Mapping the Oxford hip score onto the EQ-5D utility index

A systematic review of crosswalks for converting patient-reported outcome measure scores in hip, knee, and shoulder replacement surgery

BACKGROUND AND PURPOSE

 We aimed to systematically review studies of crosswalks for converting patient-reported outcome measure (PROM) scores used in joint replacement, and develop a database of published crosswalks.

METHODS

 4 electronic databases were searched from January 2000 to May 2023 to identify studies reporting the development and/or validation of crosswalks to convert PROM scores in patients undergoing elective hip, knee, or shoulder replacement surgery. Data on study and sample characteristics, source and target PROMs, and crosswalk development and validation methods were extracted from eligible studies. Study reporting was evaluated using the Mapping onto Preference-based measures reporting Standards (MAPS) checklist.

RESULTS

17 studies describing 35 crosswalks were eligible for inclusion. Unidirectional crosswalks were available to convert hip-specific (Oxford Hip Score [OHS]) and knee-specific (Oxford Knee Score [OKS]) scores to the EQ-5D-3L/EQ-5D-5L. Similar crosswalks to convert disease-specific scores (WOMAC) to the EQ-5D-3L, EQ-5D-5L, and ICECAP-O Capability Index were identified. Bidirectional crosswalks for converting OHS and OKS to the HOOS-JR/HOOS-12 and KOOS-JR/KOOS-12, for converting WOMAC to the HOOS-JR/KOOS-JR, and for converting HOOS-Function/KOOS-Function to the PROMIS-Physical Function were also available. Additionally, crosswalks to convert generic PROM scores from the UCLA Activity Scale to the Lower Extremity Activity Scale in both directions were available. No crosswalks were identified for converting scores in shoulder replacement. Development methods varied with the type of target score; most studies used regression, item response theory, or equipercentile equating approaches. Reporting quality was variable, particularly for methods and results items, impacting crosswalk application.

CONCLUSION

 This is the first synthesis of published crosswalks for converting joint-specific (OHS, OKS, HOOS, KOOS), disease-specific (WOMAC), and generic PROMs scores (PROMIS-Physical Function, UCLA Activity Scale, Lower Extremity Activity Scale) used to assess joint replacement outcomes, providing a resource for data harmonization and pooled analysis. Crosswalks were developed using regression methods (9 studies), equipercentile equating methods (5 studies), a combination of equipercentile equating and item response theory methods (2 studies), and a combination of regression and equipercentile equating methods (1 study). A range of crosswalk validation approaches were adopted, including the use of external datasets, separate samples or subsets, follow-up data from additional time points, or bootstrapped samples. Efforts are needed to standardize crosswalk methodology and achieve consistent reporting.

Mapping the Oxford Shoulder Score onto the EQ-5D utility index

PURPOSE

In order to enable cost-utility analysis of shoulder pain conditions and treatments, this study aimed to develop and evaluate mapping algorithms to estimate the EQ-5D health index from the Oxford Shoulder Score (OSS) when health outcomes are only assessed with the OSS.

METHODS

5437 paired OSS and EQ-5D questionnaire responses from four national multicentre randomised controlled trials investigating different shoulder pathologies and treatments were split into training and testing samples. Separate EQ-5D-3L and EQ-5D-5L analyses were undertaken. Transfer to utility (TTU) regression (univariate linear, polynomial, spline, multivariable linear, two-part logistic-linear, tobit and adjusted limited dependent variable mixture models) and response mapping (ordered logistic regression and seemingly unrelated regression (SUR)) models were developed on the training sample. These were internally validated, and their performance evaluated on the testing sample. Model performance was evaluated over 100-fold repeated training-testing sample splits.

RESULTS

For the EQ-5D-3L analysis, the multivariable linear and splines models had the lowest mean square error (MSE) of 0.0415. The SUR model had the lowest mean absolute error (MAE) of 0.136. Model performance was greatest in the mid-range and best health states, and lowest in poor health states. For the EQ-5D-5L analyses, the multivariable linear and splines models had the lowest MSE (0.0241-0.0278) while the SUR models had the lowest MAE (0.105-0.113).

CONCLUSION

The developed models now allow accurate estimation of the EQ-5D health index when only the OSS responses are available as a measure of patient-reported health outcome.

Significant deterioration in quality of life and increased frailty in patients waiting more than six months for total hip or knee arthroplasty

Aims

The primary aim of this study was to assess whether patients waiting six months or more for a total hip (THA) or knee (KA) arthroplasty had a deterioration in their health-related quality of life (HRQoL). Secondary aims were to assess changes in frailty and the number of patients living in a state considered to be worse than death (WTD), and factors associated with changes in HRQoL and frailty.

Methods

This cross-sectional study included 326 patients, 150 males (46.0%) and 176 females (54.0%), with a mean age of 68.6 years (SD 9.8) who were randomly selected from waiting lists at four centres and had been waiting for six months or more (median 13 months, interquartile range 10 to 21) for a primary THA (n = 161) or KA (n = 165). The EuroQol five-dimension questionnaire (EQ-5D) and visual analogue scores (EQ-VAS), Rockwood Clinical Frailty Scale (CFS), and 36-Item Short Form Survey subjective change in HRQoL were assessed at the time and recalled for six months earlier. A state that was WTD was defined as an EQ-5D of less than zero.

Results

There were significant deteriorations in the EQ-5D (mean 0.175, 95% confidence interval (CI) 0.145 to 0.204; p < 0.001), EQ-VAS (mean 8.6, 95% CI 7.0 to 10.4; < 0.001), and CFS (from 3 “managing well” to 4 “vulnerable”; p < 0.001), and a significant increase in the number of those in a state that was WTD (n = 48; p < 0.001) during the previous six months for the whole cohort. A total of 110 patients (33.7%) stated that their health was much worse and 107 (32.8%) felt it was somewhat worse compared with six months previously. A significantly greater EQ-5D (-0.14, 95% CI 0.08 to 0.28; p = 0.038) and a state that was not WTD (-0.14, 95% CI 0.01 to 0.26; p = 0.031) were associated with a deterioration in the EQ-5D. THA (0.21, 95% CI 0.07 to 0.34; p = 0.002) or a lower (better) CFS (0.14, 95% CI 0.07 to 0.20; p < 0.001) were independently significantly associated with a deterioration in the CFS.

Conclusion

Patients waiting more than six months for THA or KA had a significant deterioration in their HRQoL and increased frailty, with two-thirds of patients feeling that their health had worsened. Cite this article: Bone Joint J 2022;104-B(11):1215–1224.

Total Hip and Knee Arthroplasties Are Highly Cost-Effective Procedures: The Importance of Duration of Follow-Up

BACKGROUND

Total hip and knee arthroplasties (THA/TKA) are clinically effective but high cost procedures. The aim of this study is to perform a cost-effectiveness analysis of THA and TKA in the New Zealand (NZ) healthcare system.

METHODS

Data were collected from 713 patients undergoing THA and 520 patients undergoing TKA at our local public hospital. SF-6D utility values were obtained from participants preoperatively and 1-year postoperatively, and deaths and any revision surgeries from patient records and the New Zealand Joint Registry at minimum 8-year follow-up. A continuous-time state-transition simulation model was used to estimate costs and health gains to 15 years. Quality-adjusted life years (QALYs), treatment costs, and incremental cost-effectiveness ratios (ICERs) were calculated to determine cost effectiveness. ICERs below NZ gross domestic product (GDP; NZ$60 600) and 0.5 times GDP per capita were considered "cost effective" and "highly cost effective" respectively.

RESULTS

Cumulative health gains were 2.8 QALYs (THA) and 2.3 QALYs (TKA) over 15 years. Cost effectiveness improved from ICERs of NZ$74,400 (THA) and NZ$93,000 (TKA) at 1 year to NZ$6000 (THA) and NZ$7500 (TKA) at 15 years. THA and TKA were cost effective after 2 years and highly cost effective after 3 years. QALY gains and cost effectiveness were greater in patients with worse preoperative functional status and younger age.

CONCLUSION

THA and TKA are highly cost-effective procedures over longer term horizons. Although preoperative status and age were associated with cost effectiveness, both THA and TKA remained cost effective in patients with less severe preoperative scores and older ages.

The Arthroplasty Candidacy Help Engine tool to select candidates for hip and knee replacement surgery: development and economic modelling

BACKGROUND

There is no good evidence to support the use of patient-reported outcome measures (PROMs) in setting preoperative thresholds for referral for hip and knee replacement surgery. Despite this, the practice is widespread in the NHS.

OBJECTIVES/RESEARCH QUESTIONS

Can clinical outcome tools be used to set thresholds for hip or knee replacement? What is the relationship between the choice of threshold and the cost-effectiveness of surgery?

METHODS

A systematic review identified PROMs used to assess patients undergoing hip/knee replacement. Their measurement properties were compared and supplemented by analysis of existing data sets. For each candidate score, we calculated the absolute threshold (a preoperative level above which there is no potential for improvement) and relative thresholds (preoperative levels above which individuals are less likely to improve than others). Owing to their measurement properties and the availability of data from their current widespread use in the NHS, the Oxford Knee Score (OKS) and Oxford Hip Score (OHS) were selected as the most appropriate scores to use in developing the Arthroplasty Candidacy Help Engine (ACHE) tool. The change in score and the probability of an improvement were then calculated and modelled using preoperative and postoperative OKS/OHSs and PROM scores, thereby creating the ACHE tool. Markov models were used to assess the cost-effectiveness of total hip/knee arthroplasty in the NHS for different preoperative values of OKS/OHSs over a 10-year period. The threshold values were used to model how the ACHE tool may change the number of referrals in a single UK musculoskeletal hub. A user group was established that included patients, members of the public and health-care representatives, to provide stakeholder feedback throughout the research process.

RESULTS

From a shortlist of four scores, the OHS and OKS were selected for the ACHE tool based on their measurement properties, calculated preoperative thresholds and cost-effectiveness data. The absolute threshold was 40 for the OHS and 41 for the OKS using the preferred improvement criterion. A range of relative thresholds were calculated based on the relationship between a patient's preoperative score and their probability of improving after surgery. For example, a preoperative OHS of 35 or an OKS of 30 translates to a 75% probability of achieving a good outcome from surgical intervention. The economic evaluation demonstrated that hip and knee arthroplasty cost of < £20,000 per quality-adjusted life-year for patients with any preoperative score below the absolute thresholds (40 for the OHS and 41 for the OKS). Arthroplasty was most cost-effective for patients with lower preoperative scores.

LIMITATIONS

The ACHE tool supports but does not replace the shared decision-making process required before an individual decides whether or not to undergo surgery.

CONCLUSION

The OHS and OKS can be used in the ACHE tool to assess an individual patient's suitability for hip/knee replacement surgery. The system enables evidence-based and informed threshold setting in accordance with local resources and policies. At a population level, both hip and knee arthroplasty are highly cost-effective right up to the absolute threshold for intervention. Our stakeholder user group felt that the ACHE tool was a useful evidence-based clinical tool to aid referrals and that it should be trialled in NHS clinical practice to establish its feasibility.

FUTURE WORK

Future work could include (1) a real-world study of the ACHE tool to determine its acceptability to patients and general practitioners and (2) a study of the role of the ACHE tool in supporting referral decisions.

FUNDING

The National Institute for Health Research Health Technology Assessment programme.

Mapping analysis to predict EQ-5D-5 L utility values based on the Oxford Hip Score (OHS) and Oxford Knee Score (OKS) questionnaires in the Spanish population suffering from lower limb osteoarthritis

BACKGROUND

The EQ-5D-5 L is a quality-of-life questionnaire based on individuals' preferences that is widely employed for cost-effectiveness analysis. Given the current demand for mapping algorithms to directly assign "utilities", this study aimed to generate different mapping models for predicting EQ-5D-5 L utility values based on scores of the Oxford Hip Score (OHS) and Oxford Knee Score (OKS) questionnaires provided by patients suffering from hip and knee osteoarthritis (OA), respectively, and to assess the predictive capability of these functions.

METHODS

This was a prospective, observational study. Following the criteria of the American Rheumatism Association, 361 patients with hip OA and 397 with knee OA from three regions in Spain were included. Health-related quality of life (HRQoL) was assessed through the EQ-5D-5 L general questionnaire and the OHS and OKS specifically for lower limb OA. Based on the scores on the OHS and OKS questionnaires, EQ-5D-5 L utilities were estimated using 4 models: ordinary least squares (OLS), Tobit, generalized linear model (GLM), and beta regression (Breg). The models were validated on the same patients after 6 months: the mean absolute error (MAE) and mean squared error (MSE) with their 95% confidence intervals (CI), mean values of standard errors (SE), intraclass correlation coefficients (ICC), and Bland-Altman plots were obtained.

RESULTS

The lowest MAEs were obtained using GLM and Breg models, with values of 0.1103 (0.0993-0.1214) and 0.1229 (0.1102-0.1335) for hip OA, and values of 0.1127 (0.1014-0.1239) and 0.1141 (0.1031-0.1251) for knee OA. MSE values were also lower using GLM and Breg. ICCs between predicted and observed values were around or over the 0.8 cut-off point. Bland-Altman plots showed an acceptable correlation, but precision was lower for subjects with worse HRQoL, which was also evident when comparing MAEs of the bottom and top halves of the utilities scale. Predictive equations for utilities based on OHS/OKS scores were proposed.

CONCLUSIONS

The OHS and OKS scores allow for estimating EQ-5D-5 L utility indexes for patients with hip and knee OA, respectively, with adequate validity and precision. GLM and Breg produce the best predictions. The predictive power of proposed equations is more consistent for subjects in better health condition.

Mapping WOMAC Onto the EQ-5D-5L Utility Index in Patients With Hip or Knee Osteoarthritis

OBJECTIVES

To map the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) onto the EQ-5D-5L in patients with hip or knee osteoarthritis (OA).

METHODS

A prospective observational study was conducted on 758 patients with hip or knee OA who completed the EQ-5D-5L and WOMAC questionnaires, of whom 644 completed them both again 6 months later. Baseline data were used to derive mapping functions. Generalized additive models were used to identify to which powers the WOMAC subscales should be raised to achieve a linear relationship with the response. For the modeling, general linear models (GLM), Tobit models, and beta regression models were used. Age, sex, and affected joints were also considered. Preferred models were selected based on Akaike and Bayesian information criteria, adjusted R², mean absolute error (MAE), and root mean squared error (RMSE). The functions were validated with the follow-up data using MAE, RMSE, and the intraclass correlation coefficient.

RESULTS

The preferred models were a GLM with Pain²+Pain³+Function+Pain·Function as covariates and a beta model with Pain³+Function+Function²+Function³ as covariates. The adjusted R² were similar (0.6190 and 0.6136, respectively). The predictive performance of these models in the validation sample was similar and both models showed an overprediction for health states worse than death.

CONCLUSION

To our knowledge, these are the first functions mapping the WOMAC onto the EQ-5D-5L in patients with hip or knee OA. They showed an acceptable fit and precision and could be very useful for clinicians and researchers when cost-effectiveness studies are needed and generic preference-based health-related quality of life instruments to derive utilities are not available.

An Updated Systematic Review of Studies Mapping (or Cross-Walking) Measures of Health-Related Quality of Life to Generic Preference-Based Measures to Generate Utility Values

BACKGROUND

Mapping is an increasingly common method used to predict instrument-specific preference-based health-state utility values (HSUVs) from data obtained from another health-related quality of life (HRQoL) measure. There have been several methodological developments in this area since a previous review up to 2007.

OBJECTIVE

To provide an updated review of all mapping studies that map from HRQoL measures to target generic preference-based measures (EQ-5D measures, SF-6D, HUI measures, QWB, AQoL measures, 15D/16D/17D, CHU-9D) published from January 2007 to October 2018.

DATA SOURCES

A systematic review of English language articles using a variety of approaches: searching electronic and utilities databases, citation searching, targeted journal and website searches.

STUDY SELECTION

Full papers of studies that mapped from one health measure to a target preference-based measure using formal statistical regression techniques.

DATA EXTRACTION

Undertaken by four authors using predefined data fields including measures, data used, econometric models and assessment of predictive ability.

RESULTS

There were 180 papers with 233 mapping functions in total. Mapping functions were generated to obtain EQ-5D-3L/EQ-5D-5L-EQ-5D-Y (n = 147), SF-6D (n = 45), AQoL-4D/AQoL-8D (n = 12), HUI2/HUI3 (n = 13), 15D (n = 8) CHU-9D (n = 4) and QWB-SA (n = 4) HSUVs. A large number of different regression methods were used with ordinary least squares (OLS) still being the most common approach (used ≥ 75% times within each preference-based measure). The majority of studies assessed the predictive ability of the mapping functions using mean absolute or root mean squared errors (n = 192, 82%), but this was lower when considering errors across different categories of severity (n = 92, 39%) and plots of predictions (n = 120, 52%).

CONCLUSIONS

The last 10 years has seen a substantial increase in the number of mapping studies and some evidence of advancement in methods with consideration of models beyond OLS and greater reporting of predictive ability of mapping functions.

Predicting EuroQoL 5 Dimensions 5 Levels (EQ-5D-5L) Utilities from Older People's Quality of Life Brief Questionnaire (OPQoL-Brief) Scores

BACKGROUND AND OBJECTIVE

Economic evaluation of healthcare treatment and services targeted at older people requires measurement of utility-based quality-of-life outcomes but it is not always possible to collect such outcome data. It may, however, be possible to estimate these outcomes using non-utility measures of quality of life where the latter have been collected. The objective of this study was to develop a regression-based algorithm to map a non-utility-based outcome, the Older People's Quality of Life brief questionnaire (OPQoL-brief), onto a utility-based outcome, the EuroQoL 5 Dimensions 5 Levels (EQ-5D-5L).

METHODS

The estimation sample comprised 330 community-based Australian older people (>65 years), while the validation sample consisted of 293 older people from a separate study. Six regression techniques were employed to estimate utilities from OPQoL-brief. The predictive accuracy of 54 regression models (six regression techniques × nine model specifications) was assessed using six criteria: mean absolute error (MAE), root mean squared error (RMSE), correlation, distribution of predicted utilities, distribution of residuals, and proportion of predictions with absolute errors <0.05.

RESULTS

The 54 regression models predicted EQ-5D-5L utilities that performed differently when assessed by the six criteria. However, best results were obtained from an ordinary least squares (OLS) model where all 13 OPQoL-brief items were included as continuous variables (OLS 4). RMSE and MAE estimates for this model (0.2201 and 0.1638, respectively) were within the range of published estimates.

CONCLUSIONS

It is possible to predict valid utilities from OPQoL-brief using regression methods. We recommend OLS model (4) for this exercise.

Predicting health-related quality of life (EQ-5D-5 L) and capability wellbeing (ICECAP-A) in the context of opiate dependence using routine clinical outcome measures: CORE-OM, LDQ and TOP

Background

Economic evaluation normally requires information to be collected on outcome improvement using utility values. This is often not collected during the treatment of substance use disorders making cost-effectiveness evaluations of therapy difficult. One potential solution is the use of mapping to generate utility values from clinical measures. This study develops and evaluates mapping algorithms that could be used to predict the EuroQol-5D (EQ-5D-5 L) and the ICEpop CAPability measure for Adults (ICECAP-A) from the three commonly used clinical measures; the CORE-OM, the LDQ and the TOP measures.

Methods

Models were estimated using pilot trial data of heroin users in opiate substitution treatment. In the trial the EQ-5D-5 L, ICECAP-A, CORE-OM, LDQ and TOP were administered at baseline, three and twelve month time intervals. Mapping was conducted using estimation and validation datasets. The normal estimation dataset, which comprised of baseline sample data, used ordinary least squares (OLS) and tobit regression methods. Data from the baseline and three month time periods were combined to create a pooled estimation dataset. Cluster and mixed regression methods were used to map from this dataset. Predictive accuracy of the models was assessed using the root mean square error (RMSE) and the mean absolute error (MAE). Algorithms were validated using sample data from the follow-up time periods.

Results

Mapping algorithms can be used to predict the ICECAP-A and the EQ-5D-5 L in the context of opiate dependence. Although both measures can be predicted, the ICECAP-A was better predicted by the clinical measures. There were no advantages of pooling the data. There were 6 chosen mapping algorithms, which had MAE scores ranging from 0.100 to 0.138 and RMSE scores ranging from 0.134 to 0.178.

Conclusion

It is possible to predict the scores of the ICECAP-A and the EQ-5D-5 L with the use of mapping. In the context of opiate dependence, these algorithms provide the possibility of generating utility values from clinical measures and thus enabling economic evaluation of alternative therapy options.

Trial registration

ISRCTN22608399. Date of registration: 27/04/2012. Date of first randomisation: 14/08/2012.

Electronic supplementary material

The online version of this article (10.1186/s12955-018-0926-7) contains supplementary material, which is available to authorized users.

Mapping CHU9D Utility Scores from the PedsQLTM 4.0 SF-15

BACKGROUND

The Pediatric Quality of Life Inventory™ 4.0 Short Form 15 Generic Core Scales (hereafter the PedsQL) and the Child Health Utility-9 Dimensions (CHU9D) are two generic instruments designed to measure health-related quality of life in children and adolescents in the general population and paediatric patient groups living with specific health conditions. Although the PedsQL is widely used among paediatric patient populations, presently it is not possible to directly use the scores from the instrument to calculate quality-adjusted life-years (QALYs) for application in economic evaluation because it produces summary scores which are not preference-based.

OBJECTIVE

This paper examines different econometric mapping techniques for estimating CHU9D utility scores from the PedsQL for the purpose of calculating QALYs for cost-utility analysis.

METHODS

The PedsQL and the CHU9D were completed by a community sample of 755 Australian adolescents aged 15-17 years. Seven regression models were estimated: ordinary least squares estimator, generalised linear model, robust MM estimator, multivariate factorial polynomial estimator, beta-binomial estimator, finite mixture model and multinomial logistic model. The mean absolute error (MAE) and the mean squared error (MSE) were used to assess predictive ability of the models.

RESULTS

The MM estimator with stepwise-selected PedsQL dimension scores as explanatory variables had the best predictive accuracy using MAE and the equivalent beta-binomial model had the best predictive accuracy using MSE.

CONCLUSIONS

Our mapping algorithm facilitates the estimation of health-state utilities for use within economic evaluations where only PedsQL data is available and is suitable for use in community-based adolescents aged 15-17 years. Applicability of the algorithm in younger populations should be assessed in further research.

Elective hospital admissions: secondary data analysis and modelling with an emphasis on policies to moderate growth

Background

The English NHS faces financial pressures that may render the growth rates of elective admissions seen between 2001/2 and 2011/12 unsustainable. A better understanding of admissions growth, and the influence of policy, are needed to minimise the impact on health gain for patients.

Objectives

This project had several objectives: (1) to better understand the determinants of elective activity and policy to moderate growth at minimum health loss for patients; (2) to build a rich data set integrating health, practice and local area data to study general practitioner (GP) referrals and resulting admissions; (3) to predict patients whose treatment is unlikely to be cost-effective using patient-reported outcomes and to examine variation in provider performance; and (4) to study how policies that aim to reduce elective admissions may change demand for emergency care. The main drivers of elective admissions growth have increased either supply of or demand for care, and could include, for example, technical innovations or increased awareness of treatment benefits. Of the factors studied, neither system reform nor population ageing appears to be a key driver. The introduction of the prospective payment tariff ‘Payment by Results’ appears to have led to primary care trusts (PCTs) having increasingly similar lengths of stay. In deprived areas, increasing GP supply appears to moderate elective admissions. Reducing the incidence of single-handed practices tends to reduce referrals and admissions. Policies to reduce referrals are likely to reduce admissions but treatments may be particularly reduced in the lowest referring practices, in which resulting health loss may be greatest. In this model, per full-time equivalent, female and highly experienced GPs identify more patients admitted by specialists.

Results

It appears from our studies that some patient characteristics are associated with not achieving sufficient patient gain to warrant cost-effective treatment. The introduction of independent sector treatment centres is estimated to have caused an increase in emergency activity rates at local PCTs. The explanations offered for increasing elective admissions indicate that they are manageable by health policy.

Conclusions

Further work is required to understand some of the results identified, such as whether or not high-volume Clinical Commissioning Groups are fulfilling unmet need; why some practices refer at low rates relative to admissions; why the period effect, which results from factors that equally affect all in the study at a point in time, dominates in the age–period–cohort analysis; and exactly how the emergency and elective sections of hospital treatment interact. This project relies on the analysis of secondary data. This type of research does not easily facilitate the important input of clinical experts or service users. It would be beneficial if other methods, including surveys and consultation with key stakeholders, could be incorporated into future research now that we have uncovered important questions.

Funding

The National Institute for Health Research Health Services and Delivery Research programme.

Mapping Between the Sydney Asthma Quality of Life Questionnaire (AQLQ-S) and Five Multi-Attribute Utility Instruments (MAUIs)

PURPOSE

Economic evaluation of health services commonly requires information regarding health-state utilities. Sometimes this information is not available but non-utility measures of quality of life may have been collected from which the required utilities can be estimated. This paper examines the possibility of mapping a non-utility-based outcome, the Sydney Asthma Quality of Life Questionnaire (AQLQ-S), onto five multi-attribute utility instruments: Assessment of Quality of Life 8 Dimensions (AQoL-8D), EuroQoL 5 Dimensions 5-Level (EQ-5D-5L), Health Utilities Index Mark 3 (HUI3), 15 Dimensions (15D), and the Short-Form 6 Dimensions (SF-6D).

METHODS

Data for 856 individuals with asthma were obtained from a large Multi-Instrument Comparison (MIC) survey. Four statistical techniques were employed to estimate utilities from the AQLQ-S. The predictive accuracy of 180 regression models was assessed using six criteria: mean absolute error (MAE), root mean squared error (RMSE), correlation, distribution of predicted utilities, distribution of residuals, and proportion of predictions with absolute errors <0.0.5. Validation of initial 'primary' models was carried out on a random sample of the MIC data.

RESULTS

Best results were obtained with non-linear models that included a quadratic term for the AQLQ-S score along with demographic variables. The four statistical techniques predicted models that performed differently when assessed by the six criteria; however, the best results, for both the estimation and validation samples, were obtained using a generalised linear model (GLM estimator).

CONCLUSIONS

It is possible to predict valid utilities from the AQLQ-S using regression methods. We recommend GLM models for this exercise.

Clinical improvement and satisfaction after total joint replacement: a prospective 12-month evaluation on the patients' perspective

PURPOSE

To determine short-term improvements, satisfaction rates and the patient acceptable symptom state (PASS) after total joint replacement (TJR) for different patient-reported outcome measures (PROMs).

METHODS

This prospective cohort study included 426 consecutive patients undergoing total hip (n = 193) or knee arthroplasty (n = 233). The following PROMs were completed before TJR, and at 3, 6 and 12 months after surgery, respectively: WOMAC, Oxford Hip or Knee Score, Lower Extremity Functional Scale, University of California at Los Angeles (UCLA) activity scale and EuroQol-5 dimension (EQ-5D). Satisfaction rates and the PASS thresholds were also assessed.

RESULTS

THA patients improved quicker and achieved higher outcome scores than TKA patients. Comorbidities according to the Sangha score were moderately correlated with all PROM values in an inverse direction at all time points (r = -0.27 to -0.47, p < 0.01) in both groups. Satisfaction with the result of surgery improved over time. At 12 months, more than 90 % of the patients were satisfied or very satisfied with the achieved result. The THA group showed a higher proportion of very satisfied patients than the TKA group at all time points. PASS thresholds increased over time for all PROMs except for the UCLA and the EQ-5D in TKA patients.

CONCLUSIONS

More than 90 % of the patients will be satisfied 1 year after TJR. THA patients recover faster than TKA patients, i.e., they achieve higher PROM values at earlier follow-up time points. Cutoff values defining a successful result in terms of the PASS could be defined for all PROMs at different time points and can serve as reference for future studies and patient-oriented follow-ups.

Comparison of pre- and post-operative health-related quality of life and length of stay after primary total hip replacement in matched English and German patient cohorts

PURPOSE

We compare pre- and post-operative health-related quality of life (HRQoL) and length of stay after total hip replacement (THR) in matched German and English patient cohorts to test for differences in admission thresholds, clinical effectiveness and resource utilisation between the healthcare systems.

METHODS

German data (n = 271) were collected in a large orthopaedic hospital in Munich, Germany; English data (n = 26,254) were collected as part of the national patient-reported outcome measures programme. HRQoL was measured using the EuroQoL-5D instrument. Propensity score matching was used to construct two patient cohorts that are comparable in terms of preoperative patient characteristics.

RESULTS

Before matching, patients in England showed lower preoperative EQ-5D scores (0.35 vs 0.52, p < 0.001) and experienced a larger improvement in HRQoL (0.43 vs 0.33, p < 0.001) than German patients. Patients in the German cohort were more likely to report no or only moderate problems with mobility and pain preoperatively than their English counterparts. After matching, improvements in HRQoL were comparable (0.32 vs 0.33, p = 0.638); post-operative scores were slightly higher in the German cohort (0.82 vs 0.85, p = 0.585). Length of stay was substantially lower in England than in Germany (4.5 vs 9.0 days, p < 0.001).

CONCLUSIONS

Our results highlight differences in preoperative health status between countries, which may arise due to different admission thresholds and access to surgery. In terms of quality of life, THR surgery is equally effective in both countries when performed on similar patients, but hospital stay is shorter in England.

Mapping EQ-5D utility scores from the PedsQL™ generic core scales

PURPOSE

The Pediatric Quality of Life Inventory™ (PedsQL™) General Core Scales (GCS) were designed to provide a modular approach to measuring health-related quality of life in healthy children, as well as those with acute and chronic health conditions, across the broadest, empirically feasible, age groups (2-18 years). Currently, it is not possible to estimate health utilities based on the PedsQL™ GCS, either directly or indirectly. This paper assesses different mapping methods for estimating EQ-5D health utilities from PedsQL™ GCS responses.

METHODS

This study is based on data from a cross-sectional survey conducted in four secondary schools in England amongst children aged 11-15 years. We estimate models using both direct and response mapping approaches to predict EQ-5D health utilities and responses. The mean squared error (MSE) and mean absolute error (MAE) were used to assess the predictive accuracy of the models. The models were internally validated on an estimation dataset that included complete PedsQL™ GCS and EQ-5D scores for 559 respondents. Validation was also performed making use of separate data for 337 respondents.

RESULTS

Ordinary least squares (OLS) models that used the PedsQL™ GCS subscale scores, their squared terms and interactions (with and without age and gender) to predict EQ-5D health utilities had the best prediction accuracy. In the external validation sample, the OLS model with age and gender had a MSE (MAE) of 0.036 (0.115) compared with a MSE (MAE) of 0.036 (0.114) for the OLS model without age and gender. However, both models generated higher prediction errors for children in poorer health states (EQ-5D utility score <0.6). The response mapping models encountered some estimation problems because of insufficient data for some of the response levels.

CONCLUSION

Our mapping algorithms provide an empirical basis for estimating health utilities in childhood when EQ-5D data are not available; they can be used to inform future economic evaluations of paediatric interventions. They are likely to be robust for populations comparable to our own (children aged 11-15 years in attendance at secondary school). The performance of these algorithms in childhood populations, which differ according to age or clinical characteristics to our own, remains to be evaluated.

A reference case for economic evaluations in osteoarthritis: an expert consensus article from the European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis (ESCEO)

BACKGROUND

General recommendations for a reference case for economic studies in rheumatic diseases were published in 2002 in an initiative to improve the comparability of cost-effectiveness studies in the field. Since then, economic evaluations in osteoarthritis (OA) continue to show considerable heterogeneity in methodological approach.

OBJECTIVES

To develop a reference case specific for economic studies in OA, including the standard optimal care, with which to judge new pharmacologic and non-pharmacologic interventions.

METHODS

Four subgroups of an ESCEO expert working group on economic assessments (13 experts representing diverse aspects of clinical research and/or economic evaluations) were charged with producing lists of recommendations that would potentially improve the comparability of economic analyses in OA: outcome measures, comparators, costs and methodology. These proposals were discussed and refined during a face-to-face meeting in 2013. They are presented here in the format of the recommendations of the recently published Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement, so that an initiative on economic analysis methodology might be consolidated with an initiative on reporting standards.

RESULTS

Overall, three distinct reference cases are proposed, one for each hand, knee and hip OA; with diagnostic variations in the first two, giving rise to different treatment options: interphalangeal or thumb-based disease for hand OA and the presence or absence of joint malalignment for knee OA. A set of management strategies is proposed, which should be further evaluated to help establish a consensus on the "standard optimal care" in each proposed reference case. The recommendations on outcome measures, cost itemisation and methodological approaches are also provided.

CONCLUSIONS

The ESCEO group proposes a set of disease-specific recommendations on the conduct and reporting of economic evaluations in OA that could help the standardisation and comparability of studies that evaluate therapeutic strategies of OA in terms of costs and effectiveness.

Outcome assessment after hip fracture: is EQ-5D the answer?

Objectives

To study the measurement properties of a joint specific patient reported outcome measure, a measure of capability and a general health-related quality of life (HRQOL) tool in a large cohort of patients with a hip fracture.

Methods

Responsiveness and associations between the Oxford Hip Score (a hip specific measure: OHS), ICEpop CAPability (a measure of capability in older people: ICECAP-O) and EuroQol EQ-5D (general health-related quality of life measure: EQ-5D) were assessed using data available from two large prospective studies. The three outcome measures were assessed concurrently at a number of fixed follow-up time-points in a consecutive sequence of patients, allowing direct assessment of change from baseline, inter-measure associations and validity using a range of statistical methods.

Results

ICECAP-O was not responsive to change. EQ-5D was responsive to change from baseline, with an estimated standardised effect size for the two datasets of 0.676 and 0.644 at six weeks and four weeks respectively; this was almost as responsive to change as OHS (1.14 at four weeks). EQ-5D correlated strongly with OHS; Pearson correlation coefficients were 0.74, 0.77 and 0.70 at baseline, four weeks and four months. EQ-5D is a moderately good predictor of death at 12 months following hip fracture. Furthermore, EQ-5D reported by proxies (relatives and carers) behaves similarly to self-reported scores.

Conclusions

Our findings suggest that a general HRQOL tool such as EQ-5D could be used to measure outcome for patients recovering from hip fracture, including those with cognitive impairment.

Cite this article: Bone Joint Res 2014;3:69–75.

Body mass index is not a clinically meaningful predictor of patient reported outcomes of primary hip replacement surgery: prospective cohort study

OBJECTIVES

To describe whether body mass index (BMI) is a clinically meaningful predictor of patient reported outcomes following primary total hip replacement (THR) surgery.

DESIGN

Combined data from prospective cohort studies. We obtained information from four cohorts of patients receiving primary THR for osteoarthritis: Exeter Primary Outcomes Study (EPOS) (n = 1431); EUROHIP (n = 1327); Elective Orthopaedic Centre (n = 2832); and St. Helier (n = 787). The exposure of interest was pre-operative BMI. Confounding variables included: age, sex, SF-36 mental health, comorbidities, fixed flexion, analgesic use, college education, OA in other joints, expectation of less pain, radiographic K&L grade, ASA grade, years of hip pain. The primary outcome was the Oxford Hip Score (OHS). Regression models describe the association of BMI on outcome adjusting for all confounders.

RESULTS

For a 5-unit increase in BMI, the attained 12-month OHS decreases by 0.78 points 95%CI (0.27-1.28), P-value 0.001. Compared to people of normal BMI (20-25), those in the obese class II (BMI 35-40) would have a 12-month OHS that is 2.34 points lower. Although statistically significant this effect is small and not clinically meaningful in contrast to the substantial change in OHS seen across all BMI groupings. In obese class II patients achieved a 22.2 point change in OHS following surgery.

CONCLUSIONS

Patients achieved substantial change in OHS after THR across all BMI categories, which greatly outweighs the small difference in attained post-operative score. The findings suggest BMI should not present a barrier to access THR in terms of PROMs.

A comparison of direct and indirect methods for the estimation of health utilities from clinical outcomes

BACKGROUND

Analysts frequently estimate health state utility values from other outcomes. Utility values like EQ-5D have characteristics that make standard statistical methods inappropriate. We have developed a bespoke, mixture model approach to directly estimate EQ-5D. An indirect method, "response mapping," first estimates the level on each of the 5 dimensions of the EQ-5D and then calculates the expected tariff score. These methods have never previously been compared.

METHODS

We use a large observational database from patients with rheumatoid arthritis (N = 100,398). Direct estimation of UK EQ-5D scores as a function of the Health Assessment Questionnaire (HAQ), pain, and age was performed with a limited dependent variable mixture model. Indirect modeling was undertaken with a set of generalized ordered probit models with expected tariff scores calculated mathematically. Linear regression was reported for comparison purposes. Impact on cost-effectiveness was demonstrated with an existing model.

RESULTS

The linear model fits poorly, particularly at the extremes of the distribution. The bespoke mixture model and the indirect approaches improve fit over the entire range of EQ-5D. Mean average error is 10% and 5% lower compared with the linear model, respectively. Root mean squared error is 3% and 2% lower. The mixture model demonstrates superior performance to the indirect method across almost the entire range of pain and HAQ. These lead to differences in cost-effectiveness of up to 20%.

CONCLUSIONS

There are limited data from patients in the most severe HAQ health states. Modeling of EQ-5D from clinical measures is best performed directly using the bespoke mixture model. This substantially outperforms the indirect method in this example. Linear models are inappropriate, suffer from systematic bias, and generate values outside the feasible range.

Review of studies mapping from quality of life or clinical measures to EQ-5D: an online database

Systematic literature searches were conducted to identify studies that conducted statistical mapping to predict EQ-5D utilities or responses from any source instrument and reported the estimated algorithms in sufficient detail to allow other researchers to use them to predict EQ-5D in other studies. Ninety studies reporting 121 mapping algorithms met the inclusion criteria. The studies estimated EQ-5D utilities from 80 source instruments. All but two studies included direct utility mapping to predict EQ-5D utilities, while 20 studies (22%) conducted response mapping to predict responses to each EQ-5D domain. Seventy-two studies (80%) explored ordinary least squares regression and 16 (18%) used censored least absolute deviations (CLAD) models. The details of the studies identified are made available in an online database, which will be updated regularly to enable researchers to easily identify studies that can help them to estimate utilities for economic evaluation.