Evidence map›Paper›PMID 15244488›Full record

ArticlePharmacoEconomics2004

An economic model of 2-hour post-dose ciclosporin monitoring in renal transplantation.

Paul A Keown, Bryce Kiberd, Robert Balshaw, Shideh Khorasheh, Carlo Marra, Philip Belitsky, Zoltan Kalo

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Article in PharmacoEconomics, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Paul A KeownUniversity of British Columbia, Vancouver, British Columbia, Canada. keown@interchange.ubc.ca
Bryce Kiberd
Robert Balshaw
Shideh Khorasheh
Carlo Marra
Philip Belitsky
Zoltan Kalo

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMonitoring of microemulsion ciclosporin (cyclosporine; Neoral) by 2-hour post-dose drug concentrations (C2) is an accurate measure of ciclosporin absorption efficiency and exposure, and appears superior to trough (C0) monitoring for prediction of rejection risk. A predictive decision model was used to determine if this approach also reduces total treatment costs in the first 12 months after renal transplantation.

methodsParameter estimates for key clinical events were derived from the literature and from prospective pharmacokinetic studies comprising 234 adult HLA-non-identical renal graft recipients at seven Canadian centres. Patients were treated with microemulsion ciclosporin (Neoral), corticosteroids and azathioprine or mycophenolate mofetil. Using the perspective of the Canadian healthcare provider, total treatment costs for the C2 versus the C0 strategy were modelled over 12 months, and then remodelled using conservative estimates to extend the timeframe to 5 years. Health resources were valued in 1999 Canadian dollars.

resultsThe incidence of acute rejection was estimated to be 25% at 1 year in patients monitored by C0 and 18% in those monitored by C2. Patient survival was considered to be independent of monitoring strategy, and graft loss was predicted to be 1.4% lower in the C2 group. The studies suggested no important differences in comorbidity and the costs of C0 and C2 monitoring and ambulatory-based adverse events were held equivalent. Using these inputs, the average cost per patient for the first year post-transplant was Can dollars 46,857 for C0 monitoring and Can dollars 45,306 for C2 monitoring, rising to Can dollars 146,879 and Can dollars 142,569 after 5 years. The predicted cost for initial hospitalisation was Can dollars 11,280 for C0 and Can dollars 10,806 for C2 monitoring. The cost of maintenance immunosuppressive drug use, graft loss and dialysis was Can dollars 19,098 in the C0 group and Can dollars 18,612 in the C2 group, while acute rejection treatment costs were Can dollars 2169 and Can dollars 1577, respectively. An additional Can dollars 14,310 was consumed by other events, including repeat hospitalisation, for each group. Sensitivity analysis indicated that the most influential parameters affecting savings due to C2 monitoring were a reduction in the duration of initial and follow-up hospitalisations and reduced risks of acute rejection and subsequent graft loss.

conclusionsCompared with traditional trough concentration monitoring, ciclosporin monitoring at 2 hours post-dose produced a predicted saving of Can dollars 1551 during the first year after renal transplant. Although modelling assumptions become more restrictive over time, this projection allows a preliminary assessment of the long-term economic impact of the routine use of C2 monitoring.

Indexed as

Health Care CostsModels, EconomicAdultCost-Benefit AnalysisCyclosporineDrug MonitoringFemaleGraft RejectionHospitalizationHumansImmunosuppressive AgentsIncidenceKidney TransplantationMaleMiddle AgedPredictive Value of TestsCyclosporineImmunosuppressive Agents

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.