Time Trade-off Research Articles

The Efficiency of Surface Impedance Technique in the Transverse Wave Approach for the EM-Modeling of Fractal-Like Tree Structure used in 5G Applications

Fractal antenna technology is a promising approach for 5G applications because its complex nature offers optimization potential in terms of time and space trade-offs. However, the computational effort required to analyze such antennas is significant. This paper investigates the Advanced Transverse Wave Approach (ATWA), which utilizes the surface impedance technique to improve simulation efficiency. This study introduces and analyzes a fractal-like 5G tree structure, displaying improved computational accuracy and efficacy, as well as peak memory utilization compared to current works. The proposed approach demonstrates significant effectiveness in enhancing the performance of complex fractal antennas for 5G technology and shows promise for integration with cloud, fog, and edge computing environments. This integration could potentially optimize data processing and network efficiency in these advanced computing landscapes.

Estimation of health utility values for alopecia areata

PurposeAlopecia areata (AA) is an autoimmune-mediated inflammatory dermatological disease characterised by non-scarring hair loss affecting the scalp and sometimes other hair-bearing sites. This study aimed to elicit health state utility values (HSUVs) from the UK general population for AA using time trade off (TTO) interviews.MethodsVignette descriptions of health states defined by the extent of hair loss were developed (as well as one describing caregiver burden). These were developed using data from standardised patient reported outcome (PRO) measures, a literature review and qualitative interviews. Health states were defined based on the severity of alopecia tool (SALT), which assesses extensiveness of scalp hair loss. HSUVs were then elicited for each health state in TTO interviews with the UK public.ResultsOne caregiver and five patient health states were developed based on the literature review findings, clinical trial PRO (Hospital Anxiety and Depression Scale and Alopecia Areata Patient Priority Outcomes Questionnaire) data and qualitative interviews with patients (N = 11), clinical experts (N = 4) and caregivers of adolescents with AA (N = 10). These data showed a more severe impact among patients with more extensive hair loss. One hundred and twenty participants evaluated the vignettes in TTO interviews. Patient HSUVs ranged from 0.502 for the most extensive hair loss health state (SALT 50–100 + eyebrow and eyelash loss) to 0.919 (SALT 0–10) for the mildest health state. The caregiver HSUV was 0.882.ConclusionQuantitative and qualitative data sources were used to develop and validate vignettes describing different AA health states. Patient and caregiver HSUVs demonstrate a large impact associated with AA, especially for states defined by more extensive hair loss.

Is Blepharoplasty Cost-effective? Utility Analysis of Dermatochalasis and Cost-effectiveness Analysis of Upper Eyelid Blepharoplasty.

This cross-sectional prospective study measured utility values of upper eyelid dermatochalasis to quantify its impact on quality of life and assess cost-effectiveness of upper blepharoplasty. Utility of dermatochalasis was assessed using the standard reference gamble and time trade-off methods, with dual anchor points of perfect eye function and perfect health. The utility value obtained was used to create a Markov model and run a cost-effectiveness analysis of blepharoplasty as a treatment for dermatochalasis while utilizing the societal perspective. One hundred three patients with dermatochalasis recruited from an urban outpatient ophthalmology clinic completed the utility survey. The authors determined utility values for dermatochalasis ranging from 0.74 to 0.92 depending on the measurement method (standard reference gamble/time trade-off) and anchor points. The cost-effectiveness analysis yielded an incremental cost-effectiveness ratio of $3,146 per quality-adjusted life year, well under the conventional willingness-to-pay threshold of $50,000 per quality-adjusted life year. Probabilistic sensitivity analysis with Monte Carlo simulation demonstrated that blepharoplasty would be cost-effective in 88.1% of cases at this willingness-to-pay threshold. Dermatochalasis has an impact on quality of life that is significantly associated with level of perceived functional impairment. Rising health care costs have underscored the importance of providing value-based treatment to patients, and the results of this study suggest that blepharoplasty is a cost-effective treatment option for symptomatic bilateral upper eyelid dermatochalasis.

Performance Optimization Across the Edge-Cloud Continuum: A Multi-agent Rollout Approach for Cloud-Native Application Workload Placement

The advancements in virtualization technologies and distributed computing infrastructures have sparked the development of cloud-native applications. This is grounded in the breakdown of a monolithic application into smaller, loosely connected components, often referred to as microservices, enabling enhancements in the application’s performance, flexibility, and resilience, along with better resource utilization. When optimizing the performance of cloud-native applications, specific demands arise in terms of application latency and communication delays between microservices that are not taken into consideration by generic orchestration algorithms. In this work, we propose mechanisms for automating the allocation of computing resources to optimize the service delivery of cloud-native applications over the edge-cloud continuum. We initially introduce the problem’s Mixed Integer Linear Programming (MILP) formulation. Given the potentially overwhelming execution time for real-sized problems, we propose a greedy algorithm, which allocates resources sequentially in a best-fit manner. To further improve the performance, we introduce a multi-agent rollout mechanism that evaluates the immediate effect of decisions but also leverages the underlying greedy heuristic to simulate the decisions anticipated from other agents, encapsulating this in a Reinforcement Learning framework. This approach allows us to effectively manage the performance–execution time trade-off and enhance performance by controlling the exploration of the Rollout mechanism. This flexibility ensures that the system remains adaptive to varied scenarios, making the most of the available computational resources while still ensuring high-quality decisions.

A time trade-off study to determine health-state utilities of transplant recipients with refractory cytomegalovirus infection with or without resistance

BackgroundHealth-state utility values (HSUVs) for post-transplant refractory cytomegalovirus (CMV) infection (with or without resistance [R/R]) were determined using a time trade-off (TTO) survey completed by 1,020 members of the UK general public.MethodsExisting literature and qualitative interviews with clinicians experienced in treating R/R CMV were used to develop initial draft vignettes of health states. The vignettes were refined to describe three clinical states of R/R CMV: clinically significant and symptomatic (CS-symptomatic CMV); clinically significant and asymptomatic (CS-asymptomatic CMV); and non-clinically significant (non-CS CMV). Each clinical state was valued independently and combined with three events of interest: graft-versus-host disease; kidney graft loss; and lung graft loss to generate twelve vignettes. The final vignettes were evaluated by a sample of the UK general public using an online TTO survey. Exclusion criteria were applied to the final data to ensure that responses included in the analysis met pre-defined quality control criteria.ResultsOverall, 738 participants met the inclusion criteria and were included in the analysis. The sample was representative of the UK general population in terms of age and sex. Non-CS CMV had the highest mean HSUV (95% confidence interval) (0.815 [0.791, 0.839]), followed by CS-asymptomatic CMV (0.635 [0.602, 0.669]), and CS-symptomatic CMV (0.443 [0.404, 0.482]). CS-symptomatic CMV with lung graft loss had the lowest mean HSUV (0.289), with none of the health states considered on average worse than dead.ConclusionsPost transplant R/R CMV has substantial impact on the health-related quality of life of patients. The utility values obtained in this study may be used to support economic evaluations of therapies for R/R CMV infection.

Preference-based utility weights for the Individualized Neuromuscular Quality of Life Questionnaire (INQoL), with a focus on non-dystrophic myotonia (NDM).

The Individualized Neuromuscular Quality of Life Questionnaire (INQoL) is used to measure quality of life in neuromuscular disorders such as non-dystrophic myotonia (NDM). Here we report methods to estimate utilities, with a focus on NDM, from this questionnaire based on two preference elicitation exercises. Eight items from the INQoL were selected with input from three neuromuscular disorder clinical experts with expertise in treating NDM. A discrete choice experiment (DCE) survey of UK general public respondents (n = 508) described outcomes defined by the INQoL items. The same 8 items were also valued using time trade-off (TTO) face-to-face interviews (n = 200). A hybrid regression modelling approach combined both datasets to inform the utility weights. Hybrid modelling of DCE and TTO data in conjunction improved out-of-sample predictive accuracy. The selected INQoL utility model indicates substantial disutility associated with all eight dimensions of health, with the greatest losses associated with subjective items such as pain and depression. The hybrid modelling approach allows us to combine data from the two methodologies and maximize the information from each to inform the utility weights for the INQoL. The TTO is the more conventional valuation method, but combined with the larger DCE study produced better descriptive coverage. This is a relatively novel method for estimating weights which we think is particularly well suited to economic evaluations of orphan drugs.

Preference Sensitive Care and Shared Decision-Making in Lumbar Spinal Stenosis: A Scoping Review.

Scoping review. The objective of this study was to conduct a scoping review exploring the extent to which preference sensitivity has been studied in treatment decisions for lumbar spinal stenosis (LSS), utilizing shared decision-making (SDM) as a proxy. Preference-sensitive care involves situations where multiple treatment options exist with significant tradeoffs in cost, outcome, recovery time, and quality of life. LSS has gained research focus as a preference-sensitive care scenario. A scoping review protocol in accordance with "Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews" regulations was registered with the Open Science Framework (ID: 9ewup) and conducted across multiple databases from January 2000 to October 2022. Study selection and characterization were performed by 3 independent reviewers and an unbiased moderator. The search resulted in the inclusion of 16 studies varying in design and sample size, with most published between 2016 and 2021. The studies examined variables related to SDM, patient preferences, surgeon preferences, and decision aids (DAs). The outcomes assessed included treatment choice, patient satisfaction, and patient understanding. Several studies reported that SDM influenced treatment choice and patient satisfaction, while the impact on patient understanding was less clear. DAs were used in some studies to facilitate SDM. The scoping review identified a gap in comprehensive studies analyzing the preference sensitivity of treatment for LSS and the role of DAs. Further research is needed to better understand the impact of patient preferences on treatment decisions and the effectiveness of DAs in LSS care. This review provides a foundation for future research in preference-sensitive care and SDM in the context of lumbar stenosis treatment.

Prognostic Information on Progression to Dementia: Quantification of the Impact on Quality of Life.

The increasing interest in early identification of people at risk of developing dementia, has led to the development of numerous models aimed at estimating the likelihood of progression from mild cognitive impairment (MCI) to dementia. It is important to study both the need for and possible outcomes related with such prediction models, including the impact of risk predictions on perceived quality of life (QoL). This study aimed to quantify the impact that receiving a risk prediction on progression from MCI to dementia has on QoL. A Discrete Choice Experiment (DCE) and Time Trade Off (TTO) study were performed. Participants completed choice tasks related to dementia prognosis while imagining having MCI. We collected DCE data by an online survey, and TTO data via videoconferencing interviews. DCE data were analyzed using a mixed multinomial logit model and were anchored to a health state utility scale using mean observed TTO valuations. 296 people participated in the DCE and 42 in the TTO. Moderate and high predicted dementia risks were associated with decrements in utility (-0.05 and -0.18 respectively), compared to no prognostic information. Low predicted risk was associated with an increase in utility (0.06), as well as the availability of medication or lifestyle interventions (0.05 and 0.13 respectively). This study shows a significant impact of dementia risk predictions on QoL and highlights the importance of caution when sharing information about expected MCI disease courses.

Comparison of four value sets derived using different TTO and DCE approaches: application to the new region-specific PBM, AP-7D

BackgroundAP-7D is a newly developed preference-based measure (PBM) in East and Southeast Asia. However, no value set has been established yet. Comparison of the characteristics of value sets obtained by different methods is necessary to consider the most appropriate methodology for valuation survey of AP-7D.MethodWe surveyed the general population’s preference of AP-7D health states by four valuation methods (a) composite time trade-off (cTTO); (b) simple discrete choice experiment (DCE); (c) DCE with duration; and (d) ternary DCE. In Japan, we collected approximately 1,000 samples for cTTO tasks through a face-to-face survey and 2,500 samples for each of the three DCE tasks. Respondents were selected through quota sampling based on the sex and age. The cTTO data were analyzed using a linear mixed and tobit model; the DCE data were analyzed using a simple and panel conditional logit model. Where the results of the analysis showed inconsistencies, a constrained model was used.ResultsSince all the unconstrained models, except simple DCE, showed one or more inconsistencies, the constrained model was used for the analyses. The minimum values for the models were as follows: TTO model, -0.101; simple DCE model, -0.106; DCE with duration model, -0.706; ternary DCE model, -0.306. The score for the DCE with the duration model was much lower than that for the other models. Although the value sets for AP-7D differed among the four valuation methods, the ternary DCE model showed intermediate characteristics between those of the cTTO and DCE with duration models. As compared with to EQ-5D-5L, the distributions of all the scores on the Japanese AP-7D moved to the left. Although “Energy” was one of the domains with the least influence on the AP-7D score in all four models, “Burden to others” had the largest impact on the preferences.ConclusionWe constructed four value sets using different TTO and DCE methods. Our findings are expected not only to contribute to the development of AP-7D, but also other preference-based measures.

Comparing heuristic valuation processes between health state valuation from child and adult perspectives

ObjectivesHealth state valuation assumes that respondents trade off between all aspects of choice tasks and maximize their utility. Yet, respondents may use heuristic valuation processes, i.e., strategies to simplify or avoid the trade-offs that are core to health state valuation. The objective of this study is to explore if heuristic valuation processes are more prevalent for valuation from a 10-year-old child’s perspective compared to the use of an adult perspective.MethodsWe reused existing data in which EQ-5D health states were valued from adult and child perspectives with composite time trade-off (cTTO) and discrete choice experiment (DCE) tasks. Our analyses focused on comparing completion time and responding patterns across both perspectives. We also explored how reflective of a set of heuristic strategies respondents’ choices were in both perspectives.ResultsWe found no evidence for systematic differences in completion time across perspectives. Generally, we find different responding patterns in child perspectives, e.g., more speeding, dominance violations, and clustering of utilities at 1.0, 0.8, and 0. Very few heuristic strategies provide a coherent explanation for the observed DCE responses.ConclusionOur results provide some, albeit indirect, evidence for differences in heuristic valuation processes between perspectives, although not across all data sources. Potential effects of heuristic valuation processes, such as transfer of responsibility, may be identified through studying responding patterns in cTTO and DCE responses.

Abstract WP13: Derivation and Validation of Utility Weights for the Modified Rankin Scale From the AcT Thrombolysis Trial

Introduction: Utility-weighted mRS (UW-mRS) is increasingly being adopted as an important clinical endpoint in stroke trials as it offers some gains in statistical efficiency and power when estimating treatment effects. The widely used utility weights for estimating UW-mRS, derived from a systematic review of acute stroke trials, are prone to substantial variability across and between mRS categories. This study aims to derive utility weights for UW-mRS by directly mapping 5-item EuroQoL (EQ-5D-5L) responses to mRS scores. Methods: Data were collected from all patients included in Alteplase compared to Tenecteplase (AcT) trial. Quality of life at 90 days post-randomization was assessed using EQ-5D-5L. Health utilities (EQ-5D index) were estimated using the time trade-off approach based on Canadian norms and imputed as zero for patients who died. Using a predictive linear model, utility weights were derived by regressing the ordinal mRS on the utilities. Model performance was measured using R 2 and root mean square error (RMSE) after 5-fold cross-validation. We compared the distribution of the UW-mRS scores using the systematic review and model-based weights. Results: Of the 1503 acute stroke patients who completed the EQ-5D-5L questionnaire at 90 days, 717 (47.7%) were female, and the median (interquartile range [IQR]) age was 74.0 (20.0). The median (IQR) estimated health utility was 0.81 (0.52). The utility weights for mRS categories 0-6 were 0.93, 0.90, 0.80, 0.67, 0.41, 0.24, and 0.00. The model performed well after 5-fold cross-validation (R 2 = 0.89; RMSE = 0.12). The model-based weights had higher mean and median UW-mRS scores but smaller variability across mRS levels than those from the systematic review-based weights. There was no statistically significant difference in the median UW-mRS scores across both treatment groups for each utility weight type. Conclusion: The estimation of UW-mRS scores largely depends on the choice of weights used, which depends on sample heterogeneity in treatment interventions and stroke severity of the cohorts. Model-based approaches result in reduced variability between and across mRS levels. Future research will seek to validate these utility weights externally in an independent cohort of patients with stroke.

Exploring health preference heterogeneity in the UK: Using the online elicitation of personal utility functions approach to construct EQ-5D-5L value functions on societal, group and individual level.

A new method has recently been developed for valuing health states, called 'Online elicitation of Personal Utility Functions' (OPUF). In contrast to established methods, such as time trade-off or discrete choice experiments, OPUF does not require hundreds of respondents, but allows estimating utility functions for small groups and even at the individual level. In this study, we used OPUF to elicit EQ-5D-5L health state preferences from a (not representative) sample of the UK general population, and then compared utility functions on the societal-, group-, and individual level. A demo version of the survey is available at: https://eq5d5l.me. Data from 874 respondents were included in the analysis. For each respondent, we constructed a personal EQ-5D-5L value set. These personal value sets predicted respondents' choices in three hold-out discrete choice tasks with an accuracy of 78%. Overall, preferences varied greatly between individuals. However, PERMANOVA analysis showed that demographic characteristics explained only a small proportion of the variability between subgroups. While OPUF is still under development, it has important strengths: it can be used to construct value sets for patient reported outcome instruments such as EQ-5D-5L, while also allowing examination of underlying preferences in an unprecedented level of detail. In the future, OPUF could be used to complement existing methods, allowing valuation studies in smaller samples, and providing more detailed insights into the heterogeneity of preferences across subgroups.

Are Web-Based Valuation Surveys for Preference-Based Measures as Reliable as Face-to-Face Surveys? TTO, DCE and DCE with Duration.

Valuation surveys of preference-based measures are typically conducted face-to-face or on web panels. In this survey, we considered whether face-to-face and online surveys were reliable using three tasks: composite time trade-off (cTTO), discrete choice experiment (DCE), and DCE with duration. Respondents (aged 20-69 years) for both face-to-face (N = 1000, target sample size) and web surveys were selected through quota sampling by sex and age from each panel of the general population in Japan. They were then allocated to one of the three tasks and divided into six groups (two survey modes × three tasks, N = 334 per group). For the cTTO, respondents were asked to rate ten health states described by the EQ-5D-5L. For the DCE and DCE with duration surveys, respondents were asked about 15 health-state pairs. For all participants, as in the second-stage survey, a similar process was repeated two weeks after the first survey. Reliability was evaluated by calculating the percentage of agreement and intraclass correlation coefficients. The cTTO scores of the face-to-face and web surveys were systematically different. Between the face-to-face and web surveys, the agreement of the TTO survey was not good. The intraclass correlation coefficient (ICC) was 0.37 for the face-to-face test-test and 0.59 for the web test-retest. Discrete choice experiment (DCE) and DCE with duration had similarly good agreement (more than 70%), regardless of face-to-face or web surveys. However, between the first and second surveys (test-retest) of DCE and DCE with duration, the agreement depends on whether the positions of the two cards (health states) are identical. If the face-to-face cTTO score is the gold standard, a web-based survey of cTTO is not recommended regardless of the ICC. If a DCE survey is performed, positioning effects should be considered.

Valuing selected WAItE health states using the Time Trade-Off methodology: findings from an online interviewer-assisted remote survey

PurposeThe Weight-Specific Adolescent Instrument for Economic Evaluation (WAItE) is a physical weight-specific patient reported outcome measure for use in adolescence. The purpose of this study was to use the Time Trade-Off (TTO) methodology, administered using an online interviewer-assisted remote survey, to obtain utility values for several health states from the WAItE descriptive system from a sample of the UK adult general population.MethodsThe adult sample was gathered using a market research company and a sample of local residents. All participants completed the same interviewer-assisted remote survey, which included rating WAItE states of varying impairment using the TTO.Results42 adults completed the survey. Utility values were gathered for four health states, ranging from low impairment to the most severe health from the WAItE descriptive system (the Pits state). Consistent orderings of the WAItE health states were observed; the health state with the lowest level of impairment was valued highest and the Pits state was valued lowest. Several respondents (n = 7, 17%) considered the Pits state to be worse than death; however, the mean value of this health state was 0.23.ConclusionsThe utility value of the Pits state relative to death generated from this study will be used to anchor latent values for WAItE health states generated from a Discrete Choice Experiment onto the 0 = death, 1 = full health Quality Adjusted Life Year (QALY) scale as part of a valuation study for the WAItE in the UK population. This study also provides further evidence that interviewer-assisted digital studies are feasible for collecting TTO data.

A Multi-Objective Mathematical Programming Model for Project-Scheduling Optimization Considering Customer Satisfaction in Construction Projects

The aim of this study was to develop a multi-objective mathematical programming model for the trade-off of time, cost, and quality in the project-scheduling problem (PSP) by taking priorities and resource constraints as well as activity preemption into account. First, a small-sized problem instance that was a sub-project of an oil and gas construction project was used for te validation of the proposed model and algorithm. Subsequently, considering the sensitivity, complexity, and importance of oil and gas projects, the proposed model was implemented in a large-sized oil and gas construction project. Considering the NP-hardness of this problem, the NSGA-II metaheuristic algorithm was used to deal with the time, cost, and quality trade-off problem. Finally, a sensitivity analysis was implemented on the three main parameters of time, cost, and quality to investigate the effects of changes on the results. The findings show that the proposed model is more sensitive to cost changes, so an increase in project costs leads to a drastic change in the values of other objective functions.

Health State Utilities Associated with False-Positive Cancer Screening Results.

Early cancer detection can significantly improve patient outcomes and reduce mortality rates. Novel cancer screening approaches, including multi-cancer early detection tests, have been developed. Cost-utility analyses will be needed to examine their value, and these models require health state utilities. The purpose of this study was to estimate the disutility (i.e., decrease in health state utility) associated with false-positive cancer screening results. In composite time trade-off interviews using a 1-year time horizon, UK general population participants valued 10 health state vignettes describing cancer screening with true-negative or false-positive results. Each false-positive vignette described a common diagnostic pathway following a false-positive result suggesting lung, colorectal, breast, or pancreatic cancer. Every pathway ended with a negative result (no cancer detected). The disutility of each false positive was calculated as the difference between the true-negative and each false-positive health state, and because of the 1-year time horizon, each disutility can be interpreted as a quality-adjusted life-year decrement associated with each type of false-positive experience. A total of 203 participants completed interviews (49.8% male; mean age = 42.0 years). The mean (SD) utility for the health state describing a true-negative result was 0.958 (0.065). Utilities for false-positive health states ranged from 0.847 (0.145) to 0.932 (0.059). Disutilities for false positives ranged from -0.031 to -0.111 (-0.041 to -0.111 for lung cancer; -0.079 for colorectal cancer; -0.031 to -0.067 for breast cancer; -0.048 to -0.088 for pancreatic cancer). All false-positive results were associated with a disutility. Greater disutility was associated with more invasive follow-up diagnostic procedures, longer duration of uncertainty regarding the eventual diagnosis, and perceived severity of the suspected cancer type. Utility values estimated in this study would be useful for economic modeling examining the value of cancer screening procedures.

Exploring the roles of AI-Assisted ChatGPT in the field of data science

In this study, we explore the roles of AI-assisted ChatGPT (Generative Pre-trained Transformer) in the field of data science. AI-assisted ChatGPT, a powerful language model, is fine-tuned using domain-specific data for specialised data science tasks, such as sentiment analysis and named entity recognition (NER). The results reveal significant reductions in model size and memory usage with minor trade-offs in inference time, providing valuable resource-efficient deployment. Various data augmentation methods, including back-translation, synonym replacement, and contextual word embeddings, are employed to augment the training dataset. The study's results are subjected to rigorous statistical analysis, including paired t-tests and ANOVA tests, to determine the significance of the findings. The research concludes with insightful suggestions and future scope, including advanced fine-tuning strategies, model optimization techniques, and ethical considerations.

Navigating Time and Energy Trade-Offs in Reactive Heterogeneous Systems

Navigating Time and Energy Trade-Offs in Reactive Heterogeneous Systems

An Analysis of the Determinants of the Health-Related Quality of Life in Asian Patients With Cluster Headaches During Cluster Periods Using the Time Trade-Off Method.

Patients with cluster headache (CH) exhibit impaired health-related quality of life (HRQoL). However, there have been few studies related to the HRQoL of patients with CH from Asian backgrounds. This study aimed to determine the impact of CH on HRQoL and to identify the factors affecting HRQoL in patients with CH during cluster periods. This prospective study enrolled patients with CH from 17 headache clinics in South Korea between September 2016 and February 2021. The study aimed to determine HRQoL in patients with CH using the EuroQol 5 Dimensions (EQ-5D) index and the time trade-off (TTO) method. Age- and sex-matched headache-free participants were recruited as a control group. The study included 423 patients with CH who experienced a cluster period at the time. EQ-5D scores were lower in patients with CH (0.88±0.43, mean±standard deviation) than in the controls (0.99±0.33, p<0.001). The TTO method indicated that 58 (13.6%) patients with CH exhibited moderate-to-severe HRQoL deterioration. The HRQoL states in patients with CH were associated with current smoking patterns, headache severity, frequency, and duration, and scores on the Generalized Anxiety Disorder 7-item scale (GAD-7), Patient Health Questionnaire 9-item scale (PHQ-9), 6-item Headache Impact Test, and 12-item Allodynia Symptom Checklist. Multivariable logistic regression analyses demonstrated that the HRQoL states in patients with CH were negatively correlated with the daily frequency of headaches, cluster period duration, and GAD-7 and PHQ-9 scores. Patients with CH experienced a worse quality of life during cluster periods compared with the headache-free controls, but the degree of HRQoL deterioration varied among them. The daily frequency of headaches, cluster period duration, anxiety, and depression were factors associated with HRQoL deterioration severity in patients with CH.

Quality-of-life survey of pancreatic cancer patients: a comparison between general public and physicians.

Quality-of-life (QOL) is important for cancer patients with poor prognosis. However, conducting a QOL survey with patients is difficult. Therefore, we conducted a QOL survey with physicians. Specifically, this study aimed to clarify how physicians assess QOL in patients with pancreatic cancer by conducting a survey and comparing the results between physicians and the general public. A survey was conducted by interviewing physicians administering chemotherapy to patients for recurrent/metastatic pancreatic cancer. This method is similar to that of the QOL survey conducted among the general public. Responses were evaluated using the composite time trade-off (cTTO) and the visual analog scale (VAS) for 11 pancreatic cancer status scenarios (survey scenarios). These scenarios consisted of patients' health states as well as the types and grades of adverse events (AEs). Health status was classified into two categories: Stable disease (SD) and Progressive disease (PD). In addition, we conducted a survey using the EuroQol 5 Dimensions 5-Level (EQ-5D-5l) as reference values. Twenty physicians responded to the survey. SD had the highest mean QOL value for both assessment methods (Physicians: 0.78, General public: 0.63), whereas PD had the lowest mean QOL value (Physicians: 0.15, General public: -0.12). The physicians assigned higher QOL values on both the VAS and cTTO than the general public did in all survey scenarios. The QOL values obtained from physicians were consistent with the degree of status in any assessment scenarios. Based on the differences in the QOL survey results between physicians and the general public, physicians tended to assign higher QOL values than the general public in cTTO and VAS assessments.