Direct and Indirect Mapping of Assessment of Quality of Life - 6 Dimensions (AQoL-6D) Onto EQ-5D-5L Utilities Using Data From a Multicenter, Cross-Sectional Study of Malaysians With Chronic Heart Failure.
The Assessment of Quality of Life - 6 Dimensions (AQoL-6D), a generic preference-based measure, is an appealing alternative to EQ-5D-5L for assessing health status in patients with chronic heart failure (HF), given its expanded scope. However, without a Malaysian value set, the AQoL-6D cannot generate health state utility values (HSUVs) to support local economic evaluations. This study intended to develop algorithms for predicting EQ-5D-5L HSUVs from AQoL-6D in an HF population.
Cross-sectional data from a multicenter cohort of 419 HF outpatients were used. Both direct and indirect mapping approaches were attempted using 5 sets of explanatory variables and 8 models (ordinary least squares, Tobit, censored least absolute deviations, generalized linear model, 2-part model [TPM], beta regression-based model, adjusted limited dependent variable mixture model, and multinomial ordinal regression [MLOGIT]). The models' predictive performance was assessed through 10-fold cross-validated mean absolute error [MAE] and root mean squared error [RMSE]). Potential prediction bias was also examined graphically. The best-performing models, with the lowest RMSE and no bias, were then identified.
Among the models evaluated, TPM, which included age, sex, and 5 AQoL-6D dimension scores as predictors, appears to be the best-performing model for directly predicting EQ-5D-5L HSUVs from AQoL-6D. TPM yielded the lowest MAE (0.0802) and RMSE (0.1116), and demonstrated predictive accuracy for HSUVs >0.2 without significant bias. A MLOGIT model developed for response mapping had suboptimal predictive accuracy.
This study developed potentially useful mapping algorithms for generating Malaysian EQ-5D-5L HSUVs from AQoL-6D responses among patients with HF when direct EQ-5D-5L data are unavailable.
Tan YJ
，Ong SC
《-》
The EORTC QLU-C10D distinguished better between cancer patients and the general population than PROPr and EQ-5D-5L in a cross-sectional study.
Health state utility (HSU) instruments for calculating quality-adjusted life years, such as the European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Utility - Core 10 Dimensions (QLU-C10D), derived from the EORTC QLQ-30 questionnaire, the Patient-Reported Outcome Measurement Information System (PROMIS) preference score (PROPr), and the EuroQoL-5-Dimensions-5-Levels (EQ-5D-5L), yield different HSU values due to different modeling and different underlying descriptive scales. For example the QLU-C10D includes cancer-relevant dimensions such as nausea. This study aimed to investigate how these differences in descriptive scales contribute to differences in HSU scores by comparing scores of cancer patients receiving chemotherapy to those of the general population.
EORTC QLU-C10D, PROPr, and EQ-5D-5L scores were obtained for a convenience sample of 484 outpatients of the Department of Oncology, Charité - Universitätsmedizin Berlin, Germany. Convergent and known group's validity were assessed using Pearson's correlation and intraclass correlation coefficients (ICC). We assessed each descriptive dimension score's discriminatory power and compared them to those of the general population (n > 1000) using effect size (ES; Cohen's d) and area under the curve (AUC).
The mean scores of QLU-C10D (0.64; 95% CI 0.62-0.67), PROPr (0.38; 95% CI 0.36-0.40), and EQ-5D-5L (0.72; 95% CI 0.70-0.75) differed significantly, irrespective of sociodemographic factors, condition, or treatment. Conceptually similar descriptive scores as obtained from the HSU instruments showed varying degrees of discrimination in terms of ES and AUC between patients and the general population. The QLU-C10D and its dimensions showed the largest ES and AUC.
The QLU-C10D and its domains distinguished best between health states of the two populations, compared to the PROPr and EQ-5D-5L. As the EORTC Core Quality of Life Questionnaire (QLQ-C30) is widely used in clinical practice, its data are available for economic evaluation.
The assessment of dimensions of health-related quality of life (HRQoL), such as physical functioning or depression, is important to cancer patients and physicians for treatment and side effect monitoring. Descriptive HRQoL is measured by patient-reported outcomes measures (PROM). The European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30 questionnaire and the Patient-Reported Outcome Measurement Information System (PROMIS) are the most common PROM in the clinical HRQoL assessment. In recent years, multidimensional preference-based HRQoL measures were developed using these PROM as dimensions. These preference-based measures, also referred to as health state utility (HSU) scores, are needed for economic evaluations of treatments. The QLQ-C30's corresponding HSU score is the Quality of Life Utility measure-Core 10 Dimensions (QLU-C10D), and PROMIS' HSU score is the PROMIS preference score (PROPr). Both new HSU scores are frequently compared to the well-established EuroQoL-5-dimensions-5-levels (EQ-5D-5L). They all conceptualize HSU differently, as they assess different dimensions of HRQoL und use different models. Both the QLU-C10D and the PROPr have thus shown systematic differences to the EQ-5D-5L but these were largely consistent across the subgroups. Convergent and known groups validity can therefore be considered established. However, as HSU is a multidimensional construct, it remains unclear how differences in its dimensions, for example, its descriptive scales, contribute to differences in HSU scores. This is of importance as it is the descriptive scales that measure clinical HRQoL. We investigated this question by assessing each dimension's ability to distinguish between a sample of 484 cancer patients and the German general population. We could show that the ability to distinguish depended on the domain: for example, for depression, the QLU-C10D and EQ-5D-5L distinguished clearer, while for physical function, PROMIS did. Overall, the QLU-C10D and its dimensions distinguish best between cancer patients and general population.
Döhmen A
，Obbarius A
，Kock M
，Nolte S
，Sidey-Gibbons CJ
，Valderas JM
，Rohde J
，Rieger K
，Fischer F
，Keilholz U
，Rose M
，Klapproth CP
... -
《-》
Mapping KDQOL-36 Onto EQ-5D-5L and SF-6Dv2 in Patients Undergoing Dialysis in China.
To develop mapping algorithms based on Kidney Disease Quality of Life-36 (KDQOL-36) scores to the EQ-5D-5L and SF-6Dv2 utility values among dialysis patients in China.
We used data from a cross-sectional multicenter survey in China to map the KDQOL-36 to the EQ-5D-5L and SF-6Dv2. The conceptual overlap between the KDQOL-36 and the EQ-5D-5L or SF-6Dv2 was evaluated using Spearman's correlation coefficients. Direct mapping, including ordinary least squares, generalized linear model, beta regression model, Tobit regression model (TRM), censored least absolute deviations model, adjusted limited dependent variable mixture model (ALDVMM), response mapping, and seemingly unrelated ordered probit model, were used to derive mapping functions using the data set. Model performance was assessed by the mean absolute error (MAE) and root mean square error (RMSE) using cross-validation.
A total of 378 patients (50.53% female; mean [SD] age: 49.05 [13.34]) were included in this study. The mean utility values of EQ-5D-5L and SF-6Dv2 were 0.72 and 0.57, respectively. When mapping to the EQ-5D-5L, the ALDVMM with 1 component was the best-performing model (MAE = 0.1579, RMSE = 0.2289). When mapping to SF-6Dv2, TRM was the best-performing model (MAE = 0.1108, RMSE = 0.1508). Generally, KDQOL-36 subscale scores and their squares were the optimal predictor set for each model. Overall, the models using KDQOL-36 subscale scores showed a better fit than those using the Kidney Disease Component Summary.
The ALDVMM and TRM models with the KDQOL-36 scores can be used to predict the EQ-5D-5L and SF-6Dv2 utility values, respectively, among dialysis patients in China.
Chen Z
，Yang L
，Zhang Y
《-》
Falls prevention interventions for community-dwelling older adults: systematic review and meta-analysis of benefits, harms, and patient values and preferences.
About 20-30% of older adults (≥ 65 years old) experience one or more falls each year, and falls are associated with substantial burden to the health care system, individuals, and families from resulting injuries, fractures, and reduced functioning and quality of life. Many interventions for preventing falls have been studied, and their effectiveness, factors relevant to their implementation, and patient preferences may determine which interventions to use in primary care. The aim of this set of reviews was to inform recommendations by the Canadian Task Force on Preventive Health Care (task force) on fall prevention interventions. We undertook three systematic reviews to address questions about the following: (i) the benefits and harms of interventions, (ii) how patients weigh the potential outcomes (outcome valuation), and (iii) patient preferences for different types of interventions, and their attributes, shown to offer benefit (intervention preferences).
We searched four databases for benefits and harms (MEDLINE, Embase, AgeLine, CENTRAL, to August 25, 2023) and three for outcome valuation and intervention preferences (MEDLINE, PsycINFO, CINAHL, to June 9, 2023). For benefits and harms, we relied heavily on a previous review for studies published until 2016. We also searched trial registries, references of included studies, and recent reviews. Two reviewers independently screened studies. The population of interest was community-dwelling adults ≥ 65 years old. We did not limit eligibility by participant fall history. The task force rated several outcomes, decided on their eligibility, and provided input on the effect thresholds to apply for each outcome (fallers, falls, injurious fallers, fractures, hip fractures, functional status, health-related quality of life, long-term care admissions, adverse effects, serious adverse effects). For benefits and harms, we included a broad range of non-pharmacological interventions relevant to primary care. Although usual care was the main comparator of interest, we included studies comparing interventions head-to-head and conducted a network meta-analysis (NMAs) for each outcome, enabling analysis of interventions lacking direct comparisons to usual care. For benefits and harms, we included randomized controlled trials with a minimum 3-month follow-up and reporting on one of our fall outcomes (fallers, falls, injurious fallers); for the other questions, we preferred quantitative data but considered qualitative findings to fill gaps in evidence. No date limits were applied for benefits and harms, whereas for outcome valuation and intervention preferences we included studies published in 2000 or later. All data were extracted by one trained reviewer and verified for accuracy and completeness. For benefits and harms, we relied on the previous review team's risk-of-bias assessments for benefit outcomes, but otherwise, two reviewers independently assessed the risk of bias (within and across study). For the other questions, one reviewer verified another's assessments. Consensus was used, with adjudication by a lead author when necessary. A coding framework, modified from the ProFANE taxonomy, classified interventions and their attributes (e.g., supervision, delivery format, duration/intensity). For benefit outcomes, we employed random-effects NMA using a frequentist approach and a consistency model. Transitivity and coherence were assessed using meta-regressions and global and local coherence tests, as well as through graphical display and descriptive data on the composition of the nodes with respect to major pre-planned effect modifiers. We assessed heterogeneity using prediction intervals. For intervention-related adverse effects, we pooled proportions except for vitamin D for which we considered data in the control groups and undertook random-effects pairwise meta-analysis using a relative risk (any adverse effects) or risk difference (serious adverse effects). For outcome valuation, we pooled disutilities (representing the impact of a negative event, e.g. fall, on one's usual quality of life, with 0 = no impact and 1 = death and ~ 0.05 indicating important disutility) from the EQ-5D utility measurement using the inverse variance method and a random-effects model and explored heterogeneity. When studies only reported other data, we compared the findings with our main analysis. For intervention preferences, we used a coding schema identifying whether there were strong, clear, no, or variable preferences within, and then across, studies. We assessed the certainty of evidence for each outcome using CINeMA for benefit outcomes and GRADE for all other outcomes.
A total of 290 studies were included across the reviews, with two studies included in multiple questions. For benefits and harms, we included 219 trials reporting on 167,864 participants and created 59 interventions (nodes). Transitivity and coherence were assessed as adequate. Across eight NMAs, the number of contributing trials ranged between 19 and 173, and the number of interventions ranged from 19 to 57. Approximately, half of the interventions in each network had at least low certainty for benefit. The fallers outcome had the highest number of interventions with moderate certainty for benefit (18/57). For the non-fall outcomes (fractures, hip fracture, long-term care [LTC] admission, functional status, health-related quality of life), many interventions had very low certainty evidence, often from lack of data. We prioritized findings from 21 interventions where there was moderate certainty for at least some benefit. Fourteen of these had a focus on exercise, the majority being supervised (for > 2 sessions) and of long duration (> 3 months), and with balance/resistance and group Tai Chi interventions generally having the most outcomes with at least low certainty for benefit. None of the interventions having moderate certainty evidence focused on walking. Whole-body vibration or home-hazard assessment (HHA) plus exercise provided to everyone showed moderate certainty for some benefit. No multifactorial intervention alone showed moderate certainty for any benefit. Six interventions only had very-low certainty evidence for the benefit outcomes. Two interventions had moderate certainty of harmful effects for at least one benefit outcome, though the populations across studies were at high risk for falls. Vitamin D and most single-component exercise interventions are probably associated with minimal adverse effects. Some uncertainty exists about possible adverse effects from other interventions. For outcome valuation, we included 44 studies of which 34 reported EQ-5D disutilities. Admission to long-term care had the highest disutility (1.0), but the evidence was rated as low certainty. Both fall-related hip (moderate certainty) and non-hip (low certainty) fracture may result in substantial disutility (0.53 and 0.57) in the first 3 months after injury. Disutility for both hip and non-hip fractures is probably lower 12 months after injury (0.16 and 0.19, with high and moderate certainty, respectively) compared to within the first 3 months. No study measured the disutility of an injurious fall. Fractures are probably more important than either falls (0.09 over 12 months) or functional status (0.12). Functional status may be somewhat more important than falls. For intervention preferences, 29 studies (9 qualitative) reported on 17 comparisons among single-component interventions showing benefit. Exercise interventions focusing on balance and/or resistance training appear to be clearly preferred over Tai Chi and other forms of exercise (e.g., yoga, aerobic). For exercise programs in general, there is probably variability among people in whether they prefer group or individual delivery, though there was high certainty that individual was preferred over group delivery of balance/resistance programs. Balance/resistance exercise may be preferred over education, though the evidence was low certainty. There was low certainty for a slight preference for education over cognitive-behavioral therapy, and group education may be preferred over individual education.
To prevent falls among community-dwelling older adults, evidence is most certain for benefit, at least over 1-2 years, from supervised, long-duration balance/resistance and group Tai Chi interventions, whole-body vibration, high-intensity/dose education or cognitive-behavioral therapy, and interventions of comprehensive multifactorial assessment with targeted treatment plus HHA, HHA plus exercise, or education provided to everyone. Adding other interventions to exercise does not appear to substantially increase benefits. Overall, effects appear most applicable to those with elevated fall risk. Choice among effective interventions that are available may best depend on individual patient preferences, though when implementing new balance/resistance programs delivering individual over group sessions when feasible may be most acceptable. Data on more patient-important outcomes including fall-related fractures and adverse effects would be beneficial, as would studies focusing on equity-deserving populations and on programs delivered virtually.
Not registered.
Pillay J
，Gaudet LA
，Saba S
，Vandermeer B
，Ashiq AR
，Wingert A
，Hartling L
... -
《Systematic Reviews》
ResearchGate
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