| Title |
A Decision-Analytic Model to Assess the Cost-Effectiveness of Etelcalcetide vs. Cinacalcet
|
|---|---|
| Published in |
PharmacoEconomics, February 2018
|
| DOI | 10.1007/s40273-017-0605-2 |
| Pubmed ID | |
| Authors |
Björn Stollenwerk, Sergio Iannazzo, Ron Akehurst, Michael Adena, Andrew Briggs, Bastian Dehmel, Patrick Parfrey, Vasily Belozeroff |
| Abstract |
Etelcalcetide is a novel intravenous calcimimetic for the treatment of secondary hyperparathyroidism (SHPT) in haemodialysis patients. The clinical efficacy and safety of etelcalcetide (in addition to phosphate binders and vitamin D and/or analogues [PB/VD]) was evaluated in three phase III studies, including two placebo-controlled trials and a head-to-head study versus the oral calcimimetic cinacalcet. The objective of this study was to develop a decision-analytic model for economic evaluation of etelcalcetide compared with cinacalcet. We developed a life-time Markov model including potential treatment effects on mortality, cardiovascular events, fractures, and subjects' persistence. Long-term efficacy of etelcalcetide was extrapolated from the reduction in parathyroid hormone (PTH) in the phase III trials and the available data from the outcomes study in cinacalcet (EVOLVE trial). Etelcalcetide was compared with cinacalcet, both in addition to PB/VD. We applied unit costs averaged from five European countries and a range of potential etelcalcetide pricing options assuming parity price to weekly use of cinacalcet and varying it by a 15 or 30% increase. Compared with cinacalcet, the incremental cost-effectiveness ratio of etelcalcetide was €1,355 per QALY, €24,521 per QALY, and €47,687 per QALY for the three prices explored. The results were robust across the probabilistic and deterministic sensitivity analyses. Our modelling approach enabled cost-utility assessment of the novel therapy for SHPT based on the observed and extrapolated data. This model can be used for local adaptations in the context of reimbursement assessment. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 54 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 13 | 24% |
| Student > Ph. D. Student | 8 | 15% |
| Student > Master | 5 | 9% |
| Researcher | 4 | 7% |
| Professor | 3 | 6% |
| Other | 6 | 11% |
| Unknown | 15 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 16 | 30% |
| Economics, Econometrics and Finance | 7 | 13% |
| Nursing and Health Professions | 3 | 6% |
| Business, Management and Accounting | 2 | 4% |
| Agricultural and Biological Sciences | 1 | 2% |
| Other | 8 | 15% |
| Unknown | 17 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 February 2018.
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#18,584,192
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Outputs from PharmacoEconomics
#1,653
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#329,168
of 439,370 outputs
Outputs of similar age from PharmacoEconomics
#34
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