Mapping the kidney disease quality of life 36-item short form survey (KDQOL-36) to the EQ-5D-3L and the EQ-5D-5L in patients undergoing dialysis

Mapping the EORTC QLQ-C30 and QLQ H&N35 to the EQ-5D-5L and SF-6D for papillary thyroid carcinoma

PURPOSE

Empirical evidence for the EORTC QLQ C30 scale in thyroid cancer mapping algorithms has not been found in China, which limits the cost-utility analysis of patients with papillary thyroid carcinoma (PTC) population. We developed mapping algorithms that use the EORTC QLQ-C30 and QLQ H&N35 to predict EQ-5D-5L and SF-6D health utility scores for PTC patients.

METHODS

Data from 1050 Chinese PTC patients who completed the EORTC QLQ-C30, QLQ H&N35, EQ-5D-5L and SF-6D instruments were collected. Direct mapping (OLS, Tobit, Betamix) and indirect mapping functions (Order Probit) were used to estimate algorithms. The goodness-of-fit of mapping performance was assessed by MAE, RMSE, AIC, BIC, AE, and ICC. A fivefold cross-validation and random sample validation approach were used to test the stability of the models.

RESULTS

The mean EQ-5D-5L and SF-6D utility scores were 0.8704 and 0.6368, respectively. We recommend the Betamix model for the EQ-5D-5L (MAE = 0.0363, RMSE = 0.0505, AIC = -3458.73, BIC = -3096.91, AE > 0.05(%) = 48.38, AE > 0.1(%) = 8.67, ICC = 0.8288 for the full sample dataset) and the Betamix model for the SF-6D (MAE = 0.0328, RMSE = 0.0417, AIC = -2788.91, BIC = -2605.51, AE > 0.05(%) = 42.76, AE > 0.1(%) = 3.62, ICC = 0.8657 for the full sample dataset), with EORTC QLQ-C30 all items, QLQ H&N35 all items, age and gender as the predicted variables showing the best performance.

CONCLUSION

In the absence of preference-based quality of life tools, the mapping algorithms reported here are effective alternative for predicting the health utility of PTC patients, contributing to the cost-utility analysis studies.

Economic evaluation of dialysis and comprehensive conservative care for chronic kidney disease using the ICECAP-O and EQ-5D-5L; a comparison of evaluation instruments

BACKGROUND

Chronic Kidney Disease (CKD) patients often require long-term care, and while Hemodialysis (HD) is the standard treatment, Comprehensive Conservative Care (CCC) is gaining popularity as an alternative. Economic evaluations comparing their cost-effectiveness are crucial. This study aims to perform a cost-utility analysis comparing HD and CCC using the EQ-5D-5L and ICECAP-O instruments to assessing healthcare interventions in CKD patients.

METHODS

This short-term economic evaluation involved 183 participants (105 HD, 76 CCC) and collected data on demographics, comorbidities, laboratory results, treatment costs, and HRQoL measured by ICECAP-O and EQ-5D-5L. Incremental Cost-Effectiveness Ratios (ICERs) and Net Monetary Benefit (NMB) were calculated separately for each instrument, and Probabilistic Sensitivity Analysis (PSA) assessed uncertainty.

RESULTS

CCC demonstrated significantly lower costs (mean difference $8,544.52) compared to HD. Both EQ-5D-5L and ICECAP-O indicated higher Quality-Adjusted Life Years (QALYs) for both groups, but the difference was not statistically significant (p > 0.05). CCC dominated HD in terms of HRQoL measures, with ICERs of -$141,742.67 (EQ-5D-5L) and -$4,272.26 (ICECAP-O). NMB was positive for CCC and negative for HD, highlighting its economic feasibility.

CONCLUSION

CCC proves a preferable and more cost-effective treatment option than HD for CKD patients aged 65 and above, regardless of the quality-of-life measure used for QALY calculations. Both EQ-5D-5L and ICECAP-O showed similar results in cost-utility analysis.

Cross-walk of the Chronic Liver Disease Questionnaire for Nonalcoholic Steatohepatitis (CLDQ-NASH) and the EuroQol EQ-5D-5L in patients with NASH

BACKGROUND

Nonalcoholic steatohepatitis (NASH) is a chronic progression of nonalcoholic fatty liver disease, which can negatively impact the health-related quality of life (HRQoL) of affected individuals. HRQoL in NASH has been assessed using the disease-specific Chronic Liver Disease Questionnaire for NASH (CLDQ-NASH) and the generic EuroQol EQ-5D-5L. As the performance of these instruments relative to each other is unknown, we performed a cross-walk analysis of CLDQ-NASH to EQ-5D-5L using data from a real-world NASH population.

METHODS

Data were drawn from the Adelphi Real World 2019 NASH Disease Specific Programme, a cross-sectional survey of physicians and their patients in the United States. Patients with physician-diagnosed NASH completed a questionnaire that included the CLDQ-NASH and EQ-5D-5L. Mapping from CLDQ-NASH to EQ-5D-5L was done using tenfold cross-validation; performance was assessed using root-mean squared error as accuracy measure. Subgroup analyses compared performance of the models in obese versus non-obese patients and patients with versus without type 2 diabetes (T2D).

RESULTS

Data from 347 patients were included in this analysis. Overall, 2172 models were tested for predicting EQ-5D-5L index score from CLDQ-NASH score. The best model for this mapping was a generalized linear model using Gaussian distribution and a power link. The best model for mapping from CLDQ-NASH domains to the EQ-5D-5L was a fractional logistic model. Models performed better at predicting upper versus lower values of EQ-5D-5L, for non-obese versus obese patients, and for patients without versus with T2D.

CONCLUSION

We describe a scoring algorithm for cross-walking the CLDQ-NASH to the EQ-5D-5L enabling health status comparisons of HRQoL across studies.

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.

Mapping the Peds QLTM 4.0 onto CHU-9D: a cross-sectional study in functional dyspepsia population from China

Objective

The study aims to develop a mapping algorithm from the Pediatric Quality of Life Inventory™ 4. 0 (Peds QL 4.0) onto Child Health Utility 9D (CHU-9D) based on the cross-sectional data of functional dyspepsia (FD) children and adolescents in China.

Methods

A sample of 2,152 patients with FD completed both the CHU-9D and Peds QL 4.0 instruments. A total of six regression models were used to develop the mapping algorithm, including ordinary least squares regression (OLS), the generalized linear regression model (GLM), MM-estimator model (MM), Tobit regression (Tobit) and Beta regression (Beta) for direct mapping, and multinomial logistic regression (MLOGIT) for response mapping. Peds QL 4.0 total score, Peds QL 4.0 dimension scores, Peds QL 4.0 item scores, gender, and age were used as independent variables according to the Spearman correlation coefficient. The ranking of indicators, including the mean absolute error (MAE), root mean squared error (RMSE), adjusted R², and consistent correlation coefficient (CCC), was used to assess the predictive ability of the models.

Results

The Tobit model with selected Peds QL 4.0 item scores, gender and age as the independent variable predicted the most accurate. The best-performing models for other possible combinations of variables were also shown.

Conclusion

The mapping algorithm helps to transform Peds QL 4.0 data into health utility value. It is valuable for conducting health technology evaluations within clinical studies that have only collected Peds QL 4.0 data.

Mapping the Patient-Reported Outcomes Measurement Information System (PROMIS-29) to EQ-5D-5L

BACKGROUND AND OBJECTIVE

The Patient-Reported Outcomes Measurement Information System (PROMIS-29) is gaining popularity as healthcare system funders increasingly seek value-based care. However, it is limited in its ability to estimate utilities and thus inform economic evaluations. This study develops the first mapping algorithm for estimating EuroQol 5-Dimension 5-Level (EQ-5D-5L) utilities from PROMIS-29 responses using a large dataset and through extensive comparisons between econometric models.

METHODS

An online survey was conducted to collect responses to PROMIS-29 and EQ-5D-5L from the general Australian population (N = 3013). Direct and indirect mapping methods were explored, including linear regression, Tobit, generalised linear model, censored regression model, beta regression (Betamix), the adjusted limited dependent variable mixture model (ALDVMM) and generalised ordered logit. The most robust model was selected by assessing the performance based on average ten-fold cross-validation geometric mean absolute error and geometric mean squared error, the predicted mean, maximum and minimum utilities, as well as the fitting across the entire distribution.

RESULTS

The direct approach using ALDVMM was considered the preferred model based on lowest geometric mean absolute error and geometric mean squared error in cross-validation (0.0882, 0.0299) and its superiority in predicting the actual observed mean, full health states and lower utility extremes. The robustness and precision in prediction across the entire distribution of utilities with ALDVMM suggest it is an accurate and valid mapping algorithm. Moreover, the suggested mapping algorithm outperformed previously published algorithms using Australian data, indicating the validity of this model for economic evaluations.

CONCLUSIONS

This study developed a robust algorithm to estimate EQ-5D-5L utilities from PROMIS-29. Consistent with the recent literature, the ALDVMM outperformed all other econometric models considered in this study, suggesting that the mixture models have relatively better performance and are an ideal candidate model for mapping.

Mapping study of papillary thyroid carcinoma in China: Predicting EQ-5D-5L utility values from FACT-H&N

Objective

To develop a mapping algorithm that can be used to predict EQ-5D-5L health utility scores from FACT-H&N and obtain health utility parameters for Chinese patients with papillary thyroid carcinoma (PTC), which can be used for cost-utility analysis in health economic.

Methods

A total of 1,050 patients with PTC from a tertiary hospital in China were included, and they completed FACT-H&N and EQ-5D-5L. Four mapping algorithms of direct mapping functions were used to derive the models: Ordinary least squares (OLS), Tobit model (Tobit), Two-part model (TPM), and Beta mixture regression model (Beta). The goodness-of-fit of models was assessed by the mean absolute error (MAE), root mean square error (RMSE), Akaike information criteria (AIC), Bayesian information criteria (BIC), and absolute error (AE). A fivefold cross-validation method was used to test the stability of the models.

Results

The mean utility value of the EQ-5D-5L was 0.870 ± 0.094. The mean EQ-VAS score was 76.5 ± 13.0. The Beta mixture regression model mapping FACT-H&N to EQ-5D-5L achieved the best performance [fivefold cross-validation MAE = 0.04612, RMSE = 0.06829, AIC = -2480.538, BIC = -2381.137, AE > 0.05 (%) = 32.48, AE > 0.1 (%) = 8.95]. The independent variables in this model were Physical Well-Being (PWB), Emotional Well-Being (EWB), Head & Neck Cancer Subscale (HNCS) scores and its square term and interaction term scores.

Conclusions

This study calculated the health utility score of Chinese patients with PTC. The reported algorithms can be used to map the FACT-H&N into the EQ-5D-5L, which can be applied in the cost-utility related study of patients with PTC.

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.

An examination of machine learning to map non-preference based patient reported outcome measures to health state utility values

Non-preference-based patient-reported outcome measures (PROMs) are popular in health outcomes research. These measures, however, cannot be used to estimate health state utilities, limiting their usefulness for economic evaluations. Mapping PROMs to a multi-attribute utility instrument is one solution. While mapping is commonly conducted using econometric techniques, failing to specify the complex interactions between variables may lead to inaccurate prediction of utilities, resulting in inaccurate estimates of cost-effectiveness and suboptimal funding decisions. These issues can be addressed using machine learning. This paper evaluates the use of machine learning as a mapping tool. We adopt a comprehensive approach to compare six machine learning techniques with eight econometric techniques to map the Patient-Reported Outcomes Measurement Information System Global Health 10 (PROMIS-GH10) to the EuroQol five dimensions (EQ-5D-5L). Using data collected from 2015 Australians, we find the least absolute shrinkage and selection operator (LASSO) model out-performed all machine learning techniques and the adjusted limited dependent variable mixture model (ALDVMM) out-performed all econometric techniques, with the LASSO performing better than ALDVMM. The variable selection feature of LASSO was then used to enhance the performance of the ALDVMM in a hybrid model. Our analysis identifies the potential benefits and challenges of using machine learning techniques for mapping and offers important insights for future research.

Electronic Patient-Reported Outcomes in Nephrology: Focus on Hemodialysis

The success of hemodialysis (HD) treatments has been evaluated using objective measures of analytical parameters, or machine-measured parameters, despite having available validated instruments that assess patient perspective. There is an emerging interest regarding the use and relevance of patient-related outcomes (PROs). Electronic PROs (ePROs) involve the use of electronic technology, provide rapid access to this information, and are becoming more widely used in clinical trials and studies to evaluate efficacy and safety. Despite the scarce literature, this review suggests that ePROs are useful in providing a more customized and multidimensional approach to patient management and in making better clinical decisions in relevant aspects such as vascular access, duration and frequency of dialysis sessions, treatment of anemia, mental health, fatigue, and quality of life. The purpose of this review is to raise interest in the systematic use of ePROs in HD and to promote the development of studies in this field, which can respond to the gaps in knowledge and contribute to the implementation of the use of ePROs through new technologies, helping to improve the quality of health care.

Biomarkers for assessing acute kidney injury for people who are being considered for admission to critical care: a systematic review and cost-effectiveness analysis

BACKGROUND

Acute kidney injury is a serious complication that occurs in the context of an acute critical illness or during a postoperative period. Earlier detection of acute kidney injury may facilitate strategies to preserve renal function, prevent further disease progression and reduce mortality. Acute kidney injury diagnosis relies on a rise in serum creatinine levels and/or fall in urine output; however, creatinine is an imperfect marker of kidney function. There is interest in the performance of novel biomarkers used in conjunction with existing clinical assessment, such as NephroCheck^® (Astute Medical, Inc., San Diego, CA, USA), ARCHITECT^® urine neutrophil gelatinase-associated lipocalin (NGAL) (Abbott Laboratories, Abbott Park, IL, USA), and urine and plasma BioPorto NGAL (BioPorto Diagnostics A/S, Hellerup, Denmark) immunoassays. If reliable, these biomarkers may enable earlier identification of acute kidney injury and enhance management of those with a modifiable disease course.

OBJECTIVE

The objective was to evaluate the role of biomarkers for assessing acute kidney injury in critically ill patients who are considered for admission to critical care.

DATA SOURCES

Major electronic databases, conference abstracts and ongoing studies were searched up to June 2019, with no date restrictions. MEDLINE, EMBASE, Health Technology Assessment Database, Cumulative Index to Nursing and Allied Health Literature, Cochrane Central Register of Controlled Trials, Web of Science, World Health Organization Global Index Medicus, EU Clinical Trials Register, International Clinical Trials Registry Platform and ClinicalTrials.gov were searched.

REVIEW METHODS

A systematic review and meta-analysis were conducted to evaluate the performance of novel biomarkers for the detection of acute kidney injury and prediction of other relevant clinical outcomes. Random-effects models were adopted to combine evidence. A decision tree was developed to evaluate costs and quality-adjusted life-years accrued as a result of changes in short-term outcomes (up to 90 days), and a Markov model was used to extrapolate results over a lifetime time horizon.

RESULTS

A total of 56 studies (17,967 participants), mainly prospective cohort studies, were selected for inclusion. No studies addressing the clinical impact of the use of biomarkers on patient outcomes, compared with standard care, were identified. The main sources of bias across studies were a lack of information on blinding and the optimal threshold for NGAL. For prediction studies, the reporting of statistical details was limited. Although the meta-analyses results showed the potential ability of these biomarkers to detect and predict acute kidney injury, there were limited data to establish any causal link with longer-term health outcomes and there were considerable clinical differences across studies. Cost-effectiveness results were highly uncertain, largely speculative and should be interpreted with caution in the light of the limited evidence base. To illustrate the current uncertainty, 15 scenario analyses were undertaken. Incremental quality-adjusted life-years were very low across all scenarios, ranging from positive to negative increments. Incremental costs were also small, in general, with some scenarios generating cost savings with tests dominant over standard care (cost savings with quality-adjusted life-year gains). However, other scenarios generated results whereby the candidate tests were more costly with fewer quality-adjusted life-years, and were thus dominated by standard care. Therefore, it was not possible to determine a plausible base-case incremental cost-effectiveness ratio for the tests, compared with standard care.

LIMITATIONS

Clinical effectiveness and cost-effectiveness results were hampered by the considerable heterogeneity across identified studies. Economic model predictions should also be interpreted cautiously because of the unknown impact of NGAL-guided treatment, and uncertain causal links between changes in acute kidney injury status and changes in health outcomes.

CONCLUSIONS

Current evidence is insufficient to make a full appraisal of the role and economic value of these biomarkers and to determine whether or not they provide cost-effective improvements in the clinical outcomes of acute kidney injury patients.

FUTURE WORK

Future studies should evaluate the targeted use of biomarkers among specific patient populations and the clinical impact of their routine use on patient outcomes and management.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42019147039.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Evidence Synthesis programme and will be published in full in Health Technology Assessment; Vol. 26, No. 7. See the NIHR Journals Library website for further project information.

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.

Mapping the PHQ-8 to EQ-5D, HUI3 and SF6D in patients with depression

BACKGROUND

There is limited evidence of mapping clinical instruments to a generic preference-based instrument in Asian patient populations. The current study aims to map the eight-item Patient Health Questionnaire depression scale (PHQ-8) onto the EuroQol Five-Dimension (EQ-5D), the Health Utilities Index Mark 3 (HUI3) and the Short Form Six-Dimension (SF-6D) which helps to inform future cost-utility analyses of treatments for depression.

METHODS

A total of 249 participants who had completed PHQ-8, EQ-5D, SF-6D and HUI3 questionnaires were included in the analyses. A beta regression mixture model was used to map the utility scores as a function of PHQ-8 total scores, PHQ-squared, age and gender. The predictive accuracy of the models was examined using mean absolute error and root mean square error.

RESULTS

The results were compared against two common regression methods including Ordinary Least Square (OLS) and Tobit regression models. The mean age of the sample was 36.2 years (SD = 11.1). The mean EQ-5D-3L, EQ-5D-5L, HUI3 and SF-6D utility scores were 0.615, 0.709, 0.461 and 0.607, respectively. The EQ-5D-3L, EQ-5D-5L and SF-6D utility scores were best predicted by the beta mixture regression model consisting of PHQ-8 total sores, PHQ-squared, and covariates including age and gender. The HUI3 was best predicted by the OLS regression model.

CONCLUSIONS

The current study provides important evidence to clinicians and researchers about the mapping algorithms that can be used in economic evaluation among patients with depression.

Cost-effectiveness analysis of hemodialysis plus hemoperfusion versus hemodialysis alone in adult patients with end-stage renal disease in China

Background

This study evaluates the cost-effectiveness of hemodialysis (HD) plus hemoperfusion (HP) with HD alone in adult patients with end-stage renal disease (ESRD) in China.

Methods

A Markov model was constructed to assess the cost-effectiveness of interventions over a lifetime horizon. Model parameters were informed by the HD/HP trial, the first randomized, open-label multicenter trial comparing survival outcomes and incidence of cardiovascular disease (CVD) for HD + HP versus HD alone, and supplemented by published literature and expert opinion. The primary outcome was the incremental cost-effectiveness ratio (ICER) with respect to quality adjusted life-years (QALY). The robustness of the results was examined in extensive sensitivity analyses. Analyses were conducted from a healthcare perspective. Costs were reported in both Chinese Renminbi (RMB) and US Dollars (USD) in 2019 values.

Results

The base case ICER of HD + HP is RMB 174,486 (USD 25,251) per QALY, which is lower than the RMB 212,676 (USD 30,778) willingness-to-pay threshold of three times Gross Domestic Product. This conclusion is sensitive to the mortality for patients with no severe CVD events, the incidence of CVD events, and the cost of HP and HD. At a willingness-to-pay threshold of RMB 212,676 (USD 30,778) per QALY gained, the probability that HD + HP is cost-effective is 58%.

Conclusions

Our results indicate a potential for HD + HP to be cost-effective for patients with ESRD. Further evidence on the longer-term impact of HD + HP on CVD event rates and mortality unrelated to CVD is needed to robustly demonstrate the cost-effectiveness of HD + HP.

Trial Registration

The HD/HP trial was registered with the Chinese Clinical Trial Registry (ChiCTR-IOR-16009332).

An initial evaluation of expanded hemodialysis on hospitalizations, drug utilization, costs, and patient utility in Colombia

To examine new evidence linking expanded hemodialysis (HDx) using a medium cut‐off (MCO) membrane with hospitalizations, hospital days, medication use, costs, and patient utility. This retrospective study utilized data from Renal Care Services medical records database in Colombia from 2017 to 2019. Clinics included had switched all patients from high flux hemodialysis (HD HF) to HDx and had at least a year of data on HD HF and HDx. Data included demographic characteristics, comorbidities, years on dialysis, hospitalizations, medication use, and quality of life measured by the 36 item and Short Form versions of the Kidney Disease Quality of Life survey at the start of HDx, and 1 year after HDx, which were mapped to EQ‐5D utilities. Generalized linear models were run on the outcomes of interest with an indicator for being on HDx. Annual cost estimates were also constructed. The study included 81 patients. HDx was significantly associated with lower dosing of erythropoietin stimulating agents, iron, hypertension medications, and insulin. HDx was also significantly associated with lower hospital days per year (5.94 on HD vs. 4.41 on HDx) although not with the number of hospitalizations. Estimates of annual hospitalization costs were 23.9% lower using HDx and patient utilities did not appear to decline. HDx was statistically significantly associated with reduced hospitalization days and lower medication dosages. Furthermore, this preliminary analysis suggested potential for HDx being a dominant strategy in terms of costs and utility and should motivate future work with larger samples and better controls.

Predicting EQ-5D-5L crosswalk from the PROMIS-29 profile for the United Kingdom, France, and Germany

Background

EQ-5D health state utilities (HSU) are commonly used in health economics to compute quality-adjusted life years (QALYs). The EQ-5D, which is country-specific, can be derived directly or by mapping from self-reported health-related quality of life (HRQoL) scales such as the PROMIS-29 profile. The PROMIS-29 from the Patient Reported Outcome Measures Information System is a comprehensive assessment of self-reported health with excellent psychometric properties. We sought to find optimal models predicting the EQ-5D-5L crosswalk from the PROMIS-29 in the United Kingdom, France, and Germany and compared the prediction performances with that of a US model.

Methods

We collected EQ-5D-5L and PROMIS-29 profiles and three samples representative of the general populations in the UK (n = 1509), France (n = 1501), and Germany (n = 1502). We used stepwise regression with backward selection to find the best models to predict the EQ-5D-5L crosswalk from all seven PROMIS-29 domains. We investigated the agreement between the observed and predicted EQ-5D-5L crosswalk in all three countries using various indices for the prediction performance, including Bland–Altman plots to examine the performance along the HSU continuum.

Results

The EQ-5D-5L crosswalk was best predicted in France (nRMSE_FRA = 0.075, nMAE_FRA = 0.052), followed by the UK (nRMSE_UK = 0.076, nMAE_UK = 0.053) and Germany (nRMSE_GER = 0.079, nMAE_GER = 0.051). The Bland–Altman plots show that the inclusion of higher-order effects reduced the overprediction of low HSU scores.

Conclusions

Our models provide a valid method to predict the EQ-5D-5L crosswalk from the PROMIS-29 for the UK, France, and Germany.

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

OBJECTIVE

The objective of this study was to develop algorithms to map the EORTC QLQ-C30 (QLQ-C30) onto EQ-5D-5L in a sample of patients with lymphomas.

METHODS

An online nationwide survey of patients with lymphoma was carried out in China. Ordinary least squares (OLS), beta-based mixture, adjusted limited dependent variable mixture regression, and a Tobit regression model were used to develop the mapping algorithms. The QLQ-C30 subscales/items, their squared and interaction terms, and respondents' demographic variables were used as independent variables. The root mean square error (RMSE), mean absolute error (MAE), and R-squared (R²) were estimated based on tenfold cross-validation to assess the predictive ability of the selected models.

RESULTS

Data of 2222/4068 respondents who self-completed the online survey were elicited for analyses. The mean EQ-5D-5L index score was 0.81 (SD 0.21, range - 0.81-1.0). 19.98% of respondents reported an index score at 1.0. In total, 72 models were generated based on four regression methods. According to the RMSE, MAE and R², the OLS model including QLQ-C30 subscales, squared terms, interaction terms, and demographic variables showed the best fit for overall and the Non-Hodgkin's lymphoma sample; for Hodgkin's lymphoma, the ALDVMM with 1-component model, including QLQ-C30 subscales, squared terms, interaction terms, and demographic variables, showed a better fit than the other models.

CONCLUSION

The mapping algorithms enable the EQ-5D-5L index scores to be predicted by QLQ-C30 subscale/item scores with good precision in patients living with lymphomas.

Comparing the reliability and validity of the SF-36 and SF-12 in measuring quality of life among adolescents in China: a large sample cross-sectional study

OBJECTIVE

We compare the reliability and validity of the Short Form 36 (version 1, SF-36) and the Short Form 12 (version 1, SF-12) in adolescence, the period of life when a child develops into an adult, i.e., the period from puberty to maturity terminating legally at the age of majority (10-19 years), thus supplying evidence for the selection of instruments measuring the quality of life (QOL) and decision-making processes of adolescents in China.

METHODS

Stratified cluster random sampling was adopted according to geographical location, and the SF-36 was administered to assess QOL. The Pearson correlation coefficient was used to show correlation. Cronbach's alpha and construct reliability (CR) were used to evaluate the reliability of SF-36 and SF-12, while criterion validity and average variance extracted (AVE, convergence validity) were used to evaluate validity. Confirmatory factor analysis was used to calculate the load factors for the items of the SF-36 and SF-12, then to obtain the CR and AVE. The Semejima grade response model (logistic two-parameter module) in item response theory was used to estimate item discrimination, item difficulty, and item average information for the items of the SF-36 and SF-12.

RESULTS

19,428 samples were included in the study. The mean age of respondents was 14.78 years (SD = 1.77). Reliability of each domain of the SF-36 was better than for the corresponding domain of the SF-12. The domains of PF, RP, BP, and GH in SF-36 had good construct reliability (CR > 0.6). The criterion validities of some domains of the SF-36 were a little higher in some corresponding dimensions of the SF-12, except for PCS. The convergence validities of the SF-12 were higher than the SF-36 in PF, RP, BP, and PCS. The items of BP, SF, RP, and VT in the SF-12 had acceptable discrimination of items that were higher than in the SF-36. The items' average amounts of information on BP, VT, SF, RE, and MH in the SF-36 and SF-12 were poor.

CONCLUSION

Two component (PCS and MCS) measurements of the SF-12 appeared to perform at least as well as the SF-36 in cross-sectional settings in adolescence, but the reliability and validity of the 8 domains of the SF-36 were better than those of the SF-12. Some domains, for instance SF and BP, were not suitable for adolescents or need to be studied further.

Patient-reported outcomes from the investigational device exemption study of the Tablo hemodialysis system

INTRODUCTION

We recently completed an Investigational Device Exemption (IDE) study in which 30 patients were enrolled (13 patients previously on home hemodialysis (HHD) and 17 patients new to HHD) and treated with the Tablo Hemodialysis System (Outset Medical, Inc., San Jose, CA) for 8 weeks in-center and 8 weeks in-home with an interim 2-4 week transition period for home training.

METHODS

In addition to assessments of urea kinetics, events related to safety, and operational issues (e.g., alarm resolution), we obtained data on several parameters of health-related quality of life, including time to recovery (TTR), the EQ-5D-5L (a well-validated measure of general health status), and the quality of sleep and related symptoms, to further assess the safety of HHD with Tablo. We compared results obtained during the in-center and in-home phases of the trial.

RESULTS

Twenty-eight of 30 patients (93%) completed all trial periods. Adherence to the prescribed four treatments per week schedule was 96% in-center and 99% in-home. Median TTR was 1.5 hours (10th, 90th percentile range 0.17 to 12, mean TTR 3.68 ± 5.88 hours) during the in-center and 2 hours (10th, 90th percentile range 0 to 6.0, mean TTR 3.04 ± 5.14 hours) during the at-home phase (Wilcoxon signed rank p = 0.57). Median index values on the EQ-5D-5L were similar during the in-center (0.832, 10th, 90th percentile range 0.617 to 1, mean 0.817 ± 0.165) and in-home (0.826, 10th, 90th percentile range 0.603 to 1, mean 0.821 ± 0.163) trial phases (Wilcoxon signed rank p = 0.36). Patients reported feeling alert or well-rested with little difficulty falling or staying asleep or feeling tired and worn out when using Tablo in either environment.

CONCLUSION

When using Tablo in-home, patients reported similar TTR, general health status, and sleep quality and related symptoms compared to using Tablo in-center. (294 words).

Evaluating symptom burden in kidney transplant recipients: validation of the revised Edmonton Symptom Assessment System for kidney transplant recipients - a single-center, cross-sectional study

We assessed the validity of the Edmonton Symptom Assessment System (ESAS-r) in kidney transplant recipients (KTR). A cross-sectional sample of 252 KTR was recruited. Individual ESAS-r symptom scores and symptom domain scores were evaluated. Internal consistency, convergent validity, and construct validity were assessed with Cronbach's α, Spearman's rank correlations, and a priori-defined risk group comparisons. Mean (SD) age was 51 (16), 58% were male, and 58% Caucasian. ESAS-r Physical, Emotional, and Global Symptom Scores demonstrated good internal consistency (α > 0.8 for all). ESAS-r Physical and Global Symptom Scores strongly correlated with PHQ-9 scores (0.72, 95% CI: 0.64-0.78 and 0.74, 95% CI: 0.67-0.80). For a priori-defined risk groups, individual ESAS-r symptom score differed between groups with lower versus higher eGFR [pain: 1 (0-3) vs. 0 (0-2), delta = 0.18; tiredness: 3 (1-5) vs. 1.5 (0-4), delta = 0.21] and lower versus higher hemoglobin [tiredness: 3 (1-6) vs. 2 (0-4), delta = 0.27]. ESAS-r Global and Physical Symptom Scores differed between groups with lower versus higher hemoglobin [13 (6-29) vs. 6.5 (0-18.5), delta = 0.3, and 9 (2-19) vs. 4 (0-13), delta = 0.24] and lower versus higher eGFR [11 (4-20) vs. 6.5 (2-13), delta = 0.21, and 7 (2-16) vs. 3 (0-9), delta = 0.26]. These data support reliability and construct validity of ESAS-r in KTR. Future studies should explore its clinical utility for symptom assessment among KTR.