Deterministic and Probabilistic Analysis of a Simple Markov Model: How Different Could They Be?

Evaluating the Long-Term Cost-Effectiveness of the English NHS Diabetes Prevention Programme using a Markov Model

BACKGROUND

In 2016, England launched the largest nationwide diabetes mellitus prevention programme, the NHS Diabetes Prevention Programme (NHS DPP). This paper seeks to evaluate the long-term cost-effectiveness of this programme.

METHODS

A Markov cohort state transition model was developed with a 35-year time horizon and yearly cycles to compare referral to the NHS DPP to usual care for individuals with non-diabetic hyperglycaemia. The modelled cohort of individuals mirrored the age profile of referrals received by the programme by April 2020. A health system perspective was taken, with costs in UK £ Sterling (price year 2020) and outcomes in terms of quality-adjusted life-years (QALYs). Probabilistic analysis with 10,000 Monte Carlo simulations was used. Several sensitivity analyses were conducted to explore the uncertainty surrounding the base case results, particularly varying the length of time for which the effectiveness of the programme was expected to last.

RESULTS

In the base case, using only the observed effectiveness of the NHS DPP at 3 years, it was found that the programme is likely to dominate usual care, by generating on average 40.8 incremental QALYs whilst saving £135,755 in costs for a cohort of 1000. At a willingness to pay of £20,000 per QALY, 98.1% of simulations were on or under the willingness-to-pay threshold. Scaling this up to the number of referrals actually received by the NHS DPP prior to April 2020, cost savings of £71.4 million were estimated over the 35-year time horizon and an additional 21,472 QALYs generated. These results are robust to several sensitivity analyses.

CONCLUSION

The NHS DPP is likely to be cost-effective. Indeed, in the majority of the simulations, the NHS DPP was cost-saving and generated greater QALYs, dominating usual care. This research should serve as evidence to support the continued investment or recommissioning of diabetes prevention programmes.

Identifying the Optimum Strategy for Identifying Adults and Children With Celiac Disease: A Cost-Effectiveness and Value of Information Analysis

OBJECTIVES

Celiac disease (CD) is thought to affect around 1% of people in the United Kingdom, but only approximately 30% are diagnosed. The aim of this work was to assess the cost-effectiveness of strategies for identifying adults and children with CD in terms of who to test and which tests to use.

METHODS

A decision tree and Markov model were used to describe testing strategies and model long-term consequences of CD. The analysis compared a selection of pre-test probabilities of CD above which patients should be screened, as well as the use of different serological tests, with or without genetic testing. Value of information analysis was used to prioritize parameters for future research.

RESULTS

Using serological testing alone in adults, immunoglobulin A (IgA) tissue transglutaminase (tTG) at a 1% pre-test probability (equivalent to population screening) was most cost-effective. If combining serological testing with genetic testing, human leukocyte antigen combined with IgA tTG at a 5% pre-test probability was most cost-effective. In children, the most cost-effective strategy was a 10% pre-test probability with human leukocyte antigen plus IgA tTG. Value of information analysis highlighted the probability of late diagnosis of CD and the accuracy of serological tests as important parameters. The analysis also suggested prioritizing research in adult women over adult men or children.

CONCLUSIONS

For adults, these cost-effectiveness results suggest UK National Screening Committee Criteria for population-based screening for CD should be explored. Substantial uncertainty in the results indicate a high value in conducting further research.

Improved estimation of overall survival and progression-free survival for state transition modeling

Aim: National Institute for Health and Care Excellence guidance (Technical Support Document 19) highlights a key challenge of state transition models (STMs) being their difficulty in achieving a satisfactory fit to the observed within-trial endpoints. Fitting poorly to data over the trial period can then have implications for long-term extrapolations. A novel estimation approach is defined in which the predicted overall survival (OS) and progression-free survival (PFS) extrapolations from an STM are optimized to provide closer estimates of the within-trial endpoints. Materials & methods: An STM was fitted to the SQUIRE trial data in non-small-cell lung cancer (obtained from Project Data Sphere). Two methods were used: a standard approach whereby the maximum likelihood was utilized for the individual transitions and the best-fitting parametric model selected based on AIC/BIC, and a novel approach in which parameters were optimized by minimizing the area between the STM-predicted OS and PFS curves and the corresponding OS and PFS Kaplan-Meier curves. Sensitivity analyses were conducted to assess uncertainty. Results: The novel approach resulted in closer estimations to the OS and PFS Kaplan-Meier for all combinations of parametric distributions analyzed compared with the standard approach. Though the uncertainty associated with the novel approach was slightly larger, it provided better estimates to the restricted mean survival time in 10 of the 12 parametric distributions analyzed. Conclusion: A novel approach is defined which provides an alternative STM estimation method enabling improved fits to modeled endpoints, which can easily be extended to more complex model structures.

The cost-effectiveness of a bimekizumab versus IL-17A inhibitors treatment-pathway in patients with active axial spondyloarthritis in Scotland

OBJECTIVE

To estimate the cost-effectiveness of a treatment-pathway initiated with bimekizumab, a monoclonal IgG1 antibody that selectively inhibits interleukin (IL)-17F and IL-17A, in patients with axial spondyloarthritis (axSpA) compared with IL-17Ai's, ixekizumab, and secukinumab, from the NHS Scotland perspective.

METHODS

The axSpA treatment-pathway was modeled using a decision tree followed by a lifetime Markov model. The pathway included first- and second-line biologic disease-modifying antirheumatic drugs (bDMARD), followed by best supportive care (bDMARD, nonbiologic). Bimekizumab followed by any bDMARD ("BKZ") was compared with IL-17Ai's: secukinumab 150 mg followed by a blend ("SEC") of dose up-titration to secukinumab 300 mg and any bDMARD, or ixekizumab followed by any bDMARD ("IXE"). Transition to the next therapy was triggered by Bath Ankylosing Spondylitis Disease Activity Index-50% (BASDAI50) non-response or any-cause discontinuation. A published network meta-analysis provided efficacy data. EuroQoL-5-dimensions utilities were derived by mapping from Ankylosing Spondylitis Disease Activity Score. Costs included disease management (linked to functional limitations), biologics acquisition (list prices), administration and monitoring (NHS 2021/22). Discounting was 3.5%/year. Probabilistic results from patients with non-radiographic axSpA and ankylosing spondylitis were averaged to reflect the axSpA disease spectrum. Scenario and sensitivity analyses were performed.

RESULTS

The incremental cost-effectiveness ratio (ICER) of BKZ was £24,801/quality-adjusted life-year (QALY) vs. SEC (95% credible interval £24,163-£25,895). BKZ had similar costs (Δ -£385 [-£15,239-£14,468]) and QALYs (Δ 0.039 [-0.748-0.825]) to IXE, with £1,523 (£862-£2,222) net monetary benefit. Conclusions remained unchanged in most scenarios. Results' drivers included BASDAI50 response rate and disease management cost.

LIMITATIONS

Results were based on list prices. Data concerning up-titration to secukinumab 300 mg was scarce.

CONCLUSIONS

The bimekizumab treatment-pathway represents a cost-effective option across the axSpA disease spectrum in Scotland. Bimekizumab is cost-effective compared to a secukinumab-pathway that includes dose up-titration, and has similar costs and QALYs to an ixekizumab-pathway.

Economic Evaluation of Digital Therapeutic Care Apps for Unsupervised Treatment of Low Back Pain: Monte Carlo Simulation

BACKGROUND

Digital therapeutic care (DTC) programs are unsupervised app-based treatments that provide video exercises and educational material to patients with nonspecific low back pain during episodes of pain and functional disability. German statutory health insurance can reimburse DTC programs since 2019, but evidence on efficacy and reasonable pricing remains scarce. This paper presents a probabilistic sensitivity analysis (PSA) to evaluate the efficacy and cost-utility of a DTC app against treatment as usual (TAU) in Germany.

OBJECTIVE

The aim of this study was to perform a PSA in the form of a Monte Carlo simulation based on the deterministic base case analysis to account for model assumptions and parameter uncertainty. We also intend to explore to what extent the results in this probabilistic analysis differ from the results in the base case analysis and to what extent a shortage of outcome data concerning quality-of-life (QoL) metrics impacts the overall results.

METHODS

The PSA builds upon a state-transition Markov chain with a 4-week cycle length over a model time horizon of 3 years from a recently published deterministic cost-utility analysis. A Monte Carlo simulation with 10,000 iterations and a cohort size of 10,000 was employed to evaluate the cost-utility from a societal perspective. Quality-adjusted life years (QALYs) were derived from Veterans RAND 6-Dimension (VR-6D) and Short-Form 6-Dimension (SF-6D) single utility scores. Finally, we also simulated reducing the price for a 3-month app prescription to analyze at which price threshold DTC would result in being the dominant strategy over TAU in Germany.

RESULTS

The Monte Carlo simulation yielded on average a €135.97 (a currency exchange rate of EUR €1=US $1.069 is applicable) incremental cost and 0.004 incremental QALYs per person and year for the unsupervised DTC app strategy compared to in-person physiotherapy in Germany. The corresponding incremental cost-utility ratio (ICUR) amounts to an additional €34,315.19 per additional QALY. DTC yielded more QALYs in 54.96% of the iterations. DTC dominates TAU in 24.04% of the iterations for QALYs. Reducing the app price in the simulation from currently €239.96 to €164.61 for a 3-month prescription could yield a negative ICUR and thus make DTC the dominant strategy, even though the estimated probability of DTC being more effective than TAU is only 54.96%.

CONCLUSIONS

Decision-makers should be cautious when considering the reimbursement of DTC apps since no significant treatment effect was found, and the probability of cost-effectiveness remains below 60% even for an infinite willingness-to-pay threshold. More app-based studies involving the utilization of QoL outcome parameters are urgently needed to account for the low and limited precision of the available QoL input parameters, which are crucial to making profound recommendations concerning the cost-utility of novel apps.

Cost-effectiveness analysis of cabozantinib compared with everolimus, axitinib, and nivolumab in subsequent line advanced renal cell carcinoma in Japan

AIMS

The treatment landscape of renal cell carcinoma has changed with the introduction of targeted therapies. While the clinical benefit of cabozantinib is well-established for Japanese patients who have received prior treatment, the economic benefit remains unclear. The objective of this study was to assess the cost-effectiveness of cabozantinib compared with everolimus, axitinib, and nivolumab in patients with advanced renal cell carcinoma who have failed at least one prior therapy in Japan.

METHODS

A cost-effectiveness model was developed using a partitioned survival approach and a public healthcare payer's perspective. Over a lifetime horizon, clinical and economic implications were estimated according to a three-health-state structure: progression-free, post-progression, and death. Key clinical inputs and utilities were derived from the METEOR trial, and a de novo network meta-analysis and cost data were obtained from publicly available Japanese data sources. Costs, quality-adjusted life-years, and incremental cost-effectiveness ratios were estimated. Costs and health benefits were discounted annually at 2%.

RESULTS

Cabozantinib was more costly and effective compared with everolimus and axitinib, with deterministic incremental cost-effectiveness ratios of ¥5,375,559 and ¥2,223,138, respectively. Compared to nivolumab, cabozantinib was predicted to be less costly and more effective. Sensitivity and scenario analyses demonstrated that the key drivers of cost-effectiveness results were the estimation of overall survival and treatment duration, relative efficacy, drug costs, and subsequent treatment costs.

LIMITATIONS

METEOR was an international trial but did not enroll any patients from Japan. Efficacy and safety data from METEOR were used as a proxy for the Japanese population following validation by clinical experts, and alternative assumptions specific to clinical practice in Japan were evaluated in scenario analyses.

CONCLUSIONS

In Japan, cabozantinib is a cost-effective alternative to everolimus, axitinib, and nivolumab for the treatment of patients with advanced renal cell carcinoma who have received at least one prior line of therapy.