1 Centre for Health Policy and Law, Erasmus University Rotterdam, Rotterdam, The Netherlands, 2 Department of Nephrology, University Hospital St Radboud, Nijmegen, The Netherlands, 3 Renal Division, Baxter Healthcare Inc., Deerfield, IL, USA, 4 Renal Unit, AMC, University of Amsterdam, Amsterdam, The Netherlands, 5 Department of Nephrology, Red Cross Hospital, The Hague, The Netherlands and 6 Department of Nephrology, Vrije Universiteit Medical Center, Amsterdam, The Netherlands
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Abstract |
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Methods. Scenarios were forecast over a 10 year period using aggregate data from the End-Stage Renal Registry in The Netherlands (Renine). Three scenarios were simulated in which the median PD technique survival was extended by 8, 10 and 12 months. Two other scenarios explored the impact of the combined effect of ETOT of 10 months together with a 10% and 20% increase of PD inflow shares. Reductions of costs to society due to ETOT were estimated using Dutch cost data on renal replacement therapies.
Results. PD share increases from 30.0% in the null scenario to 34.5% in the scenario with an ETOT of 10 months and an increased PD inflow share of 20%. The reduction in total costs to society of the renal replacement therapies is 0.96%. The average societal costs per discounted patient year for haemodialysis (HD) are €84 100. For PD, these costs are €60 300. A shift from HD to PD results in average cost savings of 28% per patient year.
Conclusions. In view of high dialysis costs to society, a reduction of 0.96% can be considered to be relevant for healthcare policy makers.
Keywords: economic evaluation; extended time on treatment; Markov chain modelling; peritoneal dialysis; polyglucose
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Introduction |
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In this paper a Markov chain model was applied, to investigate the impact of extended time on PD treatment (ETOT) in The Netherlands. Anonymous and aggregated data from the Dutch Renal Disease Registry (Renine) was used to forecast patient numbers over a 10 year period in six different scenarios. A null scenario describes a situation where there is no impact resulting from ETOT. To model the effects of ETOT, three scenarios were defined where the transition rates in the Markov chain model were adapted. In addition, two scenarios described the effects of ETOT together with increased PD inflow shares. The effect measures were: the PD share in total ESRD patients at the end of the 10 year model period; the discounted patient years shifted from HD to PD over the model period; and the impact of this shift in patient years on the costs of the ESRD programme.
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Subjects and methods |
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The total effect of the use of polyglucose in ultrafiltration patients can be divided into direct and indirect effects. The direct effect results from the increase in PD treatment time. The indirect effect results from the increase in the number of patients starting on PD instead of HD. It is expected that more patients will start on PD because the chances of staying for a longer period on stable PD treatment are higher.
Markov chain model
A Markov chain model simulates the dynamics in a patient population, distributed over a number of treatment and age groups. Continuous time is divided into a sequence of discrete periods. The model estimates the number of patients in the different treatment and age groups at the end of each period. In this application of the Markov chain model, a period equals 1 month. Consequently, a scenario covering 10 years consists of 120 periods. In the first month of the model period, the calculations begin with a known distribution of patients over treatment and age groups. The number of patients per treatment and age groups at the end of the month are derived from: (a) the number of patients entering the ESRD treatmentthis is the inflow; (b) the distribution of inflow over the treatment and age groups; (c) the application of the transition rates that indicate the number of patients moving to another treatment or age group within the period; and (d) the transition rates of patients ending the treatmentthis is the outflow from the model.
The transition rates and the relative distribution of the new patients over the groups are exogenously determined. The transition rates were calculated from the actual transitions that occurred in The Netherlands in the period 19971999. The relative distribution of the new patients over the groups equals the average relative distribution over the years 19971999.
Figure 1 shows a simplified representation of the Markov chain for three treatment groups and two calculation periods. The number of patients in each group at the end of the month is used as a starting point for the calculations in the next period. Again, the patients entering the different treatment and age groups are added to the patient numbers at the start and the transition rates are applied.
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Within treatment groups, two sub-treatments were distinguished for transitions occurring in the first year of treatment and transitions occurring in later years. The reason for this is that in some treatments, transitions in the first year are higher than in later years. The model has a total of 40 different groups (4 age groupsx5 modes of treatmentx2 sub-treatments) to describe developments in the patient population. In addition to the 40 treatment groups, the model has two absorbing states. These states are related to death and to recovery of patients' own kidney function. Both death and recovery constitute the outflow from the model.
Data
Anonymous and aggregated data were provided by the End-Stage Renal Registry in The Netherlands (Renine). Renine has data available for transitions between modes of treatment, incidence in the ESRD programme and mortality [3]. These data were used to calculate the transition rates and the distribution of the new patients over the treatment and age groups
On the basis of the number of new patients per age group in the period 19901999, a linear trend was estimated describing the incidence in the four age groups per million of the population. This trend, combined with predictions of the age-specific growth of the Dutch population, was used to calculate the absolute number of new patients per age group in the 10 year model period [4,5].
The null scenario
The null scenario explores the developments without ETOT. The incidence per million of the age-specific population in the 10 year model period is assessed according to the calculated linear trend. The distribution of these new patients over treatment groups is equal to the average distribution in the period 19971999. In the null scenario, the transition rates are the average transition rates from the 3 year period 19971999. Monthly transition rates were calculated as the ratio of the transitions actually observed in a month and the number of patients at the beginning of that month.
Scenarios with extended time on PD
Three scenarios were defined to explore the direct effects of ETOT. These scenarios differ from the null scenario in the transition rates from PD to HD. For the period 19901999, technique survival on PD was calculated. Figure 2 shows the technique survival on PD, for patients starting their PD treatment in the period 19901999. Using the Renine data, it was found that for The Netherlands, median time on PD until a transition to HD was 3.9 years for all PD patients. In PD patients with ultrafiltration failure, Wilkie et al. [1] found a median extension of technique survival on PD of 22 months as a result of the use of polyglucose as a dialysis fluid. Peers et al. [6] found an extended continuous ambulatory peritoneal dialysis (CAPD) technique survival of at least 1 year. It was estimated that incidence of ultrafiltration failure in PD patients is 5% in the first year of treatment, 30% after 3 years of PD treatment and 50% after 4 years [7,8]. To represent these estimates in the Markov model, the transition rates from PD to HD in the first year of treatment were kept constant. The assumption is that in the first year of treatment there is no effect of the use of polyglucose. In one scenario it was assumed that the median time until technique failure on PD increases by 10 months for all PD patients. This corresponds with
22 months of ETOT for the 50% of patients with ultrafiltration failure. Two other scenarios were defined, a scenario with a lower median ETOT of 8 months and a scenario with a higher extension of median technique survival of 12 months.
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The adjusted transition rates were obtained by correcting for the adjusted failure rate as an impact of ETOT. The theoretical survival (st) can be defined as:
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The extended median time is Te=T+extension. The adjusted failure for each ETOT can be described as:
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The adjusted transition rates were calculated by multiplying all transition rates from PD to HD with a factor re/r. With a median time on PD of 3.9 years, the monthly failure rate (r) is equal to 0.0147 and the failure rate for an extended time on PD (re) of 8 months is equal to 0.0126. As a consequence, the correction factor for all transition rates from PD to HD is 0.8649. For the extended times of 10 and 12 months, the correction factors for all transition rates are 0.8366 and 0.8101, respectively.
Scenarios with increased PD incidence and extended time of 10 months
Because of ETOT, PD treatment will be more attractive to patients and doctors. It can therefore be anticipated that the share of patients starting their renal replacement therapy with PD will increase. The relationship between ETOT and increasing incidence in PD is unknown. Two scenarios have been defined in which the PD incidence increases by 10% or by 20% compared with the inflow share in the null scenario. The relative distribution of PD incidence over the age groups has been kept equal to this distribution in the null scenario. Compared with the null scenario, total ESRD incidence does not change. Also, the share of transplants in the new patient does not differ. In these two scenarios with increased PD incidence, the extended time on PD treatment is 10 months.
Costs
To estimate the cost impact of extended time on PD treatment, total costs of the renal replacement programme in five scenarios were compared with total costs in the null scenario.
The cost estimates were based on a cost study in The Netherlands [5]. In this study, total costs to society were calculated per patient per year for different treatment and age groups. Treatment groups were: FCCHD, LCCHD, HHD, CAPD, continuous cycling peritoneal dialysis (CCPD) and KTX; age groups were: 044, 4564, 6574 and 75+ years. The costs of PD used in the estimates consisted of a weighted average of CAPD and CCPD costs. The weights were the age-related shares of CAPD and CCPD patients in total PD patients. Costs to society included costs of dialysis, other dialysis-related healthcare costs and patient costs. Costs of home adaptation for PD patients and travel costs for HD and PD patients were also included.
Costs in the first year on treatment and costs in the later years on treatment were distinguished for each treatment and age group. Total costs in the first year of treatment were higher than in the later years. In the first year, costs of hospitalization, vascular access operations and of training of patients are higher than in later years. In the dialysis treatment groups, costs in the two older age groups of 6574 and 75+ are higher than costs in the two younger age groups. This is due to the higher costs of hospitalization in the older age groups.
In the original cost study, additional costs of polyglucose were not taken into account. In The Netherlands, these costs amount to €3313 per patient per year. The extra costs of polyglucose were added to the costs of PD for the additional patient years as a result of ETOT. In general, resource use was valued at real cost to society, not at reimbursement rates. Originally costs were calculated at a 1996 price level. Using a price index for healthcare services, costs have been updated to 1999 prices. To calculate total costs of dialysis over a 10 year period in the six scenarios, yearly costs were discounted using a rate of 4%.
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Results |
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Table 1 summarizes the distribution of total number of new patients over HD and PD treatment in shares of total new patients per age group. The shares in the null scenario are derived from the average relative distribution of new patients over treatment and age groups in the period 19971999 in The Netherlands. Table 1
also presents the relative distribution in the two scenarios with a 10% or 20% increased PD inflow share.
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Discussion |
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In the scenarios in which the median time on PD treatment increases by 8, 10 and 12 months, the predicted PD share at the end of 2009 increases to 30.8%, 31.0% and 31.1%, respectively. The scenario with the 10 months extended time on PD treatment and a 10% increase of the PD inflow shares shows a PD share of 32.7% at the end of 2009. When the PD inflow share increases by 20%, the share of PD in total dialysis patients increases to 34.5% at the end of the model period.
Compared with the null scenario, the scenarios in which median technique success increases by 10 months combined with increased PD inflow shares of 10% and 20%, show a shift in discounted patient years from HD to PD of 2.9% and 4.9%, respectively. Although this seems to be low, the absolute number of discounted patient years shifted from HD to PD is 988 and 1638 patient years respectively. The scenarios with an ETOT of 8, 10 and 12 months show a shift in patient years from HD to PD of 0.8%, 1.0% and 1.1%, respectively. In the model period, average societal costs per patient on PD are estimated to be 28% lower than average societal costs per HD patient (PD: €60 300 per year; HD €84 100 per year). Total societal costs of dialysis can decrease by 0.6% to 1.0% as a result of both the direct and indirect effects. This implies for The Netherlands that societal costs decrease by €35.4 million in the scenario with an ETOT of 10 months and an increased PD inflow share by 20%.
The analysis indicates that the impact resulting from increased inflow shares is larger than the direct effect of the ETOT. An additional analysis was performed to investigate the sensitivity of different assumptions for our conclusion. In this sensitivity analysis, a number of scenarios was used to investigate the influence of increasing PD inflow shares and increased time on treatment on the overall PD share. In one group of scenarios, the PD-inflow share was increased by 50%, in 10 steps of 5%. In another group of scenarios the time on treatment was increased in 36 steps of 1 month. The model results from these scenarios were used to estimate the influence of increased PD-inflow shares and ETOT on overall PD shares. Ordinary least square regressions were applied to estimate these relationships. The regressions indicated that an increase of the PD inflow by 1% causes the PD shares to increase by 0.57%. An increase of the technique survival on PD by 1% causes the PD share to increase by 0.11%. The sensitivity analysis confirmed our conclusion that the influence of increasing PD shares is larger than the influence of ETOT.
It is possible that PD patients with ultrafiltration failure switch to CCPD when using polyglucose to extend time on PD treatment. This could have an impact on costs because CCPD is more expensive than CAPD. It is unknown whether ETOT would result in a substantial increase in CCPD. The possible cost impact has already been partially incorporated into our cost estimates. The PD costs per patient per year used in the cost estimates are an average of CAPD and CCPD costs weighted by the age-specific shares of CAPD and CCPD in total PD patients. The question is whether ETOT changes these age-specific shares. The relationship between ETOT and a switch from CAPD to CCPD needs further investigation before a possible impact on costs can be estimated.
This study concentrated on the effect the use of polyglucose has on PD shares in total renal replacement therapy. The results from the Markov modelling indicated higher PD shares. Consequently, direct and indirect effects of extended time on PD treatment result in cost savings that can amount to 1.0% of the total cost of dialysis treatment in The Netherlands. Although the relative cost savings are low, the absolute cost savings are substantial. These cost savings make it possible to offer dialysis treatment to more patients with equal budgets. In The Netherlands, the cost savings would allow for 452 more HD patient years or 635 more PD patient years in the 10 year model period. On a worldwide scale, the dialysis budget is estimated to be $100 billion [9]. In view of these high dialysis costs to society, a saving of 1.0% can be considered to be relevant for healthcare policy makers.
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Acknowledgments |
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Notes |
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References |
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