Multi-attribute Utility Instruments Research Articles

Japanese value set for the EORTC QLU-C10D: A multi-attribute utility instrument based on the EORTC QLQ-C30 cancer-specific quality-of-life questionnaire

Abstract Purpose This study aimed to develop a Japanese value set for the EORTC QLU-C10D, a multi-attribute utility measure derived from the cancer-specific health-related quality-of-life (HRQL) questionnaire, the EORTC QLQ-C30. The QLU-C10D contains ten HRQL dimensions: physical, role, social and emotional functioning, pain, fatigue, sleep, appetite, nausea, and bowel problems. Methods Quota sampling of a Japanese online panel was used to achieve representativeness of the Japanese general population by sex and age (≥ 18 years). The valuation method was an online discrete choice experiment. Each participant considered 16 choice pairs, randomly assigned from 960 choice pairs. Each pair included two QLU-C10D health states and life expectancy. Data were analyzed using conditional logistic regression, parameterized to fit the quality-adjusted life-year framework. Preference weights were calculated as the ratio of each dimension-level coefficient to the coefficient for life expectancy. Results A total of 2809 eligible panel members consented, 2662/2809 (95%) completed at least one choice pair, and 2435/2662 (91%) completed all choice pairs. Within dimensions, preference weights were generally monotonic. Physical functioning, role functioning, and pain were associated with the largest utility weights. Intermediate utility weights were associated with social functioning and nausea; the remaining symptoms and emotional functioning were associated with smaller utility decrements. The value of the worst health state was − 0.221, lower than that seen in most other existing QLU-C10D country-specific value sets. Conclusions The Japan-specific QLU-C10D value set is suitable for evaluating the cost and utility of oncology treatments for Japanese health technology assessment and decision-making.

Danish value sets for the EORTC QLU-C10D utility instrument

PurposeIn this study, we developed Danish utility weights for the European Organisation for Research and Treatment of Cancer (EORTC) QLU-C10D, a cancer-specific utility instrument based on the EORTC QLQ-C30.MethodsFollowing a standardized methodology, 1001 adult participants from the Danish general population were quota-sampled and completed a cross-sectional web-based survey and discrete choice experiment (DCE). In the DCE, participants considered 16 choice sets constructed from the key 10 dimensions of the QLU-C10D and chose their preferred health state for each one. Utility weights were calculated using conditional logistic regression with correction for non-monotonicity.ResultsThe sample (n = 1001) was representative of the Danish general population with regard to age and gender. The domains with the largest utility decrements, i.e., the domains with the biggest impact on health utility, were physical functioning (− 0.224), pain (− 0.160), and role functioning (− 0.136). The smallest utility decrements were observed for the domains lack of appetite (− 0.024), sleep disorders (− 0.057), and fatigue (− 0.064). Non-monotonicity of severity levels was observed for the domains sleep disturbances, lack of appetite, and bowel problems. Deviations from monotonicity were not statistically significant.ConclusionThe EORTC QLU-C10D is a relatively new multi-attribute utility instrument and is a promising cancer-specific health technology assessment candidate measure. The country-specific Danish utility weights from this study can be used for cost-utility analyses in Danish patients and for comparison with other country-specific utility data.

UnitedStates Value Set for the Functional Assessment of Cancer Therapy-General Eight Dimensions (FACT-8D), a Cancer-Specific Preference-Based Quality of Life Instrument.

To develop a value set reflecting the United States (US) general population's preferences for health states described by the Functional Assessment of Cancer Therapy (FACT) eight-dimensions preference-based multi-attribute utility instrument (FACT-8D), derived from the FACT-General cancer-specific health-related quality-of-life (HRQL) questionnaire. A US online panel was quota-sampled to achieve a general population sample representative by sex, age (≥ 18 years), race and ethnicity. A discrete choice experiment (DCE) was used to value health states. The valuation task involved choosing between pairs of health states (choice-sets) described by varying levels of the FACT-8D HRQL dimensions and survival (life-years). The DCE included 100 choice-sets; each respondent was randomly allocated 16 choice-sets. Data were analysed using conditional logit regression parameterized to fit the quality-adjusted life-year framework, weighted for sociodemographic variables that were non-representative of the US general population. Preference weights were calculated as the ratio of HRQL-level coefficients to the survival coefficient. 2562 panel members opted in, 2462 (96%) completed at least one choice-set and 2357 (92%) completed 16 choice-sets. Pain and nausea were associated with the largest utility weights, work and sleep had more moderate utility weights, and sadness, worry and support had the smallest utility weights. Within dimensions, more severe HRQL levels were generally associated with larger weights. A preference-weighting algorithm to estimate US utilities from responses to the FACT-General questionnaire was generated. The worst health state's value was -0.33. This value set provides US population utilities for health states defined by the FACT-8D for use in evaluating oncology treatments.

Psychometric Performance of Generic Childhood Multi-Attribute Utility Instruments in Preterm and Low Birthweight Populations: A Systematic Review.

Individuals born preterm (gestational age < 37 weeks) and/or at low birthweight (<2500 g) are at increased risk of health impairments from birth to adulthood. This review aimed to evaluate the psychometric performance of generic childhood-specific or childhood-compatible multi-attribute utility instruments (MAUIs) in preterm and/or low birthweight (PLB) populations. Searches covered seven databases, including studies that targeted childhood (aged < 18 years) and/or adult (≥18 years) PLB populations; provided psychometric evidence for generic childhood-specific or compatible MAUI(s) (any language version); and published in English. Eighteen psychometric properties were evaluated using a four-part criteria rating system. Data syntheses identified psychometric evidence gaps and summarised the psychometric assessment methods/results. A total of 42 studies were included, generating 178 criteria rating outputs across four MAUIs: 17D, CHSCS-PS, HUI2, and HUI3. Moreover, 64.0% of outputs concerned the HUI3 MAUI, and 38.2% related to known-group validity. There was no evidence for five psychometric properties. Only 6.7% of outputs concerned reliability and proxy-child agreement. No MAUI outperformed others across all properties. The frequently applied HUI2 and HUI3 lacked content validity evidence. This psychometric evidence catalogue should inform the selection of MAUI(s) suited to the specific aims of applications targeting PLB populations. Further psychometric research is warranted to address the gaps in psychometric evidence.

Assessing health state utilities for people with myalgic encephalomyelitis/chronic fatigue syndrome in Australia using the EQ-5D-5L, AQoL-8D and EQ-5D-5L-psychosocial instruments

PurposeMyalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic condition with a constellation of symptoms presenting as severe and profound fatigue of ≥ 6 months not relieved by rest. ME/CFS affects health-related quality of life (HRQoL), which can be measured using multi-attribute health state utility (HSU) instruments. The aims of this study were to quantify HSUs for people living with ME/CFS, and to identify an instrument that is preferentially sensitive for ME/CFS.MethodsCross-sectional national survey of people with ME/CFS using the AQoL-8D and EQ-5D-5L. Additional questions from the AQoL-8D were used as ‘bolt-ons’ to the EQ-5D-5L (i.e., EQ-5D-5L-Psychosocial). Disability and fatigue severity were assessed using the De Paul Symptom Questionnaire-Short Form (DSQ-SF). HSUs were generated using Australian tariffs. Mean HSUs were stratified for sociodemographic and clinical factors. Bland–Altman plots were used to compare the three HSU instruments.ResultsFor the 198 participants, mean HSUs (95% confidence intervals) were EQ-5D-5L: 0.46 (0.42–0.50); AQoL-8D: 0.43 (0.41–0.45); EQ-5D-5L-Psychosocial: 0.44 (0.42–0.46). HSUs were substantially lower than population norms: EQ-5D-5L: 0.89; AQoL-8D: 0.77. As disability and fatigue severity increased, HSUs decreased in all three instruments. Bland–Altman plots revealed interchangeability between the AQoL-8D and EQ-5D-5LPsychosocial. Floor and ceiling effects of 13.5% and 2.5% respectively were observed for the EQ-5D-5L instrument only.ConclusionsME/CFS has a profound impact on HRQoL. The AQoL-8D and EQ-5D-5L-Psychosocial can be used interchangeably: the latter represents a reduced participant burden.

Translation and Cultural Adaptation of Multi-Attribute Utility Instrument (MAUI) Indonesian Version of the 15D Questionnaire

Background: Diabetes mellitus is a chronic metabolic disorder that cannot be cured and progressively develop into a complication affecting the patient's health-related quality of life (HRQoL). The utility is a measure of preference-based HRQoL. Indirect utility measurements can be measured using the Multi-Attribute Utility Instrument (MAUI) instrument, one of which is the 15D questionnaire that has never been translated and adapted culturally in Indonesian. Objective: Translating and culturally adapting the 15D questionnaire to Indonesian diabetes mellitus patients. Methods: The translation process was carried out through the stages of forward translation, reconciliation, and backward translation involving two qualified translators and three experts in their field. The pilot test stage involved eight respondents consisting of 6 diabetes mellitus patients and two healthy individuals. Results: Problems in the linguistic validation process led to more conformity of word equivalents from the original to the target language. The agreement found was in the area of semantic equivalence, idiomatic equivalence, and experiential equivalence. The problem was resolved by reconciliation during the Focus Group Discussion, which translators and experts in their field attended and discussed with the original author to get equality of meaning in terms of language and culture. The Indonesian version of the 15D questionnaire tested on eight respondents showed results that were easy to understand and straightforward. Conclusion: The Indonesian version of the 15D questionnaire is valid from the linguistic and cultural adaptation stage. Further research is needed relating to the validation and reliability of the questionnaire.

Estimating the disutility of relapse in relapsing–remitting and secondary progressive multiple sclerosis using the EQ-5D-5L, AQoL-8D, EQ-5D-5L-psychosocial, and SF-6D: implications for health economic evaluation models

Background and aimsRelapses are an important clinical feature of multiple sclerosis (MS) that result in temporary negative changes in quality of life (QoL), measured by health state utilities (HSUs) (disutilities). We aimed to quantify disutilities of relapse in relapsing remitting MS (RRMS), secondary progressive MS (SPMS), and relapse onset MS [ROMS (including both RRMS and SPMS)] and examine these values by disability severity using four multi-attribute utility instruments (MAUIs).MethodsWe estimated (crude and adjusted and stratified by disability severity) disutilities (representing the mean difference in HSUs of ‘relapse’ and ‘no relapse’ groups as well as ‘unsure’ and ‘no relapse’ groups) in RRMS (n = 1056), SPMS (n = 239), and ROMS (n = 1295) cohorts from the Australian MS Longitudinal Study’s 2020 QoL survey, using the EQ-5D-5L, AQoL-8D, EQ-5D-5L-Psychosocial, and SF-6D MAUIs.ResultsAdjusted mean overall disutilities of relapse in RMSS/SPMS/ROMS were − 0.101/− 0.149/− 0.129 (EQ-5D-5L), − 0.092/− 0.167/− 0.113 (AQoL-8D), − 0.080/− 0.139/− 0.097 (EQ-5D-5L-Psychosocial), and − 0.116/− 0.161/− 0.130 (SF-6D), approximately 1.5 times higher in SPMS than in RRMS, in all MAUI. All estimates were statistically significant and/or clinically meaningful. Adjusted disutilities of RRMS and ROMS demonstrated a U-shaped relationship between relapse disutilities and disability severity. Relapse disutilities were higher in ‘severe’ disability than ‘mild’ and ‘moderate’ in the SPMS cohort.ConclusionMS-related relapses are associated with substantial utility decrements. As the type and severity of MS influence disutility of relapse, the use of disability severity and MS-type-specific disutility inputs is recommended in future health economic evaluations of MS. Our study supports relapse management and prevention as major mechanisms to improve QoL in people with MS.

Bayesian Models with Spatial Correlation Improve the Precision of EQ-5D-5L Value Sets.

Health utilities from value sets for the EQ-5D-5L are commonly used in economic evaluations. We examined whether modeling spatial correlation among health states could improve the precision of the value sets. Using data from 7 EQ-5D-5L valuation studies, we compared the predictive precision of the published linear model, a recently proposed cross-attribute level effects (CALE) model, and 2 Bayesian models with spatial correlation. Predictive precision was quantified through the root mean squared error (RMSE) for out-of-sample predictions of state-level mean utilities on omitting individual states, as well as omitting blocks of states. In all 7 countries, on omitting single health states, Bayesian models with spatial correlation improved upon the published linear model: the RMSEs for the originally published models, 0.050, 0.051, 0.060, 0.061, 0.039, 0.050, and 0.087 for Canada, China, Germany, Indonesia, Japan, Korea, and the Netherlands, respectively, could be reduced to 0.043, 0.042, 0.051, 0.054, 0.037, 0.037, and 0.085, respectively. On omitting blocks of health states, Bayesian models with spatial correlation led to smaller RMSEs in 3 countries, while the CALE model led to smaller RMSEs in the remaining 4 countries. Bayesian models incorporating spatial correlation and CALE models are promising for improving the precision of value sets for the EQ-5D-5L. The differential performance of the Bayesian models on omitting single states versus blocks of states suggests that designing valuation studies to capture more health states may further improve precision. We suggest that Bayesian and CALE models be considered as candidates when creating value sets and that alternative designs be explored; this is vital as the prediction errors in value sets need to be smaller than the minimal important difference of the instrument. The accuracy of value sets of multi-attribute utility instruments is typically of the same order of magnitude as the instrument's minimal important difference and would benefit from improvement.Bayesian models with spatial correlation have been shown to improve value set accuracy in isolated cases.We showed that Bayesian approaches with spatial correlation improved predictive precision in 7 EQ-5D-5L valuation studies.We recommend that Bayesian models incorporating spatial correlation be considered when creating value sets and have provided code for fitting them.

Efficient Designs for Valuation Studies That Use Time Tradeoff (TTO) Tasks to Map Latent Utilities from Discrete Choice Experiments to the Interval Scale: Selection of Health States for TTO Tasks.

In eliciting utilities to value multiattribute utility instruments, discrete choice experiments (DCEs) administered online are less costly than interviewer-facilitated time tradeoff (TTO) tasks. DCEs capture utilities on a latent scale and are often coupled with a small number of TTO tasks to anchor utilities to the interval scale. Given the costly nature of TTO data, design strategies that maximize value set precision per TTO response are critical. Under simplifying assumptions, we expressed the mean square prediction error (MSE) of the final value set as a function of the number of TTO-valued health states and the variance of the states' latent utilities. We hypothesized that even when these assumptions do not hold, the MSE 1) decreases as increases while holding fixed and 2) decreases as increases while holding fixed. We used simulation to examine whether there was empirical support for our hypotheses a) assuming an underlying linear relationship between TTO and DCE utilities and b) using published results from the Dutch, US, and Indonesian EQ-5D-5L valuation studies. Simulation set (a) supported the hypotheses, as did simulations parameterized using valuation data from Indonesia, which showed a linear relationship between TTO and DCE utilities. The US and Dutch valuation data showed nonlinear relationships between TTO and DCE utilities and did not support the hypotheses. Specifically, for fixed , smaller values of reduced rather than increased the MSE. Given that, in practice, the underlying relationship between TTO and DCE utilities may be nonlinear, health states for TTO valuation should be placed evenly across the latent utility scale to avoid systematic bias in some regions of the scale. Valuation studies may feature a large number of respondents completing discrete choice tasks online, with a smaller number of respondents completing time tradeoff (TTO) tasks to anchor the discrete choice utilities to an interval scale.We show that having each TTO respondent complete multiple tasks rather than a single task improves value set precision.Keeping the total number of TTO respondents and the number of tasks per respondent fixed, having 20 health states directly valued through TTO leads to better predictive precision than valuing 10 health states directly.If DCE latent utilities and TTO utilities follow a perfect linear relationship, choosing the TTO states to be valued by weighting on the 2 ends of the latent utility scale leads to better predictive precision than choosing states evenly across the latent utility scale.Conversely, if DCE latent utilities and TTO utilities do not follow a linear relationship, choosing the states to be valued using TTO evenly across the latent utility scale leads to better predictive precision than weighted selection does.In the context of valuation of the EQ-5D-Y-3L, we recommend valuing 20 or more health states using TTO and placing them evenly across the latent utility scale.

Higher diet quality is associated with short and long-term benefits on SF-6D health state utilities: a 5-year cohort study in an international sample of people with multiple sclerosis

Background/PurposeHealth state utilities (HSU) are a subjective measure of an individual's health-related quality of life (HRQoL), adjusted by societal or patient relative preference weights for living in different states of health-related quality of life (HRQoL), derived from patient-reported responses to multi-attribute utility instrument (MAUI), and can be used as inputs for cost-utility analyses and in clinical assessment. This research assessed associations of diet with subsequent HSU in a large international cohort of people living with multiple sclerosis (MS), a progressive autoimmune condition of the central nervous system.MethodsHSUs were generated from responses to Short-Form Six-Dimension (SF-6D) MAUI, and quality-of-the-diet by Diet Habits Questionnaire (DHQ). Cross-sectional, and short- and long-term prospective associations of DHQ with HSU evaluated by linear regression at 2.5- and 5-years. Pooled prospective associations between DHQ and HSU evaluated using linear and quantile regression. Analyses adjusted for relevant demographic and clinical covariates.ResultsAmong 839 participants, baseline DHQ scores showed short- and long-term associations with subsequent HSU, each 10-unit increase in total DHQ score associated with 0.008–0.012 higher HSU (out of 1.00). These associations were dose-dependent, those in the top two quartiles of baseline DHQ scores having 0.01–0.03 higher HSU at follow-up, 0.03 being the threshold for a minimally clinically important difference. Fat, fiber, and fruit/vegetable DHQ subscores were most strongly and consistently associated with better HSU outcomes. However, baseline meat and dairy consumption were associated with 0.01–0.02 lower HSU at subsequent follow-up.ConclusionsA higher quality-of-the-diet showed robust prospective relationships with higher HSUs 2.5- and 5-years later, substantiating previous cross-sectional relationships in this cohort. Subject to replication, these results suggest interventions to improve the quality-of-the-diet may be effective to improve HRQoL in people living with MS.

Prospective study of loss of health-related quality adjusted life years in children and their families due to uncomplicated and hospitalised varicella.

Although usually benign, varicella can lead to serious complications and sometimes long-term sequelae. Vaccines are safe and effective but not yet included in immunisation programmes in many countries. We aimed to quantify the impact on health-related quality of life (HRQoL) in terms of quality-adjusted life years (QALY) in children with varicella and their families, key to assessing cost-utility in countries with low mortality due to this infection. Children with varicella in the community and admitted to hospitals in Portugal were included over 18months from January 2019. Children's and carers' HRQoL losses were assessed prospectively using standard multi-attribute utility instruments for measuring HRQoL (EQ-5D and CHU9D), from presentation to recovery, allowing the calculation of QALYs. Among 109 families with children with varicella recruited from attendees at a pediatric emergency service (community arm), the mean HRQoL loss/child was 2.0days (95% CI 1.9-2.2, n=101) (mean 5.4 QALYs/1000 children (95% CI 5.3-6.1) and 1.3days/primary carer (95% CI 1.2-1.6, n=103) (mean 3.6 QALYs /1000 carers (95% CI 3.4-4.4). Among 114 families with children admitted to hospital because of severe varicella or a complication (hospital arm), the mean HRQoL loss/child was 9.8days (95% CI 9.4-10.6, n=114) (mean 26.8 QALYs /1000 children (95% CI 25.8-29.0) and 8.5days/primary carer (95% CI 7.4-9.6, n=114) (mean 23.4 QALYs/1000 carers (95% CI 20.3-26.2). Mean QALY losses/1000 patients were particularly high for bone and joint infections [67.5 (95% CI 43.9-97.6)]. Estimates for children's QALYs lost using the CHU9D tool were well correlated with those obtained using EQ-5D, but substantially lower. The impact of varicella on HRQoL is substantial. We report the first measurements of QALYs lost in hospitalised children and in the families of children both in the community and admitted to hospital, providing important information to guide vaccination policy recommendations.

The relative contribution of co-morbidities to health-related quality of life of people with idiopathic pulmonary fibrosis using the Assessment of Quality of Life-8-Dimension multi-attribute utility instrument.

Little is known about the impact of co-morbidities on health-related quality of life (HRQoL) for people with idiopathic pulmonary fibrosis (IPF). We aimed to investigate the relative contribution of co-morbidities to HRQoL of people with IPF. N = 157 participants were recruited from the Australian IPF Registry (AIPFR). Health state utilities (HSUs), and the super-dimensions of physical and psychosocial scores were measured using the Assessment of Quality of Life-8-Dimensions (AQoL-8D). The impact of co-morbidities on HRQoL was investigated using linear regression and general dominance analyses. A higher number of co-morbidities was associated with lower HSUs (p trend = 0.002). Co-morbidities explained 9.1% of the variance of HSUs, 16.0% of physical super-dimensional scores, and 4.2% of psychosocial super-dimensional scores. Arthritis was associated with a significant reduction on HSUs (β = - 0.09, 95% confidence interval [CI] - 0.16 to - 0.02), largely driven by reduced scores on the physical super-dimension (β = - 0.13, 95% CI - 0.20 to - 0.06). Heart diseases were associated with a significant reduction on HSUs (β = - 0.09, 95% CI - 0.16 to - 0.02), driven by reduced scores on physical (β = - 0.09, 95% CI - 0.16 to - 0.02) and psychosocial (β = -0.10, 95% CI - 0.17 to - 0.02) super-dimensions. Co-morbidities significantly impact HRQoL of people with IPF, with markedly negative impacts on their HSUs and physical health. A more holistic approach to the care of people with IPF is important as better management of these co-morbidities could lead to improved HRQoL in people with IPF.

Assessing Outcomes for Cost-Utility Analysis in Children and Adolescents With Mental Health Problems: Are Multiattribute Utility Instruments Fit for Purpose?

ObjectivesThe objective of this study was to compare the concurrent and construct validity, as well as the sensitivity of 5 multiattribute utility instruments (MAUIs), including the Assessment of Quality of Life-6D (AQoL-6D), EQ-5D-Y, Health Utilities Index (HUI)-2 and HUI-3, and the Child Health Utility 9D, 1 generic pediatric quality of life instrument, with 3 routinely collected outcome measures in Australian mental health services (Strengths and Difficulties Questionnaire, Clinical Global Assessment Scale [CGAS] and the Health of the Nation Outcome Scale for Children and Adolescents) in children and adolescents diagnosed of internalizing (eg, anxiety/depression), externalizing (eg, attention deficit hyperactivity disorder/conduct disorders), and trauma/stress related mental disorders. MethodsA cross-sectional survey of measures, including demographic and basic treatment information, in children/adolescents recruited via 5 child and youth mental health services in Queensland and Victoria, Australia. Measures were either proxy or self-report completed, the CGAS and the Health of the Nation Outcome Scale for Children and Adolescents were clinician completed. ResultsThe sample included 426 participants and had a mean age of 13.7 years (range 7-18 years). Utilities (as calculated from MAUIs) were generally lower in older adolescents and those with internalizing disorders. All MAUIs and self-reported clinical measures significantly correlated with each other (absolute correlation range 0.40-0.90), with the AQoL-6D showing generally higher levels of correlations. Correlations between the MAUIs and clinician/proxy-reported measures were weak, regardless of diagnosis (absolute correlation range 0.09-0.47). Generally, EQ-5D-Y, HUI-2, and AQoL-6D were more sensitive than Child Health Utility 9D and HUI-3 when distinguishing between different severities according to clinician-assessed CGAS (effect size range 0.17-0.84). ConclusionsThe study showed that the commonly used MAUIs had good concurrent and construct validity compared with routinely used self-complete measures but poor validity when compared with clinician/proxy-completed measures. These findings generally held across different diagnoses.

PCR66 How Would the Choice of the Multi-Attribute Utility Instrument Affect the Cost-Effectiveness of Cancer Interventions? A Comparison of the FACT-8D and the AQoL

To compare the performance of the Functional Assessment of Cancer Therapy-Eight Dimension (FACT-8D), a cancer-specific multi-attribute utility instrument derived from the FACT-General (FACT-G) questionnaire, with the Assessment of Quality of Life (AQoL) as a generic instrument.

The economic evaluation of an Internet-based parental wellbeing intervention.

Internet-based parental programmes may improve parental wellbeing and mitigate the burden of mental health issues during the perinatal period. However, few studies have explored the cost and clinical impacts of such interventions. In the present study, we sought to evaluate the cost-effectiveness associated with an online cognitive behaviour therapy intervention (Baby Steps Wellbeing) to an information-only programme (Baby Care). An alongside-trial cost-effectiveness analysis was undertaken using data from a randomised clinical trial comparing the Baby Steps Wellbeing intervention to Baby Care. Direct healthcare costs, as well as indirect costs attributed to income loss, were considered. The Assessment of Quality of Life-8 Dimensions multi-attribute utility instrument was used to estimate participant utilities, and subsequently calculate quality-adjusted life years (QALYs). Incremental cost-effectiveness ratios were calculated to assess the cost-effectiveness of the intervention. The economic evaluation adopted a societal perspective. In total, 496 parents were randomised to either the Baby Steps Wellbeing intervention or the Baby Care control arm. No significant differences in costs (-$27, 95% confidence interval (CI): -$1189-$1134) or QALYs (0.051, 95% CI: -0.097-0.200) were identified. Bootstrapped results showed that the Baby Steps Wellbeing programme was cost-saving and health improving in 38% of simulations and cost-effective in another 37% of simulations. The Baby Steps Wellbeing programme was slightly cost-saving with slightly improved health outcomes compared with Baby Care. Bootstrapped results indicate the Baby Steps Wellbeing was cost-effective in 75% of simulations. Overall, the Baby Steps Wellbeing programme is an online programme that is cost-effective. Australian & New Zealand Clinical Trials Registry: ANZCTR12614001256662.

Protocol for a systematic review and meta-analysis of minimal important differences for generic multiattribute utility instruments

IntroductionGeneric multiattribute utility instruments (MAUIs) are efficient tools for determining and enumerating health-related quality of life. MAUIs accomplish this by generating health state utilities (HSUs) via algorithms. Minimal important differences...

Validation of the EQ-5D-5L and psychosocial bolt-ons in a large cohort of people living with multiple sclerosis in Australia

BackgroundMultiple sclerosis (MS) is an inflammatory, neurodegenerative disease of the central nervous system which results in disability over time and reduced quality of life. To increase the sensitivity of the EQ-5D-5L for psychosocial health, four bolt-on items from the AQoL-8D were used to create the nine-item EQ-5D-5L-Psychosocial. We aimed to externally validate the EQ-5D-5L-Psychosocial in a large cohort of people with MS (pwMS) and explore the discriminatory power of the new instrument with EQ-5D-5L/AQoL-8D.MethodsA large representative sample from the Australian MS Longitudinal Study completed the AQoL-8D and EQ-5D-5L (including EQ VAS) and both instruments health state utilities (HSUs) were scored using Australian tariffs. Sociodemographic/clinical data were also collected. External validity of EQ-5D-5L-Psychosocial scoring algorithm was assessed with mean absolute errors (MAE) and Spearman’s correlation coefficient. Discriminatory sensitivity was assessed with an examination of ceiling/floor effects, and disability severity classifications.ResultsAmong 1683 participants (mean age: 58.6 years; 80% female), over half (55%) had moderate or severe disability. MAE (0.063) and the distribution of the prediction error were similar to the original development study. Mean (± standard deviation) HSUs were EQ-5D-5L: 0.58 ± 0.32, EQ-5D-5L-Psychosocial 0.62 ± 0.29, and AQoL-8D: 0.63 ± 0.20. N = 157 (10%) scored perfect health (i.e. HSU = 1.0) on the EQ-5D-5L, but reported a mean HSU of 0.90 on the alternative instruments. The Sleep bolt-on dimension was particularly important for pwMS.ConclusionsThe EQ-5D-5L-Psychosocial is more sensitive than the EQ-5D-5L in pwMS whose HSUs approach those reflecting full health. When respondent burden is taken into account, the EQ-5D-5L-Psychosocial is preferential to the AQoL-8D. We suggest a larger confirmatory study comparing all prevalent multi-attribute utility instruments for pwMS.

Beyond QALYs and DALYs: factoring in the well-being effects of dietary supplementation with omega-3 fatty acids in dry eye syndrome

PurposeThis study aims to explore the use and relevance of WALYs (well-being-adjusted life years) in light of the utilitarian premises of neoclassical economics that continue to dominate health outcomes evaluation. QALYs (quality-adjusted life years) and DALYs (disability-adjusted life years) measure longevity and quality of life in terms of purely health-related aspects and outcomes of medical interventions. However, evaluative questions of subjective well-being may be equally important in comparing outcomes and cost-effectiveness of these interventions.Design/methodology/approachA two-phase online search strategy for refereed research on dry eye treatment with omega-3 fatty acids (omega-3s) was adopted. Phase I aimed to identify and contrast clinical parameters of efficacy in omega-3 dietary supplementation. Phase II aimed to find a preference-based, multi-attribute utility instrument specific and sensitive enough to dry eye and its consequences on patients’ subjective well-being. We then illustrate how WALYs can be conceptualized and calculated based on the search results.FindingsEmpiric therapies like omega-3s can be assessed in terms of reducing or relieving symptomatic discomfort and pain, and enabling the patient to enjoy life and derive satisfaction from daily activities. We find in VisQoL (Vision and Quality of Life Index) a viable alternative to conventional multi-attribute utility instruments, including those typically used in QALY and DALY calculations. Clinical efficacy indices of dry eye can be linked to VisQoL’s quality of life dimensions. Differently weighted outcomes can be aggregated. And WALYs per patient per year can be computed by scaling aggregated outcomes to match the WALY rating scale. The implications of subjective well-being for both patient and society can thus be approached from a broader and richer perspective.Originality/valueTo the best of our knowledge, this is the first study of its kind in pharmaceutical outcomes valuation and marketing. It offers a framework for analyzing life satisfaction and well-being among dry eye patients under treatment. It is also the first to use and adapt a multi-attribute utility measure to treatment outcomes of omega-3s in ocular diseases, from which this study suggests WALYs may be computed. However, it does not suggest that WALYs should supplant QALYs and DALYs in evaluating health outcomes. Medical economics is enriched if alternative methods of outcomes evaluations can help fill in the gaps in existing paradigms and do so by accounting for other effects of condition-specific interventions. Costs and benefits of interventions to the individual and society can then be valued not just more effectively, but also more equitably.

An examination of machine learning to map non-preference based patient reported outcome measures to health state utility values.

Non‐preference‐based patient‐reported outcome measures (PROMs) are popular in health outcomes research. These measures, however, cannot be used to estimate health state utilities, limiting their usefulness for economic evaluations. Mapping PROMs to a multi‐attribute utility instrument is one solution. While mapping is commonly conducted using econometric techniques, failing to specify the complex interactions between variables may lead to inaccurate prediction of utilities, resulting in inaccurate estimates of cost‐effectiveness and suboptimal funding decisions. These issues can be addressed using machine learning. This paper evaluates the use of machine learning as a mapping tool. We adopt a comprehensive approach to compare six machine learning techniques with eight econometric techniques to map the Patient‐Reported Outcomes Measurement Information System Global Health 10 (PROMIS‐GH10) to the EuroQol five dimensions (EQ‐5D‐5L). Using data collected from 2015 Australians, we find the least absolute shrinkage and selection operator (LASSO) model out‐performed all machine learning techniques and the adjusted limited dependent variable mixture model (ALDVMM) out‐performed all econometric techniques, with the LASSO performing better than ALDVMM. The variable selection feature of LASSO was then used to enhance the performance of the ALDVMM in a hybrid model. Our analysis identifies the potential benefits and challenges of using machine learning techniques for mapping and offers important insights for future research.

Criteria for developing, assessing and selecting candidate EQ-5D bolt-ons

Purpose‘Bolt-on’ dimensions are additional items added to multi-attribute utility instruments (MAUIs) such as EQ-5D that measure constructs not included in the core descriptive system. The use of bolt-ons has been proposed to improve the content validity and responsiveness of the descriptive system in certain settings and health conditions. EQ-5D bolt-ons serve a particular purpose and thus satisfy a certain set of criteria. The aim of this paper is to propose a set of criteria to guide the development, assessment and selection of candidate bolt-on descriptors.MethodsCriteria were developed using an iterative approach. First, existing criteria were identified from the literature including those used to guide the development of MAUIs, the COSMIN checklist and reviews of existing bolt-ons. Second, processes used to develop bolt-ons based on qualitative and quantitative approaches were considered. The information from these two stages was formalised into draft development and selection criteria. These were reviewed by the project team and iteratively refined.ResultsOverall, 23 criteria for the development, assessment and selection of candidate bolt-ons were formulated. Development criteria focused on issues relating to i) structure, ii) language, and iii) consistency with the existing EQ-5D dimension structure. Assessment and selection criteria focused on face and content validity and classical psychometric indicators.ConclusionThe criteria generated can be used to guide the development of bolt-ons across different health areas. They can also be used to assess existing bolt-ons, and inform their inclusion in studies and patient groups where the EQ-5D may lack content validity.