Aims The EORTC QLQ-C30 is one of the most commonly used measures in cancer but in its current form cannot be used in economic evaluation as it does not incorporate preferences. We address this gap by estimating a preference-based single index for cancer from the EORTC QLQ-C30 for use in economic evaluation. Methods Factor analysis, Rasch analysis and other psychometric analyses were undertaken on a clinical trial dataset of 655 patients with Multiple Myeloma to derive a health state classification from the QLQ-C30 that is amenable to valuation. A valuation study was conducted of 350 members of the UK general population using ranking and time trade-off. A series of regression models were fitted to the data, including the episodic random utility model (RUM) to derive preference weights for the classification system. Results The resulting health state classification system has 8 dimensions (physical functioning, role functioning, social functioning, emotional functioning, pain, fatigue and sleep disturbance, nausea, and constipation and diarrhoea) with 4 or 5 levels each. Mean and individual level additive multivariate regression models were estimated and compared. Mean absolute error ranges from 0.050 to 0.054 with no systematic errors. All models have few inconsistencies (0 to 2) in estimated preference weights. Conclusions It is feasible to derive a preference-based measure from the EORTC QLQ-C30 for use in economic evaluation, but this work needs to be extended to other countries and replicated across other conditions.

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Background: Formative qualitative research is foundational to the methodological development process of quantitative health preference research (HPR). Despite its ability to improve the validity of the quantitative evidence, formative qualitative research is underreported.Objective: To improve the frequency and quality of reporting, we developed guidelines for reporting this type of research. The guidelines focus on formative qualitative research used to develop robust and acceptable quantitative study protocols and corresponding survey instruments in HPR.Methods: In December 2018, a steering committee was formed as a means to accumulate the expertise of the HPR community on the reporting guidelines (21 members, seven countries, multiple settings, and disciplines). Using existing guidelines and examples, the committee constructed, revised, and refined the guidelines. The guidelines underwent beta-testing by three researchers and further revision to the guidelines were made based on their feedback as well as from comments from members of the International Academy of Health Preference Research (IAHPR) and the editorial board of The Patient.Results: The guidelines have five components: introductory material (4 domains); methods (12); results/findings (2); discussion (2); and other (2). They are concordant with existing guidelines, published examples, beta testing results, and expert comments.Conclusions: Publishing formative qualitative research is a necessary step towards strengthening the foundation of any quantitative study, enhancing the relevance of its preference evidence. The guidelines should aid researchers, reviewers and regulatory agencies as well as promote transparency within HPR more broadly. Key Points for Decision Makers• These are the first guidelines on reporting formative qualitative research on patient experience that support the development of quantitative preference study protocols and corresponding instruments. • These guidelines focus on reporting techniques that enhance transparency and trustworthiness, thereby improving the likelihood that the scientific contributions of quantitative preference studies are well-founded, improving the validity of the quantitative evidence.

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BackgroundOut-of-pocket expenditures of over $34 billion per year in the US are an apparent testament to a widely held belief that complementary and alternative medicine (CAM) therapies have benefits that outweigh their costs. However, regardless of public opinion, there is often little more than anecdotal evidence on the health and economic implications of CAM therapies. The objectives of this study are to present an overview of economic evaluation and to expand upon a previous review to examine the current scope and quality of CAM economic evaluations.MethodsThe data sources used were Medline, AMED, Alt-HealthWatch, and the Complementary and Alternative Medicine Citation Index; January 1999 to October 2004. Papers that reported original data on specific CAM therapies from any form of standard economic analysis were included. Full economic evaluations were subjected to two types of quality review. The first was a 35-item checklist for reporting quality, and the second was a set of four criteria for study quality (randomization, prospective collection of economic data, comparison to usual care, and no blinding).ResultsA total of 56 economic evaluations (39 full evaluations) of CAM were found covering a range of therapies applied to a variety of conditions. The reporting quality of the full evaluations was poor for certain items, but was comparable to the quality found by systematic reviews of economic evaluations in conventional medicine. Regarding study quality, 14 (36%) studies were found to meet all four criteria. These exemplary studies indicate CAM therapies that may be considered cost-effective compared to usual care for various conditions: acupuncture for migraine, manual therapy for neck pain, spa therapy for Parkinson's, self-administered stress management for cancer patients undergoing chemotherapy, pre- and post-operative oral nutritional supplementation for lower gastrointestinal tract surgery, biofeedback for patients with "functional" disorders (eg, irritable bowel syndrome), and guided imagery, relaxation therapy, and potassium-rich diet for cardiac patients.ConclusionWhereas the number and quality of economic evaluations of CAM have increased in recent years and more CAM therapies have been shown to be of good value, the majority of CAM therapies still remain to be evaluated.

Protocol violations may occur in any valuation study; handling them in the analysis can improve external validity. The resulting EQ-5D-5L value set (model 3) can be applied to inform Spanish health technology assessments.

Objective-The purpose of this study was to assess the accuracy of BMI categories based on selfreported height and weight in adult women. Methods-BMIcategories from self-reported responses were compared to categories measured during physical examination from women, age 18 or older, who participated in the National Health and Examination Survey, 1999Survey, -2004. We first examined strength of agreement using Cohen's kappa, which, unlike sensitivity and specificity, allows for the comparison of polychotomous measures beyond chance agreement. Kappa regression identifies potential threats to accuracy. Likelihood of bias, as measured by under-reporting, was examined using logistic regression.Results-Cohen's kappa estimates were 0.443 for pregnant women (N = 724) and 0.705 for nonpregnant women (N = 5,910). Kappa varied by age and race, but was largely unrelated to socioeconomic status, health and health behaviors. Women who visited a physician in the last year or been diagnosed with osteoporosis were more accurate, while women most likely to under-report were older, white, non-Hispanic, and college-educated.Conclusions-Our results suggest substantial agreement between self-reported and measured categories, except for women who are pregnant, above the age of 75 or without physician visits. Under-reporting may be more prevalent in well-educated, white populations than minority populations. KeywordsObesity; Body mass index; Cohen's kappa Obesity is a major public health epidemic and is an important risk factor contributing to morbidity and mortality from diseases such as heart disease, diabetes and cancer [1]. One of the challenges facing epidemiologists studying trends in the obesity epidemic is tracking changes over time. Both epidemiologists and clinicians often rely on self-reported height and weight, which are then used to calculate body mass index (BMI). Many studies have examined the accuracy of self-reported height, weight and BMI in a variety of cohorts [2][3][4][5][6] Fewer studies have examined the accuracy of self-reported height and weight when they are used to determine BMI categories [7][8][9][10]; yet, BMI categories are routinely used in studies of health outcomes [3]. Many of these studies showed significant differences in allocation to BMI categories based on self-reported versus measured height and weight, thus biasing relative risks of diseases associated with increasing BMI [3][4][5][6][7][8].In women, bias in self-reported height and weight may occur due to social desirability, cultural or demographic characteristics or health characteristics (such as pregnancy or osteoporosis) [9]. In general, women tend to under-report weight more than men [2], while men tend to overreport height more than women [6]. It is important to examine the potential threats to accuracy particular to women since under-or over-reporting may affect the prevalence and categorization of BMI differently among women than among men. Understanding of sources of bias among women is important in planning and interpreting e...

Objective To develop a set of EQ-5D health state values for the Argentine general population. Methods Consecutive subjects attending six primary care centers in Argentina were selected based on quota sampling and interviewed using the EuroQol Group protocol for measurement and valuation of health studies. Initially respondents were randomly assigned a unique card set; however, to improve efficiency, subjects were later randomly assigned to one of three fixed sets of EQ-5D states. Using the VAS and TTO responses for these states, we estimated a valuation model using ordinary least squares regression clustered by respondent. Predicted values for EQ-5D health states are compared to published values for the United States. Results Six hundred eleven subjects were interviewed by 14 trained interviewers, rendering 6,887 TTO and 6,892 VAS responses. The model had an R2 of 0.897 and 0.928 for TTO and VAS respectively. The mean absolute difference between observed and predicted values was 0.039 for TTO and 0.020 for VAS, each showing a Lin’s concordance coefficient above 0.98. United States and Argentine TTO predicted values were highly correlated (Pearson’s rho=0.963), though the average absolute difference was clinically meaningful (0.06), rejecting the US values for nearly two thirds of the states (62.8%). The Argentine population placed lower values on mild states and higher values on severe states. Conclusion This study provides an Argentine value set that could be used locally or regionally, with meaningful and significant differences with that of the US. Health policy in Latin America must incorporate local values for sovereignty and validity.