Mapping of the EORTC QLQ-C30 to EQ-5D-5L index in patients with lymphomas

EQ-5D-5L and SF-6Dv2 health utilities scores of diffuse large B-cell lymphoma patients in China

BACKGROUND

This study evaluates the health-related quality of life (HRQoL) of persons with diffuse large B-cell lymphoma (DLBCL) by using EQ-5D-5L and SF-6Dv2 and compares the measurement properties of the two instruments.

METHOD

DLBCL patients were identified via a patient group and were surveyed using web-based questionnaires. Demographic information, socioeconomic status (SES), clinical characteristics, and EQ-5D-5L and SF-6Dv2 responses were collected and statistically described. The association between the EQ-5D-5L and SF-6Dv2 dimensions were analyzed using the Spearman's correlation coefficient, whereas the correlation of the utility scores was evaluated using Pearson's correlation coefficient. The agreement between the responses of the two instruments were examined using a Bland-Altman (B-A) plot. A one-way analysis of variance (ANOVA) was performed to compare the utility scores across subgroups in different clinical states (a t-test was used if there were two subgroups). In addition, the graded response model (GRM) was used to describe the discrimination ability and difficulty characteristics of the dimensions in the two instruments.

RESULTS

In total, 582 valid responses were collected, among which 477 respondents were associated with initial-treatment and 105 respondents were relapsed/refractory (RR) patients. The mean (standard deviation [SD]) EQ-5D-5L and SF-6Dv2 utility scores of the DLBCL patients were 0.828 (0.222) and 0.641 (0.220), respectively. The correlation between the EQ-5D-5L and SF-6Dv2 dimensions ranged from 0.299 to 0.680, and the correlation between their utility scores was 0.787. The B-A plot demonstrated an acceptable but not strong agreement between EQ-5D-5L and SF-6Dv2 utility scores. The GRM model results indicated that all dimensions of each instrument were highly discriminating overall, but EQ-5D-5L had suboptimal discriminative power among patients with good health.

CONCLUSION

Both the EQ-5D-5L and SF-6Dv2 showed valid properties to assess the HRQoL of DLBCL patients. However, utility scores derived from the two instruments had substantial difference, thereby prohibiting the interchangeable use of utilities from the two instruments.

Mapping from SIBDQ to EQ-5D-5L for patients with inflammatory bowel disease

OBJECTIVE

Clinical studies commonly use disease-specific measures to assess patients' health-related quality of life. However, economic evaluation often requires preference-based utility index scores to calculate cost per quality-adjusted life-year (QALY). When utility index scores are not directly available, mappings are useful. To our knowledge, no mapping exists for the Short Inflammatory Bowel Disease Questionnaire (SIBDQ). Our aim was to develop a mapping from SIBDQ to the EQ-5D-5L index score with German weights for inflammatory bowel disease (IBD) patients.

METHODS

We used 3856 observations of 1055 IBD patients who participated in a randomised controlled trial in Germany on the effect of introducing regular appointments with an IBD nurse specialist in addition to standard care with biologics. We considered five data availability scenarios. For each scenario, we estimated different regression and machine learning models: linear mixed-effects regression, mixed-effects Tobit regression, an adjusted limited dependent variable mixture model and a mixed-effects regression forest. We selected the final models with tenfold cross-validation based on a model subset and validated these with observations in a validation subset.

RESULTS

For the first four data availability scenarios, we selected mixed-effects Tobit regressions as final models. For the fifth scenario, mixed-effects regression forest performed best. Our findings suggest that the demographic variables age and gender do not improve the mapping, while including SIBDQ subscales, IBD disease type, BMI and smoking status leads to better predictions.

CONCLUSION

We developed an algorithm mapping SIBDQ values to EQ-5D-5L index scores for different sets of covariates in IBD patients. It is implemented in the following web application: https://www.bwl.uni-hamburg.de/hcm/forschung/mapping.html .

Measurement properties of the EQ-5D-5L and PROPr in patients with spinal muscular atrophy

OBJECTIVES

Spinal muscular atrophy (SMA) is a rare monogenic neuromuscular disorder caused by loss of function mutations. Measuring health-related quality of life to support economic evaluations in this population is encouraged. However, empirical evidence on the performance of preference-based measures (PBMs) in individuals with SMA is limited. This study aimed to assess the psychometric properties of the EQ-5D-5L and the Patient-Reported Outcomes Measure Information System Preference measure (PROPr) in individuals with SMA.

METHODS

The data used in this study were obtained via a web-based, cross-sectional survey. All participants completed the self-reporting EQ-5D-5L and PROMIS-29 questionnaires. Information about their socioeconomic and health status was also obtained. Ceiling and floor effects, convergent and divergent validity, known-group validity, and the agreement between the two measures were assessed.

RESULTS

Strong ceiling and floor effects were observed for four dimensions of the EQ-5D-5L and three subscales, including pain intensity, pain interference, and physical function, of the PROMIS-29. All hypothesized associations between EQ-5D-5L/PROMIS-29 and other neuromuscular questions were confirmed, supporting good convergent validity. Moreover, both EQ-5D-5L and PROPr scores differentiated between impaired functional groups, demonstrating good discriminative ability. Poor agreement between the EQ-5D-5L and PROPr utility scores was observed.

CONCLUSIONS

The EQ-5D-5L and PROPr both appear to be valid PBMs for individuals with SMA. However, PROPr yielded considerably lower utility scores than EQ-5D-5L and their agreement was poor. Therefore, these two PBMs may not be used interchangeably in economic evaluations of SMA-related interventions.

EQ-5D and SF-6D health utility scores in patients with spinal and bulbar muscular atrophy

OBJECTIVE

This study assessed patient-reported health-related quality of life (HRQoL) using two generic preference-based measures in Chinese patients with spinal and bulbar muscular atrophy (SBMA) and identified demographic and clinical determinants of health utility scores in this population.

METHODS

This study used cross-sectional data of 212 Chinese patients with SBMA who completed both the EQ-5D and SF-6D. Association between response to EQ-5D and SF-6D dimensions was examined using Spearman's correlation coefficient, and the association between the two utility scores was assessed using Pearson's correlation coefficient. The variations in utility scores across patients in different subgroups were compared using one-way ANOVA. Bland-Altman (B-A) plot was used to assess the agreement of utility scores between EQ-5D and SF-6D. A multivariate Tobit regression model was employed to estimate the association between utility scores and the presence of symptoms and chronic conditions.

RESULTS

The mean utility scores for the EQ-5D and SF-6D were 0.54 and 0.56, respectively. The hypothesized correlation between the EQ-5D and SF-6D dimensions ranged from 0.31 to 0.58, and the correlation between their utility scores was 0.64. An acceptable agreement between EQ-5D and SF-6D utility scores was identified by B-A plot. Patients with chronic diseases, misdiagnosis, high financial burden, and several clinical symptoms were highly likely to report a low health utility score.

CONCLUSIONS

This study is the first to investigate the HRQoL of patients with SBMA worldwide. The estimated health utility scores for EQ-5D and SF-6D can be utilized as baseline data for future cost-utility analyses of SBMA-related interventions.

Mapping Studies to Estimate Health-State Utilities From Nonpreference-Based Outcome Measures: A Systematic Review on How Repeated Measurements are Taken Into Account

OBJECTIVES

Mapping algorithms are developed using data sets containing patient responses to a preference-based questionnaire and another health-related quality-of-life questionnaire. When data sets include repeated measurements from the same individuals over time, the assumption of observations' independence, required by standard models, is violated, and standard errors are underestimated. This review aimed to identify how studies deal with methodological challenges of repeated measurements, provide an overview of practice to date, and potential implications for future work.

METHODS

We conducted a systematic literature search of MEDLINE, Cumulative Index to Nursing and Allied Health Literature, specialized databases, and previous systematic reviews. A data template was used to extract, among others, start and target instruments if the data set(s) used for estimation and validation had repeated measurements per patient, used regression techniques, and which (if any) adjustments were made for repeated measurements.

RESULTS

We identified 278 publications developing at least 1 mapping algorithm. Of the 278 publications, 121 used a data set with repeated measurements, among which 92 used multiple time points for estimation, and 39 selected specific time points to have 1 observation per participant. A total of 36 studies did not account for repeated measurements. An adjustment was conducted using cluster-robust standard errors (21), random-effects models (30), generalized estimating equations (7), and other methods (7).

CONCLUSIONS

The inconsistent use of methods to account for interdependent observations in the literature indicates that mapping guidelines should include recommendations on how to deal with repeated measurements, and journals should update their guidelines accordingly.

Gradient Boosted Tree Approaches for Mapping European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 Onto 5-Level Version of EQ-5D Index for Patients With Cancer

OBJECTIVES

This study aimed to develop direct and response mapping algorithms from the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 onto the 5-level version of EQ-5D index based on the gradient boosted tree (GBT), a promising modern machine learning method.

METHODS

We used the Quality of Life Mapping Algorithm for Cancer study data (903 observations from 903 patients) for training GBTs and testing their predictive performance. In the Quality of Life Mapping Algorithm for Cancer study, patients with advanced solid tumor were enrolled, and the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 and 5-level version of EQ-5D were simultaneously evaluated. The Japanese value set was used for direct mapping, whereas the Japanese and US value sets were used for response mapping. We trained the GBTs in the training data set (80%) with cross-validation and tested the predictive performance measured by the root mean squared error (RMSE), mean absolute error (MAE), and mean error in the test data set (20%).

RESULTS

The RMSE and MAE in the test data set were larger in the GBT approaches than in the previously developed regression-based approaches. The mean error in the test data set tended to be smaller in the GBT approaches than in the previously developed regression-based approaches.

CONCLUSIONS

The predictive performances in the RMSE and MAE did not improve by the GBT approaches compared with regression approaches. The flexibility of the GBT approaches had the potential to reduce overprediction and underprediction in poor and good health, respectively. Further research is needed to establish the role of machine learning methods in mapping a nonpreference-based measure onto health utility.

Association of lifestyle behaviors with health-related quality of life among patients with hematologic diseases

PURPOSE

Health-related quality of life (HRQoL) is a multi-dimensional construct used to assess the impact of health status on quality of life, and it is known to be affected by lifestyle behaviors. This study focused on multiple lifestyle behaviors among patients with hematologic diseases, including physical activity, dietary intake, sleep quality, occupational exposure, alcohol consumption and smoking. The main objective was to investigate the association of both individual and clustering of health behaviors with HRQoL among the population with hematologic diseases based on a comprehensive lifestyle survey.

METHODS

A total of 539 patients with hematologic diseases aged over 18 years were enrolled in this cross-sectional study. Latent class analysis was used to identify homogeneous, mutually exclusive lifestyle classes, and multinomial logistic regression was then performed to explore the association of lifestyle classes membership with HRQoL. Meanwhile, multiple linear regression and quantile regression were used to identify the relationship between individual lifestyle behaviors and HRQoL.

RESULTS

A three-class model was selected based on conceptual interpretation and model fit. We found no association between multiple lifestyle behaviors and HRQoL in the 3-class model, either in the whole patients or in subgroups stratified by hematological malignancies. Further research on each lifestyle found that physical activity, dietary intake, occupational exposure, alcohol consumption or smoking were independent of HRQoL. Sleep quality was positively associated with HRQoL.

CONCLUSION

Our findings suggested that clustering of lifestyle behaviors may not be an indicator to reflect the health quality of patients with hematologic diseases. Sleep represents a viable intervention target that can confer health benefits on the hematologic patients.

Mapping health assessment questionnaire disability index onto EQ-5D-5L in China

Objective

This research aimed to develop the more accurate mapping algorithms from health assessment questionnaire disability index (HAQ-DI) onto EQ-5D-5L based on Chinese Rheumatoid Arthritis patients.

Methods

The cross-sectional data of Chinese RA patients from 8 tertiary hospitals across four provincial capitals was used for constructing the mapping algorithms. Direct mapping using Ordinary least squares regression (OLS), the general linear regression model (GLM), MM-estimator model (MM), Tobit regression model (Tobit), Beta regression model (Beta) and the adjusted limited dependent variable mixture model (ALDVMM) and response mapping using Multivariate Ordered Probit regression model (MV-Probit) were carried out. HAQ-DI score, age, gender, BMI, DAS28-ESR and PtAAP were included as the explanatory variables. The bootstrap was used for validation of mapping algorithms. The average ranking of mean absolute error (MAE), root mean square error (RMSE), adjusted R ² (adjR ²) and concordance correlation coefficient (CCC) were used to assess the predictive ability of the mapping algorithms.

Results

According to the average ranking of MAE, RMSE, adjR ², and CCC, the mapping algorithm based on Beta performed the best. The mapping algorithm would perform better as the number of variables increasing.

Conclusion

The mapping algorithms provided in this research can help researchers to obtain the health utility values more accurately. Researchers can choose the mapping algorithms under different combinations of variables based on the actual data.

Psychometric evaluation of the Fear of Cancer Recurrence Inventory (FCRI) and development of a short version in patients with follicular lymphoma

PURPOSE

To evaluate the psychometric properties of the Chinese Fear of Cancer Recurrence Inventory (FCRI-C) in follicular lymphoma (FL) survivors.

MATERIALS AND METHODS

A nationwide cross-sectional study was conducted online between July and September 2020. The following psychometric properties of the FCRI-C were evaluated: construct, convergent, and discriminant validity, and reliability. Item variance was assessed using differential item functioning (DIF). A short version of the FCRI-C was developed using a two-parameter item response theory (IRT) model. The patterns of response scale, item fit, and item information were assessed. The receiver operating characteristic (ROC) curve was used to determine the clinical cut-off point for the FCRI-C.

RESULTS

A total of 326 FL survivors completed the questionnaire. The confirmatory factor analysis supported the bi-factor structure of the FCRI-C. The IRT analysis confirmed a 10-item short version of the FCRI-C. Satisfactory convergent and discriminant validity were underpinned by a priori hypotheses. Cronbach's alpha of 0.95 and intraclass correlation coefficient of 0.82 indicated good internal consistency and test-retest reliability. The ROC curve determined a cut-off point of 83 and 20 for the full and short versions, respectively.

CONCLUSIONS

The FCRI-C used to measure and screen the levels of FCR in Chinese FL survivors was found to be valid and reliable.Implications for RehabilitationThe Chinese Fear of Cancer Recurrence Inventory (FCRI-C) is a reliable and valid measure to evaluate the fear of cancer recurrence (FCR) in follicular lymphoma survivors.The short version of the FCRI-C provides a rapid screening tool for the clinical detection of FCR in patients.The cut-off point of the FCRI-C could differentiate patients between "high" and "low" levels of FCR in clinical practice.

Mapping the Haem-A-QoL to the EQ-5D-5L in patients with hemophilia

OBJECTIVE

This study's objective was to develop an algorithm that mapping the Haem-A-QoL scores to EQ-5D-5L utility scores in patients with hemophilia in China.

METHODS

A national sample of 862 patients with hemophilia completed both the EQ-5D-5L and Haem-A-QoL instruments. Eight regression models were selected to develop the mapping algorithm, they were: the ordinary least squares, general linear regression, Tobit regression, censored least absolute deviation, mixture beta regression, adjusted limited dependent variable mixture, the two-part, and robust MM-estimator model. Root mean squared error (RMSE), mean absolute error (MAE), and R-square (R²) calculated using the tenfold cross-validation and random sample validation methods were used to assess the predictive ability of the models.

RESULTS

Based on RMSE, MAE, and R², the mixture beta regression model with selected Haem-A-QoL subscale scores as the predicted variables showed the best performance.

CONCLUSIONS

Our mapping algorithm bolsters the calculation of QALYs while conducting an economic evaluation of hemophilia-related interventions when only Haem-A-QoL data are available. The external validity of the algorithm should be further assessed in the other populations.