Condition-specific Preference-based Measures Research Articles

Assessing the Content Validity of Preference-Based Measures in Cancer

ObjectivesThis study assessed the content validity of generic and condition-specific preference-based measures (PBMs) with patients treated for cancer, evaluated against 10 Consensus-Based Standards for the Selection of Health Measurement Instruments criteria for good content validity, to best inform measurement strategies regarding the use of PBMs in oncology development programs and real-world applications. MethodsIndividual, semistructured interviews were conducted with patients who received drug treatment for cancer in the United Kingdom (n = 47) and the United States (n = 49). During the interview, patients completed 3 generic PBMs (EQ-5D-5L, EuroQol Health and Wellbeing measure–Short Form, Château Santé Base) and 2 condition-specific PBMs (Quality of Life Utility-Core 10 Dimension, Functional Assessment of Cancer Therapy Eight Dimension [FACT-8D]). Interviews were conducted via teleconference, audio recorded, and transcribed verbatim. Transcripts were coded using thematic and content analysis methods. ResultsCondition-specific measures were evaluated as having better relevancy than generic PBMs. Overall, the FACT-8D was evaluated as holding the best content validity in terms of relevancy, and the EuroQol Health and Wellbeing measure–Short Form received the most favorable evaluation of relevancy for generic PBMs. All measures demonstrated comparable comprehensiveness, with all suggested by patients to be missing concepts. The EQ-5D-5L was evaluated best in terms of comprehensibility. This was followed by the Quality of Life Utility-Core 10 Dimension and FACT-8D; both received similar evaluations. ConclusionsAll measures were generally seen by patients as adequate in capturing appropriate aspects of health-related quality of life for measuring cancer outcomes, although together condition-specific measures were evaluated as having better relevancy than generic PBMs. Further health-related quality of life instrument development is encouraged, particularly with regard to the longer-term detrimental impacts of cancer and treatment side effects. Other developments could include new cancer-specific tools inclusive of conventional health items, treatment impacts, and psychological items.

A Comparison of Generic and Condition-Specific Preference-Based Measures Using Data From Nivolumab Trials: EQ-5D-3L, Mapping to the EQ-5D-5L, and European Organisation for Research and Treatment of Cancer Quality of Life Utility Measure-Core 10 Dimensions

ObjectivesThere is growing interest in condition-specific preference measures, including the European Organisation for Research and Treatment of Cancer Quality of Life Utility Measure-Core 10 Dimensions (QLU-C10D). This research assessed the implications of using utility indices on the basis of the EQ-5D-3L, a mapping of EQ-5D-3L to the EQ-5D-5L, and the QLU-C10D, and compared their psychometric properties. MethodsData were taken from 8 phase 3 randomized controlled trials of nivolumab with or without ipilimumab for the treatment of solid tumors. Utilities for progression-related states were calculated using the UK and English value sets and incremental quality-adjusted life-years (QALYs) derived from established UK cost-effectiveness models. The psychometric properties of the utility indices were assessed using pooled trial data. ResultsCompared with the EQ-5D-3L index, the mapped EQ-5D-5L index yielded an average of 6% more and the QLU-C10D index an average of 2% fewer incremental QALYs for nivolumab versus comparators. All indices could differentiate between groups defined by performance status, cancer stage, or self-reported health status at baseline and detect meaningful changes in performance status, tumor response, health status, and quality of life over approximately 12 weeks of treatment. ConclusionsThe lower QALY yield of the QLU-C10D was balanced by evidence of greater validity and responsiveness. Benefits gained from using the QLU-C10D may be apparent when treatments affect targeted symptoms and functional aspects, including sleep, bowel function, appetite, nausea, and fatigue. The observed differences in QALYs may not be sufficiently large to affect health technology assessment decisions.

Discrete choice experiments to generate utility values for multi-attribute utility instruments: a systematic review of methods.

In recent years, discrete choice experiments (DCEs) have become frequently used to generate utility values, but there are a diverse range of approaches to do this. The primary focus of this systematic review is to summarise the methods used for the design and analysis of DCEs when estimating utility values in both generic and condition-specific preference-based measures. Published literature using DCEs to estimate utility values from preference-based instruments were identified from MEDLINE, Embase, Cochrane Library and CINAHL using PRISMA guidelines. To assess the different DCE methods, standardised information was extracted from the articles including the DCE design method, the number of choice sets, the number of DCE pairs per person, randomisation of questions, analysis method, logical consistency tests and techniques for anchoring utilities. The CREATE checklist was used to assess the quality of the studies. A total of 38 studies with samples from the general population, students and patients were included. Values for health states described using generic multi attribute instruments (MAUIs) (especially the EQ-5D) were the most commonly explored using DCEs. The studies showed considerable methodology and design diversity (number of alternatives, attributes, sample size, choice task presentation and analysis). Despite these differences, the quality of articles reporting the methods used for the DCE was generally high. DCEs are an important approach to measure utility values for both generic and condition-specific instruments. However, a gold standard method cannot yet be recommended.

The Role of Condition-Specific Preference-Based Measures in Health Technology Assessment.

A condition-specific preference-based measure (CSPBM) is a measure of health-related quality of life (HRQOL) that is specific to a certain condition or disease and that can be used to obtain the quality adjustment weight of the quality-adjusted life-year (QALY) for use in economic models. This article provides an overview of the role and the development of CSPBMs, and presents a description of existing CSPBMs in the literature. The article also provides an overview of the psychometric properties of CSPBMs in comparison with generic preference-based measures (generic PBMs), and considers the advantages and disadvantages of CSPBMs in comparison with generic PBMs. CSPBMs typically include dimensions that are important for that condition but may not be important across all patient groups. There are a large number of CSPBMs across a wide range of conditions, and these vary from covering a wide range of dimensions to more symptomatic or uni-dimensional measures. Psychometric evidence is limited but suggests that CSPBMs offer an advantage in more accurate measurement of milder health states. The mean change and standard deviation can differ for CSPBMs and generic PBMs, and this may impact on incremental cost-effectiveness ratios. CSPBMs have a useful role in HTA where a generic PBM is not appropriate, sensitive or responsive. However, due to issues of comparability across different patient groups and interventions, their usage in health technology assessment is often limited to conditions where it is inappropriate to use a generic PBM or sensitivity analyses.

Condition-specific or generic preference-based measures in oncology? A comparison of the EORTC-8D and the EQ-5D-3L

PurposeIt has been argued that generic health-related quality of life measures are not sensitive to certain disease-specific improvements; condition-specific preference-based measures may offer a better alternative. This paper assesses the validity, responsiveness and sensitivity of a cancer-specific preference-based measure, the EORTC-8D, relative to the EQ-5D-3L.MethodsA longitudinal prospective population-based cancer genomic cohort, Cancer 2015, was utilised in the analysis. EQ-5D-3L and the EORTC QLQ-C30 (which gives EORTC-8D values) were asked at baseline (diagnosis) and at various follow-up points (3 months, 6 months, 12 months). Baseline values were assessed for convergent validity, ceiling effects, agreement and sensitivity. Quality-adjusted life-years (QALYs) were estimated and similarly assessed. Multivariate regression analyses were employed to understand the determinants of the difference in QALYs.ResultsComplete case analysis of 1678 patients found that the EQ-5D-3L values at baseline were significantly lower than the EORTC-8D values (0.748 vs 0.829, p < 0.001). While the correlation between the instruments was high, agreement between the instruments was poor. The baseline health state values using both instruments were found to be sensitive to a number of patient and disease characteristics, and discrimination between disease states was found to be similar. Mean generic QALYs (estimated using the EQ-5D-3L) were significantly lower than condition-specific QALYs (estimated using the EORTC-8D) (0.860 vs 0.909, p < 0.001). The discriminatory power of both QALYs was similar.ConclusionsWhen comparing a generic and condition-specific preference-based instrument, divergences are apparent in both baseline health state values and in the estimated QALYs over time for cancer patients. The variability in sensitivity between the baseline values and the QALY estimations means researchers and decision makers are advised to be cautious if using the instruments interchangeably.

A Systematic Review of the Literature on the Development of Condition-Specific Preference-Based Measures of Health.

Health state utility values (HSUVs) are required to calculate quality-adjusted life-years (QALYs). They are frequently derived from generic preference-based measures of health. However, such generic measures may not capture health attributes of relevance to specific conditions. In such cases, a condition-specific preference-based measure (CSPBM) may be more appropriate. This systematic review aimed to identify all published accounts of developing CSPBMs to describe and appraise the methods used. We undertook a systematic search (of Embase, MEDLINE, PsycINFO, Web of Science, the Cochrane Library, CINAHL, EconLit, ASSIA and the Health Management Information Consortium database) to identify published accounts of CSPBM development up to July 2015. Studies were reviewed to investigate the methods used to design classification systems, estimate HSUVs, and validate the measures. A total of 86 publications were identified, describing 51 CSPBMs. Around two-thirds of these were QALY measures; the remainder were designed for clinical decision making only. Classification systems for 33 CSPBMs were derived from existing instruments; 18 were developed de novo. HSUVs for 34 instruments were estimated using a 'composite' approach, involving statistical modelling; the remainder used a 'decomposed' approach based on multi-attribute utility theory. Half of the papers that described the estimation of HSUVs did not report validating their measures. Various methods have been used at all stages of CSPBM development. The choice between developing a classification system de novo or from an existing instrument may depend on the availability of a suitable existing measure, while the choice between a decomposed or composite approach appears to be determined primarily by the purpose for which the instrument is designed. The validation of CSPBMs remains an area for further development.

Economic evaluation in short bowel syndrome (SBS): an algorithm to estimate utility scores for a patient-reported SBS-specific quality of life scale (SBS-QoL™)

Condition-specific preference-based measures can offer utility data where they would not otherwise be available or where generic measures may lack sensitivity, although they lack comparability across conditions. This study aimed to develop an algorithm for estimating utilities from the short bowel syndrome health-related quality of life scale (SBS-QoL™). SBS-QoL™ items were selected based on factor and item performance analysis of a European SBS-QoL™ dataset and consultation with 3 SBS clinical experts. Six-dimension health states were developed using 8 SBS-QoL™ items (2 dimensions combined 2 SBS-QoL™ items). SBS health states were valued by a UK general population sample (N = 250) using the lead-time time trade-off method. Preference weights or 'utility decrements' for each severity level of each dimension were estimated by regression models and used to develop the scoring algorithm. Mean utilities for the SBS health states ranged from -0.46 (worst health state, very much affected on all dimensions) to 0.92 (best health state, not at all affected on all dimensions). The random effects model with maximum likelihood estimation regression had the best predictive ability and lowest root mean squared error and mean absolute error, and was used to develop the scoring algorithm. The preference-weighted scoring algorithm for the SBS-QoL™ developed is able to estimate a wide range of utility values from patient-level SBS-QoL™ data. This allows estimation of SBS HRQL impact for the purpose of economic evaluation of SBS treatment benefits.

Development of DEMQOL-U and DEMQOL-PROXY-U: generation of preference-based indices from DEMQOL and DEMQOL-PROXY for use in economic evaluation

Dementia is one of the most common and serious disorders in later life and the economic and personal cost of caring for people with dementia is immense. There is a need to be able to evaluate interventions in dementia using cost-effectiveness analyses, but the generic preference-based measures typically used to measure effectiveness do not work well in dementia. Existing dementia-specific measures can effectively measure health-related quality of life but in their current form cannot be used directly to inform cost-effectiveness analysis using quality-adjusted life-years as the measure of effectiveness. The aim was to develop two brief health-state classifications, one from DEMQOL and one from DEMQOL-Proxy, to generate health states amenable to valuation. These classification systems consisted of items taken from DEMQOL and DEMQOL-Proxy so they can be derived from any study that has used these instruments. In the first stage of the study we used a large, clinically representative sample aggregated from two sources: a sample of patients and carers attending a memory service in south London and a sample of patients and carers from other community services in south London. This included 644 people with a diagnosis of mild/moderate dementia and 689 carers of those with mild/moderate dementia. For the valuation study, the general population sample of 600 respondents was drawn to be representative of the UK general population. Households were sampled in urban and rural areas in northern England and balanced to the UK population according to geodemographic profiles. In the patient/carer valuation study we interviewed a sample of 71 people with mild dementia and 71 family carers drawn from a memory service in south London. Finally, the instruments derived were applied to data from the HTA-SADD (Study of Antidepressants for Depression in Dementia) trial. This was a complex multiphase study with four linked phases: phase 1 - derivation of the health-state classification system; phase 2 - general population valuation survey and modelling to produce values for every health state; phase 3 - patient/carer valuation survey; and phase 4 - application of measures to trial data. All four phases were successful and this report details this development process leading to the first condition-specific preference-based measures in dementia, an important new development in this field. The first limitation relates to the lack of an external data set to validate the DEMQOL-U and DEMQOL-Proxy-U classification systems. Throughout the development process we have made decisions about which methodology to use. There are other valid techniques that could be used and it is possible to criticise the choices that we have made. It is also possible that the use of a mild to moderate dementia sample has resulted in classification systems that do not fully reflect the challenges of severe dementia. The results presented are sufficiently encouraging to recommend that the DEMQOL instruments be used alongside a generic measure such as the European Quality of Life-5 Dimensions (EQ-5D) in future studies of interventions in dementia as there was evidence that they can be more sensitive for patients at the milder end of disease and some limited evidence that the person with dementia measure may be able to reflect deterioration. The National Institute for Health Research Health Technology Assessment programme.

Developing and testing methods for deriving preference-based measures of health from condition-specific measures (and other patient-based measures of outcome).

Generic preference-based measures such as EQ-5D are widely used to estimate quality-adjusted life-years but may not be available or, more importantly, appropriate in some medical conditions. Condition-specific preference-based measures (CSPBMs) provide an alternative to generic measures that may be more relevant in some conditions. This project conducted five studies to examine issues in the development and use of CSPBMS: (1) literature review of measures; (2) deriving health states values for classifications with highly correlated dimensions; (3) impact of condition labelling; (4) impact of add-on dimensions; and (5) comparative performance of measures. (1) Systematic search and literature review; (2) and (5) psychometric analyses on existing data; (2), (3) and (4) valuation surveys and survey analyses. Valuation surveys conducted using face-to-face interviews in the respondents' homes. Valuation surveys conducted using representative samples of the UK general population. Not applicable. The project developed a CSPBM CORE-6D and analyses AQL-5D, CORE-6D, EORTC-8D, EQ-5D, OAB-5D and SF-6D data. (1) There was substantial variability in methods used to develop CSPBMs. (2) A new method for generating states using Rasch analysis was undertaken, which successfully dealt with the problem of highly correlated domains. (3) Condition labels affected utility values but this was dependent on the condition and severity of the health state. (4) Adding on an extra dimension affected health-state values and preference weights for other dimensions. (5) The performance of CSPBMs was comparable with that of their parent instrument and of generic preference-based measures with better performance for discrimination between severity groups. CSPBMs have an important role for economic evaluation, for which generic measures are inappropriate. However, their use in economic evaluation may be compromised by naming the condition; the exclusion of side effects and comorbidities; and focusing effects. Whether a reduction in comparability should be accepted depends on the extent of any gain in validity and responsiveness. This will depend on the condition and measure in question. Research agenda: (1) The appropriateness of generic preference-based measures should be examined in more conditions (and compared with CSPBMs). (2) Further quantitative and qualitative work is requested into the impact of, and reasons for labelling effects. (3) Use of add-ons for condition-specific measures (for side effects and comorbidities) and as a solution to the limitation of generic measures should be explored. The National Institute for Health Research Health Technology Assessment programme.

Condition-Specific Preference-Based Measures: Benefit or Burden?

ObjectivesSome argue that generic preference-based measures (PBMs) are not sensitive to certain disease-specific improvements. To overcome this problem, new condition-specific PBMs (CS-PBMs) are being developed, but it is not yet clear how such measures compare with existing generic PBMs. MethodWe generated CS-PBMs from three condition-specific questionnaires (Health Assessment Questionnaire for arthritis, Quality of Life Questionnaire for Cancer 30 for cancer, and Multiple Sclerosis Impact Scale 29 for multiple sclerosis). First, the questionnaires were reduced in content, and then, a time trade-off study was conducted in the general public (N = 402) to obtain weights associated with the dimensions and levels of the new questionnaire. Finally, we compared utilities obtained by using the CS-PBMs with utilities obtained by using the EuroQol five-dimensional (EQ-5D) questionnaire in four data sets. ResultsUtility values generated by the CS-PBMs were higher than those of the EQ-5D questionnaire. The Health Assessment Questionnaire–based measure for arthritis proved to be insensitive to comorbidities. Measures based on the Multiple Sclerosis Impact Scale 29 and the Quality of Life Questionnaire for Cancer 30 discriminated comorbidities and side effect equally well as the EQ-5D questionnaire and were more sensitive than the EQ-5D questionnaire for mild impairments. ConclusionsThe introduction of PBMs that are specific to a certain disease may have the merit of sensitivity to disease-specific effects of interventions. That gain, however, is traded off to the loss of comparability of utility values and, in some cases, insensitivity to side effects and comorbidity. The use of a CS-PBM for cost-utility analysis is warranted only under strict conditions.

Utility Estimation in Chronic Obstructive Pulmonary Disease

Economic evaluations of chronic obstructive pulmonary disease (COPD) incorporate utilities through multi-attribute utility (MAU) measures, most commonly the EQ-5D, to report health-related quality-of-life (HR-QOL) changes or differences. Questions have been raised about the sensitivity of these measures in COPD. Limitations in detecting adequate patient-level changes in HR-QOL over time in stable and exacerbation states compared with disease-specific instruments could also result in underestimation of known treatment benefits. The purpose of this article was to present and discuss the empirical evidence on the validity of generic MAU measures within the COPD population. We built upon a previously conducted validation review for the period 1997-2007 that used 'respiratory disease' and 'EQ-5D' as keywords. For this discussion, PubMed and EMBASE databases were searched for articles in English from 1988 to August 2009, using similar search words. Based on the performance of MAU measures in COPD and exacerbations, they appear to have limited discriminatory ability, particularly between moderate and severe COPD, despite known differences in HR-QOL. Sensitivity to clinically relevant change in stable COPD over time due to treatment also appears limited. Current research suggests adequate sensitivity regarding detecting the onset and resolution of an exacerbation; however, sensitivity is limited in the short term, such as daily changes in health status. The evidence suggests responsiveness of MAU measures may be restricted to large within-patient change, which leads to difficulties in evaluating the subtle but important impact of exacerbations. Studies presenting alternative methods of deriving COPD-related utilities are also discussed. Overall, the insensitivities of generic MAU measures in COPD can lead to biased cost-effectiveness analyses and ill-informed economic decisions. Alternative measures such as condition-specific preference-based measures may be used in circumstances where more sensitivity is needed. The trade-off allows relevant and sensitive matters most important to patients to be evaluated; however inevitable gaps such as those related to adverse events are not considered.

Comparison of health state utility values derived using time trade-off, rank and discrete choice data anchored on the full health-dead scale

Recent years have seen increasing interest in the use of ordinal methods to elicit health state utility values as an alternative to conventional methods such as standard gamble and time trade-off (TTO). However, in order to use these ordinal methods to produce health state values for use in cost-effectiveness analysis using cost per quality adjusted life year (QALY) analysis, these values must be anchored on the full health-dead scale. The paper reports on two feasibility studies that use two approaches to anchor health state utility values derived from discrete choice data on the full health-dead scale: normalising using (1) the TTO value of the worst state and (2) the coefficient on the 'dead' dummy variable. Health state utility values obtained using rank and discrete choice data are compared to more commonly used TTO utility values for two condition-specific preference-based measures; asthma and overactive bladder. Ordinal methods were found to offer a promising alternative to conventional cardinal methods of standard gamble and TTO. There remains a large and important research agenda to address.

The impact of adding an extra dimension to a preference-based measure

The ability to compare incremental changes in Quality Adjusted Life Years (QALYs) generated by different condition-specific preference-based measures (CSPBMs), or indeed between generic measures, is often criticised even where the valuation methods and source of values are the same. A key concern is the impact of excluding key dimensions from a descriptive system. This study examines the impact of adding a generic pain/discomfort dimension to a CSPBM, the AQL-5D (an asthma-specific CSPBM), by valuing samples of states from the AQL-5D with and without the new dimension using an interviewer administered time trade-off with a sample of the UK general public. 180 respondents provided 720 valuations for states with and without pain/discomfort. As expected the additional pain/discomfort dimension was found to have a significant and relatively large coefficient. More importantly for comparing changes in QALYs across populations the addition of pain/discomfort significantly impacts on the coefficients of the other dimensions and the degree of impact differs by dimension and severity level. The net effect on the utility value depends on the severity of their state: the addition of pain/discomfort at level 1 (no pain/discomfort) or 2 (moderate pain/discomfort) significantly increased the mean health state values in an asthma patient population; whereas level 3 pain/discomfort (extreme) reduced values. Comparability between measures requires that the impact of different dimensions on preferences is additive, whether or not they are included in the classification system. Our results cast doubt on this assumption, implying that the chosen measure must contain all important and relevant dimensions in its classification system.

Estimation of a Preference-Based Index from a Condition-Specific Measure: The King's Health Questionnaire

Generic preference-based measures of health may not adequately cover the impact of some conditions. There is therefore increasing interest in developing condition-specific preference-based measures. The purpose of this study was to estimate a preference-based measure from a condition-specific measure of health for urinary incontinence, the 21-item King's Health Questionnaire, for use in economic evaluation. The King's Health Questionnaire (KHQ) was revised into a 5-dimensional health state classification amenable to valuation using items selected using psychometric evidence. Forty-nine states were valued using standard gamble by a representative sample of patients with urinary incontinence attending UK hospital outpatient clinics. Each respondent was asked to value 9 health states. Models have been estimated for predicting health state valuations for all 1024 states defined by the KHQ classification. The modeling had to cope with the clustering of data by respondent and its skewed distribution. In total, 110 usable interviews were obtained from 169 patients approached to participate in the study. These responders generated 959 health state valuations. Mean health state values ranged from 0.77 to 0.98. Models were estimated using mean health state values and random effects models of individual-level health state values. These models generated robust estimates of the "main effects," and in general, the results support the ordinality of the KHQ health state classification. There were problems modeling interaction effects, and a number of alternatives were explored. The recommended model for estimating a preference-based measure from the condition-specific KHQ is presented.

Psychological therapies including dialectical behaviour therapy for borderline personality disorder: a systematic review and preliminary economic evaluation

To summarise the available evidence on the clinical effectiveness and cost-effectiveness of psychological therapies including dialectical behaviour therapy (DBT) for borderline personality disorder (BPD). Electronic databases were searched up to March 2005. Relevant studies were assessed using standard checklists and data were abstracted by two reviewers using standardised forms. Separate economic evaluations were undertaken for six selected randomised controlled trials (RCTs). Cost-effectiveness was assessed in terms of cost per parasuicide event avoided in all six trials and cost per quality-adjusted life-year (QALY) in four of them. All results are at 2003-4 prices and for 12 months follow-up. Nine RCTs and one non-RCT of moderate to poor quality were identified in the clinical effectiveness review. They provided some evidence that DBT is more effective than treatment as usual (TAU) for the treatment of chronically parasuicidal and drug-dependent borderline women; that DBT-orientated therapy is more effective than client-centred therapy (CCT) for the treatment of BPD; and that DBT is as effective as comprehensive validation therapy plus 12-Step for the treatment of opioid-dependent borderline women. There was also some evidence that partial hospitalisation is more effective than TAU in the treatment of BPD, good evidence that manual-assisted cognitive behavioural therapy (MACT) is no more effective than TAU in the treatment of BPD and some evidence that interpersonal group therapy is no more effective than individual mentalisation-based partial hospitalisation (MBT) for the treatment of BPD. However, these results should be interpreted with caution as not all studies were primarily targeted to borderline symptoms and there were considerable differences between the studies. The assessment of cost-effectiveness found a mix of results in the four trials of DBT, along with the high levels of uncertainty and the limitations in the analyses. The findings do not support the cost-effectiveness of DBT though they suggest it has the potential to be cost-effective. The results for MBT are promising, though again surrounded by a high degree of uncertainty and for MACT, the analysis suggests that the intervention is unlikely to be cost-effective. The overall efficacy of psychological therapies is promising; however, at this stage the evidence is inconclusive. The cost-effectiveness of the intervention in six RCTs examined, however, does not support the cost-effectiveness of DBT although potential is suggested. There is a need for considerable research in this area. This research should involve appropriately powered head-to-head RCTs of psychological therapies; a survey of current practice and the use of the full range of services by people with BPD to inform future economic analyses; full resource-use data collected in the context of pragmatic clinical trials; psychometric assessment of the validity of the EQ-5D or other generic and condition-specific preference-based measures in BPD, and the development of a more formal cost-effectiveness model using the above data.