What do national pharmacoeconomic guidelines recommend regarding the statistical analysis of trial-based economic evaluations?

Cost-effectiveness of Transforaminal epidural steroid injections for patients with ACUTE sciatica: a randomized controlled trial

BACKGROUND

Transforaminal epidural injections with steroids (TESI) are increasingly being used in patients sciatica. The STAR (steroids against radiculopathy)-trial aimed to evaluate the (cost-) effectiveness of TESI in patients with acute sciatica (< 8 weeks). This article contains the economic evaluation of the STAR-trial.

METHODS

Participants were randomized to one of three study arms: Usual Care (UC), that is oral pain medication with or without physiotherapy, n = 45); intervention group 1: UC and transforaminal epidural steroid injection (TESI) 1 ml of 0.5% Levobupivacaine and 1 ml of 40 mg/ml Methylprednisolone and intervention group 2: UC and transforaminal epidural injection (TEI) with 1 ml of 0,5% Levobupivacaine and 1 ml of 0.9% NaCl (n = 50). The primary effect measure was health-related quality of life. Secondary outcomes were pain, functioning, and recovery. Costs were measured from a societal perspective, meaning that all costs were included, irrespective of who paid or benefited. Missing data were imputed using multiple imputation, and bootstrapping was used to estimate statistical uncertainty.

RESULTS

None of the between-group differences in effects were statistically significant for any of the outcomes (QALY, back pain, leg pain, functioning, and global perceived effect) at the 26-weeks follow-up. The adjusted mean difference in total societal costs was €1718 (95% confidence interval [CI]: - 3020 to 6052) for comparison 1 (intervention group 1 versus usual care), €1640 (95%CI: - 3354 to 6106) for comparison 2 (intervention group 1 versus intervention group 2), and €770 (95%CI: - 3758 to 5702) for comparison 3 (intervention group 2 versus usual care). Except for the intervention costs, none of the aggregate and disaggregate cost differences were statistically significant. The maximum probability of all interventions being cost-effective compared to the control was low (< 0.7) for all effect measures.

CONCLUSION

These results suggest that adding TESI (or TEI) to usual care is not cost-effective compared to usual care in patients with acute sciatica (< 8 weeks) from a societal perspective in a Dutch healthcare setting.

TRIAL REGISTRATION

Dutch National trial register: NTR4457 (March, 6th, 2014).

Handling Missing Data in Health Economics and Outcomes Research (HEOR): A Systematic Review and Practical Recommendations

BACKGROUND

Missing data in costs and/or health outcomes and in confounding variables can create bias in the inference of health economics and outcomes research studies, which in turn can lead to inappropriate policies. Most of the literature focuses on handling missing data in randomized controlled trials, which are not necessarily always the data used in health economics and outcomes research.

OBJECTIVES

We aimed to provide an overview on missing data issues and how to address incomplete data and report the findings of a systematic literature review of methods used to deal with missing data in health economics and outcomes research studies that focused on cost, utility, and patient-reported outcomes.

METHODS

A systematic search of papers published in English language until the end of the year 2020 was carried out in PubMed. Studies using statistical methods to handle missing data for analyses of cost, utility, or patient-reported outcome data were included, as were reviews and guidance papers on handling missing data for those outcomes. The data extraction was conducted with a focus on the context of the study, the type of missing data, and the methods used to tackle missing data.

RESULTS

From 1433 identified records, 40 papers were included. Thirteen studies were economic evaluations. Thirty studies used multiple imputation with 17 studies using multiple imputation by chained equation, while 15 studies used a complete-case analysis. Seventeen studies addressed missing cost data and 23 studies dealt with missing outcome data. Eleven studies reported a single method while 20 studies used multiple methods to address missing data.

CONCLUSIONS

Several health economics and outcomes research studies did not offer a justification of their approach of handling missing data and some used only a single method without a sensitivity analysis. This systematic literature review highlights the importance of considering the missingness mechanism and including sensitivity analyses when planning, analyzing, and reporting health economics and outcomes research studies.

Conducting Trial-Based Economic Evaluations Using R: A Tutorial

Trial-based economic evaluations are increasingly being conducted to support healthcare decision-making. When analysing trial-based economic evaluation data, different methodological challenges may be encountered, including (i) missing data, (ii) correlated costs and effects, (iii) baseline imbalances and (iv) skewness of costs and/or effects. Despite the broad range of methods available to account for these methodological challenges in effectiveness studies, they may not always be directly applicable in trial-based economic evaluations where costs and effects are analysed jointly, and more than one methodological challenge typically needs to be addressed simultaneously. The use of inappropriate methods can bias results and conclusions regarding the cost-effectiveness of healthcare interventions. Eventually, such low-quality evidence can hamper healthcare decision-making, which may in turn result in a waste of already scarce healthcare resources. Therefore, this tutorial aims to provide step-by-step guidance on how to combine appropriate statistical methods for handling the abovementioned methodological challenges using a ready-to-use R script. The theoretical background of the described methods is provided, and their application is illustrated using a simulated trial-based economic evaluation.

A scoping review of statistical methods for trial-based economic evaluations: The current state of play

The statistical quality of trial-based economic evaluations is often suboptimal, while a comprehensive overview of available statistical methods is lacking. Therefore, this review summarized and critically appraised available statistical methods for trial-based economic evaluations. A literature search was performed to identify studies on statistical methods for dealing with baseline imbalances, skewed costs and/or effects, correlated costs and effects, clustered data, longitudinal data, missing data and censoring in trial-based economic evaluations. Data was extracted on the statistical methods described, their advantages, disadvantages, relative performance and recommendations of the study. Sixty-eight studies were included. Of them, 27 (40%) assessed methods for baseline imbalances, 39 (57%) assessed methods for skewed costs and/or effects, 27 (40%) assessed methods for correlated costs and effects, 18 (26%) assessed methods for clustered data, 7 (10%) assessed methods for longitudinal data, 26 (38%) assessed methods for missing data and 10 (15%) assessed methods for censoring. All identified methods were narratively described. This review provides a comprehensive overview of available statistical methods for dealing with the most common statistical complexities in trial-based economic evaluations. Herewith, it can provide valuable input for researchers when deciding which statistical methods to use in a trial-based economic evaluation.

Cost transferability problems in economic evaluation as a framework for an European health care and social costs database

This article presents part of the work within Work Package 3 (WP3) of Impact HTA (Improved methods and actionable tools for enhancing HTA), a H2020 EU-funded research project, intended to enhance and promote collaboration in HTA across EU MS. Amongst other objectives, and in close collaboration with WP4, WP3 addressed setting up a multi-country unit-cost database: the European health care and social costs database (EU HCSCD). The purpose of the database is to facilitate the transference of healthcare economic evaluation analyses across countries, jurisdictions and settings. WP3 concentrates on healthcare costs; WP4 on social costs. This paper discusses the state of the art on this topic, building an appropriate conceptual and theoretical framework for Database development. We conducted a broad, but not systematic, literature and gray-literature review (LR), identifying existing practices and problems, and their implications, described in the Results section. We discuss practical implications and draw important conclusions behind the construction, and future evolution, of this database.

The statistical approach in trial-based economic evaluations matters: get your statistics together!

Background

Baseline imbalances, skewed costs, the correlation between costs and effects, and missing data are statistical challenges that are often not adequately accounted for in the analysis of cost-effectiveness data. This study aims to illustrate the impact of accounting for these statistical challenges in trial-based economic evaluations.

Methods

Data from two trial-based economic evaluations, the REALISE and HypoAware studies, were used. In total, 14 full cost-effectiveness analyses were performed per study, in which the four statistical challenges in trial-based economic evaluations were taken into account step-by-step. Statistical approaches were compared in terms of the resulting cost and effect differences, ICERs, and probabilities of cost-effectiveness.

Results

In the REALISE study and HypoAware study, the ICER ranged from 636,744€/QALY and 90,989€/QALY when ignoring all statistical challenges to − 7502€/QALY and 46,592€/QALY when accounting for all statistical challenges, respectively. The probabilities of the intervention being cost-effective at 0€/ QALY gained were 0.67 and 0.59 when ignoring all statistical challenges, and 0.54 and 0.27 when all of the statistical challenges were taken into account for the REALISE study and HypoAware study, respectively.

Conclusions

Not accounting for baseline imbalances, skewed costs, correlated costs and effects, and missing data in trial-based economic evaluations may notably impact results. Therefore, when conducting trial-based economic evaluations, it is important to align the statistical approach with the identified statistical challenges in cost-effectiveness data. To facilitate researchers in handling statistical challenges in trial-based economic evaluations, software code is provided.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06513-1.

Taking the Analysis of Trial-Based Economic Evaluations to the Next Level: The Importance of Accounting for Clustering

OBJECTIVES

The aim of this study was to assess the performance and impact of multilevel modelling (MLM) compared with ordinary least squares (OLS) regression in trial-based economic evaluations with clustered data.

METHODS

Three thousand datasets with balanced and unbalanced clusters were simulated with correlation coefficients between costs and effects of - 0.5, 0, and 0.5, and intraclass correlation coefficients (ICCs) varying between 0.05 and 0.30. Each scenario was analyzed using both MLM and OLS. Statistical uncertainty around MLM and OLS estimates was estimated using bootstrapping. Performance measures were estimated and compared between approaches, including bias, root mean squared error (RMSE) and coverage probability. Cost and effect differences, and their corresponding confidence intervals and standard errors, incremental cost-effectiveness ratios, incremental net-monetary benefits and cost-effectiveness acceptability curves were compared.

RESULTS

Cost-effectiveness outcomes were similar between OLS and MLM. MLM produced larger statistical uncertainty and coverage probabilities closer to nominal levels than OLS. The higher the ICC, the larger the effect on statistical uncertainty between MLM and OLS. Significant cost-effectiveness outcomes as estimated by OLS became non-significant when estimated by MLM. At all ICCs, MLM resulted in lower probabilities of cost effectiveness than OLS, and this difference became larger with increasing ICCs. Performance measures and cost-effectiveness outcomes were similar across scenarios with varying correlation coefficients between costs and effects.

CONCLUSIONS

Although OLS produced similar cost-effectiveness outcomes, it substantially underestimated the amount of variation in the data compared with MLM. To prevent suboptimal conclusions and a possible waste of scarce resources, it is important to use MLM in trial-based economic evaluations when data are clustered.

Evaluation of quality of pharmacoeconomic studies involved in traditional Chinese medicine in China

OBJECTIVES

The pharmacoeconomic studies of traditional Chinese medicine (TCM) are still in its infancy. Assessing the quality of pharmacoeconomic studies of TCM to improve the efficiency of health resource allocation and guide the rational use of medicine.

METHODS

Four databases were searched from inception to January 2018. The Consolidated Health Economic Evaluation Reporting Standards statement (CHEERS) and the Quality of Health Economic Studies (QHES) were used to assess the reporting quality and methodological quality. STATA 12.0 and Meta analyst 3.13 were used to analyze the related data.

RESULTS

A total of 178 studies were included. The methodological evaluation of the study found that the total score of QHES was 47.85 ± 8.09. The report quality evaluation results found that many studies did not report comprehensive information, such as lack of detailed reports on abstracts, study perspectives, time frames, discount rates, model selection, but the titles, study background and location, and health results, resource and cost estimates, analysis methods, and heterogeneity analysis are reported in more detail. Six of the ten stratification factors have statistically significant differences.

CONCLUSION

The overall quality of pharmacoeconomic studies of TCM is low, and further standardization and improvement are needed to obtain reliable study results.