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NDT Advance Access originally published online on June 25, 2007
Nephrology Dialysis Transplantation 2007 22(10):2867-2878; doi:10.1093/ndt/gfm367
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© The Author [2007]. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org


Economic evaluation of sevelamer in patients with end-stage renal disease

Braden Manns1,2,3, Scott Klarenbach3,4, Helen Lee1, Bruce Culleton2, Fiona Shrive1 and Marcello Tonelli3,4,5,6

1Department of Community Health Sciences, 2Department of Medicine, Division of Nephrology, University of Calgary, Calgary, 3Institute of Health Economics, 4Department of Medicine, Division of Nephrology, 5Division of Critical Care Medicine and 6Department of Public Health Sciences, University of Alberta, Edmonton, AB, Canada

Correspondence and offprint requests to: Dr Marcello Tonelli, University of Alberta, Division of Nephrology and Immunology, 7-129 Clinical Science Building, 8440 112 Street, Edmonton, Alberta T6B 2b7 Canada. Email: mtonelli{at}ualberta.ca



   Abstract
Top
 Abstract
Introduction
 Methods
 Results
 Discussion
 Conclusion
 Appendix 1
 Acknowledgements
 References
 
Background. There is uncertainty about the most cost-effective way to treat hyperphosphataemia in patients with end-stage renal disease.

Methods. We performed an economic analysis which compared the use of sevelamer with calcium carbonate in a simulated cohort of North American dialysis patients, using the perspective of the health care purchaser and a lifetime horizon. Outcomes considered were quality-adjusted life years (QALYs) gained and health care costs. To account for uncertainty, we considered four separate modelling strategies, obtaining data on the relative effectiveness of sevelamer from the recent Dialysis Clinical Outcomes Revisited study.

Results. In the base analysis, the use of sevelamer was associated with a cost per QALY gained of CAN$157 500, compared with calcium carbonate. Assuming no survival or hospitalization advantage for sevelamer, use of sevelamer resulted in an incremental cost of CAN$17 000 per patient. In alternate models which assumed sevelamer to be more effective than calcium-based phosphate binders, the use of sevelamer was associated with a cost per QALY gained ranging from CAN$127 000–$278 100. Assuming that sevelamer resulted in a differential reduction in mortality in patients ≥65 years of age, use of sevelamer in this subgroup was associated with a cost per QALY of CAN$105 500. Results were similar in groups defined by age ≥55 or by ≥45 years. Since dialysis is expensive, interventions for dialysis patients that improve survival without reducing the need for dialysis will be associated with a cost-utility ratio at least as great as that of dialysis itself. As such, we repeated the primary analysis excluding the costs of dialysis and transplantation and found that the cost per QALY gained for sevelamer was $77 600.

Conclusions. The cost per QALY gained for treating all dialysis patients with sevelamer exceeds what would usually be considered good value for the money. While the high cost per QALY was in part due to the inclusion of the costs of dialysis and transplant in the analysis, the cost per QALY gained remained relatively unattractive even when these costs were excluded. Although a lower cost per QALY gained is realized when only patients older than 65 years are treated, this strategy remains economically unattractive, particularly given the uncertainty of clinical benefit in this group.

Keywords: Sevelamer; Calcium; Hyperphosphatemia; Economic Evaluation



   Introduction
Top
 Abstract
 Introduction
Methods
 Results
 Discussion
 Conclusion
 Appendix 1
 Acknowledgements
 References
 
Patients with end-stage renal disease (ESRD) have abnormal mineral metabolism and high mortality rates [1]. Observational data have linked markers of abnormal mineral metabolism such as hyperphosphataemia to increased morbidity and mortality in patients with ESRD [2–4]. The treatment for hyperphosphataemia in ESRD includes the use of oral phosphate binders with meals. Calcium-based phosphate binders have traditionally been used as first line therapy, since they correct hypocalcaemia in addition to reducing serum phosphate levels and because they are inexpensive [5].

Non-calcium-based phosphate binders such as sevelamer have recently been developed for treatment of hyperphosphataemia in patients with ESRD. These agents are theoretically preferable to calcium-based agents, since they might permit control of serum phosphate at lower levels of serum calcium, which in turn could reduce adverse outcomes due to calcification of cardiac and vascular tissue [1]. Current practice guidelines (published in 2004) recommend the use of sevelamer in many common clinical situations [1], although the impact of this strategy on hard outcomes such as mortality and hospitalization was unknown until recently. The Dialysis Clinical Outcomes Revisited (DCOR) study compared mortality and morbidity over 3 years for patients randomized to treatment with sevelamer compared with those receiving calcium-based phosphate binders [6]. The primary analysis showed no difference in overall mortality (RR 0.91, P = 0.30) between treatment groups. However, in a pre-specified secondary analysis, sevelamer was associated with better survival in patients aged older than 65 years.

Since there is a large differential cost between sevelamer and calcium-based phosphate binders, we conducted an economic evaluation comparing these two treatment strategies in patients with ESRD on dialysis.



   Methods
Top
 Abstract
 Introduction
 Methods
Results
 Discussion
 Conclusion
 Appendix 1
 Acknowledgements
 References
 
We sought to determine whether scarce resources should be allocated to use of sevelamer in ESRD patients using cost-utility analysis, a special form of cost-effectiveness analysis [7], where health benefits are expressed as ‘quality adjusted life years’ (QALYs). There are two broad methods of performing a cost-utility analysis; in conjunction with a clinical trial or using decision analytic modelling [8]. Our analysis combined both methods, taking the estimate of effectiveness for sevelamer from DCOR and using decision analysis to extrapolate the potential clinical benefits and costs of sevelamer over the lifetime of an ESRD patient. The objective of this analysis was to determine the cost per QALY gained for sevelamer compared with calcium-based phosphate binders in North American patients with dialysis-dependent ESRD.

Patient population
In the base case analysis, we evaluated a simulated cohort of dialysis patients who were ≥18 years and whose characteristics were representative of typical Canadian dialysis patients. In sensitivity analyses, we considered patients more reflective of dialysis patients in the US [9], as well as patients enrolled in DCOR [6]. For the population considered in the base case analysis, we used data from the Canadian Organ Replacement Registry (CORR) which collects information on Canadian dialysis patients undergoing dialysis or transplantation [10]. For another analysis, CORR provided us with data from a random sample of 37% of patients initiating renal replacement in Canada between 1 January 1996 and 31 December 2000 (n = 7034 after excluding children) [11]. This is an appropriate comparative group given that sevelamer would not have been used in the majority of these patients. Data taken from this cohort is described subsequently and in Table 1.


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  		Table 1. Baseline clinical effects

 
Treatment comparators
We sought to compare sevelamer with the most commonly used phosphate binder in use in patients with ESRD in Canada, calcium carbonate [5]. This was also one of the calcium-based phosphate binders used as standard care for many of the patients enrolled in sevelamer clinical trials [12–15], including DCOR [6].

Analytical approach
To determine the cost-effectiveness of sevelamer, we used a Markov model, adapted from previous analyses [16,17]. We considered yearly transitions between three clinical states, alive on dialysis, alive with a transplant and dead (Figure 1). The model was analysed over the patient's lifetime, with shorter timelines considered in sensitivity analysis. This analysis was conducted from the perspective of the health care purchaser, consistent with published guidelines [18] and reasonable given the absence of data as to whether sevelamer impacts indirect costs experienced by patients [6]. The model outputs were QALYs, life years gained, costs and the cost per QALY gained. All analyses were performed using Treeage Pro 2005 (Treeage Software, Inc., Williamstown, USA).


Figure 1
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  		Fig. 1. Markov model, displaying the possible clinical outcomes in ESRD patients treated with either sevelamer or calcium carbonate.

 
Clinical effects of patients treated with calcium-based phosphate binders
Baseline transition probabilities and clinical effects for patients treated with calcium-based phosphate binders are noted in Table 1. The probabilities of mortality and transplantation for patients treated with calcium-based phosphate binders were based on the observed rates within the Canadian patient cohort described above [11]. In sensitivity analysis, we considered the mortality rates observed in a national registry of dialysis patients in the US [9] and within DCOR itself [6].

Efficacy of sevelamer
The DCOR study is the only randomized study with sufficient statistical power to investigate the impact of sevelamer on clinically relevant endpoints such as mortality [6]. This currently unpublished study reported efficacy in several different ways, making it uncertain how best to model the efficacy of sevelamer. We considered several alternative strategies, described in Table 2, and developed an a priori analysis plan before performing analyses.


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  		Table 2. Four alternate ways of modelling the efficacy of sevelamer

 
Since the primary DCOR analysis compared survival without stratifying by time on therapy, our primary analysis used this estimate of efficacy, reflecting a constant relative risk over time of 0.91 [6] for all age groups; [Model 1 (primary model)]. Since the primary analysis of the DCOR study was non-significant, we also performed a cost-minimization analysis [Model 2 (cost minimization model); Table 2].

Since the assumption of constant proportional hazards was not met in the primary DCOR analysis [6], we performed an exploratory analysis in which the effect of treatment on mortality differed before and after 2 years of follow-up [Model 3 (mortality over time model); Table 2]. As only 50.6% of patients completed the unblinded DCOR study [6], the balance between treatment groups introduced by randomization at study entry might no longer be present among patients remaining in the trial after 2 years. Therefore, the findings of this post hoc analysis are of uncertain clinical significance and are presented as a secondary analysis only. Finally, since the DCOR investigators reported an interaction between treatment efficacy and patient age (<65 or ≥65 years) [6], we also performed an exploratory analysis modelling the efficacy of sevelamer in patients aged < 65 years and ≥65 years separately [Model 4 (mortality by age model)].

Other clinical effects
Kidney transplantation
Transplant rates for patients aged <65 and ≥65 years were derived from the Canadian patient cohort described before (Table 1) [11]. Survival of transplant patients and the risk of a transplant failure necessitating a return to dialysis were estimated from a contemporary cohort of North American transplant patients [19]. We assumed transplant failure and patient survival to be similar for patients treated with calcium-based phosphate binders and sevelamer.

Health-related quality of life
A comprehensive literature search was done to identify estimates of utility scores for contemporary North American dialysis and transplant patients, favouring estimates from more recent studies which were done in ‘unselected’ patient populations [20–22]. Base case analyses use the results of a contemporary cohort of ESRD patients [20]. Given that quality of life was not reported in DCOR [6] or any other sevelamer study to date, we assumed similar utility values for patients treated with calcium-based phosphate binders and sevelamer.

Costs
Given the perspective of our analysis (i.e. publicly funded government health care in Canada or Medicare in the United States), it only included direct costs to the health care purchaser [18]. Baseline estimates of cost are reported in Table 3. Costs were inflated to 2004 values [23] and are reported in CAN$ (1US$ = 1.30CAN$) except for the US scenario analyses, where costs are reported in US$. Health care costs considered were classified into one of three categories:

  1. Drug costs (cost category 1): Average daily consumption of sevelamer and calcium-based phosphate binders in the DCOR study have not yet been reported. In the primary analysis, the cost of sevelamer and calcium carbonate was therefore estimated based on the average doses (sevelamer 6.5 g/day; calcium carbonate 4.3 g/day) consumed in another large clinical trial of sevelamer (n = 200) [13].
  2. Hospitalization costs (cost category 2): The DCOR study reported that the number of hospitalizations (per patient year) was non-significantly reduced from 2.3 ± 4.9 to 2.1 ± 4.4 (P = 0.06) for patients treated with sevelamer [6]. To determine the potential reduction in hospital costs associated with sevelamer use, we required information on the average cost and frequency of hospitalization for North American ESRD patients, which was determined in detail using a focused literature search (Tables 1 and 3) [24–26].
  3. Associated health care costs: Given that any therapy which extends life will increase the cost of associated health care (i.e. such as the cost of dialysis and transplant care), we also estimated the cost of ongoing dialysis and transplant therapy (cost category 3), favouring estimates from more recent studies which were done in ‘unselected’ patient populations (Table 3).


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  		Table 3. Baseline costs

 
Some methodological controversy exists as to, which costs to include in economic evaluations that are performed within ESRD [27]. For the primary analysis, we considered all health care costs (cost categories i–iii) [27]. However, since dialysis is expensive, interventions for dialysis patients that improve survival without reducing the need for dialysis, will be associated with a cost-utility ratio at least as great as that of dialysis itself [27]. Inclusion of such costs (which, in and of itself, is methodologically correct) in economic evaluations in this area may mitigate against the acceptance of interventions which improve patient survival. In sensitivity analysis, we explored the cost per QALY gained considering only the costs within cost categories (i) and (ii).

Sensitivity analysis and scenario analysis
Various one-way sensitivity analyses were performed varying the values for uncertain variables within the ranges noted in Tables 1–3GoGo. As noted, we performed various analyses modelling the efficacy of sevelamer in different ways (Table 2). In the base case analysis, we assumed that the relative risk of death associated with sevelamer treatment remained constant throughout the patient's lifetime. The impact of this assumption was tested in a sensitivity analysis which assumed no survival benefit beyond 4 years (consistent with the timeline of the DCOR study).

The DCOR study protocol identified six subgroups for which subgroup analyses were planned a priori and specified that stratified analyses would be performed in subgroups for which a test for interaction was statistically significant (P = 0.03). Although the tests for interaction were not corrected for multiple comparisons, the nominally significant interaction between treatment and age <65 vs ≥5 years raises the possibility that sevelamer is more effective in older patients. In scenario analyses, we modelled the cost-effectiveness of sevelamer in patients aged ≥65 years. In exploratory analyses, we also modelled the cost-effectiveness of sevelamer in patients aged ≥45 years and those aged ≥55 years, varying baseline mortality and hospitalization rates [11], hospitalization costs [25] and the relative risk of mortality as reported in DCOR [6].

Many of our model inputs (baseline mortality rates, cost and frequency of hospitalization) were based on Canadian data. To improve the generalizability of this analysis for US decision makers, we undertook scenario analyses that better represented a US setting. In addition, we present a scenario analysis using data on baseline mortality and hospitalization frequency taken directly from DCOR. Model inputs used in the US and DCOR-specific scenarios are described in Table 4. Probabilistic sensitivity analyses were performed as described in Appendix 1 (Figure A1-A–E).


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  		Table 4. Clinical and costing estimates used for United States- and DCOR-specific scenario analyses

 

Figure 2
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  		Fig. A1. Incremental cost effectiveness ratio (ICER) scatter plots (in CAN$). The ICER scatter plots plot points for all iterations in the Monte Carlo simulation. Each point represents the incremental cost and effectiveness of sevelamer relative to calcium-based phosphate binders for a particular iteration. The willingness-to-pay value (arbitrarily set as $50 000 per QALY gained in these examples) is displayed as the slope of a dashed line intersecting the origin of the plot. A 95% confidence ellipse is also shown in all the graphs. (A) Model 1 (Primary model). (B) Model 2 (Cost minimization model). (C) Model 3 (Mortality over time model). (D) Model 4 (Mortality by age model). (E) ≥65 subgroup using Model 4.

 


   Results
Top
 Abstract
 Introduction
 Methods
 Results
Discussion
 Conclusion
 Appendix 1
 Acknowledgements
 References
 
Model validity
Consistent with published guidelines [28–30], we tested for logical inconsistencies in our decision model by evaluating them under hypothetical conditions. We determined that our models had face validity and confirmed that the mathematical calculations were accurate and consistent with the specifications of the model. We also confirmed that our model had predictive validity by comparing model outputs (a function of both input variables and model structure) with observed data from the DCOR study (data not shown). This comprehensive validation increases confidence in each of these models.

Base case analyses
In the base case analysis, which used a lifetime horizon, Model 1 (primary model), the use of sevelamer, in comparison to calcium-based phosphate binders, resulted in an incremental cost of CAN$33 000 and an increase in quality adjusted life years of 0.211, resulting in a cost per QALY gained of CAN$157 500 overall.

Since the effect of sevelamer on mortality and hospitalization was not statistically significant compared with calcium-based phosphate binders in the DCOR study (P = 0.30 and P = 0.06, respectively) [6], we repeated our analysis considering no survival or hospitalization advantage for sevelamer (RR 1.0 for both outcomes). In this analysis [Model 2 (cost minimization model); Table 2], the use of sevelamer, in comparison with calcium-based phosphate binders, resulted in an incremental cost of CAN$17 000, but, as expected, no increase in quality adjusted life years.

Since the DCOR study suggested differential benefit to patients based on their age and length of follow-up, we also considered other methods of modelling efficacy. In Model 3 (mortality over time model; Table 2), we modelled the effectiveness of sevelamer differently for the first 2 years, compared with 3 years and onwards, which resulted in an incremental cost per QALY gained for sevelamer compared with calcium-based phosphate binders overall of CAN$127 000 (Table 5). Lastly, in Model 4 (mortality by age model; Table 2), which modelled the efficacy of patients aged <65 years and ≥65 years separately; the incremental cost per QALY gained overall was CAN$278 100 (Table 5).


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  		Table 5. Base case cost effectiveness analysis, considering a lifetime time horizon (in CAN$)

 
Scenario analyses
We repeated the analyses for each of the models noted above over a 4 year time horizon; the cost per QALY gained varied between CAN$380 400 and $2.4 million for Models 1, 3 and 4. We also reanalysed Models 1, 3 and 4, excluding the related health care costs associated with dialysis and transplantation and noted that the cost per QALY gained varied from CAN$43 800 to $186 800 (Appendix 2, Table A1). Assuming that sevelamer resulted in a differential reduction in mortality in patients ≥65 years of age, the use of sevelamer in this subgroup was associated with a cost per QALY gained of CAN$105 500. In exploratory analyses that examined the cost-effectiveness of sevelamer in subgroups of patients aged ≥45 years and ≥55 years, the cost per QALY gained was CAN$97 000 and $102 700, respectively. Excluding the costs of dialysis and transplantation and including only patients ≥65 using Model 4, the cost per QALY gained becomes $23 300 (Appendix 2, Table A1), though, given the uncertainty associated with subgroup analysis, this likely represents an unrealistically optimistic estimate of the cost-effectiveness of sevelamer.


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  		Table A1. Base case cost-effectiveness analysis, excluding the cost of dialysis and transplantation

 
Given that American ESRD patients experience higher mortality rates and incur higher healthcare costs than Canadian ESRD patients, we repeated analyses using probabilities and costs that would be more reflective of the US health care system (Table 4). We also considered calcium acetate as a comparator given its frequency of use, assuming equal efficacy between calcium carbonate and calcium acetate. In the US scenario, the use of sevelamer, in comparison with calcium carbonate and calcium acetate resulted in an incremental cost per QALY gained of US$156 700 and US$175 000, respectively. In the DCOR-specific scenario, the use of sevelamer, in comparison with calcium carbonate and calcium acetate, respectively, resulted in an incremental cost per QALY gained of US$179 200 and US$205 000.

Sensitivity analysis
Our results were robust to clinically plausible changes in all uncertain variables (Table 6). Excluding the impact of quality of life (but using baseline mortality rates from our Canadian cohort), the use of sevelamer, compared with calcium-based phosphate binders, resulted in a cost per life year gain of CAN$102 600. If the average dose per day of sevelamer was reduced or increased by 25%, the cost per QALY gained for sevelamer was CAN$135 800 and CAN$179 200, respectively. The results of the probabilistic sensitivity analysis demonstrated significant uncertainty in the true cost-effectiveness of sevelamer (Appendix 1, Figure A1-A–E).


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  		Table 6. Sensitivity analysis of the cost per quality adjusted life year gained for sevelamer compared with calcium-based phosphate binders in the treatment of dialysis patients (in CAN$)

 
As the DCOR study found no significant difference in mortality, but a trend towards a reduction in hospitalization rates (which would generate cost savings), we also sought to determine to what extent sevelamer use would have to lower hospitalization rates in order for the savings to offset the additional medication costs of sevelamer. Assuming no difference in survival, the risk of hospitalization would have to be lowered by 30% to offset the additional medication cost of sevelamer.



   Discussion
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
Conclusion
 Appendix 1
 Acknowledgements
 References
 
The primary analysis of the only randomized study powered to investigate the impact of sevelamer on relevant clinical endpoints showed no statistically significant difference in mortality. Secondary analyses of this DCOR study, based on patient age and more speculatively, time on treatment, suggested a possible benefit in certain subgroups [6]. The most straightforward conclusion would be to adopt the results of the primary analysis, conclude that sevelamer does not improve clinical outcomes and perform a cost-minimization analysis. However, to avoid prematurely discarding the possibility that sevelamer represents an economically efficient treatment and consistent with guidelines for economic analyses [18,28], we considered several different modelling strategies.

Considering only the models that assume sevelamer to be more effective than calcium-based phosphate binders, the use of sevelamer was associated with a cost per QALY gained ranging from CAN$127 000 to $278 100. This is higher than the cost per QALY gained for most therapies that are considered an efficient use of finite health care resources [31].

In part, the high cost per QALY gained for sevelamer is due to the observation that therapies which prolong life in ESRD patients result in a significant increase in related health care costs for dialysis [27]. When these costs were excluded (which would be inconsistent with accepted practice within economic evaluation), the cost per QALY gained for sevelamer decreased but still ranged between CAN$43 800 and $186 800. This observation does raise potential ethical issues that will need to be considered when interpreting economic evaluations of new therapies that improve survival for patients with ESRD. It is important to note that other factors besides effectiveness and cost-effectiveness influence funding decisions. For instance, dialysis is funded in all developed countries, despite the fact that it is associated with high cost per QALY gained [27]. In part, this is due to the fact that without dialysis, patients face certain death; this has been termed the ‘rule of rescue’, whereby societies tend to be willing to direct resources to therapies that avert ‘certain’ death [32]. It should be noted that this is not the case with therapies like sevelamer, which, at best, may reduce the statistical likelihood of dying. Nonetheless, these important ethical issues deserve careful consideration by decision-makers who fund ESRD care.

An interaction was noted in the DCOR study between treatment efficacy and patient age (<65 years or ≥65 years), with patients older than 65 years experiencing a statistically significant reduction in mortality. While the use of sevelamer in this subgroup was more attractive, particularly when the costs of dialysis and transplant were excluded, the effectiveness of sevelamer in this subgroup remains uncertain and the cost per QALY gained for this subgroup (CAN$105 500) is still high and was similar when slightly different subgroups of older patients (≥55 or ≥45 years) were included. In addition, since this test for interaction was non-significant after correcting for multiple comparisons [33], it could be argued that the benefit of sevelamer in older populations requires confirmation in specifically designed trials.

This is the first study to model the cost-effectiveness of sevelamer using clinical rather than surrogate endpoints. In the only other full economic evaluation of sevelamer performed in ESRD patients, Huybrechts et al. [34] used efficacy data taken from the Treat to Goal study [13] which suggested that sevelamer reduced coronary artery calcification, an unproven surrogate endpoint for mortality in ESRD patients. Based on the ability of sevelamer to reduce coronary artery calcification and assuming that reduction in such calcification would reduce subsequent mortality, cardiovascular disease and hospital costs, these authors suggested that the use of sevelamer was cost-effective. However, reducing vascular calcification has not been shown to reduce mortality, and therefore, it is uncertain whether the findings of Huybrechts et al. [34] are valid.

Like all economic models, our analysis depends on certain assumptions and has some limitations. First, uncertainty remains as to the most appropriate method of modelling the effectiveness of sevelamer in unselected ESRD patients. However, it is reassuring that the results of the models were generally consistent across a spectrum of sensitivity analyses. Second, the cost-effectiveness of sevelamer may be improved if its use significantly reduces the cost of hospitalization. While we modelled a reduction in the frequency of hospitalization in our analyses, the actual reduction in hospitalization costs remains speculative until further DCOR analyses based on Medicare data become available. It should be noted that a 30% reduction in the risk of hospitalization would be required to offset the increased cost of sevelamer. Third, due to the lack of data on the impact of sevelamer on patient-related costs (i.e. time off work to receive medical care, productivity losses), analyses using a full societal perspective were not presented. However, even if indirect costs are shown to be reduced by sevelamer, the magnitude of these costs are likely to be small and therefore it is unlikely that adopting a broader perspective would have qualitatively changed the results of this analysis. Finally, our analyses considered North American cohorts of dialysis patients. We did not estimate the cost-effectiveness of sevelamer in a European context as we could not obtain accurate information on important input parameters including the incidence and costs of hospitalization in representative cohorts of European patients. However, given that mortality rates in European and Canadian ESRD patients [11,35] appear similar and that the cost differential between sevelamer and calcium are similar in Europe, it is likely that the cost-effectiveness of sevelamer in Europe is similar to that observed in Canada.

We did not consider scenarios where sevelamer was restricted to ESRD patients with specific abnormalities in mineral metabolism, such as concomitant hyperphosphataemia and hypercalcaemia, a criteria used by some health care purchasers [5]. There is no data indicating that such a strategy will reduce mortality or morbidity in these patients and consequently the cost-effectiveness of this approach is unknown. However, since calcium-based phosphate binders reduce serum phosphate levels to the same extent as sevelamer, it seems unlikely that sevelamer will be more cost-effective in this patient subgroup.

While sensitivity and scenario analyses were relatively robust to plausible variations in model parameters, probabilistic sensitivity analysis (Appendix 1, Figure A1-A–E) demonstrated significant uncertainty in the true cost-effectiveness of sevelamer. While health care funding decisions must be made using the best currently available data, it is possible that future estimates of the cost-effectiveness of sevelamer may differ, but only if several key parameters are found in future studies to differ substantially from those used in this analysis.



   Conclusion
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Conclusion
Appendix 1
 Acknowledgements
 References
 
Even assuming that sevelamer is associated with a clinical benefit, as we did within our primary economic evaluation, we noted that the cost per QALY gained for treating all ESRD patients with sevelamer, compared with calcium-based phosphate binders, exceeds what would usually be considered good value for the money. While the high cost per QALY was in part due to inclusion of the costs of dialysis and transplantation in the analysis, the cost per QALY gained remained relatively unattractive even when these costs were excluded. Although lower, the cost per QALY gained for treating patients older than 65 years is still relatively high given the uncertainty of clinical effectiveness in this subgroup, suggesting that additional trials conducted specifically in this population may be useful to decision-makers and health care payers.



   Appendix 1
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Conclusion
 Appendix 1
Acknowledgements
 References
 
Probabilistic sensitivity analysis
Methods
The standard method of expressing uncertainty in classical statistics is through use of measures of variance, such as the 95% confidence interval (CI) around a mean for normally distributed variables. This approach is problematic in economic evaluation and has led to the use of other methods designed to deal with and express analytical uncertainty [39,40]. Classical univariate sensitivity analysis has been criticized since it only considers the uncertainty present in one (or two) variables at a time and it may underestimate the uncertainty present within a cost-effectiveness ratio [39,40]. As a result, some analysts have attempted to construct 95% CIs around cost-effectiveness ratios [40]. Given the lack of independence between the incremental costs (the numerator) and incremental QALYs gained (the denominator), this is statistically problematic and as such, most recommend against the use of CIs for cost-effectiveness ratios and for the use of Monte Carlo simulation (probabilistic sensitivity analysis) as performed in this analysis [41,42].

Monte Carlo simulation enables simultaneous sensitivity analysis of all uncertain variables. It does so by replacing estimates of probabilities, utilities and costs with specific probability distributions, which are based on the reported means and variances of each variable [41,43,44]. The analysis is then repeated 25 000 times, sampling different values from the appropriate distributions for each of the variables. In such a way, a statistical distribution is built up around the incremental cost-effectiveness ratio giving a better reflection of the uncertainty inherent in the analysis.

With Monte Carlo simulation, one can also consider the uncertainty with respect to the maximum cost per QALY gained that decision-makers would consider acceptable (i.e. some decision-makers will choose only to fund therapies associated with cost per QALY gained < $20 000 [31]; others, with larger budgets, may choose to fund therapies with cost per QALY gained up to $50 000–100 000). This is displayed graphically as a cost-effectiveness acceptability curve demonstrating the probability that a therapy is associated with a cost per QALY gained lower than a range of displayed maximum cost-effectiveness ratios.

We performed Monte Carlo simulation for our overall model and patients aged ≥65 years. Statistical distributions were created around all of the variables for which significant measurement uncertainty existed and for which distributions could be estimated. In general, normal distributions were used for probabilities and utilities, as appropriate and log normal distributions were used for costs.

Results
With the use of second-order Monte Carlo simulation, the Appendix Figures A1-A–E present incremental cost-effectiveness ratio (ICER) scatter plots highlighting the uncertainty in the ICER when the uncertainty in all variables is considered simultaneously. In all models and subgroups considered, there is significant uncertainty in the 95% confidence ellipse, with a significant proportion of simulations falling into each quadrant of the cost-effectiveness plane.

The probability that the use of sevelamer would be cost-effective (i.e. more effective and either cost saving or associated with a cost per QALY gained below the threshold) if a decision-maker was willing to pay only CAN$50 000 or $100 000 per QALY gained and considering Model 1 is 15 or 32%, respectively. Considering the subgroup of patients ≥65 years separately, the probability that the use of sevelamer would be cost-effective if a decision-maker was willing to pay only CAN$50 000 or $100 000 per QALY gained is 21 or 44%.



   Acknowledgements
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Conclusion
 Appendix 1
 Acknowledgements
References
 
This study was funded by the Canadian Agency for Drugs and Technologies in Health.

Conflict of interest statement. None declared.

(See related article by M. Tonelli et al. Systematic review of the clinical efficacy and safety of sevelamer in dialysis patients. Nephrol Dial Transplant 2007; 22: 2856–2866.)

(See related article by S. C. Palmer et al. Sevelamer: a promising but unproven drug. Nephrol Dial Transplant 2007; 22: 2742–2745.)



   References
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Conclusion
 Appendix 1
 Acknowledgements
 References
 

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Received for publication: 7. 3.07
Accepted in revised form: 14. 5.07


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