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.

No evidence for stratified exercise therapy being cost-effective compared to usual exercise therapy in patients with knee osteoarthritis: Economic evaluation alongside cluster randomized controlled trial.

BACKGROUND: A stratified approach to exercise therapy may yield superior clinical and economic outcomes, given the large heterogeneity of individuals with knee osteoarthritis (OA). OBJECTIVE: To evaluate the cost-effectiveness during a 12-month follow-up of a model of stratified exercise therapy compared to usual exercise therapy in patients with knee OA, from a societal and healthcare perspective. METHODS: An economic evaluation was conducted alongside a cluster-randomized controlled trial in patients with knee OA (n = 335), comparing subgroup-specific exercise therapy for a 'high muscle strength subgroup', 'low muscle strength subgroup', and 'obesity subgroup' supplemented by a dietary intervention for the 'obesity subgroup' (experimental group), with usual ('non-stratified') exercise therapy (control group). Clinical outcomes included quality-adjusted life years - QALYs (EuroQol-5D-5 L), knee pain (Numerical Rating Scale) and physical functioning (Knee Injury and Osteoarthritis Outcome Score in daily living). Costs were measured by self-reported questionnaires at 3, 6, 9 and 12-month follow-up. Missing data were imputed using multiple imputation. Data were analyzed through linear regression. Bootstrapping techniques were applied to estimate statistical uncertainty. RESULTS: During 12-month follow-up, there were no significant between-group differences in clinical outcomes. The total societal costs of the experimental group were on average lower compared to the control group (mean [95% confidence interval]: € 405 [-1728, 918]), albeit with a high level of uncertainty. We found a negligible difference in QALYs between groups (mean [95% confidence interval]: 0.006 [-0.011, 0.023]). The probability of stratified exercise therapy being cost-effective compared to usual exercise therapy from the societal perspective was around 73%, regardless of the willingness-to-pay threshold. However, this probability decreased substantially to 50% (willingness-to-pay threshold of €20.000/QALY) when using the healthcare perspective. Similar results were found for knee pain and physical functioning. CONCLUSIONS: We found no clear evidence that stratified exercise therapy is likely to be cost-effective compared to usual exercise therapy in patients with knee OA. However, results should be interpreted with caution as the study power was lower than intended, due to the Coronavirus disease (COVID-19) pandemic.

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.