A B S T R A C TObjective: To derive a US-based value set for the EQ-5D-5L questionnaire using an international, standardized protocol developed by the EuroQol Group.Methods: Respondents from the US adult population were quota-sampled on the basis of age, sex, ethnicity, and race. Trained interviewers guided participants in completing composite time trade-off (cTTO) and discrete choice experiment (DCE) tasks using the EuroQol Valuation Technology software and routine quality control measures. Data were modeled using a Tobit model for cTTO data, a mixed logit model for DCE data, and a hybrid model that combined cTTO and DCE data. Model performance was compared on the basis of logical ordering of coefficients, statistical significance, parsimony, and theoretical considerations.Results: Of 1134 respondents, 1062, 1099, and 1102 respondents provided useable cTTO, DCE, and cTTO or DCE responses, respectively, on the basis of quality control criteria and interviewer judgment. Respondent demographic characteristics and health status were similar to the 2015 US Census. The Tobit model was selected as the preferred model to generate the value set. Values ranged from 20.573 (55 555) to 1 (11111), with 20% of all predicted health states scores less than 0 (ie, worse than dead). Conclusions:A societal value set for the EQ-5D-5L was developed that can be used for economic evaluations and decision making in US health systems. The internationally established, standardized protocol used to develop this US-based value set was recommended by the EuroQol Group and can facilitate cross-country comparisons.

Background Several multi-attribute utility instruments (MAUIs) are available from which utilities can be derived for use in cost-utility analysis (CUA). This study provides a review of recommendations from national health technology assessment (HTA) agencies regarding the choice of MAUIs. Methods A list was compiled of HTA agencies that provide or refer to published official pharmacoeconomic (PE) guidelines for pricing, reimbursement or market access. The guidelines were reviewed for recommendations on the indirect calculation of utilities and categorized as: a preference for a specific MAUI; providing no MAUI preference, but providing examples of suitable MAUIs and/or recommending the use of national value sets; and recommending CUA, but not providing examples of MAUIs. Results Thirty-four PE guidelines were included for review. MAUIs named for use in CUA: EQ-5D (n = 29 guidelines), the SF-6D (n = 11), HUI (n = 10), QWB (n = 3), AQoL (n = 2), CHU9D (n = 1). EQ-5D was a preferred MAUI in 15 guidelines. Alongside the EQ-5D, the HUI was a preferred MAUI in one guideline, with DALY disability weights mentioned in another. Fourteen guidelines expressed no preference for a specific MAUI, but provided examples: EQ-5D (n = 14), SF-6D (n = 11), HUI (n = 9), QWB (n = 3), AQoL (n = 2), CHU9D (n = 1). Of those that did not specify a particular MAUI, 12 preferred calculating utilities using national preference weights. Conclusions The EQ-5D, HUI, and SF-6D were the three MAUIs most frequently mentioned in guidelines. The most commonly cited MAUI (in 85% of PE guidelines) was EQ-5D, either as a preferred MAUI or as an example of a suitable MAUI for use in CUA in HTA.

Objective Long‐term weight loss is important and difficult to achieve for many women with polycystic ovary syndrome (PCOS). Lifestyle interventions (LS) in PCOS have shown moderate short‐term effects. Three‐component LS that combine nutrition advice, exercise, and cognitive behavioral therapy have not been tested in long‐term interventions. Methods Women (N = 183) with PCOS who were trying to conceive and had BMI > 25 kg/m2 were assigned to 20 group sessions of cognitive behavioral therapy combined with nutrition advice and exercise (LS with or without Short Message Service [SMS] via mobile phone) or care as usual (CAU). Results More weight loss was observed in LS than in CAU (P < 0.001). Adding SMS was even more effective (P = 0.017). In CAU, 13 of 60 (21.8%) succeeded in achieving a 5% weight loss, as did 32 of 60 (52.8%) in LS without SMS and 54 of 63 (85.7%) in LS with SMS. The odds of achieving a 5% weight loss were 7.0 (P < 0.001) in LS compared with CAU. More than 18 of 60 (29.0%) of the women in CAU gained weight versus 5 of 60 (8.5%) and 2 of 63 (3.1%) in LS without or with SMS, respectively. The overall dropout rate was 116 of 183 (63.4%). Conclusions A three‐component LS program resulted in reasonable weight loss in women with PCOS. Adding SMS resulted in more weight loss.