Mapping onto Eq-5 D for patients in poor health

<p>Abstract</p> <p>Background</p> <p>An increasing amount of studies report mapping algorithms which predict EQ-5 D utility values using disease specific non-preference-based measures. Yet many mapping algorithms have been found to systematically overpredict EQ-5 D utility values for patients in poor health. Currently there are no guidelines on how to deal with this problem. This paper is concerned with the question of why overestimation of EQ-5 D utility values occurs for patients in poor health, and explores possible solutions.</p> <p>Method</p> <p>Three existing datasets are used to estimate mapping algorithms and assess existing mapping algorithms from the literature mapping the cancer-specific EORTC-QLQ C-30 and the arthritis-specific Health Assessment Questionnaire (HAQ) onto the EQ-5 D. Separate mapping algorithms are estimated for poor health states. Poor health states are defined using a cut-off point for QLQ-C30 and HAQ, which is determined using association with EQ-5 D values.</p> <p>Results</p> <p>All mapping algorithms suffer from overprediction of utility values for patients in poor health. The large decrement of reporting 'extreme problems' in the EQ-5 D tariff, few observations with the most severe level in any EQ-5 D dimension and many observations at the least severe level in any EQ-5 D dimension led to a bimodal distribution of EQ-5 D index values, which is related to the overprediction of utility values for patients in poor health. Separate algorithms are here proposed to predict utility values for patients in poor health, where these are selected using cut-off points for HAQ-DI (> 2.0) and QLQ C-30 (< 45 average of QLQ C-30 functioning scales). The QLQ-C30 separate algorithm performed better than existing mapping algorithms for predicting utility values for patients in poor health, but still did not accurately predict mean utility values. A HAQ separate algorithm could not be estimated due to data restrictions.</p> <p>Conclusion</p> <p>Mapping algorithms overpredict utility values for patients in poor health but are used in cost-effectiveness analyses nonetheless. Guidelines can be developed on when the use of a mapping algorithms is inappropriate, for instance through the identification of cut-off points. Cut-off points on a disease specific questionnaire can be identified through association with the causes of overprediction. The cut-off points found in this study represent severely impaired health. Specifying a separate mapping algorithm to predict utility values for individuals in poor health greatly reduces overprediction, but does not fully solve the problem.</p

Societal Utilities for Cognitive Impairment in Schizophrenia:Developing a Preference-Based Scoring Algorithm Based on the Schizophrenia Cognition Rating Scale

Introduction: Loss of cognitive function is a common feature in schizophrenia. However, generic measures of health-related quality of life favored by decision-makers, such as the EQ-5D, are not designed to detect changes in cognitive function. We report the valuation of the Schizophrenia Cognition Rating Scale (SCoRS), a schizophrenia-specific measure of cognitive impairment.Methods: Expert opinion and psychometric analysis of the SCoRS from clinical trial data was undertaken to select 5 key items from the measure. These items were combined orthogonally to develop health-state vignettes. Vignettes were valued using composite time trade-off (cTTO) in one-on-one video calls. Several econometric models were fitted to the data to estimate disutilities. Performance of EQ-5D- and SCoRS-based utilities were compared in the trial data. Results: The SCoRS items selected for the valuation study represented attention, learning, processing speed, social cognition and memory. Four hundred respondents participated in the valuation study. The best observed health state was valued at 0.855 [standard deviation (SD) = 0.179] and the worst at 0.152 (SD = 0.575). At the most severe levels, ‘social cognition’ received the largest disutility followed by ‘learning’ and ‘memory’. The final model to estimate utilities had 15 parameters. SCoRS-based utilities were sensitive to change in cognition, but the EQ-5D was not. Conclusion: It is feasible to value different dimensions of cognition separately using a validated instrument for proxy assessment. The resulting utilities indicate loss of quality of life due to reduced cognitive functioning.</p

Dutch Tariff for the Five-Level Version of EQ-5D

Background: In 2009, a new version of the EuroQol five-dimensional questionnaire (EQ-5D) was introduced with five rather than three answer levels per dimension. This instrument is known as the EQ-5D-5L. To make the EQ-5D-5L suitable for use in economic evaluations, societal values need to be attached to all 3125 health states. Objectives: To derive a Dutch tariff for the EQ-5D-5L. Methods: Health state values were elicited during face-to-face interviews in a general population sample stratified for age, sex, and education, using composite time trade-off (cTTO) and a discrete choice experiment (DCE). Data were modeled using ordinary least squares and tobit regression (for cTTO) and a multinomial conditional logit model (for DCE). Model performance was evaluated on the basis of internal consistency, parsimony, goodness of fit, handling of left-censored values, and theoretical considerations. Results: A representative sample (N = 1003) of the Dutch population participated in the valuation study. Data of 979 and 992 respondents were included in the analysis of the cTTO and the DCE, respectively. The cTTO data were left-censored at -1. The tobit model was considered the preferred model for the tariff on the basis of its handling of the censored nature of the data, which was confirmed through comparison with the DCE data. The predicted values for the EQ-5D-5L ranged from -0.446 to 1. Conclusions: This study established a Dutch tariff for the EQ-5D-5L on the basis of cTTO. The values represent the preferences of the Dutch population. The tariff can be used to estimate the impact of health care interventions on quality of life, for example, in context of economic evaluations.</p

Estimating the Prognostic Value of the NTRK Fusion Biomarker for Comparative Effectiveness Research in The Netherlands

Objectives: We evaluated the prognostic value of the neurotrophic tyrosine receptor kinase (NTRK) gene fusions by comparing the survival of patients with NTRK+ tumours with patients without NTRK+ tumours. Methods: We used genomic and clinical registry data from the Center for Personalized Cancer Treatment (CPCT-02) study containing a cohort of cancer patients who were treated in Dutch clinical practice between 2012 and 2020. We performed a propensity score matching analysis, where NTRK+ patients were matched to NTRK− patients in a 1:4 ratio. We subsequently analysed the survival of the matched sample of NTRK+ and NTRK− patients using the Kaplan–Meier method and Cox regression, and performed an analysis of credibility to evaluate the plausibility of our result. Results:Among 3556 patients from the CPCT-02 study with known tumour location, 24 NTRK+ patients were identified. NTRK+ patients were distributed across nine different tumour types: bone/soft tissue, breast, colorectal, head and neck, lung, pancreas, prostate, skin and urinary tract. NTRK fusions involving the NTRK3 gene (46%) and NTRK1 gene (33%) were most common. The survival analysis rendered a hazard ratio (HR) of 1.44 (95% CI 0.81–2.55) for NTRK+ patients. Using the point estimates of three prior studies on the prognostic value of NTRK fusions, our finding that the HR is &gt; 1 was deemed plausible. Conclusions: NTRK+ patients may have an increased risk of death compared with NTRK− patients. When using historic control data to assess the comparative effectiveness of TRK inhibitors, the prognostic value of the NTRK fusion biomarker should therefore be accounted for.</p

Estimating Informal Caregiving Time from Patient EQ-5D Data: The Informal CARE Effect (iCARE) Tool

Background: Families and friends provide a considerable proportion of care for patients and elderly people. Caregiving can have substantial effects on caregivers’ lives, health, and well-being. However, because clinical trials rarely assess these effects, no information on caregiver burden is available when evaluating the cost effectiveness of treatments. Objective: This study develops an algorithm for estimating caregiver time using information that is typically available in clinical trials: the EQ-5D scores of patients and their gender. Methods: Four datasets with a total of 8012 observations of dyads of caregivers and a gamma model with a log-link estimated with the Bayesian approach were used to estimate the statistical association between patient scores on the EQ-5D-3L dimensions and the numbers of hours of care provided by caregivers during the previous week. The model predicts hours of care as mean point estimates with 95% credible intervals or entire distributions. Results: Model predictions of hours of care based on the five EQ-5D dimensions ranged from 13.06 (12.7–14.5) h/week for female patients reporting no health problems but receiving informal care to 52.82 (39.38–66.26) for male patients with the highest level of problems on all EQ-5D dimensions. Conclusions: The iCARE algorithm developed in this study allows researchers who only have patient-level EQ-5D data to estimate the mean hours of informal care received per week, including a 95% Bayesian credible interval. Caregiver time can be multiplied with a monetary value for caregiving, enabling the inclusion of informal care costs in economic evaluations. We recommend using the tool for samples that fall within the confidence intervals of the characteristics of our samples: men (age range 47.0–104.2 years), women (age range 55–103 years)

A cost-effectiveness threshold based on the marginal returns of cardiovascular hospital spending

Traditionally, threshold levels of cost‐effectiveness have been derived from willingness‐to‐pay studies, indicating the consumption value of health (v‐thresholds). However, it has been argued that v‐thresholds need to be supplemented by so‐called k‐thresholds, which are based on the marginal returns to health care. The objective of this research is to estimate a k‐threshold based on the marginal returns to cardiovascular disease (CVD) hospital care in the Netherlands. To estimate a k‐threshold for hospital care on CVD, we proceed in two steps: First, we estimate the impact of hospital spending on mortality using a Bayesian regression modelling framework, using data on CVD mortality and CVD hospital spending by age and gender for the period 1994–2010. Second, we use life tables in combination with quality of life data to convert these estimates into a k‐threshold expressed in euros per quality‐adjusted life year gained. Our base case estimate resulted in an estimate of 41,000 per quality‐adjusted life year gained. In our sensitivity analyses, we illustrated how the incorporation of prior evidence into the estimation pushes estimates downwards. We conclude that our base case estimate of the k‐threshold may serve as a benchmark value for decision making in the Netherlands as well as for future research regarding k‐thresholds

A cost-effectiveness threshold based on the marginal returns of cardiovascular hospital spending

Traditionally, threshold levels of cost-effectiveness have been derived from willingness-to-pay studies, indicating the consumption value of health (v-thresholds). However, it has been argued that v-thresholds need to be supplemented by so-called k-thresholds, which are based on the marginal returns to health care. The objective of this research is to estimate a k-threshold based on the marginal returns to cardiovascular disease (CVD) hospital care in the Netherlands. To estimate a k-threshold for hospital care on CVD, we proceed in two steps: First, we estimate the impact of hospital spending on mortality using a Bayesian regression modelling framework, using data on CVD mortality and CVD hospital spending by age and gender for the period 1994–2010. Second, we use life tables in combination with quality of life data to convert these estimates into a k-threshold expressed in euros per quality-adjusted life year gained. Our base case estimate resulted in an estimate of 41,000 per quality-adjusted life year gained. In our sensitivity analyses, we illustrated how the incorporation of prior evidence into the estimation pushes estimates downwards. We conclude that our base case estimate of the k-threshold may serve as a benchmark value for decision making in the Netherlands as well as for future research regarding k-thresholds

Which factors may determine the necessary and feasible type of effectiveness evidence?

Objectives: Reimbursement decisions require evidence of effectiveness and, in general, a blinded randomised controlled trial (RCT) is the preferred study design to provide it. However, there are situations where a cohort study, or even patient series, can be deemed acceptable. The aim of this study was to develop an instrument that first examines which study characteristics of a blinded RCT are necessary, and then, if particular characteristics are considered necessary, examines whether these characteristics are feasible. Design: We retrospectively studied 22 interventions from 20 reimbursement reports concerning medical specialist care made by the Dutch National Health Care Institute (ZIN) to identify any factors that influenced the necessity and feasibility of blinded RCTs, and their constituent study characteristics, that is, blinding, randomisation and a control group. A literature review was performed to identify additional factors. Additional expertise was included by interviewing eight experts in epidemiology, medicine and ethics. The resulting instrument was called the FIT instrument (Feasible Information Trajectory), and was prospectively validated using three consecutive reimbursement reports. Results: (Blinded) RCT evidence was lacking in 5 of 11 positive reimbursement decisions and 3 of 11 negative decisions. In the reimbursement reports, we found no empirical evidence supporting situations where a blinded RCT is unnecessary. The literature also revealed few arguments against the necessity of a blinded RCT. In contrast, many factors influen

Comparing the effectiveness and cost-effectiveness of self-management interventions in four high-priority chronic conditions in Europe (COMPAR-EU): a research protocol

Introduction Population ageing and increasing chronic illness burden have sparked interest in innovative care models. While self-management interventions (SMIs) are drawing increasing attention, evidence of their efficacy is mostly based on pairwise meta-analysis, generally derived from randomised controlled trials comparing interventions versus a control or no intervention. As such, relevant efficacy data for comparisons among dif