Purpose Since 2000, many new treatment options have become available for relapsed and/or refractory multiple myeloma (R/R MM) after a long period in which dexamethasone and melphalan had been the standard treatment. Direct comparisons of these novel treatments, however, are lacking. This makes it extremely difficult to evaluate the relative added value of each new treatment. Our aim was to synthesize all efficacy evidence, enabling a comparison of all current treatments for R/R MM. Methods We performed a systematic literature review to identify all publicly available phase III randomized controlled trial evidence. We searched Embase, MEDLINE, MEDLINE In-Process, Cochrane Central Register of Controlled Clinical Trials, and the Web site www.ClinicalTrials.gov . In addition, two trials presented at two international hematology congresses (ie, ASCO 2016 and European Hematology Association 2016) were added to include the most recent evidence. In total, 17 randomized controlled trials were identified, including 18 treatment options. The evidence was synthesized using a conventional network meta-analysis. To include all treatments within one network, two treatment options were combined: (1) bortezomib monotherapy and bortezomib plus dexamethasone, and (2) thalidomide monotherapy and thalidomide plus dexamethasone. Results The combination of daratumumab, lenalidomide, and dexamethasone was identified as the best treatment. It was most favorable in terms of (1) hazard ratio for progression-free survival (0.13; 95% credible interval, 0.09 to 0.19), and (2) probability of being best (99% of the simulations). This treatment combination reduced the risk of progression or death by 87% versus dexamethasone, 81% versus bortezomib plus dexamethasone, and 63% versus lenalidomide plus dexamethasone. Conclusion Our network meta-analysis provides a complete overview of the relative efficacy of all available treatments for R/R MM. Until additional data from randomized studies are available, on the basis of this analysis, the combination of daratumumab, lenalidomide, and dexamethasone seems to be the best treatment option.
As shared strengths, all systems have clear objectives reflected in reimbursement criteria and all are prepared to pay for drugs with sufficient added value. However, all systems could improve the transparency of the decision-making process; especially appraisal lacks transparency. Systems could increase the use of (systematic) revisions and could make better use of HTA (among others cost-effectiveness) to obtain value for money and ensure system sustainability.
BACKGROUNDAlthough a myriad of novel treatments entered the treatment paradigm for advanced melanoma, there is a lack of head-to-head evidence. We conducted a network meta-analysis (NMA) to estimate each treatment's relative effectiveness and safety.
METHODSA systematic literature review (SLR) was conducted in Embase, MEDLINE, and Cochrane to identify all phase-III randomised controlled trials (RCTs); timeframe: January 1, 2010 to March 11, 2019. We retrieved evidence on treatment-related grade 3/4 adverse events, progression-free survival (PFS), and overall survival (OS). Evidence was synthesised using a Bayesian fixed-effect NMA. Reference treatment was dacarbazine. In accordance with RCTs, dacarbazine was pooled with temozolomide, paclitaxel, and paclitaxel plus carboplatin. To increase homogeneity of the study populations, RCTs were only included if patients were not previously treated with novel treatments.
RESULTSThe SLR identified 28 phase-III RCTs involving 14,376 patients. Nineteen (seventeen) treatments were included in the effectiveness (safety) NMA. For PFS, dabrafenib plus trametinib (hazard ratio [HR] PFS: 0.21) and vemurafenib plus cobimetinib (HR PFS: 0.22) were identified as most favourable treatments. Both had, however, less favourable safety profiles. Five other treatments closely followed
Real-world costs during treatment of relapsed/refractory multiple myeloma vary greatly. Cost drivers include hospital admissions and acquisition costs of novel agents. Costs also vary by prognostic factors and treatment-related resource use. Future studies assessing the costs of combination therapy consisting of two or more novel agents are encouraged.
Decision makers increasingly request evidence on the real-world cost effectiveness of a new treatment. There is, however, a lack of practical guidance on how to conduct an economic evaluation based on registry data and how this evidence can be used in actual decision making. This paper explains the required steps on how to perform a sound economic evaluation using examples from an economic evaluation conducted with real-world data from the Dutch Population based HAematological Registry for Observational Studies. There are three main issues related to using registry data: confounding by indication, missing data, and insufficient numbers of (comparable) patients. If encountered, it is crucial to accurately deal with these issues to maximize the internal validity and generalizability of the outcomes and their value to decision makers. Multivariate regression modeling, propensity score matching, and data synthesis are well-established methods to deal with confounding. Multiple imputation methods should be used in cases where data are missing at random. Furthermore, it is important to base the incremental cost-effectiveness ratio of a new treatment compared with its alternative on comparable groups of (matched) patients, even if matching results in a small analytical population. Unmatched real-world data provide insights into the costs and effects of a treatment in a real-world setting. Decision makers should realize that real-world evidence provides extremely valuable and relevant policy information, but needs to be assessed differently compared with evidence derived from a randomized clinical trial.
It is crucial to set up an efficient patient registry that serves its aims by collecting the right data of the right patient in the right way. It can be expected that patient registries will become the new standard alongside randomized controlled trials due to their unique value.
Both countries publish drug reimbursement information. Therapeutic value appears to be the most decisive criterion; the relative importance of full economic evaluations is more modest than would generally be expected, especially in The Netherlands. Although the assessment process is reasonably transparent, both countries could make the appraisal process more transparent by more explicitly showing the actual role of each different (societal) criterion in their decision making.
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