The current cost-minimization analysis demonstrates that, from the Dutch healthcare perspective, treating active RRMS patients with alemtuzumab results in cost savings compared to second-line alternatives fingolimod and natalizumab from ∼3 years since treatment initiation onwards. After 5 years, alemtuzumab's cost savings are estimated at €30k compared to fingolimod and €43k compared to natalizumab.

Background and purpose Existing effectiveness models of disease‐modifying drugs (DMDs) for relapsing–remitting multiple sclerosis (RRMS) evaluate a single line of treatment; however, RRMS patients often receive more than one lifetime DMD. To develop treatment sequencing models grounded in clinical reality, a detailed understanding of the decision‐making process regarding DMD switching is required. Using a modified Delphi approach, this study attempted to reach consensus on modelling assumptions. Methods A modified Delphi technique was conducted based on three rounds of discussion amongst an international group of 10 physicians with expertise in RRMS. Results The panel agreed that the expected time from disease onset to Expanded Disability Status Scale 6.0 is a proxy for disease severity as well as suitable for classifying severity into three groups. A modelled clinical decision rule regarding the timing of switching should contain at least the time between relapses, magnetic resonance imaging outcomes and the occurrence/risk of adverse events. The experts agreed that the assessment of adverse event risk for a DMD is dependent on disease severity, with more risks accepted when the patient’s disease is more severe. The effectiveness of DMDs conditional on their position in a sequence and/or disease duration was discussed: there was consensus on some statements regarding this topic but these were accompanied by a high degree of uncertainty due to considerable knowledge gaps. Conclusion Useful insights into the medical decision‐making process regarding treatment sequencing in RRMS were obtained. The knowledge gained has been used to validate the main modelling concepts and to further generate clinically meaningful results.

Introduction Schizophrenia is a chronic mental disorder that worsens with each relapse. Long-acting injectable (LAI) antipsychotics may prevent the exacerbation of symptoms and occurrence of relapses through improved continuity of care. Different dose regimens are available for the LAIs aripiprazole monohydrate (AM) and aripiprazole lauroxil (AL), but their cost effectiveness is unclear. Objectives The study aim was to compare costs and effects (relapses) of the different aripiprazole LAI dose regimens to inform clinical and US payer decisions. Methods A state-transition model calculated the outcomes of eight LAI dose regimens based on their relapse rates. As effectiveness data from randomized controlled trials were unavailable, relapse rates were modeled using pharmacokinetic and pharmacodynamic evidence. These described blood plasma levels of aripiprazole as a function of AM and AL dose regimens and described the probability of relapse as a function of aripiprazole blood plasma levels. The analysis had a time horizon of 1 year and took the US healthcare payer perspective. The incremental cost per relapse avoided and the probability of cost effectiveness were calculated in deterministic and probabilistic analyses. Scenario analyses explored the model's main assumptions, and results were validated against external data and other cost-effectiveness analyses. Results Monthly administration of AM 400 mg consistently yielded the lowest predicted number of relapses across deterministic, probabilistic, and scenario analyses. The costs of treatment and relapses were projected to be the lowest with a monthly administration of AL 441 mg. The incremental cost per relapse avoided with AM 400 mg ranged from AM 400 mg being dominant to $US83,300. From willingness-to-pay thresholds of $US30,000 per relapse avoided, the probability of cost effectiveness was highest for AM 400 mg. The validation showed alignment with external data. Conclusion The analysis highlighted the robustness of the novel framework based on pharmacokinetic and pharmacodynamic evidence and demonstrated an application in a postmarketing setting.

PurposeFocal salvage (FS) iodine 125 (125I) brachytherapy could be an effective treatment for locally radiorecurrent prostate cancer (PCa). Toxicity is often reduced compared to total salvage (TS) while cancer control can be maintained, which could increase cost-effectiveness. The current study estimates the incremental cost per quality-adjusted life year (QALY) of FS compared to TS.Material and methodsA decision analytic Markov model was developed, which compares costs and QALYs associated with FS and TS. A 3-year time horizon was adopted with six month cycles, with a hospital perspective on costs. Probabilities for genitourinary (GU) and gastrointestinal (GI) toxicity and their impact on health-related quality of life (SF-36) were derived from clinical studies in the University Medical Center Utrecht (UMCU). Probabilistic sensitivity analysis, using 10,000 Monte Carlo simulations, was performed to quantify the joint decision uncertainty up to the recommended maximum willingness-to-pay threshold of €80,000/QALY.ResultsFocal salvage dominates TS as it results in less severe toxicity and lower treatment costs. Decision uncertainty is small, with a 97-100% probability for FS to be cost-effective compared to TS (€0-€80,000/QALY). Half of the difference in costs between FS and TS was explained by higher treatment costs of TS, the other half by higher incidence of severe toxicity. One-way sensitivity analyses show that model outcomes are most sensitive to utilities and probabilities for severe toxicity.ConclusionsFocal salvage 125I brachytherapy dominates TS, as it has lower treatment costs and leads to less toxicity in our center. Larger comparative studies with longer follow-up are necessary to assess the exact influence on (biochemical disease free) survival and toxicity.

ObjectiveGather health technology assessment (HTA) experts' insights on the desirability and acceptability of treatment-sequencing models applied to relapsing-remitting multiple sclerosis (RRMS).Data source/study settingPrimary data.Study designIn-depth double-blind semi-structured telephone interviews.Data collection/extraction methodsGeneral themes were extracted from qualitative interviews.Principal findingsAlthough experts confirmed the importance of evaluating the clinical and cost-effectiveness of treatments as part of a sequence, the current HTA decision making framework is not conducive to this. Developing an RRMS treatment-sequencing model that meets HTA requirements is difficult, in particular due to scarcity of effectiveness data in later treatment lines.ConclusionsAt present, a treatment-sequencing model for RRMS may be desirable yet not requested by HTA bodies for their decision making. However, there could be other areas where a treatment-sequencing model for RRMS is of use.