Susanne Schmitz

A mixed treatment comparison of the efficacy of anti-TNF agents in rheumatoid arthritis for methotrexate non-responders demonstrates differences between treatments: a Bayesian approach

Background A number of tumour necrosis factor α (TNFα) antagonists (anti-TNFα) are available to treat rheumatoid arthritis. All of these have demonstrated considerable efficacy in placebo controlled trials, but few head-to-head comparisons exist to date. This works objective is to estimate the relative efficacy among licensed anti-TNFs in patients who have had an inadequate response to methotrexate (MTX). Different outcome measures are used to highlight the advantages of continuous measures in such analyses. Methods A systematic review identified randomised controlled trials comparing the efficacy of licensed anti-TNFα agents with placebo at 24 weeks in patients who have had an inadequate response to MTX. Relative efficacy was estimated using Bayesian mixed treatment comparison (MTC) models. Three different outcome measures were used: RR of achieving an American College of Rheumatology (ACR) 20 and ACR50 response and the percentage improvement in Health Assessment Questionnaire (HAQ) score. Results 16 published trials were included in the analysis. All anti-TNFs show considerably improved efficacy over placebo. The MTC results also provide evidence of some differences in efficacy of the TNFα antagonists. Etanercept appears superior to infliximab and golimumab, and certolizumab to infliximab and adalimumab. ACR results indicate improved efficacy of certolizumab over golimumab. On HAQ analysis, adalimumab, certolizumab, etanercept and golimumab appear superior to infliximab, and etanercept shows improved efficacy compared with adalimumab. Conclusions There are differences in efficacy among the TNFα antagonists. In a MTC, a continuous outcome measure has more strength to detect such differences than a binomial outcome measure because of its enhanced sensitivity to change.

Incorporating data from various trial designs into a mixed treatment comparison model

Estimates of relative efficacy between alternative treatments are crucial for decision making in health care. Bayesian mixed treatment comparison models provide a powerful methodology to obtain such estimates when head-to-head evidence is not available or insufficient. In recent years, this methodology has become widely accepted and applied in economic modelling of healthcare interventions. Most evaluations only consider evidence from randomized controlled trials, while information from other trial designs is ignored. In this paper, we propose three alternative methods of combining data from different trial designs in a mixed treatment comparison model. Naive pooling is the simplest approach and does not differentiate between-trial designs. Utilizing observational data as prior information allows adjusting for bias due to trial design. The most flexible technique is a three-level hierarchical model. Such a model allows for bias adjustment while also accounting for heterogeneity between-trial designs. These techniques are illustrated using an application in rheumatoid arthritis.

Body mass index is associated with biological CSF markers of core brain pathology of Alzheimer's disease.

Weight changes are common in aging and Alzheimers disease (AD) and postmortem findings suggest a relation between lower body mass index (BMI) and increased AD brain pathology. In the current multicenter study, we tested whether lower BMI is associated with higher core AD brain pathology as assessed by cerebrospinal fluid (CSF)-based biological markers of AD in 751 living subjects: 308 patients with AD, 296 subjects with amnestic mild cognitive impairment (MCI), and 147 elderly healthy controls (HC). Based upon a priori cutoff values on CSF concentration of total tau and beta-amyloid (Aβ(1-42)), subjects were binarized into a group with abnormal CSF biomarker signature (CSF+) and those without (CSF-). Results showed that BMI was significantly lower in the CSF+ when compared with the CSF- group (F = 27.7, df = 746, p < 0.001). There was no interaction between CSF signature and diagnosis or apolipoprotein E (ApoE) genotype. In conclusion, lower BMI is indicative of AD pathology as assessed with CSF-based biomarkers in demented and nondemented elderly subjects.

Comparative efficacy of disease-modifying therapies for patients with relapsing remitting multiple sclerosis: Systematic review and network meta-analysis.

INTRODUCTION Randomised studies have demonstrated efficacy of disease-modifying therapies in relapsing remitting multiple sclerosis (RRMS). However it is unclear how the magnitude of treatment efficacy varies across all currently available therapies. OBJECTIVE To perform a systematic review and network meta-analysis to evaluate the comparative efficacy of available therapies in reducing relapses and disability progression in RRMS. METHODS A systematic review identified 28 randomised, placebo-controlled and direct comparative trials. A network meta-analysis was conducted within a Bayesian framework to estimate comparative annualised relapse rates (ARR) and risks of disability progression (defined by both a 3-month, and 6-month confirmation interval). Potential sources of treatment-effect modification from study-level covariates and baseline risk were evaluated through meta-regression methods. The Surface Under the Cumulative RAnking curve (SUCRA) method was used to provide a ranking of treatments for each outcome. RESULTS The magnitude of ARR reduction varied between 15-36% for all interferon-beta products, glatiramer acetate and teriflunomide, and from 50 to 69% for alemtuzumab, dimethyl fumarate, fingolimod and natalizumab. The risk of disability progression (3-month) was reduced by 19-28% with interferon-beta products, glatiramer acetate, fingolimod and teriflunomide, by 38-45% for pegylated interferon-beta, dimethyl fumarate and natalizumab and by 68% with alemtuzumab. Broadly similar estimates for the risk of disability progression (6-month), with the exception of interferon-beta-1b 250mcg which was much more efficacious based on this definition. Alemtuzumab and natalizumab had the highest SUCRA scores (97% and 95% respectively) for ARR, while ranking for disability progression varied depending on the definition of the outcome. Interferon-beta-1b 250mcg ranked among the most efficacious treatments for disability progression confirmed after six months (92%) and among the least efficacious when the outcome was confirmed after three months (30%). No significant modification of relative treatment effects was identified from study-level covariates or baseline risk. CONCLUSION Compared with placebo, clear reductions in ARR with disease-modifying therapies were accompanied by more uncertain changes in disability progression. The magnitude of the reduction and the uncertainty associated with treatment effects varied between DMTs. While natalizumab and alemtuzumab demonstrated consistently high ranking across outcomes, with older interferon-beta and glatiramer acetate products ranking lowest, variation in disability progression definitions lead to variation in the relative ranking of treatments. Rigorously conducted comparative studies are required to fully evaluate the comparative treatment effects of disease modifying therapies for RRMS.

Safety of off-label erythropoiesis stimulating agents in critically ill patients: a meta-analysis

PurposeErythropoiesis stimulating agents (ESAs) are used to treat anemia in critically ill patients. This indication is off-label, because it is not licensed by regulatory authorities. Recently ESAs were suspected to harm critically ill patients. Our objective was to assess the safety of ESAs in off-label indications in critically ill patients.MethodsEleven databases were searched up to April 2012. We considered randomized controlled trials (RCTs) and controlled observational studies in any language that compared off-label ESAs treatment with other effective interventions, placebo or no treatment in critically ill patients. Two authors independently screened and evaluated retrieved records, extracted data and assessed risk of bias and quality of reporting.ResultsWe used frequentist and Bayesian models to combine studies, and performed sensitivity and subgroup analyses. From 12,888 citations, we included 48 studies (34 RCTs; 14 observational), involving 944,856 participants. Harm reporting was of medium to low quality. There was no statistically significant increased risk of adverse events in general, serious adverse events, the most frequently reported adverse events, and death in critically ill patients treated with ESAs. These results were robust against risk of bias and analysis methods. There is evidence that ESAs increase the risk of clinically relevant thrombotic vascular events, and there is some less certain evidence that ESAs might increase the risk for venous thromboembolism.ConclusionsIn critically ill patients, administration of ESAs is associated with a significant increase in clinically relevant thrombotic vascular events but not with other frequently reported adverse events and death.

The use of continuous data versus binary data in MTC models: A case study in rheumatoid arthritis

BackgroundEstimates of relative efficacy between alternative treatments are crucial for decision making in health care. When sufficient head to head evidence is not available Bayesian mixed treatment comparison models provide a powerful methodology to obtain such estimates. While models can be fit to a broad range of efficacy measures, this paper illustrates the advantages of using continuous outcome measures compared to binary outcome measures.MethodsUsing a case study in rheumatoid arthritis a Bayesian mixed treatment comparison model is fit to estimate the relative efficacy of five anti-TNF agents currently licensed in Europe. The model is fit for the continuous HAQ improvement outcome measure and a binary version thereof as well as for the binary ACR response measure and the underlying continuous effect. Results are compared regarding their power to detect differences between treatments.ResultsSixteen randomized controlled trials were included for the analysis. For both analyses, based on the HAQ improvement as well as based on the ACR response, differences between treatments detected by the binary outcome measures are subsets of the differences detected by the underlying continuous effects.ConclusionsThe information lost when transforming continuous data into a binary response measure translates into a loss of power to detect differences between treatments in mixed treatment comparison models. Binary outcome measures are therefore less sensitive to change than continuous measures. Furthermore the choice of cut-off point to construct the binary measure also impacts the relative efficacy estimates.

Identifying and Revealing the Importance of Decision-Making Criteria for Health Technology Assessment: A Retrospective Analysis of Reimbursement Recommendations in Ireland

BackgroundDecisions on reimbursement of health interventions in many jurisdictions are informed by health technology assessments (HTAs). Historically, the focus of these has often been cost effectiveness or cost utility, while other criteria were considered informally. More recently, there has been an increasing interest in the formal incorporation of additional criteria using multi-criteria decision analysis. Such an approach has not yet formally been part of decision-making policy in Ireland.ObjectiveThe objective of this analysis is to demonstrate that cost effectiveness is not the only criterion influencing reimbursement decisions in Ireland. Furthermore, the aim is to reveal criteria that may have informally influenced reimbursement decisions in the past.MethodsA list of potential criteria was identified based on the literature, national guidelines and experience of the national HTA agency. Information on each of these criteria was sought for every assessment conducted in Ireland up to July 2015. A logistic regression was fitted to the data to identify influential parameters. Model selection was performed using the Bolasso method.ResultsThirteen criteria were considered in the analysis. Two members of the HTA review team assessed the performance of the interventions against these criteria. Model selection suggests that the incremental cost-effectiveness ratio and quality of evidence could be important drivers of reimbursement recommendations in Ireland. Less important drivers suggested include the year of assessment, the level of uncertainty, as well as safety and tolerability.ConclusionThe analysis demonstrates that recommendations for or against the reimbursement of technologies in Ireland are not only driven by cost effectiveness. This highlights the need for more formal inclusion of criteria in the process, to improve transparency and ensure consistency.

Do disparities between populations in randomized controlled trials and the real world lead to differences in outcomes

AIM To conduct a systematic review investigating reasons for the disparity between the efficacy and effectiveness rates reported in randomized controlled trials (RCTs) and observational studies of direct-acting antiviral treatment regimens licensed for use in genotype1 hepatitis C virus-infected individuals. METHODS This systematic review was conducted in accordance with the criteria of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses group. RESULTS Statistically significant (p < 0.05) differences in the baseline demographics and sustained virological response rates were observed between RCT and observational studies. CONCLUSION In order for outcomes from RCTs to be generalizable to the real world, greater consideration needs to be taken to include patient populations that are more representative of those awaiting treatment in the clinical setting.

The use of single armed observational data to closing the gap in otherwise disconnected evidence networks: a network meta-analysis in multiple myeloma

BackgroundNetwork meta-analysis (NMA) allows for the estimation of comparative effectiveness of treatments that have not been studied in head-to-head trials; however, relative treatment effects for all interventions can only be derived where available evidence forms a connected network. Head-to-head evidence is limited in many disease areas, regularly resulting in disconnected evidence structures where a large number of treatments are available. This is also the case in the evidence of treatments for relapsed or refractory multiple myeloma.MethodsRandomised controlled trials (RCTs) identified in a systematic literature review form two disconnected evidence networks. Standard Bayesian NMA models are fitted to obtain estimates of relative effects within each network. Observational evidence was identified to fill the evidence gap. Single armed trials are matched to act as each other’s control group based on a distance metric derived from covariate information. Uncertainty resulting from including this evidence is incorporated by analysing the space of possible matches.ResultsTwenty five randomised controlled trials form two disconnected evidence networks; 12 single armed observational studies are considered for bridging between the networks. Five matches are selected to bridge between the networks. While significant variation in the ranking is observed, daratumumab in combination with dexamethasone and either lenalidomide or bortezomib, as well as triple therapy of carfilzomib, ixazomib and elozumatab, in combination with lenalidomide and dexamethasone, show the highest effects on progression free survival, on average.ConclusionsThe analysis shows how observational data can be used to fill gaps in the existing networks of RCT evidence; allowing for the indirect comparison of a large number of treatments, which could not be compared otherwise. Additional uncertainty is accounted for by scenario analyses reducing the risk of over confidence in interpretation of results.

Reply to Calcagno et al

TO THE EDITOR—In their comment regarding our meta-analysis, Calcagno et al make a very salient point with regard to the longer half-life of telaprevir and the impact this may have on its therapeutic robustness in the setting of less-thanoptimal adherence [1]. However, in the clinical trials examined by our metaanalysis, although adherence was not explicitly measured or reported, the discontinuation rates were very similar between the 2 agents and the rates of failure with resistance mutations were also low [2]. The subgroup of relapsers, in whom the difference between the 2 agents was detected, looked at a patient population with proven sensitivity to pegylated interferon and ribavirin and presumably with adherence that was adequate to result in an end-of-treatment response with standard of care. Therefore, it is unlikely that differences in patient adherence to treatment would account for the difference in efficacy detected by our analysis. That being said, the point regarding adherence is well made, especially as these treatment regimens are being rolled out into standard clinical practice and away from the idealized setting of a randomized clinical trial. The pharmacokinetic properties of telaprevir may allow some “forgiveness” in practice where adherence is likely to be lower than that found in a clinical trial setting. If there is indeed a benefit from a pharmacokinetic perspective in patients with poorer adherence, it would be expected that this would become more evident with increasing availability of real-world effectiveness data. In the setting of hepatitis C virus (HCV) treatment, there has been much work done looking at barriers to HCV treatment and care in both HCV-monoinfected and HCV/human immunodeficiency virus (HIV)–coinfected populations [3, 4]. Numerous factors have been identified relating to (1) HCV treatment and side effects, (2) provider experience with HCV patients, and (3) patient perceptions of treatment success and side effects [5]. Shorter durations of treatment and increased treatment success rates have been cited by patients as important factors in deciding whether to proceed with HCV treatment [6]. The shorter duration of triple therapy with telaprevir vs boceprevir and the resultant reduced duration of additive side effects may also influence the decision of which third agent to use, especially in the setting of concerns regarding patient adherence to treatment. In HIV care and other areas of therapeutics, pill burden and regimen complexity also have a role in adherence [7, 8]. The data on the validity of twice-daily dosing of telaprevir may allow reduced regimen complexity and improve adherence [9]. Our meta-analysis did not detect a difference in efficacy between the 2 agents in the overall populations, in keeping with international treatment guidelines, which do not state a preference for either agent [10]. Thus, along with host genetic and clinical factors, viral kinetics, and the pharmacokinetics of ribavirin, consideration of patient preference and adherence and the pharmacokinetics of the third agent will be important when it comes to individualizing the treatment paradigm for a particular patient.