The Impact of Payer and Reimbursement Authorities Evidence Requirements on Healthcare Solution Design for Muscular Dystrophies

For rare diseases that start early and are slowly degenerative, despite the desire to create solutions that benefit the patient, healthcare system realities can be prohibitive to generate an affordable and effective solution. The optimal care pathway for muscular dystrophy, similar to all degenerative diseases, would be a rapid and accurate diagnosis, pathophysiological confirmation and application of therapeutics that slowly replaces damaged tissue with healthy tissue, supported by adjuvant solutions that stimulate the tissue to repair and reduce inflammation and fibrosis. This would increase the lifespan and quality of life in an affordable way. For all diseases, two key stakeholders, the paying entity and the patient, fundamentally define whether revenue can be generated. Healthcare decision-making commissioners who agree to pay for the product and patient-reported outcomes jointly inform whether the intervention increases the quality of life related to existing standards of care and, therefore, if it should be paid for. This chapter explains why this has not yet happened and efforts initiated to correct this and addresses how the components and data used in this decision-making process could be updated, adapted and integrated into every stage of the development of solutions and how organisational innovation may enable the field

Abatacept with methotrexate versus other biologic agents in treatment of patients with active rheumatoid arthritis despite methotrexate: a network meta-analysis

INTRODUCTION: The goal of this study was to compare the efficacy in terms of Health Assessment Questionnaire change from baseline (HAQ CFB), 50% improvement in American College of Rheumatology criterion (ACR-50) and Disease Activity Score in 28 joints (DAS28) defined remission (< 2.6) between abatacept and other biologic disease modifying anti-rheumatic drugs (DMARDs) in patients with rheumatoid arthritis (RA) who have inadequate response to methotrexate (MTX-IR). METHODS: A systematic literature review identified controlled trials investigating the efficacy of abatacept (three studies), etanercept (two studies), infliximab (two), adalimumab (two), certolizumab pegol (two) ritixumab (three), and tocilizumab (two) in MTX-IR patients with RA. The clinical trials included in this analysis were similar with respect to trial design, baseline patient characteristics and background therapy (MTX). The key clinical endpoints of interest were HAQ CFB, ACR-50 and DAS28 < 2.6 measured at 24 and 52 weeks. The results were analysed using network meta-analysis methods that enabled calculation of an estimate for expected relative effect of comparative treatments. Analysis results were expressed as the difference in HAQ CFB score and odds ratio (OR) of achieving an ACR-50 and DAS28 response and associated 95% credible intervals (CrI). RESULTS: The analysis of HAQ CFB at 24 weeks and 52 weeks showed that abatacept in combination with MTX is expected to be more efficacious than MTX monotherapy and is expected to show a comparable efficacy relative to other biologic DMARDs in combination with MTX. Further, abatacept showed comparable ACR-50 and DAS28 < 2.6 response rates with other biologic DMARDs at 24 and 52 weeks, except for ACR-50 compared to certolizumab pegol at 52 weeks and for DAS28 < 2.6 compared to tocilizumab at 24 weeks. Sensitivity analyses confirmed the robustness of the findings. CONCLUSIONS: Abatacept in combination with MTX is expected to result in a comparable change from baseline in HAQ score and comparable ACR-50 and DAS28 < 2.6 response rates in MTX-IR patients compared to other approved biologic agents

Patient-reported utilities in advanced or metastatic melanoma, including analysis of utilities by time to death

Background: Health-related quality of life is often collected in clinical studies, and forms a cornerstone of economic evaluation. This study had two objectives, firstly to report and compare pre- and post-progression health state utilities in advanced melanoma when valued by different methods and secondly to explore the validity of progression-based health state utility modelling compared to modelling based upon time to death. Methods: Utilities were generated from the ipilimumab MDX010-20 trial (Clinicaltrials.gov Identifier: NCT00094653) using the condition-specific EORTC QLQ-C30 (via the EORTC-8D) and generic SF-36v2 (via the SF-6D) preference-based measures. Analyses by progression status and time to death were conducted on the patient-level data from the MDX010-20 trial using generalised estimating equations fitted in Stata®, and the predictive abilities of the two approaches compared. Results: Mean utility showed a decrease on disease progression in both the EORTC-8D (0.813 to 0.776) and the SF-6D (0.648 to 0.626). Whilst higher utilities were obtained using the EORTC-8D, the relative decrease in utility on progression was similar between measures. When analysed by time to death, both EORTC-8D and SF-6D showed a large decrease in utility in the 180 days prior to death (from 0.831 to 0.653 and from 0.667 to 0.544, respectively). Compared to progression status alone, the use of time to death gave similar or better estimates of the original data when used to predict patient utility in the MDX010-20 study. Including both progression status and time to death further improved model fit. Utilities seen in MDX010-20 were also broadly comparable with those seen in the literature. Conclusions: Patient-level utility data should be analysed prior to constructing economic models, as analysis solely by progression status may not capture all predictive factors of patient utility and time to death may, as death approaches, be as or more important. Additionally this study adds to the body of evidence showing that different scales lead to different health state values. Further research is needed on how different utility instruments (the SF-6D, EORTC-8D and EQ-5D) relate to each other in different disease areas

Cost Effectiveness of Palivizumab for Respiratory Syncytial Virus Prophylaxis in High-Risk Children: A UK Analysis

Objective: To assess the cost effectiveness of palivizumab (a preventative treatment against severe respiratory syncytial virus [RSV] infection) in children at high risk of hospitalisation, i.e. preterm infantsBronchopulmonary-dysplasia, Congenital-heart-disorders, Cost-utility, Infants, Neonates, Palivizumab, Respiratory-syncytial-virus-infections

The Predicted Impact of Ipilimumab Usage on Survival in Previously Treated Advanced or Metastatic Melanoma in the UK.

BACKGROUND:Evaluating long-term prognosis is important for physicians, patients and payers. This study reports the results of a model developed to predict long-term survival for UK patients receiving second-line ipilimumab. METHODS:MDX010-20 trial data were used to predict survival for ipilimumab versus UK best supportive care. Two aspects of this analysis required novel approaches: 1) The overall survival Kaplan-Meier data shape is unusual: an initial steep decline is observed before a 'plateau'. 2) The need to extrapolate beyond the trial end (4.6 years). Based upon UK clinician advice, a three-part curve fit was used: from 0-1.5 years, Kaplan-Meier data from the trial; from 1.5-5 years, standard parametric curve fits; after 5 years, long-term data from the American Joint Committee on Cancer registry. RESULTS:This approach provided good internal validity: low mean absolute error and good match to median and mean trial data. Lifetime predicted means were 2.77 years for ipilimumab and 1.07 for best supportive care, driven by increased long-term survival with ipilimumab. CONCLUSION:To understand the full benefit of treatment and to meet reimbursement requirements, accurate estimation of treatment benefit is key. Models, such as the one presented, can be used to extrapolate beyond trials

A: Parametric curve fits applied to MDX010-20 data; B: Cumulative hazard plot for ipilimumab vs ipilimumab + gp100 vs gp100; C: Estimated survival curves using three-part curve fit; D: Comparison of modelled survival estimates with available trial data.

<p>A: Parametric curve fits applied to MDX010-20 data; B: Cumulative hazard plot for ipilimumab vs ipilimumab + gp100 vs gp100; C: Estimated survival curves using three-part curve fit; D: Comparison of modelled survival estimates with available trial data.</p