Desirability and acceptability of a treatment-sequencing model in relapsing-remitting multiple sclerosis: A health technology assessment perspective.

OBJECTIVE: Gather 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 SETTING: Primary data. STUDY DESIGN: In-depth double-blind semi-structured telephone interviews. DATA COLLECTION/EXTRACTION METHODS: General themes were extracted from qualitative interviews. PRINCIPAL FINDINGS: Although 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. CONCLUSIONS: At 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.

Impact of Nonrandomized Dropout on Treatment Switching Adjustment in the Relapsing-Remitting Multiple Sclerosis CLARITY Trial and the CLARITY Extension Study.

OBJECTIVES: Statistical methods to adjust for treatment switching are commonly applied to randomized controlled trials (RCTs) in oncology. Nevertheless, RCTs with extension studies incorporating nonrandomized dropout require consideration of alternative adjustment methods. The current study used a recognized method and a novel method to adjust for treatment switching in relapsing-remitting multiple sclerosis (MS). METHODS: The Cladribine Tablets Treating Multiple Sclerosis Orally (CLARITY) RCT evaluated the efficacy of cladribine versus placebo over 96 weeks. Many (but not all) CLARITY participants enrolled in the 96-week CLARITY extension study; placebo-treated patients from CLARITY received cladribine (PP→LL), and cladribine-treated patients were re-randomized to placebo (LL→PP) or continued cladribine (LL→LL). End points were time to first qualifying relapse (FQR) and time to 3-month and 6-month confirmed disability progression (3mCDP, 6mCDP). We aimed to estimate the effectiveness of the LL→PP treatment strategy compared with a counterfactual (unobserved) PP→PP strategy. We applied the commonly used rank-preserving structural failure time model (RPSFTM) and a novel approach that combined propensity score matching (PSM) with inverse probability of censoring weights (IPCW). RESULTS: The RPSFTM resulted in LL→PP versus PP→PP hazard ratios (HRs) of 0.48 (95% confidence interval [CI] 0.36-0.62) for FQR, 0.62 (95% CI 0.46-0.84) for 3mCDP, and 0.62 (95% CI 0.44-0.88) for 6mCDP. The PSM+IPCW resulted in HRs of 0.47 (95% CI 0.38-0.63) for FQR, 0.61 (95% CI 0.43-0.86) for 3mCDP, and 0.63 (95% CI 0.40-0.87) for 6mCDP. CONCLUSIONS: The PSM+IPCW HRs were consistent with those from the RPSFTM, suggesting that the results were not substantially biased by informative dropout, assuming that all relevant confounders were controlled for. There was no statistical evidence of a reduction in the cladribine treatment effect during the extension period.

Comparative effectiveness of cladribine tablets versus fingolimod in the treatment of highly active multiple sclerosis: A real-world study.

BACKGROUND: Cladribine tablets and fingolimod have similar marketing authorisations in Europe for the treatment of patients with highly active relapsing multiple sclerosis (HA-RMS). In the absence of direct head-to-head studies, real-world data are important to assess the comparative effectiveness of these oral disease-modifying therapies (DMTs). The primary objective of the present study was to compare relapse rates between patients who received either cladribine tablets or fingolimod. METHODS: This multicentre retrospective study conducted in the United Kingdom and Germany assessed non-inferiority in relapse rates of cladribine tablets versus fingolimod in HA-RMS patients over a 12-month period. Eligible patients who initiated treatment with cladribine tablets or fingolimod at least 12 months prior to the screening date were sampled consecutively until the target sample size was reached. Patients were censored at discontinuation of study treatment, commencement of another DMT, death, loss to follow-up, or at 12 months post-baseline, whichever happened earliest. The primary analytic timeframe for physician-confirmed relapse outcomes was the study effectiveness period (nine months of follow-up after an initial 12 weeks of treatment). Propensity score analysis was applied based on the inverse probability of treatment weighting approach. RESULTS: The primary analytic cohort consisted of 1,095 HA-RMS patients: 610 (55.7%) receiving cladribine tablets and 485 (44.3%) receiving fingolimod. Fewer patients discontinued cladribine tablets and/or switched to another DMT compared with fingolimod (0.2% versus 3.5%, respectively). The primary endpoint, adjusted annualised relapse rate (ARR), was 0.10 (95% confidence interval [CI]: 0.07-0.14) for cladribine tablets and 0.14 (95% CI: 0.10-0.20) for fingolimod. The adjusted ARR ratio of cladribine tablets versus fingolimod was 0.68 (95% CI: 0.42-1.11). Given the entire 95% CI was less than the non-inferiority margin of 1.2, cladribine tablets was non-inferior to fingolimod. CONCLUSIONS: In this real-world retrospective cohort study, cladribine tablets demonstrated comparable effectiveness to fingolimod at one year following treatment initiation. The full treatment dosage of cladribine tablets is completed over two years and so these results may be conservative.

An Innovative Approach to Modelling the Optimal Treatment Sequence for Patients with Relapsing-Remitting Multiple Sclerosis: Implementation, Validation, and Impact of the Decision-Making Approach.

INTRODUCTION: An innovative computational model was developed to address challenges regarding the evaluation of treatment sequences in patients with relapsing-remitting multiple sclerosis (RRMS) through the concept of a 'virtual' physician who observes and assesses patients over time. We describe the implementation and validation of the model, then apply this framework as a case study to determine the impact of different decision-making approaches on the optimal sequence of disease-modifying therapies (DMTs) and associated outcomes. METHODS: A patient-level discrete event simulation (DES) was used to model heterogeneity in disease trajectories and outcomes. The evaluation of DMT options was implemented through a Markov model representing the patient's disease; outcomes included lifetime costs and quality of life. The DES and Markov models underwent internal and external validation. Analyses of the optimal treatment sequence for each patient were based on several decision-making criteria. These treatment sequences were compared to current treatment guidelines. RESULTS: Internal validation indicated that model outcomes for natural history were consistent with the input parameters used to inform the model. Costs and quality of life outcomes were successfully validated against published reference models. Whereas each decision-making criterion generated a different optimal treatment sequence, cladribine tablets were the only DMT common to all treatment sequences. By choosing treatments on the basis of minimising disease progression or number of relapses, it was possible to improve on current treatment guidelines; however, these treatment sequences were more costly. Maximising cost-effectiveness resulted in the lowest costs but was also associated with the worst outcomes. CONCLUSIONS: The model was robust in generating outcomes consistent with published models and studies. It was also able to identify optimal treatment sequences based on different decision criteria. This innovative modelling framework has the potential to simulate individual patient trajectories in the current treatment landscape and may be useful for treatment switching and treatment positioning decisions in RRMS.

Assessing the Long-Term Effectiveness of Cladribine vs. Placebo in the Relapsing-Remitting Multiple Sclerosis CLARITY Randomized Controlled Trial and CLARITY Extension Using Treatment Switching Adjustment Methods.

OBJECTIVES: Treatment switching adjustment methods are often used to adjust for switching in oncology randomized controlled trials (RCTs). In this exploratory analysis, we apply these methods to adjust for treatment changes in the setting of an RCT followed by an extension study in relapsing-remitting multiple sclerosis. METHODS: The CLARITY trial evaluated cladribine tablets versus placebo over 96 weeks. In the 96-week CLARITY Extension, patients who received placebo in CLARITY received cladribine tablets; patients who received cladribine tablets in CLARITY were re-randomized to placebo or cladribine tablets. End points were time to first qualifying relapse (FQR) and time to 3- and 6-month confirmed disability progression (3mCDP, 6mCDP). We aimed to compare the effectiveness of cladribine tablets with placebo over CLARITY and the extension. The rank-preserving structural failure time model (RPSFTM) and iterative parameter estimation (IPE) were used to estimate what would have happened if patients had received placebo in CLARITY and the extension versus patients that received cladribine tablets and switched to placebo. To gauge whether treatment effect waned after the 96 weeks of CLARITY, we compared hazard ratios (HRs) from the adjustment analysis with HRs from CLARITY. RESULTS: The RPSFTM resulted in an HR of 0.48 [95% confidence interval (CI) 0.36-0.62] for FQR, 0.62 (95% CI 0.46-0.84) for 3mCDP and 0.62 (95% CI 0.44-0.88) for 6mCDP. IPE algorithm results were similar. CLARITY HRs were 0.44 (95% CI 0.34-0.58), 0.60 (95% CI 0.41-0.87) and 0.58 (95% CI 0.40-0.83) for FQR, 3mCDP and 6mCDP, respectively. CONCLUSIONS: Treatment switching adjustment methods are applicable in non-oncology settings. Adjusted CLARITY plus CLARITY Extension HRs were similar to the CLARITY HRs, demonstrating significant treatment benefits associated with cladribine tablets versus placebo. FUNDING: EMD Serono, Inc. (a business of Merck KGaA, Darmstadt, Germany).