Time Trade-off Research Articles

Rural population\u2019s preferences matter: a value set for the EQ-5D-3L health states for China\u2019s rural population

PurposeTo develop an EQ-5D-3L social value set based on Chinese rural population’s preferences using the time trade-off (TTO) method, and to compare the differences in preferences on health states between China urban and rural population.MethodsBetween Sep 2013 and Nov 2013, a total of 1201 participants were recruited from rural areas of five Chinese cities (Beijing, Chengdu, Guiyang, Nanjing, and Shenyang) using a quota sampling method. Each respondent valued 13 health states using the TTO, and a total of 97 EQ-5D-3L health states were directly valued for estimating the value set. Various models with different specifications were explored at both aggregate and individual levels. The final model was determined by a set of predefined selection criteria.FindingsAn ordinary least square model at the aggregate level included 10 dummy variables for specifying the level 2 and 3 for each dimension and an N3 term presenting any dimension on level 3 was selected as the final model. The final model provides a value set ranges from − 0.218 to 0.859. The predicted utility values were highly correlated with but consistently lower than that of the published Chinese EQ-5D-3L value set (for urban population).ConclusionThe availability of the China rural value set provides a set of social preferences weights for researchers and policy decision-makers for use in China rural area.

A Genetic-algorithm-based Approach to the Design of DCT Hardware Accelerators

As modern applications demand an unprecedented level of computational resources, traditional computing system design paradigms are no longer adequate to guarantee significant performance enhancement at an affordable cost. Approximate Computing (AxC) has been introduced as a potential candidate to achieve better computational performances by relaxing non-critical functional system specifications. In this article, we propose a systematic and high-abstraction-level approach allowing the automatic generation of near Pareto-optimal approximate configurations for a Discrete Cosine Transform (DCT) hardware accelerator. We obtain the approximate variants by using approximate operations, having configurable approximation degree, rather than full-precise ones. We use a genetic searching algorithm to find the appropriate tuning of the approximation degree, leading to optimal tradeoffs between accuracy and gains. Finally, to evaluate the actual HW gains, we synthesize non-dominated approximate DCT variants for two different target technologies, namely, Field Programmable Gate Arrays (FPGAs) and Application Specific Integrated Circuits (ASICs). Experimental results show that the proposed approach allows performing a meaningful exploration of the design space to find the best tradeoffs in a reasonable time. Indeed, compared to the state-of-the-art work on approximate DCT, the proposed approach allows an 18% average energy improvement while providing at the same time image quality improvement.

Defining utility values for patients with tardive dyskinesia

Objective To measure health state preferences and estimate utility values for tardive dyskinesia (TD) from the perspective of the US general population, accounting for factors affecting quality of life (QOL). Methods Participants from the general population were recruited and asked to watch and assess videos of professional actors simulating nine health states, including psychiatric disorders with/without TD and moderate-to-severe TD without any underlying disease. Time tradeoff (TTO) methods were used to elicit utility values, which ranged from −1 (worse than death) to +1 (perfect health) and represented individual preferences for avoiding specific health states associated with TD. Lower TTO utility values indicated individuals’ willingness to give up more years of life to avoid living in each health state. Results Based on TTO responses (n = 157), mean ± standard deviation utility for TD alone was 0.59 ± 0.38. Mean utilities for schizophrenia with negative symptoms (without TD: 0.43; with TD: 0.29) and positive symptoms (without TD: 0.44; with TD: 0.30) were generally lower than those for bipolar disorder (without TD: 0.59; with TD: 0.46) and major depressive disorder (without TD: 0.60; with TD: 0.44). According to utility decrements associated with TD (0.13–0.16), respondents were willing to give up 1.3 to 1.6 years during a 10-year lifespan to avoid living with TD. Conclusions Utility decrements for TD in this study were slightly larger than previously reported values, potentially due to incorporation of QOL and social consequences in TD health state descriptions. An important limitation of this analysis is that participants’ willingness to trade future years of healthy life may not indicate actual willingness to accept the life decrement. These findings can be leveraged to improve cost-effectiveness analyses used to assess the value of treatments for TD.

Japanese preference weights of the Adult Social Care Outcomes Toolkit for Carers (ASCOT-Carer)

PurposeWe developed preference weights of the Adult Social Care Outcomes Toolkit for Carers (ASCOT-Carer) in Japan.MethodsWe used best–worst scaling (BWS) and composite time trade-off (cTTO) to determine the preference weights for ASCOT-Carer states in the general population. TTO values were applied to convert the BWS scores to utilities. The sample number was approximately 1000 for the BWS survey and 200 for the TTO survey. Whereas face-to-face surveys by computer-assisted interviewing were adopted for the TTO tasks, a web-based survey was used for the BWS tasks. In the BWS tasks, the ASCOT-Carer states were presented, and the “best,” “worst,” “second best,” and “second worst” domains in a profile were selected. A mixed logit model was applied to the BWS data.ResultsThe respondents’ background was similar to that of the general population, although the number of people in the age and sex categories was equal. The preference weights for calculating the utilities of the ASCOT-Carer states were estimated. The estimated utilities of the ASCOT-Carer states were distributed between 1 and 0.02. All preference weights were consistent. The item with the highest preference weight was level 1 in the “space and time to be yourself.” The least preferred item was level 4 in the “space and time to be yourself” and “control over daily life” domains.ConclusionWe established Japanese preference weights for ASCOT-Carer states, the first weights of an Asian country. The estimated utilities can contribute to the measurement of caregivers’ social care-related QoL and perform of cost-effectiveness analyses.

Development of an EQ-5D Value Set for India Using an Extended Design (DEVINE) Study: The Indian 5-Level Version EQ-5D Value Set

ObjectivesThis study aimed to develop the Indian 5-level version EQ-5D (EQ-5D-5L) value set, which is a key input in health technology assessment for resource allocation in healthcare. MethodsA cross-sectional survey using the EuroQol Group’s Valuation Technology was undertaken in a representative sample of 3548 adult respondents, selected from 5 different states of India using a multistage stratified random sampling technique. The participants were interviewed using a computer-assisted personal interviewing technique. This study adopted a novel extended EuroQol Group’s Valuation Technology design that included 18 blocks of 10 composite time trade-off (c-TTO) tasks, comprising 150 unique health states, and 36 blocks of 7 discrete choice experiment (DCE) tasks, comprising 252 DCE pairs. Different models were explored for their predictive performance. Hybrid modeling approach using both c-TTO and DCE data was used to estimate the value set. ResultsA total of 2409 interviews were included in the analysis. The hybrid heteroscedastic model with censoring at −1 combining c-TTO and DCE data yielded the most consistent results and was used for the generation of the value set. The predicted values for all 3125 health states ranged from −0.923 to 1. The preference values were most affected by the pain/discomfort dimension. ConclusionsThis is the largest EQ-5D-5L valuation study conducted so far in the world. The Indian EQ-5D-5L value set will promote the effective conduct of health technology assessment studies in India, thereby generating credible evidence for efficient resource use in healthcare.

Assessment of state-of-the-art deep learning based citrus disease detection techniques using annotated optical leaf images

Citrus (Citrus reticulata) plants are affected by several diseases and require keen attention to detect and cure the diseases in time; otherwise, significant financial loss is incurred. With the advancement of computer vision and deep learning techniques, identifying various diseases is becoming simpler. However, this process requires a proper dataset of infected leaves and a suitable detector to recognise the diseases. Because the publicly available citrus leaf datasets are not annotated, they are not suited for disease detection tasks. Therefore, a new dataset (called CCL’20) comprising images of infected citrus leaves with multiple classes of diseases, including precise annotations, is developed. Primarily, machine learning models are used in plant disease detection, and only limited deep learning models are utilised in agricultural applications. This paper has identified the CNN based detectors best suited for agricultural engineering, such as CenterNet, YOLOv4, Faster-RCNN, DetectoRS, Cascade-RCNN, Foveabox and Deformabe Detr, implemented and fine-tuned them to detect citrus leaf diseases using our CCL’20 dataset. Extensive performance and computational analysis is carried out to determine how effectively these models diagnose different stages of citrus leaf diseases. This paper presents the state-of-the-art CNN detectors for citrus leaf disease detection, evaluated based on their precision, recall, and other valuable parameters such as training parameters, inference time, memory usage, speed and accuracy trade-off for each model. The results show that the Scaled YOLOv4 P7 achieves fast and early prediction of the diseases, and CenterNet2 with Res2Net 101 DCN-BiFPN predicts the early stage of citrus leaf diseases with high accuracy to other recent and efficient detecting models.

Sample Size and Model Prediction Accuracy in EQ-5D-5L Valuations Studies: Expected Out-of-Sample Accuracy Based on Resampling with Different Sample Sizes and Alternative Model Specifications.

Background. National valuation studies are costly, with ∼1000 face-to-face interviews recommended, and some countries may deem such studies infeasible. Building on previous studies exploring sample size, we determined the effect of sample size and alternative model specifications on prediction accuracy of modeled coefficients in EQ-5D-5L value set generating regression analyses. Methods. Data sets (n = 50 to ∼1000) were simulated from 3 valuation studies, resampled at the respondent level and randomly drawn 1000 times with replacement. We estimated utilities for each subsample with leave-one-out at the block level using regression models (8 or 20 parameter; with or without a random intercept; time tradeoff [TTO] data only or TTO + discrete choice experiment [DCE] data). Prediction accuracy, root mean square error (RMSE), was calculated by comparing to censored mean predicted values to the left-out block in the full data set. Linear regression was used to estimate the relative effect of changes in sample size and each model specification. Results. Results showed that doubling the sample size decreased RMSE by on average 0.012. Effects of other model specifications were smaller but can when combined compensate for loss in prediction accuracy from a small sample size. For models using TTO data only, 8-parameter models clearly outperformed 20-parameter models. Adding a random intercept, or including DCE responses, also improved mean RMSE, most prominently for variants of the 20-parameter models. Conclusions. The prediction accuracy impact of further increases in sample size after 300 to 500 were smaller than the impact of combining alternative modeling choices. Hybrid modeling, use of constrained models, and inclusion of random intercepts all substantially improve the expected prediction accuracy. Beyond a minimum of 300 to 500 respondents, the sample size may be better informed by other considerations, such as legitimacy and representativeness, than by the technical prediction accuracy achievable.HighlightsIncreases in sample size beyond a minimum in the range of 300 to 500 respondents provide smaller gains in expected prediction accuracy than alternative modeling approaches.Constrained, nonlinear models; time tradeoff + discrete choice experiment hybrid modeling; and including a random intercept all improved the prediction accuracy of models estimating values for the EQ-5D-5L based on data from 3 different valuation studies.The tested modeling choices can compensate for smaller sample sizes.

POSB381 Time Trade-Off Utility in Adult Patients with Atopic Dermatitis

Atopic dermatitis (AD) is a frequent chronic inflammatory dermatological disease. Health-related quality of life in AD has been widely investigated; nevertheless, direct utility values have been rarely studied. The objective of this study was to elicit time trade-off (TTO) utility values in adult patients with AD.

Quality of life of diabetes patients in North India

Background: India is witnessing a dramatic rise in the prevalence of diabetes mellitus. In this study, quality of life (QOL) of patients with diabetes and its determinants were assessed. Second, the valuation of QOL using different methods of measurement was examined. Methods: A community-based survey comprising 306 adults diagnosed with diabetes was undertaken in an urban slum area of Chandigarh city. Direct methods of QOL assessment such as time trade-off (TTO) and Visual Analog Scale (VAS) along with indirect like EuroQol 5-Dimensional 5-Level Instrument (EQ-5D-5L) and the QOL Instrument for Indian Diabetes Patients (QOLID) were used. Multiple linear regression was used to compute coefficients to assess point estimate of QOL using the Indian QOLID tool. Results: Overall, health utility scores for a person with diabetes were 0.68 (with TTO method), 0.60–0.64 (with VAS) analog scale, and EQ-5D-5L method, respectively. Valuation of QOL using direct methods yielded utility values which were significantly higher than indirect methods (EQ-5D-5L). Conclusion: Overall, this study found that diabetes is responsible for physical, psychological, and social role disturbance among the patients. In addition, choice of using direct or indirect methods of utility estimation may have practical implications while calculating incremental cost-effectiveness ratios.

A High-Performance ECC Processor Over Curve448 Based on a Novel Variant of the Karatsuba Formula for Asymmetric Digit Multiplier

In this paper, we present a high-performance architecture for elliptic curve cryptography (ECC) over Curve448, which to the best of our knowledge, is the fastest implementation of ECC point multiplication over Curve448 to date. Firstly, we introduce a novel variant of the Karatsuba formula for asymmetric digit multiplier, suitable for typical DSP primitive with asymmetric input. It reduces the number of required DSPs compared to previous work and preserves the performance via full parallelization and pipelining. We then construct a 244-bit pipelined multiplier and interleaved fast reduction algorithm, yielding a total of 12 stages of pipelined modular multiplication with four stages of input delay. Additionally, we present an efficient Montgomery ladder scheduling with no additional register is required. The implementation on the Xilinx 7-series FPGA: Virtex-7, Kintex-7, Artix-7, and Zynq 7020 yields execution times of 0.12, 0.13, 0.24, and 0.24 ms, respectively. It increases the throughput by 242% compared to the best previous work on Zynq 7020 and by 858% compared to the best previous work on Virtex-7. Furthermore, the proposed architecture optimizes nearly 63% efficiency improvement in terms of Area×Time tradeoff. Lastly, we extend our architecture with well-known side-channel protections such as scalar blinding, base-point randomization, and continuous randomization.

POSA319 Development of a Diminishing Marginal Disutility Model for Intravenous Iron Infusions Based on Data from a Time Trade-Off Study in China

In patients with iron deficiency anemia (IDA), intravenous iron (IVI) is the preferred and most efficacious treatment when oral iron cannot be used or where rapid iron delivery is required; however, IV infusions are burdensome for patients and require them to travel to specialist infusion units, which can have a detrimental effect on patient quality of life (QoL). Also, the number of visits varies greatly between different IVI formulations. The aim of the present study was to quantify the magnitude of the effect of different annual infusion rates on QoL.

On EMG Based Dexterous Robotic Telemanipulation: Assessing Machine Learning Techniques, Feature Extraction Methods, and Shared Control Schemes

Electromyography (EMG) signals are commonly used for the development of Muscle Machine Interfaces. EMG-based solutions provide intuitive and often hand-free control in a wide range of applications that range from the decoding of human intention in classification tasks to the continuous decoding of human motion employing regression models. In this work, we compare various machine learning and feature extraction methods for the creation of EMG based control frameworks for dexterous robotic telemanipulation. Various models are needed that can decode dexterous, in-hand manipulation motions and perform hand gesture classification in real-time. Three different machine learning methods and eight different time-domain features were evaluated and compared. The performance of the models was evaluated in terms of accuracy and time required to predict a data sample. The model that presented the best performance and prediction time trade-off was used for executing in real-time a telemanipulation task with the New Dexterity Autonomous Robotic Assistance (ARoA) platform (a humanoid robot). Various experiments have been conducted to experimentally validate the efficiency of the proposed methods. The robotic system is shown to successfully complete a series of tasks autonomously as well as to efficiently execute tasks in a shared control manner.

POSA381 Health State Utility Values for Metastatic Pancreatic Cancer in Japan, Based on the Vignette-Based Approach

There are fewer studies of utility values that focus on different health status specifically within metastatic pancreas cancer or specific adverse events and related to chemotherapy using vignette-based methods. We evaluated Japanese societal-based health related utility values for metastatic pancreas cancer and different grade toxicities commonly associated with chemotherapy treatments using composite time trade-off (cTTO).

Strut Onlay Allograft in Revision Arthroplasty: Osseous Union and Clinical Outcome.

To evaluate the clinical outcome and the osseous union of strut onlay allografts (SOAs) used as adjunct in revision total joint arthroplasty (TJA). Patients that had previously undergone SOA augmentation were considered for inclusion. Patients were invited to provide information for the following: Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), EuroQol five dimension score (EQ-5D) and Parker mobility score. Osseous union rates between SOA and the host bone were determined by radiograph with the Emerson classification system. Bone mineral density was measured via quantitative computed tomography. Seventeen patients were identified, at a mean follow-up of 2.8 years. The median total WOMAC score was 22 [interquartile range (IQR)=21]. The median EQ-5D score was 0.887 (IQR=0.350) (time trade-off). The Parker Mobility Score was 8.0 (IQR=3.5). Emerson stages of radiographic graft to host union were 'rounding off' in one case, 'partial bridging' in three and 'complete bridging' in 13. Quantitative computed tomography showed an average bone mineral density of approximately 1,300 mg/cm3. From our findings, it is concluded that SOAs used in revision total joint arthroplasty provide promising results and are recommended for broader clinical use. A complete osseous union between host and graft bone was observed in the majority of cases.

Transcranial direct current stimulation (tDCS) alters the pattern of information processing in children with ADHD: Evidence from drift diffusion modeling

ObjectivePerformance accuracy and reaction time in cognitive tasks are routinely used to evaluate the efficacy of tDCS to affect cognitive task performance. tDCS alters the excitability of targeted brain areas and thereby alters performance of cognitive tasks. The drift diffusion model (DDM) provides some additional measures to explore information processing style, such as (non)decision time, bias for decision, and speed of information processing. DDM parameters are informative for the study of cognitive impairments in children with ADHD. In the present study, we aimed to evaluate the impact of tDCS on cognitive performance via DDM measures. MethodsThis study conducted DDM modeling and reanalysis of two exploratory, single-blinded, within-subject design experiments, which were published earlier. In the first experiment, twenty- four children with ADHD performed a Go/ No- Go task during anodal or sham tDCS over the right dlPFC. In the second experiment, twenty- five children with ADHD performed the 1- back working memory task during anodal or sham tDCS over the left dlPFC. We reanalyzed the data after DDM modeling. ResultsThe conventional performance measures revealed no significant effect of tDCS on No- Go accuracy in the first experiment and 1-back accuracy in the second experiment. The 1-back reaction time and speed-accuracy tradeoff were however improved under the real stimulation condition. The DDM measures identified increased No-Go- bias and decision time with respect to inhibitory control, and an increased threshold and amount of information required for response in the 1- back test. ConclusionIn children with ADHD, anodal tDCS over the right dlPFC induces more conservative and less impulsive decisions. Furthermore, anodal tDCS over the left dlPFC enhanced efficacy of working memory performance with respect to agility and capacity. The experimental results show that drift diffusion modeling is useful for evaluation of the impact of tDCS on the style of information processing.

752 Acute coronary syndrome in young patients: long-term follow-up and quality of life assessment

Abstract Aims Early onset acute coronary syndrome (ACS) is associated with a more aggressive evolution and its consequences can be devastating to the quality of life (QOL), affecting the patient’s psychology, ability to work, and the socioeconomic burden. In the last decade, the incidence of ACS in young patients (≤45 years old) is increased but unfortunately, little is known about long-term follow-up and impact on quality of life. The aim of this study was to analyse the clinical evolutions and the QOL in this specific group of patients. Methods and results We included 91 consecutive young patients (≤45 years at the time of presentation) with ACS referred from October 2013 until March 2021 to our clinic. All enrolled patients underwent angiography. We analysed the clinical presentation, echocardiography, and therapy at the time of discharge. Furthermore, patients underwent telephone follow-up after 40 months: new hospitalizations, cardiovascular events, bleeding, and relevant changes in medical therapy were investigated. In addition, patients were also invited to participate to a survey to investigate QOL, sexual, and socioeconomic changes after ACS. QOL was explored through the EQ-5D scale using the time trade-off (TTO) and visual analogue scale (VAS) technique based on European values. Mean age was 40.6 ± 3.6 years and 17.6% were women. Most patients had obstructive coronary artery disease at angiography (90.1%) and 85.7% underwent PCI. At a median follow-up of 40 months, major adverse cardiovascular events (MACE) a composite of death, myocardial infarction, stroke and definite stent thrombosis, occurred in 12% of patients (Figure 1). Patient reported bleeding occurred in 29.8%, while bleeding requiring hospitalization in 3.6%. Univariate predictors of MACE were previous stroke, Killip class at presentation, current drug use, left ventricle ejection fraction, wall motion score index (WMSI), and haemoglobin at admission. Young patients showed reduced levels of QOL (TTO: 0.85 ± 0.17—VAD: 0.79 ± 0.17), with higher levels among individuals without obstructive coronary artery disease (Figure 2). Predictors of lower quality of life were WMSI, left anterior descending (LAD) stenting, left ventricular aneurysm and ventricular thrombus (Figure 3). After 12 months from the index event, 31.5% of patients were still on dual antiplatelet therapy, and the mean number of medications was 4.65 ± 2.3. Conclusions In conclusion, young patients have a high residual risk of ischaemic and bleeding events and impaired QOL. Optimization of medical therapy and better patient information is of upmost importance to mitigate residual risk of adverse events.

Accounting for Unobservable Preference Heterogeneity and Evaluating Alternative Anchoring Approaches to Estimate Country-Specific EQ-5D-Y Value Sets: A Case Study Using Spanish Preference Data

ObjectivesThe EuroQol Group published the EQ-5D-Y valuation protocol that recommends 2 valuation techniques to elicit preferences: composite time trade-off (C-TTO) and discrete choice experiments (DCEs). The protocol left the decision of what modeling approach to use open for researchers. Our aims were to explore modeling strategies allowing generation of EQ-5D-Y value sets and to produce an EQ-5D-Y Spanish value set. MethodsWe used EQ-5D-Y DCE and C-TTO data collected in Spain following the protocol and adopted a staged approach for our modeling exercise. First, we selected the best performing DCE latent class model and evaluated models from 2 to 10 classes. We selected the preferred model based on best goodness of fit in terms of the Bayesian information criterion. We considered 2 anchoring approaches to estimate utility values: (1) pits state anchoring and (2) hybrid models (using all available C-TTO responses). All analysis were weighted to be representative of the Spanish population. ResultsWe collected 1005 DCE and 200 C-TTO interviews. We selected a DCE model including 4 classes. Hybrid models using all available C-TTO observations produced a narrower range of values than the pits state anchoring approach. ConclusionsIn this article, we have presented an EQ-5D-Y value set that can be used for cost-utility analysis in Spain. The international EQ-5D-Y valuation protocol should be updated to include a different set of health states for the C-TTO experiment if researchers wish to use alternative anchoring approaches to the “pits state.”

Eliciting health state utilities for Aromatic L-amino Acid Decarboxylase (AADC) deficiency: a UK vignette study

PurposeThe aim of this study was to generate health state utilities for aromatic L-amino acid decarboxylase (AADC) deficiency, a rare genetic, lifelong neurogenerative condition predominantly manifesting in young infants.MethodsParticipants were presented with health state vignettes. These had been previously developed based on published literature, clinician input, interviews with parents of AADC deficiency patients and expert opinion. A total of 5 health state vignettes were presented: bedridden, head control, sitting unsupported, standing with assistance and walking with assistance. Health state utilities (HSU) were elicited using time-trade off (TTO; 10-year time horizon) and the standard gamble (SG). The vignettes were completed online by panel participants drawn from a representative sample of the United Kingdom residential population.ResultsA total of 1598 participants completed the vignettes. Around 21% had incongruent responses (higher utilities for the bedridden compared to walking health states). Incongruent responses were associated with shorter task completion times, gender and parental status. These responses were removed from the analysis. Health state utilities (HSU) increased correspondingly as health states improved for both the TTO and SG. The mean HSU (standard deviation) for the TTO task were: bedridden state 0.49 (0.34); head control 0.54 (0.33), sitting unsupported 0.63 (0.31); standing with assistance 0.68 (0.31); and walking with assistance 0.73 (0.31). For the SG, mean health state utilities were: 0.56 (0.28), 0.57 (0.27), 0.67 (0.24), 0.70 (0.24), and 0.75 (0.25), respectively.ConclusionHealth state utilities were derived for AADC deficiency through a vignette study. These will be used for a cost-effectiveness model of an AADC deficiency treatment.

P.0328 Adult bipolar disorder and attention deficit/hyperactivity disorder - a common comorbidity?

To explore the cost utility of cataract surgery in patients with stabilized vision-threatening diabetic retinopathy (DR).Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, China.Prospective case series.Patients diagnosed with cataracts combined with stabilized vision-threatening DR had successful phacoemulsification with foldable posterior chamber intraocular lens implantation. The corrected distance visual acuity (CDVA) and utility value obtained using the time tradeoff method at 3-month postoperative intervals were compared with those preoperative values. The cost per quality-adjusted life year gained was calculated using the bootstrap method. Sensitivity analyses were performed to test the robustness of the results.The study comprised 126 patients (153 eyes). All surgeries were successful. The weighted logMAR CDVA changed from 0.82 logMAR ± 0.34 (SD) to 0.58 ± 0.30 logMAR (P < .001). The utility values increased from 0.58 ± 0.14 to 0.72 ± 0.14 (P < .001). The gain in utility values was correlated with the postoperative weighted logMAR CDVA, the change between the postoperative and preoperative weighted logMAR CDVA, performance of bilateral cataract surgery, and duration of DR or diabetic macular edema. The patients gained 1.50 quality-adjusted life years by cataract surgery. The cost per quality-adjusted life year was US $768. This surgery was cost-effective at the threshold of US $22 526 per quality-adjusted life year in China. The cost per quality-adjusted life year varied from US $630 to US $8707 in sensitivity analyses.Cataract surgery was a cost-effective intervention for patients with coexisting, stabilized, vision-threatening DR.

The impact on quality of life of diet restrictions and disease symptoms associated with phenylketonuria: a time trade-off and discrete choice experiment study.

Phenylketonuria (PKU) is a metabolic disorder leading to a deficiency in the metabolism of phenylalanine (Phe). Elevated Phe levels in the blood, tissue and brain may lead to emotional, cognitive, and physical symptoms in adults. To control blood Phe levels, most individuals with PKU need to follow a strict, life-long Phe-restricted diet. The main objective of this study was to estimate the impact of PKU-related disease symptoms and dietary restrictions on health-related quality of life (HRQoL). This study was designed as a web-based survey using the methods of Time Trade-Off (TTO) and Discrete Choice Experiment with duration (DCETTO) in a survey of the Swedish general population and population with PKU. Data were collected using questionnaires for TTO diet (n = 509), TTO symptoms (n = 507), and DCETTO (n = 1117). The disutility of diet restrictions ranged from 0.050 for a partially restricted diet without medical food to 0.193 for a fully restricted diet with medical food in the TTO (DCE: 0.043-0.108). The disutility of experiencing symptoms (emotional, cognitive and physical) ranged from 0.148 for mild symptoms to 0.593 for severe symptoms in the TTO (DCE: 0.122-1.522). The study shows that both diet and symptoms have a significant negative impact on HRQoL in PKU and that utility estimates are largely consistent across methods and samples.