus (SLE) in Taiwan. Methodology A prevalence-based model was established to estimate the economic consequences of SLE after diagnosis in Taiwan. The model included four health states: (i) the three phenotypes representing mild, moderate, and severe SLE, and (ii) death. The inputs were obtained from a literature review of all the clinical trials and validated using a Delphi panel. The Delphi panel’s insights included commonly used treatment strategies for patients with SLE within the Taiwanese healthcare system. The costs mentioned in this model are disease management, monitoring, transient event, and indirect costs. One-way sensitivity analyses were conducted to assess the model uncertainty. Results The number of patients with SLE in our COI model was 20,189. At diagnosis, the number of SLE patients with mild, moderate, and severe phenotypes was 5,916, 12,255, and 2019, respectively. The total SLE cost in Taiwan over 5 years from both payer and societal perspectives was estimated at TWD 3.9 and 47 billion, respectively. The costs per patient per year from the payer and societal perspective were TWD 38,775 ($2,758) and TWD 466,119 ($33,152), respectively. Conclusion The findings demonstrated that the burden of SLE in Taiwan over a time horizon of 5 years is substantially high, mainly due to the consequences of economic loss as it affects women and men during their working age, in addition to the costs of SLE management and its consequences, such as flares, infection, and organ damage. Therefore, more attention should be paid to limiting the progression of SLE and the occurrence of flares, and further economic evaluations are necessary to assess novel treatment strategies that could control the disease.

Clinical-economic evaluation of distance education and blood glucose level monitoring in adults with diabetes mellitus

Background. Health Technology Assessment (HTA) in the Russian Federation has been performed for drugs, not for other medical technologies, which leads to decision making difficulties today. Aim. This study aimed to assess the clinical and economic efficiency of distance education and monitoring of blood glucose levels in patients with diabetes mellitus (DM) of both types. Materials and methods. The HTA was prepared using Markov model with a cost-effectiveness analysis methodology. The number of DM complications depending on glycated hemoglobin level with distance education and blood glucose level and without, that has been used for modeling cost of distance education and blood glucose monitoring as well as cost of drugs’ therapy and hospital admission due to DM complications with methodology and source of Obligatory Medical Insurance Fund on 30-yy horizon of modeling. Results. Distance education and blood glucose monitoring in DM patients leads to decrease in complication level as well as mortality, and acceptable additional financial costs from the 5th year of modeling for DM type 1 and from the 6thyear of modeling for type 2 without insulin dose changing. Conclusion. Clinical-economic reasonability of distance education and DM patients’ monitoring are demonstrated in this work. These results should be considered in the decision-making process for HTA budget financing.

Combining Recurrent Neural Network and Sigmoid Growth Models for Short-Term Temperature Forecasting and Tomato Growth Prediction in a Plastic Greenhouse

Compared with open-field cultivation, greenhouses can provide favorable conditions for crops to grow through environmental control. The prediction of greenhouse microclimates is a way to reduce environmental monitoring costs. This study used several recurrent neural network models, including long short-term memory (LSTM), gated recurrent unit, and bi-directional LSTM, with varying numbers of hidden layers and units, to establish a temperature forecasting model for a plastic greenhouse. To assess the generalizability of the proposed model, the most accurate forecasting model was used to predict the temperature in a greenhouse with different specifications. During a test period of four months, the best proposed model’s R2, MAPE, and RMSE values were 0.962, 3.216%, and 1.196 °C, respectively. Subsequently, the outputs of the temperature forecasting model were used to calculate growing degree days (GDDs), and the predicted GDDs were used as an input variable for the sigmoid growth models to simulate the leaf area index, fresh fruit weight, and aboveground dry matter of tomatoes. The R2 values of the growth model for the three growth traits were all higher than 0.80. Moreover, the fitted values and the parameter estimates of the growth models were similar, irrespective of whether the observed GDD (calculated using the actual observed data) or the predicted GDD (calculated using the temperature forecasting model output) was used. These results indicated that the proposed temperature forecasting model could accurately predict the temperature changes inside a greenhouse and could subsequently be used for the growth prediction of greenhouse tomatoes.

The Value of Regulators as Monitors: Evidence from Banking

While conventional wisdom suggests that financial supervision is costly for bank shareholders, agency theory suggests that supervisors’ audits can reduce shareholder monitoring costs. I study this trade-off in the context of an unexpected decrease in off-site surveillance intensity by the U.S. Federal Reserve. Banks subject to reduced surveillance experience a 1% loss in bank Tobin’s q and a 7% loss in equity market-to-book. These banks engage in more earnings management, and appear to compensate lower regulatory surveillance with costly internal audits. My results document a novel substitution effect between public monitoring by regulators and private monitoring by shareholders. This paper was accepted by Victoria Ivashina, finance. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.03083 .

Analysis of the Effects of Agency Costs on Financial Performance of Commercial Banks Listed at the Nairobi Securities Exchange in Mombasa County, Kenya

Agency costs result from a principal-agent relationship's conflicting interests. The relationship develops because the principal may not be able to manage the business since they are technologically illiterate, numerous, and geographically spread; as a result, they hire the agent. In a commercial bank, there are various relationships that show principal agent relationships, with the most prevalent one being the link between the shareholders and the management. Agency fees are paid with the intention of aligning the agents' and principal's ambitions in order to realize the principal's overarching intentions. Therefore, the perseverance of this study was to analyze agency costs and their effects on financial performance. In this study, the agency cost on financial performance of public commercial banks was analyzed. Specific objectives were; to establish how monitoring cost affect the financial performance of quoted commercial banks in Mombasa County, to assess the effect of bonding cost on financial performance of listed commercial banks in Mombasa county, to examine the extent to which residual loss affect the financial performance of commercial banks in Mombasa county and to determine the effects of restructuring cost on financial performance of listed commercial banks in Mombasa County- directed the study. Theories supporting this study were as follows; agency theories, free cash flow and stakeholder’s theory. Descriptive design is a kind of research methodology which establishes the connection between variables. It was used in this study to identify both the broad and the detailed study goals. A census of the 10 listed commercial banks in Mombasa County was conducted as part of the work and purposive sampling was be used. This study used qualitative and quantitative methods. Validity was tested through interview while reliability was tested using Cronbach alpha. The data was analyzed using inferential statistics like regression and correlation and descriptive statistics like mean and standard deviation using the Statistical Package for Social Science (SPSS) Version 22.0. The results were presented using cross tabulation, frequency tables, and charts. Findings indicated that there was a significant impact between; monitoring cost, bonding cost and residual cost and the financial performance. Restructuring cost were determined to have a favourable impact on financial performance. Therefore, the study recommends implementing an efficient internal control system by listed commercial bank management. This will assist in cutting down on the cost of auditing, administrative costs, and wasteful and unneeded spending, Managers should be paid more and attaching monetary or share bonuses or option entitlements to particular firm performance and to adopt a type of restructuring that will align with the relevant strategy and objectives.

Towards vision-based structural modal identification at low frame rate using blind source separation

With increasing availability of cost-effective and high-resolution cameras, their use as a non-contact sensing tool has rapidly progressed for structural health monitoring. The cameras offer unique capabilities to provide full-field measurement with high spatial density at low cost. However, extracting high-density temporal data is challenging, as a high-speed camera increases the monitoring cost with high-rate data processing. Recently, motion magnification (MM) has shown significant success in analyzing low-amplitude motion of structural systems. However, previous studies observed that MM methodology performs poorly at low frame rates for modal identifications. In this paper, the influence of low frame rate on phased-based motion magnification (PMM) has been investigated. A novel technique is proposed by combining PMM with zero mean-normalization cross-correlation tracker to determine vibrational responses, and then the spatial Wigner-Ville spectrum-based time-frequency blind source separation method is explored for modal identification using the extracted vibrational responses obtained from the video data. The experimental data of a lumped mass experimental model and a steel bridge is used to test the accuracy of the proposed method. The original and motion-magnified image response data is compared with accelerometer data for modal identification. The proposed method is able to extract the modal parameters with high accuracy for motion-magnified images, even for low frame rates.

Flexible Chitosan-Based Capacitive Humidity Sensors for Respiratory Monitoring.

As one of the most important human health indicators, respiratory status is an important basis for the diagnosis of many diseases. However, the high cost of respiratory monitoring makes its use uncommon. This study introduces a low-cost, wearable, flexible humidity sensor for respiratory monitoring. Solution-processed chitosan (CS) placed on a polyethylene terephthalate substrate was used as the sensing layer. An Arduino circuit board was used to read humidity-sensitive voltage changes. The CS-based sensor demonstrated capacitive humidity sensitivity, whereby the capacitance instantly increased from 10-2 to 30 nF when the environmental humidity changed from 43% to 97%. The capacitance logarithm sensitivity and response voltage change was 35.9 pF/%RH and 0.8 V in the RH range from 56% to 97%. And the voltage variation between inhalation and exhalation was ~0.5 V during normal breathing. A rapid response time of ~0.7 s and a recovery time of ~2 s were achieved during respiration testing. Breathing modes (i.e., normal breathing, rest breathing, deep breathing, and fast breathing) and tonal changes during speech could be clearly distinguished. Therefore, such sensors provide a means for economical and convenient wearable respiratory monitoring, and they have the potential to be used for daily health examinations and professional medical diagnoses.

Are all female directors equal? Incentives and effectiveness of female independent directors

We examine how differences in the career incentives of female directors impact their monitoring effectiveness in the context of financial reporting. We find that female independent directors who are sitting senior executives in other firms (executive FIDs) improve financial reporting quality while other female independent directors (non-executive FIDs) do not. Exogenous departure of executive FIDs leads to deterioration of financial reporting quality. Empirical approaches addressing reverse causality and selection problems support our primary findings. We also find that executive FIDs who are younger or not CEOs are more effective in improving financial reporting quality. These findings support the notion that varying career incentives of female directors contribute to the differences in their board monitoring performance. Finally, executive FIDs’ effective monitoring of financial reporting is more prominent in firms with higher monitoring costs and when they serve on more prestigious boards.

A study into strain sensor of cement-based material using CPW transmission lines

Abstract Based on the theory of coplanar waveguide (CPW) transmission line, a novel microwave non-destructive strain monitoring sensor specifically designed for cement-based material structures is presented in this study. The aim is to establish the relationship between the variation of the S11 phase parameter of the CPW strain sensor and the structural strain, utilizing a linear analysis. The feasibility of the strain monitoring by the CPW sensor is validated through simulations and experiments. The obtained results demonstrate a strong linear correlation between the phase change of the S11 parameter and the strain, with a goodness of fit of 0.987. The simulated strain sensor exhibits a sensitivity of 48.83 ppm/με, while the experimental measurement sensor shows a sensitivity of 65.82 ppm/με. These findings highlight the potential significance of the proposed method, offering a new approach that is characterized by high sensitivity, low cost, and simplicity for strain monitoring in concrete structures. Among them, the sensor cement mortar matrix made in this study was mixed with the recycled material made of waste glass steel FRP after a certain treatment process. The development of this method holds promise for the advancement of health monitoring in concrete structures.

FinTech in City Management

This study examines how FinTech is influencing modern urban governance and how these technologies are helping to address global urban challenges.It was found that in the modern city, FinTech is used to optimize the provision of public services, and mobile applications and online platforms allow city residents to easily pay bills for these services and monitor costs. FinTech is also an important catalyst for reforms in the field of urban transport systems, through mobile applications today you can order a taxi, monitor the movement of urban transport, pay for fares, manage traffic flows, which makes public transport more accessible and convenient for city dwellers. All this allows you to avoid traffic jams and improve public safety.The functional determinacy between modern financial technologies and city management is established, the opportunities provided by FinTech for optimizing city infrastructure management processes are revealed. Cases of how cities can use financial technologies to solve their problems and improve the quality of communal services are analyzed. The problem of implementing FinTech solutions for effective management decision-making with an analysis of public opinion is revealed. The importance of taking into account the financial stability of cities when using innovative financial solutions for the development of modern cities is emphasized. Attention is focused on the development of innovations and new financial opportunities for cities and their residents when using technologies to improve the quality of life of citizens and the development of the local economy.

Cost-utility analysis of ferric derisomaltose versus ferric carboxymaltose in patients with inflammatory bowel disease and iron deficiency anemia in England

Aims Anemia is the most common extraintestinal complication of inflammatory bowel disease (IBD), with approximately half of cases caused by iron deficiency (ID). Intravenous iron is the preferred ID anemia (IDA) treatment where oral iron is contraindicated, ineffective or not tolerated, or where ID correction is urgent. The objective was to evaluate the cost-utility of ferric derisomaltose (FDI) versus ferric carboxymaltose (FCM) in patients with IBD and IDA in England, in whom IV iron treatment is preferred. Materials and methods A patient-level simulation model was developed, capturing quality of life (QoL) differences based on SF-36v2 data from the PHOSPHARE-IBD randomized controlled trial, monitoring and incidence of post-infusion hypophosphatemia, and number of iron infusions required. Analyses were conducted over a five-year time horizon from the Department of Health and Social Care (DHSC) perspective, with healthcare provider and societal perspectives adopted in separate analyses. Future costs and effects were discounted at 3.5% per annum and one-way and probabilistic sensitivity analyses were performed. Results FDI increased quality-adjusted life expectancy by 0.075 QALYs versus FCM from 2.57 QALYs to 2.65 QALYs per patient. Patients receiving FDI required 1.63 fewer iron infusions over the five-year time horizon, driving infusion-related cost savings of GBP 496 per patient (GBP 2,188 versus GBP 1,692) from the DHSC perspective. Costs of monitoring and treating hypophosphatemia after FCM were GBP 226, yielding total savings of GBP 722 per patient (GBP 2,414 versus GBP 1,692) over the five-year time horizon. FDI also led to reduced costs versus FCM in the societal and provider analyses and was therefore the dominant intervention across all three perspectives. Limitations The analysis did not capture patient adherence, hypophosphatemic osteomalacia, or fractures. Conclusions Results showed that FDI improved patient QoL and reduced direct healthcare expenditure versus FCM in patients with IBD and IDA in England.

Biosensors for ocean acidification detection

Ocean acidification is a global environmental problem that significantly impacts Marine ecosystems and biodiversity. The traditional chemical analysis method has the problems of complex equipment and high cost in ocean acidification monitoring. In recent years, fluorescent protein biosensor technology, as an innovative monitoring method, has provided a new solution for the real-time detection of ocean acidification. Compared with traditional chemical analysis methods, fluorescent protein biosensors have the advantages of simple operation, high sensitivity and low cost. Current studies have demonstrated the potential of fluorescent protein biosensors for ocean acidification monitoring. The researchers designed a variety of fluorescent protein biosensors and conducted indoor and outdoor experimental validation. These results show that fluorescent protein biosensors can detect ocean acidification quickly and accurately and maintain stable performance under different environmental conditions. Further studies are needed to verify the consistency and reliability of fluorescent protein biosensors and traditional chemical analysis methods for ocean acidification monitoring. Future research directions include further improving the performance of the fluorescent protein biosensor, increasing its sensitivity and stability, and verifying its application in real Marine environments. This will help establish a better monitoring network for ocean acidification and provide a reliable scientific basis for Marine environmental protection and management decisions. The development and application of fluorescent protein biosensor technology will provide important support and guidance for us to better understand the impact of ocean acidification.

The cost of monitoring in time-based prospective memory

Time-based prospective memory (TBPM) involves remembering to perform actions at specific times in the future. Several studies suggest that monetary consequences improve prospective remembering; however, the effect of monetary consequences on strategic time monitoring (i.e., clock-checking behaviour) in TBPM is still unknown. The present study investigated how the monetary costs on clock-checking affected TBPM accuracy and strategic time monitoring. Participants performed an ongoing lexical decision task while carrying out a TBPM task every two minutes. Motivational incentives were manipulated across three experimental conditions: a single-cost condition in which missed TBPM responses led to monetary deductions, a double-cost condition in which both missed responses and time monitoring led to monetary deductions, and a control condition with no monetary deductions. Overall, the findings indicated that monetary costs on clock-checking prompted more parsimonious strategic time monitoring behaviour, which negatively impacted TBPM accuracy. These results emphasize the importance of weighing the motivational aspects involved in strategic monitoring, shedding light on the complex relationship between clock-checking behaviour, its consequences, and TBPM performance.

Estimating the clinical and budgetary impact of using angiotensin receptor neprilysin inhibitor as first line therapy in patients with HFrEF.

Recent updates of international treatment guidelines for heart failure with reduced ejection fraction (HFrEF) differ regarding the use of angiotensin receptor neprilysin inhibitor (ARNI) as first-line treatment. The American Heart Association/American College of Cardiology/Heart Failure Society of America (AHA/ACC/HFSA) 2022 guidelines gives ARNI a Class IA recommendation for HFrEF patients while the European Society of Cardiology's guidelines are less clear when ARNI could be considered as first line treatment option in de novo patients. This study aimed to model the clinical and budgetary outcomes of implementing these guidelines, comparing conservative ARNI prescription patterns with less conservative in Sweden and in the United Kingdom. A health economic model was developed to compare different treatment patterns for HFrEF. Incident cohorts were included on an annual basis and followed over 10years. The model included treatment specific all-cause mortality and hospitalization rates, as well as drug acquisition, monitoring, and hospitalization costs. Increasing the use of ARNI could lead to about 7000-12300 life years gained and 2600-4600 hospitalizations prevented in Sweden. These health benefits come with an additional cost of 112-195 million euros. Similar results were estimated for the United Kingdom, albeit on a larger population. Increasing the proportion of patients receiving ARNI instead of angiotensin converting enzyme inhibitors as first-line treatment of HFrEF will lead to a considerable number of additional life years gained and prevented hospitalizations but with additional cost in terms of health care expenditure in Sweden and in the United Kingdom.

Interpretable machine learning for predicting the fate and transport of pentachlorophenol in groundwater

Pentachlorophenol (PCP) is a commonly found recalcitrant and toxic groundwater contaminant that resists degradation, bioaccumulates, and has a potential for long-range environmental transport. Taking proper actions to deal with the pollutant accounting for the life cycle consequences requires a better understanding of its behavior in the subsurface. We recognize the huge potential for enhancing decision-making at contaminated groundwater sites with the arrival of machine learning (ML) techniques in environmental applications. We used ML to enhance the understanding of the dynamics of PCP transport properties in the subsurface, and to determine key hydrochemical and hydrogeological drivers affecting its transport and fate. We demonstrate how this complementary knowledge, provided by data-driven methods, may enable a more targeted planning of monitoring and remediation at two highly contaminated Swedish groundwater sites, where the method was validated. We evaluated 6 interpretable ML methods, 3 linear regressors and 3 non-linear (i.e., tree-based) regressors, to predict PCP concentration in the groundwater. The modeling results indicate that simple linear ML models were found to be useful in the prediction of observations for datasets without any missing values, while tree-based regressors were more suitable for datasets containing missing values. Considering that missing values are common in datasets collected during contaminated site investigations, this could be of significant importance for contaminated site planners and managers, ultimately reducing site investigation and monitoring costs. Furthermore, we interpreted the proposed models using the SHAP (SHapley Additive exPlanations) approach to decipher the importance of different drivers in the prediction and simulation of critical hydrogeochemical variables. Among these, sum of chlorophenols is of highest significance in the analyses. Setting that aside from the model, tetra chlorophenols, dissolved organic carbon, and conductivity found to be of highest importance. Accordingly, ML methods could potentially be used to improve the understanding of groundwater contamination transport dynamics, filling gaps in knowledge that remain when using more sophisticated deterministic modeling approaches.

P1070 Utilization of HLA-DQA1*05 haplotype testing in routine clinical practice to stratify advanced therapies: A prospective pilot study

Abstract Background A potential association between HLA-DQA1*05 allele and development of anti-drug antibodies in Anti-TNF treated Crohn’s Disease patients is reported in the PANTS study. The utility of stratifying treatment based on the HLA-DQA1*05 status has not been evaluated in a biomarker stratified clinical trial and there are no prospective studies evaluating the impact of using HLADQA1*05 in routine clinical practice to decide on monotherapy versus combo therapy while initiating on anti-TNFs. We aimed to determine the impact of carriage of HLADQA1*05 allele to guide the need for concomitant immunomodulators in IBD patients planned for Infliximab therapy. Methods In our prospective study, 97 adult IBD patients were included. All patients were screened for HLADQ2 haplotype as part of their routine pre-biologic screen. Stratification was done according to the presence of HLA-DQA1*05 haplotype. HLADQA1*05 positive patients were assigned combo therapy with Infliximab combined with either methotrexate or azathioprine. HLADQA1*05 negative patients were given infliximab monotherapy unless another indication for concomitant immunomodulation was present. Patients were followed for a minimum of one year after drug initiation. Primary outcome was drug persistence, expressed as time to discontinuation of infliximab, segregated by the treatment decision based on HLA-DQA1*05 status. Secondary outcomes were proportion of patients developing anti-drug antibodies and time to antibody development. Statistical analysis was done using Kaplan-Meier curves and log-rank test. Results Baseline characteristics are detailed in Table 1. HLA-DQA1*05 was positive in 41/97(42%) of patients and combo therapy was offered to 33/41(80%) of those patients. Immunomodulators were avoided in 39/97(40.2%) patients representing the subset of patients with negative HLADQA*105 to whom no immunomodulator was offered. There was no statistically significant difference in drug persistence rates between the groups treated based on HLA-DQA*105 status. 54/97(55.6%) of the patients developed anti-infliximab antibodies during their follow-up (25/41(60.9 %) in HLA positive and 29/56 (51.7%) in HLA negative). Neutralizing drug antibodies with absent drug levels were detected in 15/97(15.5%) of patients (8/41(19.5%) in HLA positive, 7/56(12.5%) in HLA negative). The median time to antibody development was 33.5 weeks (IQR 22-46.7). Conclusion This is the first prospective study suggesting HLA-DQA1*05 haplotype testing can be used in routine clinical practice to stratify therapy based on the need for immunomodulators in infliximab treated IBD patients. HLA-DQA1*05 negative patients may be started on monotherapy with potential for improving safety and reducing costs of immunomodulator monitoring.

Cost-effectiveness of testosterone treatment utilising individual patient data from randomised controlled trials in men with low testosterone levels.

Testosterone is safe and highly effective in men with organic hypogonadism, but worldwide testosterone prescribing has recently shifted towards middle-aged and older men, mostly with low testosterone related to age, diabetes and obesity, for whom there is less established evidence of clinical safety and benefit. The value of testosterone treatment in middle-aged and older men with low testosterone is yet to be determined. We therefore evaluated the cost-effectiveness of testosterone treatment in such men with low testosterone compared with no treatment. A cost-utility analysis comparing testosterone with no treatment was conducted following best practices in decision modelling. A cohort Markov model incorporating relevant care pathways for individuals with hypogonadism was developed for a 10-year-time horizon. Clinical outcomes were obtained from an individual patient meta-analysis of placebo-controlled, double-blind randomised studies. Three starting age categories were defined: 40, 60 and 75 years. Cost utility (quality-adjusted life years) accrued and costs of testosterone treatment, monitoring and cardiovascular complications were compared to estimate incremental cost-effectiveness ratios and cost-effectiveness acceptability curves for selected scenarios. Ten-year excess treatment costs for testosterone compared with non-treatment ranged between £2306 and £3269 per patient. Quality-adjusted life years results depended on the instruments used to measure health utilities. Using Beck depression index-derived quality-adjusted life years data, testosterone was cost-effective (incremental cost-effectiveness ratio <£20,000) for men aged <75 years, regardless of morbidity and mortality sensitivity analyses. Testosterone was not cost-effective in men aged >75 years in models assuming increased morbidity and/or mortality. Our data suggest that testosterone is cost-effective in men <75 years when Beck depression index-derived quality-adjusted life years data are considered; cost-effectiveness in men >75 years is dependent on cardiovascular safety. However, more robust and longer-term cost-utility data are needed to verify our conclusion.