Application of a disease-specific mapping function to estimate utility gains with effective treatment of schizophrenia

Mapping the schizophrenia quality of life scale to EQ-5D, HUI3 and SF-6D utility scores in patients with schizophrenia

OBJECTIVES

The current study aimed to map the disease-specific Schizophrenia Quality of Life Scale (SQLS) onto the three- and five-level EuroQol five-dimension (EQ-5D-3 L and EQ-5D-5 L), Health Utility Index Mark 3 (HUI3) and Short Form six-dimensional (SF-6D) preference-based instruments to inform future cost-utility analyses for treatment of patients with schizophrenia.

METHODS

Data from 251 outpatients with schizophrenia spectrum disorders was included for analysis. Ordinary least square (OLS), Tobit and beta regression mixture models were employed to estimate the utility scores. Three regression models with a total of 66 specifications were determined by goodness of fit and predictive indices. Distribution of the original data to the distributions of the data generated using the preferred estimated models were then compared.

RESULTS

EQ-5D-3 L and EQ-5D-5 L were best predicted by the OLS model, including SQLS domain scores, domain-squared scores, age, and gender as explanatory predictors. The models produced the best performance index and resembled most closely with the observed EQ-5D data. HUI3 and SF-6D were best predicted by the OLS and Tobit model respectively.

CONCLUSION

The current study developed mapping models for converting SQLS scores into generic utility scores, which can be used for economic evaluation among patients with schizophrenia.

Cognitive Behavioural Therapy for Psychosis: A Health Technology Assessment

BACKGROUND

Cognitive behavioural therapy (CBT) for psychosis is a distinct type of psychotherapy that has been recommended together with antipsychotic drugs and comprehensive usual care in the management of schizophrenia, a complex mental health disorder associated with a high economic and societal burden. The objectives of this report were to assess the effectiveness, harms, cost-effectiveness, and lived experience of CBT for psychosis in improving outcomes for adults with a primary diagnosis of schizophrenia.

METHODS

We performed literature searches on March 28 and April 5, 2017, and undertook a qualitative synthesis of systematic reviews of the clinical and economic literature comparing CBT for psychosis with any comparator interventions (e.g., usual care, waitlist control, or pharmacotherapy) in adults with a diagnosis of schizophrenia as defined by any criteria (including related disorders such as schizoaffective disorder).We developed an individual-level state-transition probabilistic model for a hypothetical cohort of adults aged 18 years and older starting with first-episode psychosis. We compared three strategies: usual care, CBT for psychosis by physicians, and CBT for psychosis by regulated nonphysician therapists. The CBT was provided in person together with usual care including pharmacotherapy: 16 structured sessions (individual or group) for first-episode psychosis and 24 individual sessions for relapse or treatment-resistant disease. We calculated incremental cost-effectiveness ratios (ICERs) over 5 years using the Ontario Ministry of Health and Long-Term Care perspective and a discount rate of 1.5%. We also estimated the 5-year budget impact of publicly funding CBT for psychosis in Ontario.In addition, we interviewed 13 people with lived experience of schizophrenia and psychosis about their values and preferences surrounding CBT and other treatments.

RESULTS

CBT for psychosis compared with usual care significantly improved overall psychotic symptoms (standard mean difference [SMD] -0.33, 95% confidence interval [CI] -0.45 to -0.21), positive symptoms (e.g., hallucinations) (SMD -0.34, 95% CI -0.58 to -0.10), auditory symptoms (SMD 0.39, 95% Cl not reported, P < .005), delusions (SMD 0.33, 95% CI not reported, P < .05) and negative symptoms (e.g., blunt affect) (SMD -0.32, 95% CI -0.59 to -0.04) at end of treatment. No significant differences were observed for social function, distress associated with psychosis, relapse, or quality of life.Compared with any control, CBT for psychosis significantly improved overall psychotic symptoms, positive symptoms, auditory hallucinations, delusions, and negative symptoms. Compared with other forms of therapy, CBT for psychosis showed inconsistent results at end of treatment for overall psychotic symptoms, positive symptoms, auditory hallucinations, and delusions. In people with first-episode psychosis, CBT for psychosis was not significantly more effective for the prevention of relapse when compared with other forms of therapy or usual care (odds ratio [OR] 1.11, 95% CI 0.63-1.95 and OR 1.15, 95% CI 0.65-2.04, respectively).Low-intensity CBT for psychosis (fewer than 16 face-to-face sessions) compared with any type of treatment significantly improved overall psychotic symptoms and social function at follow-up (SMD -0.40, 95% CI -0.74 to -0.06 and SMD -0.57, 95% CI -0.81 to -0.33, respectively).In the cost-utility analysis, CBT for psychosis provided by nonphysician therapists compared with usual care was associated with increases in both quality-adjusted life-years (mean 0.1159 QALYs, 95% credible interval [CrI] 0.09-0.14) and costs (mean $2,494, 95% Crl $1,472-$3,544), yielding an ICER of $21,520 per QALY gained. CBT for psychosis provided by physicians was dominated because it was equally effective but more expensive (mean $2,976, 95% CrI $2,822-$3,129; ICER of CBT for psychosis vs. usual care: $47,196/QALY gained).Assuming a 20% increase in access per year (from 0% at baseline to 100% in year 5), we estimated the total 5-year net budget impact of publicly funding CBT for psychosis would be about $15.2 million for nonphysician providers and about $35.4 million if provided by psychiatrists. It is estimated that by the year 2021, approximately 110 nonphysician therapists or 150 physicians would be needed to provide CBT for psychosis to more than 12,000 adults with schizophrenia (including about 8,500 incident cases) in Ontario.People with schizophrenia and their family members reported positive experiences with CBT for psychosis. They felt it provided effective tools to help manage their schizophrenia but stressed that it was only effective in conjunction with medication to control psychotic episodes and overcome a patient's denial of illness. Geographic and financial barriers have restricted access to this psychotherapy.

CONCLUSIONS

Compared with usual care or any control, CBT for psychosis significantly improved psychotic symptoms, based on evidence of moderate to adequate quality; no significant improvements were observed for social function, relapse, or quality of life outcomes. People affected by schizophrenia reported that CBT for psychosis was valuable in conjunction with antipsychotic medication but that access to this type of psychotherapy is limited. Adding CBT for psychosis to usual care in the management of adult schizophrenia probably represents good value for money in Ontario. Depending on the type of provider, therapy format, and rate of access, the net budget impact to Ontario's publicly funded health system would likely be between $15 million to $35 million over the next 5 years.

A systematic review of health economic models and utility estimation methods in schizophrenia

INTRODUCTION

There is a growing need for economic evaluations describing the disease course, as well as the costs and clinical outcomes related to the treatment of schizophrenia.

AREAS COVERED

A systematic review on studies describing health economic models in schizophrenia and a targeted literature review on utility mapping algorithms in schizophrenia were carried out. Models found in the review were collated and assessed in detail according to their type and various other attributes. Fifty-nine studies were included in the review. Modeling techniques varied from simple decision trees to complex simulation models. The models used various clinical endpoints as value drivers, 47% of the models used quality-adjusted life years, and eight percent used disability-adjusted life years to measure benefits, while others applied various clinical outcomes. Most models considered patients switching between therapies, and therapeutic adherence, compliance or persistence. The targeted literature review identified four main approaches to map PANSS scores to utility values.

EXPERT COMMENTARY

Health economic models developed for schizophrenia showed great variability, with simulation models becoming more frequently used in the last decade. Using PANSS scores as the basis of utility estimations is justifiable.

Quality-adjusted life year difference in patients with predominant negative symptoms of schizophrenia treated with cariprazine and risperidone

AIM

Our study aimed at estimating differences in quality-adjusted life year (QALY) gain for patients with predominant negative symptoms of schizophrenia treated with cariprazine compared with risperidone.

MATERIALS & METHODS

A Markov model was built, based on the Mohr-Lenert approach and data derived from clinical trials, to estimate potential QALY gains of patients.

RESULTS

Patients had higher probability of reaching better health states treated with cariprazine compared with risperidone. In the model, this resulted in an estimated QALY gain of 0.029 per patient, after 1 year of treatment.

CONCLUSION

Cariprazine, which showed clinically meaningful improvement in the symptoms, and personal and social performance, can also provide significant QALY gain in the treatment of patients with predominant negative symptoms of schizophrenia compared with risperidone.

Predictive models to estimate utility from clinical questionnaires in schizophrenia: findings from EuroSC

OBJECTIVE

The clinical symptoms of schizophrenia are associated with serious social, quality of life and functioning alterations. Typically, data on health utilities are not available in clinical studies in schizophrenia. This makes the economic evaluation of schizophrenia treatments challenging. The purpose of this article was to provide a mapping function to predict unobserved utility values in patients with schizophrenia from the available clinical and socio-demographic information.

METHODS

The analysis was performed using data from EuroSC, a 2-year, multi-centre, cohort study conducted in France (N = 288), Germany (N = 618), and the UK (N = 302), totalling 1208 patients. Utility was calculated based on the EQ-5D questionnaire. The relationships between the utility values and the patients' socio-demographic and clinical characteristics (Positive and Negative Syndrome Scale--PANSS, Calgary Depression Scale for Schizophrenia--CDSS, Global Assessment of Functioning--GAF, extra-pyramidal symptoms measured by Barnes Akathisia Scale-BAS, age, sex, country, antipsychotic type) were modelled using a random and a fixed individual effects panel linear model.

RESULTS

The analysis demonstrated the prediction ability of the used parameters for estimating utility measures in patients with schizophrenia. Although there are small variations between countries, the same variables appear to be the key predictors. From a clinical perspective, age, gender, psychopathology, and depression were the most important predictors associated with the EQ-5D.

CONCLUSION

This paper proposed a reliable, robust and easy-to-apply mapping method to estimate EQ-5D utilities based on demographic and clinical measures in schizophrenia.

Validation of disease states in schizophrenia: comparison of cluster analysis between US and European populations

BACKGROUND

There is controversy as to whether use of statistical clustering methods to identify common disease patterns in schizophrenia identifies patterns generalizable across countries.

OBJECTIVE

The goal of this study was to compare disease states identified in a published study (Mohr/Lenert, 2004) considering US patients to disease states in a European cohort (EuroSC) considering English, French, and German patients.

METHODS

Using methods paralleling those in Mohr/Lenert, we conducted a principal component analysis (PCA) on Positive and Negative Syndrome Scale items in the EuroSC data set (n=1,208), followed by k-means cluster analyses and a search for an optimal k. The optimal model structure was compared to Mohr/Lenert by assigning discrete severity levels to each cluster in each factor based on the cluster center. A harmonized model was created and patients were assigned to health states using both approaches; agreement rates in state assignment were then calculated.

RESULTS

Five factors accounting for 56% of total variance were obtained from PCA. These factors corresponded to positive symptoms (Factor 1), negative symptoms (Factor 2), cognitive impairment (Factor 3), hostility/aggression (Factor 4), and mood disorder (Factor 5) (as in Mohr/Lenert). The optimal number of cluster states was six. The kappa statistic (95% confidence interval) for agreement in state assignment was 0.686 (0.670-0.703).

CONCLUSION

The patterns of schizophrenia effects identified using clustering in two different data sets were reasonably similar. Results suggest the Mohr/Lenert health state model is potentially generalizable to other populations.

An economic evaluation of a contingency-management intervention for stimulant use among community mental health patients with serious mental illness

BACKGROUND

This study examines the cost-effectiveness of contingency-management (CM) for stimulant dependence among community mental health patients with serious mental illness (SMI) METHODS: Economic evaluation of a 12-week randomized controlled trial investigating the efficacy of CM added to treatment-as-usual (CM+TAU), relative to TAU without CM, for treating stimulant dependence among patients with a SMI. The trial included 176 participants diagnosed with SMI and stimulant dependency who were receiving community mental health and addiction treatment at one community mental health center in Seattle, Washington. Participants were also assessed during a 12-week follow-up period. Positive and negative syndrome scale (PANSS) scores were used to calculate quality-adjusted life-years (QALYs) for the primary economic outcome. The primary clinical outcome, the stimulant-free year (SFY) is a weighted measure of time free from stimulants. Two perspectives were adopted, those of the provider and the payer.

RESULTS

At 12-weeks neither the provider ($2652, p=0.74) nor the payer ($2611, p=0.99) cost differentials were statistically significant. This was also true for the payer at 24-weeks (-$125, p=1.00). QALYs gained were similar across groups, resulting in small, insignificant differences (0.04, p=0.23 at 12-weeks; 0.01, p=0.70 at 24 weeks). CM+TAU experienced significantly more SFYs, 0.24 (p<0.001) at 12 weeks and 0.20 (p=0.002) at 24 weeks, resulting in at least an 85% chance of being considered cost-effective at a threshold of $200,000/SFY.

CONCLUSION

Contingency management appears to be a wise investment for both the provider and the payer with regard to the clinical outcome of time free from stimulants.

Implications of the minimal clinically important difference for health-related quality-of-life outcomes: a comparison of sample size requirements for an incontinence treatment trial

BACKGROUND

Sample size calculations for treatment trials that aim to assess health-related quality-of-life (HRQOL) outcomes are often difficult to perform. Researchers must select a target minimal clinically important difference (MCID) in HRQOL for the trial, estimate the effect size of the intervention, and then consider the responsiveness of different HRQOL measures for detecting improvements. Generic preference-based HRQOL measures are usually less sensitive to gains in HRQOL than are disease-specific measures, but are nonetheless recommended to quantify an impact on HRQOL that can be translated into quality-adjusted life-years during cost-effectiveness analyses. Mapping disease-specific measures onto generic measures is a proposed method for yielding more efficient sample size requirements while retaining the ability to generate utility weights for cost-effectiveness analyses.

OBJECTIVES

This study sought to test this mapping strategy to calculate and compare the effect on sample size of three different methods.

METHODS

Three different methods were used for determining an MCID in HRQOL in patients with incontinence: 1) a global rating of improvement, 2) an incontinence-specific HRQOL instrument, and 3) a generic preference-based HRQOL instrument using mapping coefficients.

RESULTS

The sample size required to detect a 20% difference in the MCID for the global rating of improvement was 52 per trial arm, 172 per arm for the incontinence-specific HRQOL outcome, and 500 per arm for the generic preference-based HRQOL outcome.

CONCLUSIONS

We caution that treatment trials of conditions for which improvements are not easy to measure on generic HRQOL instruments will still require significantly greater sample size even when mapping functions are used to try to gain efficiency.

Assessment of the minimum clinically important difference in quality of life in schizophrenia measured by the Quality of Well-Being Scale and disease-specific measures

This study examines the psychometric properties of the Quality of Well Being Scale (QWB), the Positive and Negative Syndrome Scale (PANSS), the Heinrich-Carpenter Quality of Life Scale (QOLS), and the Lenert PANSS-based utility measure in a cohort of patients with schizophrenia and identifies threshold values of clinically meaningful change using the Clinical Global Impressions scale (CGI), as the anchor. The correlation of these measures at baseline and change at 6 and 12 months post enrollment in a comparative effectiveness trial was evaluated in 350 veterans with schizophrenia or schizoaffective disorder. An equipercentile method was used to estimate the minimum clinically important difference (MCID) for each measure. Effect size of 0.30-0.50 for baseline quality of life associated with inpatient status supported concurrent validity. The QWB was moderately correlated with disease-specific measures. The MCID as detected by the CGI at 6 months was 0.17 for QWB, 0.15 for the Lenert utility score, 1.13 for the QOLS, and 20.2 for the PANSS. These differences were stable at 12 months. The QWB is significantly correlated with disease specific measures of health related quality of life in schizophrenia.

Converting condition-specific measures into preference-based outcomes for use in economic evaluation

Quality-adjusted life-years (QALYs) play an important role in reimbursement decisions when one of the criteria is the cost-effectiveness of the health technology. While for many generic QALYs (e.g., based on the EQ-5D) are viewed as the gold standard, there has been a considerable increase in interest in using condition-specific data to generate QALYs. There are two main methods: mapping from the condition-specific data to a generic health-related quality of life measure; and direct valuation of condition-specific health states. Whether one believes condition-specific data are useful even if generic QALY data are available, or simply that condition-specific data are helpful in the absence of generic measures of health-related quality of life, it is timely to review recent research activity directed at making greater use of condition-specific data to inform assessments of cost-effectiveness.

Validation study of the prototype of a disease-specific index measure for health-related quality of life in dementia

BACKGROUND

Index measures for health-related quality of life (HRQoL) quantify the desirability (utility) of a certain health state. The commonly used generic index measure, e.g. EuroQol: EQ-5D, may underestimate relevant areas of specific diseases, resulting in lower validity. Disease-specific index measures on the other hand combine disease-specificity and quantification of perceived quality on several health domains of a certain disease into one single figure. These instruments have been developed for several diseases, but a dementia-specific HRQoL index instrument was not yet available. Facing the increasing individual and societal burden of dementia, specific HRQoL values with metric characteristics are especially useful because they will provide vital information for health outcome research and economic evaluations.

AIMS OF THE STUDY

To develop and validate the prototype of a dementia-specific HRQoL index measure: Dementia Quality of life Instrument (DQI), as the first step towards valuation of the dementia health state.

METHODS

For development of the DQI we created a conceptual framework based on a review of the literature, qualitative interviews with people with dementia and their carers, expert opinion and team discussion. To assess validity we undertook a survey under 241 dementia professionals. Measurements consisted of ranking (1-5) and rating (1-10) of 5 dementia-specific DQI domains (memory, orientation, independence, social activities and mood) and simultaneously rating of 9 DQI-derived health states on a visual analogue scale (VAS). We also performed a cross-sectional study in a large sample of people with very mild to moderate dementia and their caregivers (N=145) to assess feasibility and concurrent validity. In addition, caregivers valued 10 DQI and 10 EQ-5D + C derived health states of the patient simultaneously on the same VAS.

SETTING

outpatient clinics, nursing homes and patient residences.

RESULTS

All professionals judged the selected DQI domains to be relevant. Differences in ranking and rating behaviors were small. Mood was ranked (≥ 3.3) and rated (≥ 8.2) as most, orientation as least important (rank ≤ 2.6, value 7.5) health domain for dementia. For the validation part of this study the completion rates for all domains were above 98% for patients and 100% for caregivers on patients. A priori hypothesized DQI versus QOL-AD correlations that were significant in both patients and caregivers were: memory/memory, orientation/memory, independence/physical health, social activities/energy and mood/mood. Patient/caregiver inter-rater agreement was low (K <0.2) for memory/independence, fair (K 0.2-0.4) for orientation/mood, and moderate (K 0.4-0.6) for social activities. Concurrent validity of the DQI with the EQ-5D +C was moderate. The fact that most of the correlations between the domains of these two instruments were low (≤ 0.40) showed that both instruments measure different elements of health status. As expected, modest correlations (≥ 0.40) were observed between corresponding domains of the two instruments.

CONCLUSIONS

Professionals judged all domains as relevant. The DQI prototype proved valid and feasible for patients and caregivers and is appropriate for very mild to moderate dementia. The differences in concurrent correlations with generic health status instruments imply that the dementia-specific DQI health domains indeed provide different information. The finding that patient HRQoL measured with the DQI was lower supports this notion. The new DQI shows comparable psychometric properties to the best available dementia-specific (QOL-AD) and generic (EQ-5D +C) measures. Further research is needed to generate values in the general population for each of the possible DQI states and to derive an algorithm that converts the 5 separate DQI domain scores into one single DQI Index score. Introducing the DQI Index will advance dementia-related HRQoL measurement by overcoming the shortcomings of generic and non-index instruments. This will allow more unequivocal interpretation of subjective dementia HRQoL states in dementia research.

How valid and responsive are generic health status measures, such as EQ-5D and SF-36, in schizophrenia? A systematic review

OBJECTIVES

Generic health status measures such as the short form health survey (SF-36) and EuroQol-5D (EQ-5D) are increasingly being used to inform health policy. They are claimed to be applicable across disease areas and have started to be used within mental health research. This review aims to assess the construct validity and responsiveness of four generic health status measures in schizophrenia, including the preference-based SF-6D and EQ-5D.

METHOD

A systematic review of the literature was undertaken. Ten databases were searched from inception to August 2009 and reference lists scrutinized to identify relevant studies. Studies were appraised and data extracted. A narrative synthesis was performed of the evidence on construct validity including known groups validity (detecting a difference in health-related quality of life (HRQL) scores between two different groups such as samples from the general population and people with schizophrenia), convergent validity (strength of association between generic HRQL and other measures (e.g., symptom or functional), and responsiveness. Responsiveness was considered by: 1) differences in generic HRQL measure scores in responders/non-responders and 2) correlation between changes on generic HRQL measures and changes in specific measures obtained from patients and clinicians.

RESULTS

Thirty-three studies were identified that provided data on the validity and/or responsiveness of the instruments. Most of the evidence concerns the SF-36 and EQ-5D, and for these instruments there was evidence for known group validity. The evidence for convergent validity and responsiveness was mixed, with studies presenting contradictory results.

CONCLUSION

Although the evidence base is limited in a number of important respects, including problems with the measures used to develop constructs in the validation studies, it is sufficient to raise doubts about the use of generic measures of health like the EQ-5D and SF-36 in patients with schizophrenia.

A review and critique of studies reporting utility values for schizophrenia-related health states

Economic evaluation of health technologies in the form of cost-utility analysis is increasingly advocated. The most common outcome measure in this type of analysis is the QALY. In order to estimate QALYs, appropriate utility values are required. The objective of this review was to identify and critique utility values for schizophrenia-related health states. A critical appraisal was performed on utility values for schizophrenia identified in the systematic literature review that informed the economic analysis of the updated edition of the National Institute for Health and Clinical Excellence (NICE) clinical guideline on schizophrenia for England and Wales. Seven studies reporting utility values for schizophrenia were identified. The studies employed a variety of methods for generating utility values. None of the reported sets of utility values for schizophrenia were generated using the EQ-5D, which is a measure widely used in cost-utility analysis and preferred by NICE. Nevertheless, the EQ-5D may be less sensitive in capturing aspects of health-related quality of life in patients with schizophrenia. A condition-specific preference-based instrument may be more appropriate than a generic measure to inform cost-utility analyses of interventions for schizophrenia.

Quality of life and drug costs associated with switching antipsychotic medication to once-daily extended release quetiapine fumarate in patients with schizophrenia

OBJECTIVE

The objective of this study was to assess the quality of life and drug costs associated with switching from any ongoing antipsychotic treatment to once-daily extended release quetiapine fumarate (quetiapine XR) in patients with schizophrenia.

METHODS

This assessment was based on data collected during a 12-week study in patients with schizophrenia (n = 477) who switched from their current antipsychotic due to insufficient efficacy or poor tolerability to a flexible dose of quetiapine XR. Patients were assigned utilities based on their Positive and Negative Syndrome Scale (PANSS) scores and the presence of adverse events by applying the methods of Lenert et al.1. Quality adjusted life year (QALY) gains were calculated assuming a linear change of utility between two consecutive visits. Incremental costs were calculated by comparing the hypothetical mean drug cost (assuming patients stay on previous treatment) with the actual mean cost of quetiapine XR based on European prices.

RESULTS

Patients who completed the study (n = 279) increased their average utility by 0.116, corresponding to a QALY gain of 0.0207. For the total sample, the mean utility increased by 0.09, reflecting a QALY gain of 0.0170. The additional costs for quetiapine XR per QALY gained varied from approximately 16,000 euro to 24,000 euro. Notably, this is a non-comparative study; therefore, no conclusions can be reached regarding the relative impact of switching to quetiapine XR compared with other antipsychotics. Further limitations included the short trial duration on which the utility estimates are based, and the restriction of cost data to drug costs alone. Furthermore, in a 'real world' scenario, it is to be expected that other drug regimens might be introduced during periods of treatment failure.

CONCLUSION

This analysis demonstrates that patients with schizophrenia who switch their antipsychotic medication to quetiapine XR because of insufficient efficacy or poor tolerability benefit from significant QALY gains at a reasonable increase in drug cost.

Sociodemographic and clinical correlates of utility scores in Alzheimer's disease

OBJECTIVES

To examine the relationship between psychiatric symptoms, cognitive performance, functional capacity and quality of life in Alzheimer's disease (AD), and change in the Health Utilities Index (HUI)-Mark III, a widely used generic, multiattribute preference-based health-status classification system.

METHODS

Follow-up data were obtained from caregiver proxy raters at 3, to 6, and 9-months postrandom assignment concerning 421 patients with AD, living with at least one caregiver in a noninstitutional setting, who participated in the Clinical Antipsychotic Trial of Intervention Effectiveness-AD of antipsychotic medication. Spearman rank correlations, multivariate linear regression, and mixed modeling were used to examine the correlates of change in the HUI.

RESULTS

HUI scores decreased by an average of -0.061 over 9 months. Analysis revealed weak bivariate, and largely, nonsignificant multivariate relationships between change in HUI scores and sociodemographic characteristics, psychiatric symptoms, and cognitive performance. There were highly significant associations between decreases in health utilities and change in the AD Cooperative Study for Activities of Daily Living scale (ADCS-ADL) and AD-Related Quality of Life (ADRQoL) (both P < 0.001), even after controlling for other factors. Adjusted R(2) values ranged from 0.14 to 0.20.

CONCLUSION

In AD patients requiring antipsychotic treatment, only weak relationships were found between changes in the HUI and sociodemographic and clinical indicators. While functional capability and quality of life showed more significant associations, less than 20% of the variance in health utility could be explained. Significant cognitive impairment and the need to rely on proxy raters may limit the usefulness of utility measurement in AD patients with serious behavioral symptoms.

Comparing the Incomparable? A Systematic Review of Competing Techniques for Converting Descriptive Measures of Health Status into QALY-Weights

Background . Algorithms for converting descriptive measures of health status into quality-adjusted life year (QALY)—weights are now widely available, and their application in economic evaluation is increasingly commonplace. The objective of this study is to describe and compare existing conversion algorithms and to highlight issues bearing on the derivation and interpretation of the QALY-weights so obtained. Methods . Systematic review of algorithms for converting descriptive measures of health status into QALY-weights. Results . The review identified a substantial body of literature comprising 46 derivation studies and 16 studies that provided evidence or commentary on the validity of conversion algorithms. Conversion algorithms were derived using 1 of 4 techniques: 1) transfer to utility regression, 2) response mapping, 3) effect size translation, and 4) “revaluing” outcome measures using preference-based scaling techniques. Although these techniques differ in their methodological/theoretical tradition, data requirements, and ease of derivation and application, the available evidence suggests that the sensitivity and validity of derived QALY-weights may be more dependent on the coverage and sensitivity of measures and the disease area/patient group under evaluation than on the technique used in derivation. Conclusions . Despite the recent proliferation of conversion algorithms, a number of questions bearing on the derivation and interpretation of derived QALY-weights remain unresolved. These unresolved issues suggest directions for future research in this area. In the meantime, analysts seeking guidance in selecting derived QALY-weights should consider the validity and feasibility of each conversion algorithm in the disease area and patient group under evaluation rather than restricting their choice to weights from a particular derivation technique.

Depression-Free Day to Utility-Weighted Score

BACKGROUND

Cost-utility analyses using formulas to convert depression-free days (DFDs) to utility-weighted scores are increasingly common. These formulas are based on linear extrapolation of data documenting the correlation between depression symptom severity and generic health-related quality of life.

OBJECTIVE

We sought to examine the validity of formulas converting DFDs to utility weights.

METHODS

We undertook an observational study with data collection at baseline, 1 week and 1, 3, 6, 9, and 12 months on 77 subjects (42 inpatient, 35 outpatient) diagnosed with current major depression. Subjects were divided into treatment response categories based on changes in depression severity. Depression severity measures used were the Hamilton Rating Scale for Depression (HAM-17) and Beck Depression Inventory (BDI) and the health-related quality of life measure was the self-administered Quality of Well-Being scale (QWB-SA). DFD calculations were based on depression severity scores and converted to utility weights using available formulas. Utility-weighted data collected over the course of 1 year were used to estimate quality-adjusted life years (QALYs).

RESULTS

QALYs estimated from the QWB-SA were significantly lower than those based on utility-weighted DFD calculations but the incremental QALYs were not significantly different. Using a slightly lower utility-weighted conversion factor for the BDI or a larger BDI severity range to calculate DFDs resulted in a better fit compared with the QWB-SA.

CONCLUSIONS

Our results support the validity of the existing HAM-17 utility-weighted formula and suggest modifications for the BDI formula. If generic health-related quality of life measures are not available for conducting cost-utility analyses of depression interventions then the existing HAM-17 and modified BDI formulas appear to be reasonable alternatives.