RESUMEN
INTRODUCTION: Administration of intravenous (IV), high-efficacy treatments (HETs) for the treatment of multiple sclerosis (MS) poses a high resourcing and planning burden on infusion centres, resulting in treatment delays that may increase the risk of breakthrough disease activity. Simulation tools can be used to systematically analyse capacity scenarios and identify and better understand constraints, therefore enabling decision-makers to optimise patient care. We have previously applied ENTIMOS, a discrete event simulation model, to assess scenarios of patient flow and care delivery using real-life data inputs from the neurology infusion suite at Charing Cross Hospital London. The model predicted that, given current capacity and projected demand, patients would experience high-risk treatment delays within 30 months. OBJECTIVE: This study aimed to address key healthcare challenges for MS patient care management as seen from a neurologist's perspective. We used ENTIMOS to predict the impact of several distinct and clinically plausible scenarios on patient waiting times at the same MS infusion suite and to quantify mitigation strategies needed to assure continuity of care. METHODS: We used real-world experience of an expert neurologist to identify five clinical scenarios: (1) switching patients to a subcutaneous (SC) MS treatment of the same therapeutic agent, in the same hospital setting; (2) extending opening times to the weekend; (3) reducing the number of infusion chairs (to simulate social distancing measures applied during the coronavirus disease 2019 [COVID-19] pandemic); (4) increasing demand for infusions; and (5) increasing the scheduling approval time. Patient waiting time for next due infusion and time to high-risk treatment delays (≥ 30 days) were the main analysed model outputs. Previously published base case results were used as reference. All hypothetical scenarios were run over a 3-year horizon (with the exception of scenario 1, which was run over a 3- and 5-year horizon). Strategies to mitigate treatment delays were analysed and discussed. RESULTS: Switching 50% of patients to SC treatment of the same therapeutic agent administered in hospital postponed the predicted high-risk treatment delays to shortly beyond the 3-year simulation timeframe (month 38). Weekend opening reduced waiting times from 20 days to 4 days and prevented treatment delays, however, at elevated labour costs. Reducing the infusion chairs increased waiting time to 53 days on average and 86 days at the end of the simulation, leading to high-risk treatment delays within 6 months. An increased demand for infusions increased waiting time to 26 days on average and 47 days at the end of the simulation, leading to high-risk treatment delays within 22 months. Prolonged scheduling approval time did not reduce the waiting time, nor postpone the high-risk treatment delays. CONCLUSION: Decision makers need transparency on capacity constraints to better plan resourcing at infusion suites and MS treatments. Our results showed that various mitigation measures, such as increasing capacity by additional infusion chairs per year and transferring patients to other infusion suites, may help prevent treatment delays. Switching patients from IV to an SC version of the same therapeutic agent reduced the waiting time moderately and postponed high-risk treatment delays. It was insufficient to prevent high-risk treatment delays in the long term.
Patients with multiple sclerosis and other neurological conditions receive therapies that are often given intravenously. Due to increasing demand for intravenous infusions, specialist infusion centres face challenges with scheduling and insufficient personnel numbers, which contributes to the increasing costs of care. Computer-based decision support tools can help hospital administrators predict demand for infusions, plan resources and estimate overall costs. We used a computer-based decision support tool, "ENTIMOS", to predict demand at a multiple sclerosis infusion suite in London and to simulate possible solutions. The tool predicted that over the next 3 years patients would face increasing waiting time for their treatment and many would experience high-risk treatment delays of 30 days or longer. We tested several different, realistic scenarios where treatment demand was exacerbated and alleviated: we tested what would happen if patients were discharged from the infusion suite (decreasing demand), if the centre opened for 7 days instead of 5 days a week (increasing capacity), if social distancing measures were in place (decreasing capacity), and other scenarios. We found that high-risk treatment delays could be avoided if the centre adds infusion chairs to the suite or switches patients out of the infusion suite (e.g. to a treatment administered at home). The most effective long-term solution would be to have treatment options for multiple sclerosis that could be taken by patients at home. These treatments would be required to have the same benefits and the same or lower risk as the intravenous infusion therapies that are used today. It would help reduce labour costs of healthcare and may enable patients with multiple sclerosis to manage their disease at home.
RESUMEN
Background: Trials of disease-modifying therapies (DMTs) for multiple sclerosis (MS) often include patients with minimal disability. Patient-reported outcome instruments used in these trials have often not captured physical and psychological treatment effects concomitant with observed clinical benefits. Objective: To examine whether the Multiple Sclerosis Impact Scale-29 (MSIS-29) captures changes in the impact of MS in a sample of patients enrolled in the Phase 3 ASCLEPIOS studies (ofatumumab vs. teriflunomide). Methods: Measurement properties (i.e. item fit, reliability, and targeting) of the MSIS-29 were analyzed using Rasch measurement theory (RMT) in data from two phase 3 ofatumumab clinical trials including patients with relapsing-remitting or secondary progressive MS (N = 1882). Targeting of the MSIS-29 items to the patient population was explored within groups categorized by Expanded Disability Status Scale (EDSS) scores. Results: Under RMT analyses, both the Physical and Psychological Impact scales of the MSIS-29 were not appropriately targeted to the overall sample of patients. In particular, 49% and 30% of patients with an EDSS score ≤ 2.5 had fewer physical and psychological impacts, respectively, than would typically be captured by these MSIS-29 items compared to patients with EDSS scores of ≥ 3. Conclusion: The MSIS-29 is commonly used to evaluate the patient-reported physical and psychological impact of MS. However, it may be limited in evaluating changes associated with DMTs in patients with minimal disability.
RESUMEN
Aim: To assess the relative efficacy of disease-modifying therapies (DMTs) for relapsing multiple sclerosis (RMS) including newer therapies (ozanimod, ponesimod, ublituximab) using network meta-analysis (NMA). Materials & methods: Bayesian NMAs for annualised relapse rate (ARR) and time to 3-month and 6-month confirmed disability progression (3mCDP and 6mCDP) were conducted. Results: For each outcome, the three most efficacious treatments versus placebo were monoclonal antibody (mAb) therapies: alemtuzumab, ofatumumab, and ublituximab for ARR; alemtuzumab, ocrelizumab, and ofatumumab for 3mCDP; and alemtuzumab, natalizumab, and either ocrelizumab or ofatumumab (depending on the CDP definition used for included ofatumumab trials) for 6mCDP. Conclusion: The most efficacious DMTs for RMS were mAb therapies. Of the newer therapies, only ublituximab ranked among the three most efficacious treatments (for ARR).
Asunto(s)
Esclerosis Múltiple Recurrente-Remitente , Esclerosis Múltiple , Humanos , Esclerosis Múltiple Recurrente-Remitente/tratamiento farmacológico , Alemtuzumab/uso terapéutico , Metaanálisis en Red , Teorema de Bayes , RecurrenciaRESUMEN
AIMS: The aim of this study was to explore the experiences, values and preferences of people living with relapsing multiple sclerosis (PLwRMS) focusing on their treatments and what drives their treatment preferences. METHODS: In-depth, semi-structured, qualitative telephone interviews were conducted using a purposive sampling approach with 72 PLwRMS and 12 health care professionals (HCPs, MS specialist neurologists and nurses) from the United Kingdom, United States, Australia and Canada. Concept elicitation questioning was used to elicit PLwRMS' attitudes, beliefs and preferences towards features of disease-modifying treatments. Interviews with HCPs were conducted to inform on HCPs' experiences of treating PLwRMS. Responses were audio recorded and transcribed verbatim and then subjected to thematic analysis. RESULTS: Participants discussed numerous concepts that were important to them when making treatment decisions. Levels of importance participants placed on each concept, as well as reasons underpinning importance, varied substantially. The concepts with the greatest variability in terms of how much PLwRMS found them to be important in their decision-making process were mode of administration, speed of treatment effect, impact on reproduction and parenthood, impact on work and social life, patient engagement in decision making, and cost of treatment to the participant. Findings also demonstrated high variability in what participants described as their ideal treatment and the most important features a treatment should have. HCP findings provided clinical context for the treatment decision-making process and supported patient findings. CONCLUSIONS: Building upon previous stated preference research, this study highlighted the importance of qualitative research in understanding what drives patient preferences. Characterized by the heterogeneity of the RMS patient experience, findings indicate the nature of treatment decisions in RMS to be highly individualized, and the subjective relative importance placed on different treatment factors by PLwRMS to vary. Such qualitative patient preference evidence could offer valuable and supplementary insights, alongside quantitative data, to inform decision making related to RMS treatment.
Asunto(s)
Esclerosis Múltiple , Humanos , Toma de Decisiones , Individualidad , Investigación Cualitativa , Evaluación del Resultado de la Atención al PacienteRESUMEN
BACKGROUND: Ofatumumab is a subcutaneously administered anti-CD20 monoclonal antibody (MoAb) therapy that has been evaluated in two identically designed randomized controlled trials (RCTs), ASCLEPIOS I (NCT02792218) and ASCLEPIOS II (NCT02792231), in patients with relapsing multiple sclerosis (RMS). Ocrelizumab is another anti-CD20 MoAb therapy, administered intravenously, that has been evaluated in two identically designed RCTs, OPERA I (NCT01247324) and OPERA II (NCT01412333) in RMS. Given the absence of published RCTs with head-to-head comparisons between these MoAbs, this study assessed the indirect comparative efficacy of ofatumumab and ocrelizumab. METHODS: Given the availability of individual patient data for ASCLEPIOS I/II and summary-level data for OPERA I/II, simulated treatment comparisons were used to assess the comparative efficacy of ofatumumab versus ocrelizumab while adjusting for differences in baseline characteristics between trials. Comparative efficacy was estimated for the proportion of patients with 3- and 6-month confirmed disability progression (CDP) and for annualized relapse rate (ARR). Exploratory analyses were conducted for the outcome of no evidence of disease activity based on three parameters (NEDA-3) and magnetic resonance imaging (MRI) outcomes (proportion of patients with gadolinium-enhancing T1 lesions and brain volume change). RESULTS: Although comparative results were not significant for 3-month CDP (hazard ratio [HR]: 0.90 [95% confidence interval [CI]: 0.57-1.42]) or 6-month CDP (HR: 0.84 [95% CI: 0.47-1.49]), ofatumumab showed a significant improvement in ARR (rate ratio: 0.60 [95% CI: 0.43-0.84]) compared with ocrelizumab. Significantly favorable results were also associated with ofatumumab for NEDA-3 and MRI outcomes. CONCLUSION: Ofatumumab was associated with more favorable efficacy results compared with ocrelizumab for clinical, NEDA-3, and MRI outcomes.
Asunto(s)
Anticuerpos Monoclonales Humanizados , Esclerosis Múltiple Recurrente-Remitente , Humanos , Anticuerpos Monoclonales Humanizados/uso terapéutico , Gadolinio/uso terapéutico , Factores Inmunológicos/uso terapéutico , Esclerosis Múltiple Recurrente-Remitente/tratamiento farmacológico , Ensayos Clínicos Controlados Aleatorios como AsuntoRESUMEN
BACKGROUND: Improved multiple sclerosis (MS) diagnosis and increased availability of intravenous disease-modifying treatments can lead to overburdening of infusion centres. This study was focused on developing a decision-support tool to help infusion centres plan their operations. METHODS: A discrete event simulation model ('ENTIMOS') was developed using Simul8 software in collaboration with clinical experts. Model inputs included treatment-specific clinical parameters, resources such as infusion chairs and nursing staff, and costs, while model outputs included patient throughput, waiting time, queue size, resource utilisation, and costs. The model was parameterised using characteristics of the Charing Cross Hospital Infusion Centre in London, UK, where 12 infusion chairs were deployed for 170 non-MS and 860 MS patients as of March 2021. The number of MS patients was projected to increase by seven new patients per week. RESULTS: The model-estimated waiting time for an infusion is, on average, 8 days beyond clinical recommendation in the first year of simulation. Without corrective action, the delay in receiving due treatment is anticipated to reach 30 days on average at 30 months from the start of simulation. Such system compromise can be prevented either by adding one infusion chair annually or switching 7% of existing patients or 24% of new patients to alternative MS treatments not requiring infusion. CONCLUSION: ENTIMOS is a flexible model of patient flow and care delivery in infusion centres serving MS patients. It allows users to simulate specific local settings and therefore identify measures that are necessary to avoid clinically significant treatment delay resulting in suboptimal care.
Asunto(s)
Esclerosis Múltiple , Simulación por Computador , Hospitales , Humanos , Esclerosis Múltiple/tratamiento farmacológico , Programas InformáticosRESUMEN
OBJECTIVE: Head-to-head trials comparing siponimod with fingolimod or ofatumumab in patients with multiple sclerosis (MS) are lacking. Instead, the comparative efficacy of siponimod can be derived from indirect treatment comparisons (ITCs). We assessed the suitability of ITCs leveraging individual patient data from relevant phase III trials across different MS phenotypes. METHODS: One siponimod trial in patients with secondary progressive MS (SPMS), four fingolimod trials (three in relapsing-remitting MS [RRMS], and one in primary progressive MS [PPMS]), and two ofatumumab trials in relapsing MS (RMS) were considered. The suitability of ITCs was evaluated based on trial design, patient eligibility criteria, baseline patient characteristics, placebo response, and outcome definitions for each trial. Analyses deemed feasible were conducted using one-to-one propensity score matching (PSM). RESULTS: An ITC between siponimod in SPMS and either fingolimod in RRMS or ofatumumab in RMS was not feasible because of insufficient overlap in key patient characteristics (e.g. disability level and relapse history) and differences in placebo response. However, a comparison between siponimod in SPMS and fingolimod in PPMS was feasible because of sufficient overlap in eligibility criteria and baseline characteristics. One-to-one PSM demonstrated siponimod was favored relative to fingolimod for time to 6- and 3-month confirmed disability progression though not significantly different (hazard ratio 0.76 [95% confidence interval 0.48-1.20; p-value = .240] and hazard ratio 0.80 [95% confidence interval 0.52-1.22; p-value = .300], respectively). CONCLUSIONS: For trials in MS, clinical phenotype is an important determinant of ITC feasibility. An ITC between siponimod in SPMS and either fingolimod in RRMS or ofatumumab in RMS was not feasible. The only feasible comparison was between siponimod in SPMS and fingolimod in PPMS.